The Trading Floor Press

Time for data to get real

2009-04-16T15:45:00.002+01:00

Author: Chris McDonald, Managing Director of The Trading Floor

If a business is to survive, it needs to attract and retain customers regardless of whether or not there's a recession. However, the difference during a downturn is that it becomes more important than ever to maximise opportunities from existing customers and make sure that any investments in prospect data deliver a tangible return.

As a result, the smarter data providers are coming up with ways of helping marketers to get the most out of their existing assets. One way of doing this is by appending data to contacts they already hold.

Many organisations now see the benefits of adding to the customer knowledge they hold through appending key trigger data. This could include details of additional cars, motorcycles, additional homes and renewal dates.

As marketers feel the pressure to reduce spend and increase transparency around consumer responses, many are also tempted to explore new channels and digital communications. Communicating with customers using e-mail technology is extremely cost effective and there is a huge swing towards companies appending key data, including customer e-mail addresses.

So what about prospect data? Quality was already prospering over quantity long before the economic downturn with warm, multi-channel, transactional data sitting at the top of all data buyer's wish lists.

However, the downturn is accelerating the process and discerning clients now demand data that is more targeted than ever in order to reduce waste and ensure a return. The result is a very pronounced shift towards total accuracy, complete with meticulous testing and analysis, which is good news for anyone currently investing in data.

Prospect data driven from real customer transactions has consistently outperformed lifestyle data and this trend continues. Consumers are far more sophisticated in their buying patterns than they were even five years ago - they now expect their chosen providers to demonstrate knowledge of who they are, how and why they buy.

The economic downturn has also created many more opportunities to host valuable data on behalf of new contributors who would have - even as recently as 12 months ago - not viewed monetisation of their dataset as a core objective. Things have changed!

We are seeing a four-fold increase in clients wishing to join The Trading Floor, with the majority of our transactional data captured from quotation applications from insurance, mail order, e-retail, mail order and financial organisations. The result is one of the most granular and accurate transactional data pools in the UK.

For the future, we are working on a real-time platform to monetise enquiries that do not fit the profile for Company A, but will fit Company B. We also see applications in managing the retention of customers this way and building strategies around those customers you want to keep who may be looking at alternative suppliers. Only real data can do this - all the modelling in the world can never get near this level of pinpoint accuracy.

The world of data has changed exponentially in the last two to three years and continues to evolve. Companies are seeing the value embedded in their databases and are looking for ways to sell more to existing customers and through channels that work for them and their customer. Through the increased use of real data, a marketer will drive increased ROI on their marketing campaigns and we continue to innovate at a time when the data market appears to be shrinking.

Cream will always rise to the top!

Data Strategy April 2009

The Internet and Email

2008-11-20T11:07:00.005Z

The Internet has transformed business over the last decade and marketing more than most other functions. Though email was well on its way up the charts in 1998, its use for marketing was very much in its infancy while ecommerce sales were virtually non-existent. The sites on offer ran at a crawl over dial-up and were horribly clunky. Remember Barclay Square?
Without the internet, it's hard to see how any of the advances in the last decade could have happened, and it has completely changed how companies interact with their customers. Sites like mobile network Blyk run completely on-line, offering over 200,000 UK 16-24 year-olds fully opted-in to receive communications on their mobile phones. It's claimed 29% average campaign response rate would have been hard to find a decade ago too.
Nothing to do with database marketing a decade ago, web analytics is now increasingly aligned with email and other channel marketing. Efforts by leading vendors to merge on-line and off-line customer data is perhaps the most exciting targeting development of recent years. If successful and not stymied by new legislation, this linkage will bring the richest behavioural information yet on individual customers.
"The breadth of digital interactions and the ability to analyse and track them today would have been nirvana for a marketer in 1998," says james Alty, Managing Director at Apteco.
Email has been variously hailed as the saviour and the death of direct marketing. the saviour because it embodies so many of the benefits of direct mail: in 2007, marketing email volumes overtook direct mail for the first time and the DMA estimate over 30% of the marketing budget is going into email.
Email's not as easy as it used to be though.
Deliverability is emerging as the great challenge and although straightforward sending costs are still low, more companies like Thomson are investing heavily in highly-targeted data-driven campaigns.
"There's a lot more targeting going on now," says Chris McDonald, Managing Director of The Trading Floor, which gathers registration data from online insurance and other enquiries. McDonald notes this has affected the type of data companies want to buy.
"To drive targeting, the market now increasingly wants multichannel contacts for a record, plus transactional and risk data too," he says. "Those selling just an email file will struggle."As well as being the enabler of many of today's vital marketing services such as remote database cleansing sites and on-demand CRM tools, the web has also become an invaluable data collection channel for database marketers. As response to traditional printed lifestyle surveys and warranty cards has dropped off, so data gathered in different areas of the web has taken its place at the leading edge of consumer data.
"The main trend in customer data has been the digital capture of data online," confirms McDonald. With its low delivery costs and incredible automated targeting potential, the importance of the internet can only grow. According to ecommerce industry body IMRG, around half of everything we buy in the next ten years will be online and the other half will be influenced by it.

(Database Marketing 10th Anniversary Issue- November 2008)

Data Strategy Awards. Winner, Data Provider of the Year 2008

2008-10-30T11:39:00.000Z

Founded in 2005, The Trading Floor is a revolutionary way for companies to monetise dormant enquirer information. A central, independently-managed data pool, it provides contributors with a revenue stream and users with responsive and versatile data for direct marketing. Originally focused on the Insurance sector, coverage has expanded to include charities, financial services and automotive.

Year two for the business has seen phenomenal growth, despite difficulties for the wider data industry. Revenues rose 77% to £3.9 million, while data columes traded hit 117 million. The Trading Floor now aggregates data from 40 brands and has paid £1.8 million to data contributors, a rise of 103%.

Product development has seen the data pool expand with the addition of credit card, secured loan, mortgage and remortgage sources. Uncertainty in the financial services sector has seen a growing number of clients using the data for appending and profiling as part of customer retention strategies. Live customer data is also being hosted and managed for incremental sales to non-competitors.

The Trading Floor is now ranked the largest multi-channel list manager in the UK after just two years. With nine out of ten UK insurance companies and 12 of the top 15 direct marketers as clients, the business has also achieved 98% client retention.

Its data set has been used successfully by Hylton Group to drive sales of the Peugeot 207 through its dealerships. Using the predictive buying model for automotive, qualified prospects within a five mile radius were identified for email, with a direct mail follow-up to non-buyers,. The campaign achieved a 514% ROI.

Despite downward pressures in its sector, The Trading Floor has grown and launched innovative new products, many of them still undergoing confidential testing. With a team of 30 staff, it has driven tremendous growth. The company continues to challenge, improve and revolutionise data usage in both acquisition and retention marketing.

Why Pile It High, Sell It Cheap Just Does Not Wash

2008-06-13T12:59:00.003+01:00

Regular screening can be 'a six-figure cost to make your eyes water'

Andrew Campbell's comment in Precision Marketing's special report on data quality (Time to get tough, PM May 30) that data owners and list managers do not bother to screen data against MPS and other suppression files because "it's a simple equation - the more data they sell, the more money they make" is not only insulting and derisory but more importantly shows a staggering lack of knowledge about prospect data provision.

Any good data managers among us know that the key to longevity in the data sales market is to maintain fresh, accurate data that consistently performs for the end user.

Regular screening of our 13 million prospect database is a six figure cost to make your eyes water, but one we consider vital as it means instead of "pile it high, sell it cheap" we can leverage decent CPM for our contributors while maintaining integrity and churn.

Campbell needs to be questioning his data suppliers a little more closely - unless he is one of those buyers constantly looking to screw the cost of the data down as low as possible.

Zoe Vine, Head of Data Services, The Trading Floor, West Yorkshire

(Precision Marketing: Opinion - 13th June 2008)

Making Connections - Zoe Vine

2008-06-01T08:48:00.003+01:00

Too many marketers are still making the wrong moves towards truly understanding the behaviour of their prospects and customers.

"It IS possible to connect with your customers in a way that's more meaningful to them and more profitable to you" - Zoe Vine, Head of Data, The Trading Floor

The "one size fits all" approach has long been considered an outpost of modern marketing. Now more than ever, businesses are turning to strategic data analysis to gain more actionable insight into what is motivating and driving a purchasing decision.

My letter box is piled high with so much direct mail that my postman leaves me notes begging me to clear the mailbox. Telesales calls are met with the "reject call" button. Me - I'm your traditional time-poor, cash-rich kind of girl (keep this in perspective, I don't have a fleet of Porsches lining the sweeping driveway, this is Yorkshire you know) - and for the last four years I have almost exclusively bought every product and service online, often at strange hours of the day in between working, walking dogs, entertaining clients and trying to get some sleep.

Similarly, the products I buy do not necesssarily relate to my lifestyle or lifestage - last month alone I spent £130 on baby products, resulting in a glut of sales messages for multipurpose vehicles and holidays with creche facilities in that poor over-loaded letter box. Said purchase of baby products didn't mean a new addition to my household, more a spate of present buying for friends recently visited by that pesky stork.

So why do companies find it so hard to engage my interest in products that are meaningful and through a method I find acceptable?

Management by fact

Too many companies choose to focus on analysing a customer's past behaviour, when what they are really interested in is how that customer will behave in the future. The gap in knowledge between knowing how someone has previously behaved and predicting how they will behave is massive. The data that companies hold may be transactional, it may even be clean and recent, but it won't necessarily lead to any meaningful insight. Customers always act within a context, and this constantly changes as new products emerge, events happen and life stages change. Historical data can give you the what they did, but rarely the why they did it.

Piecing together the customer intelligence puzzle requires assimilation and evaluation of all the demographic, attitudinal and transactional data sets available to build your process and techniques. Three key steps help to paint this picture of the consumer's buying habit:-

Asking the questions

What data do you hold on each customer? What information can be deduced from each piece? What's the best way to harness this information for future sales? Management by fact is crucial to all these questions - basing your answers on a set of out-dated assumptions renders these questions near enough redundant.

Question the answers

Identify the key triggers within the data what happened at that point in the customer cycle to generate the sale of that product at that time? Does a shift in behaviour in one sector automatically lead to a shift in others? Adopting a variety of clustering and profiling techniques enables clear identification of customers with similar behaviour patterns and demographic trends. Drive robust statistical data sets to generate a variety of predictive models for cross and up selling purposes.

Mining the answers

Don't just ask the questions once - ask them frequently. An answer given 12 months ago may not necessarily be true of the individual if the same question was asked today. Similarly - ask WHY the answer is different - establish the cause for change driving the difference and back up an isolated piece of information with others that work to support or deny the information in question.

Reducing the assumptions made on a customer is the holy grail data-wise in the 21st century - just as a customer's purchasing decision is unlikely to sit in isolation from external events, so too that in order to examine context and behaviour a customers data needs to be cross-pollinated against external sources.

The Trading Floor recently worked with a well-known Travel company to supplement their existing knowledge by appending indications of recent significant expenditure from insurance and finance companies (purchase of a new house or a new car) against lapsed customers of their top of the range holidays, to drive financial triggers as to the likelihood of that customer to next spend with the brand. Examining travel insurance purchases have also helped the brand to identify where lapsed customers have booked through a competitor instead.

Partnership data pools are increasingly well recognised within industries as being more cost-effective, better targeted and more accurate means of reaching customers and prospects. Alongside The Trading Floor's multi-industry, multiple-channel pool, the Mail Order market has its pools with Abacus and Transactis, and Occam holds Reciprocate, their answer for the Charity market.

Undertaking to build a partnership data pool to supplement the organisation's existing data sets by matching against third party transactional, demographic and lifestyle data is horrendously time consuming, not to mention hugely expensive both in terms of licensing the data and hosting and storing the pool.

Taking advantage of partnering with companies already operating data pools built from multiple markets and across multiple channels enables marketers to quickly build a learning curve from which to concentrate on contacting the right people, at the right time, in the right way - eliminating wastage and promoting better customer relations.

Your most important assets are your customers. It costs six to nine times more to acquire a customer than it does to keep your current one, not to mention the requisite retention period to return a profit. Your competition is poised to pounce on any customer who feels that the company doesn't understand, recognise and acknowledge them for their valuable patronage.

It IS possible to connect with your customers in a way that's more meaningful to them and more profitable for you. Step forwards Debenhams - on arrival at work this morning, having got soaked in a rain-shower, waiting in my in-box was an email inviting me to look at the latest range of anoraks to counter-act the Great British Summer.

Customer Intelligence at its best - topical, relevant, through my preferred channel. Quickest £60 I've ever spent.

(Data Strategy: Opinions on Data - June 2008)

Knowledge is Power

2008-04-01T13:50:00.003+01:00

Gathering customer data is one thing. Making it work for you in an effective way to enhance return on investment and further your business is quite another.

At a time when data is the hot topic on everyone's lips, it can often seem that the more information you have, the less you actually know about what matters. Data is knowledge, and knowledge is power - and converting that data into knowledge of customers, and unlocking their spend potential, is a difficult, though crucial, task.

The fractured nature of most client databases, stemming from employing bolt-on "one size fits all" CRM solutions, means pools of valuable data sets are usually isolated and therefore unable to interact to provide the customer intelligence required to drive an effective marketing and communication strategy.

If you want to find out who your most profitable customers are you may find yourself interrogating several systems to add up their spend across each product type. Our database management division has found that generally, the more established the company, the more disparate the data storage facilities. It's a problem worth solving - the more you know about your customers, the better placed you are to maintain their custom, and to sell them additional goods and services.

Key to driving a system rationalisation is getting buy-in across the business - appoint a data steward in each business area, and agree and implement a data governance plan where sponsors are identified and accountable. Rationalising systems to create a single customer view delivers benefits across the three most important challenges marketers face: productivity, customer understanding and financial attribution.

The first piece of the customer intelligence puzzle is assimilating and evaluating your demographic, attitudinal and transactional data sets to build your processes and techniques. By profiling customers and prospects, and identifying the traits of customers that bring greatest value to the business, marketers can target new, high value customers. Equally, by having a full view of every customer's relationship with the business, and the ability to understand the customer life cycle, it is easier to spot and retain lapsed customers quickly, and to build deeper and more loyal business relationships.

Three key steps help to build the knowledge bridge:-

Data interrogation - what data you hold on each customer, what information can be deduced from each piece, how it can be harnessed for future sales prospects. Without reliable data, you can do little to build your strategies.
Segmentation - identifying groups of similar customers. A variety of clustering and profiling techniques can be adopted to identify customers with similar behaviour patterns and demographic trends.
Hypothesis - once the segmentation is complete and you have robust statistical data sets, with a clear model of the customer life cycle, you can start to generate a variety of predictive models for cross and up selling purposes to existing datasets.

"Still too many companies choose to focus on analysing a customer's past behaviour - when what they are really interested in is what the customer will buy in the future"

Because customer segments can be quickly and accurately identified, the time to market for new products is cut. Marketers can concentrate on contacting the right people, at the right time, in the right way, which will eliminate wastage and promotes better customer relations.

Yet still too many companies choose to focus on analysing a customer's past behaviour - when what they are really interested in is what the customer will buy in the future. The gap in knowledge between knowing how someone has previously behaved, and predicting how they will behave is massive. The data your company has may be transactional, it may be clean, but it won't necessarily give you the key buying triggers and variables required to drive predictive models. Customers always act within a context, and this constantly changes as new products emerge, events happen, people move. You know some of what they did, but rarely why they did it.

It's likely that in order to examine context and behaviour you will need to supplement existing data sets by matching to third party transactional, demographic and lifestyle data sets such as The Trading Floor's insurance/finance pool.

Identifying trigger data through your previous data interrogation and segmentation work, you will select variables that provide the most value to your data set - anything from date of birth, to occupation, to what newspaper they read on a Tuesday, through to flags indicating a recent house move, their car insurance renewal month and additional contact information.

Complementing your database with additional information and producing qualitative and quantitative segmentation is the cornerstone to driving a customer intelligence strategy, and really understanding why your most valuable customers are buying from you, and how to find more of them.

Pin down your what, why and your when, and you'll not only cement a customer relationship for life, you'll have the biggest competitive advantage. 'Examine. Extrapolate. Enrich' should be the 2008 mantra for the customer-savvy marketer.

(Precision Marketing: Leaders on B2B Marketing - April 2008)

King For A Day - Chris McDonald

2008-03-31T13:49:00.003+01:00

Sowerby Bridge-based Chris McDonald, MD of The Trading Floor, won't be Lonesome Tonight with Brazilian supermodel Giselle on his arm. Let's just hope he doesn't get the GI Blues when he leads his nation into battle.

Who would you choose as your Queen, and why? I would choose Giselle Bundchen. Shallow perhaps but I am the King!!!

What one law would you pass to make 'the lives of your citizens better? I would have drivers over a certain age tested every year.

Which form of Medieval torture would you re-introduce, and for whom? The ducking stool. I would start with Kerry McFadden and her husband.

Who would you bring into court to advise you on stately affairs? Jo Brand, Peter Kay and Ben Elton. Between us we could come to a realistic solution to most things!

What would you banish from this Fair Isle? Work shy fools, drugs and middle lane drivers - that would just be day one!!

Your bloodthirsty subjects want a war to boost morale - with which country do you pick a fight? How about the Americans? Only 17 per cent of them would even know where the UK was!

Finally, what monument would you like your people to build in your honour? I would like to have a monument representing England, Scotland, Wales and Ireland coming together as one - obviously in Yorkshire!

(EN Magazine - March 2008)

The Trading Floor top List Manager league table

2008-03-30T13:46:00.003+01:00

... Second-placed The Trading Floor is also a big email data supplier, earning 67 per cent of its income from email in 2007. The company's main source of income is a data pool for the insurance and financial service industries, based on enquirer data.

"People typically get three quotes before they take a policy out," says Zoe Vine, head of data services at The Trading Floor. "So companies have a lot of information on prospects that they don't do anything with for 11 months of the year."

The Trading Floor pools this data from 36 contributor companies spread across the motor, home, pet and travel insurance, mortage and credit card industries. It is then enhanced and sold back out to the wider DM industry, taking 50 per cent of the revenues itself and sharing the other half among the contributing companies, based on a complex set of ' data survivorship' rules relating to who pooled the data and who enhanced it.

(Direct Marketing: The List Report – March 2008)

Quick Counting - Listknife

2008-03-15T17:00:00.005Z

James Lawson reviews a simple but very effective fast counting tool.

Time was, all that any database marketer wanted was to have swift access to their data. Running counts and pulling out selections in minutes, no messing about with the IT department - what a dream scenario. Much more may be possible in automated direct channel marketing now, but a surprising number of volume mailers are still in the same position. Listknife might just be the tool they are looking for.

No frills or fancies
Forget about automated multi-wave, multichannel campaigns, triggered communications and clever SOA integration. Listknife is a batch tool in the classic mode, and is all about exploring large datasets quickly.

There's no disputing that it's easy to use. Drag-and-drop Windows functionality plus a selection of wizards make this a code-free experience - no SQL here. And it certainly is fast. The demo system was able to run a complex multivariable count totalling 600,000 records from a 35.5m list in under a second.

The graphical drag-and-drop query builder is the outstanding feature of Listknife

The stand-out feature of the package, and one that must have taken some considerable development, is the graphical query builder. Extremely simple to use, it is one of the more intuitive examples of the breed and something like the AnswerSets tool (last heard of around 2002) that employed interactive Venn diagrams to achieve much the same results.

Users simply choose a variable from the listing down the left-hand side and drop it into the main selection builder ("Count Logic") window to have it included within the selection. You can even drag and drop data straight from the Windows desktop. Clicking on the resulting variable object brings up a dialogue box within which you can refine the details of your count for that variable. For example, if you have included all UK cars in your selection, do you only want Mercedes?

Boolean operators are dragged and dropped in the same way to form boxes within the Logic window (the main window itself effectively acts as an AND function, combining everything within it), and to have that operator act on a variable or another operator, you simply drag the operand inside the operator box. So to exclude all people with CCJs or suppress records from a previous count, you would place the CCJ variable within a NOT box. To build complex multivariable queries, you simply nest blocks of objects to combine AND, OR and NOT operators.

Tabular profiling gives list managers what they need to know

It sounds tortured but is actually very simple in practice as the screenshots on this page should hopefully show. Lots of nested statements might get a little messy but probably less so than any other graphic selection tool.

Clicking on the "i" button on the top row then runs the count, which can easily be saved as either data or the query itself. A useful small display in the bottom corner updates the count as you then make changes to it. Other nice tweaks include flagging individual records as members of the same household during the database build. This means you can immediately get a count of the number of households within an individual-level selection.

With a selection live, clicking on the Profile tab at the top of the main window opens up a tabular profile report on the attributes within the current count: the percentage that any variable makes up of universe volume, the percentage of selection volume, and the index and z-score built from those two figures.

In same way, you can explore profiles of variables within the whole database by simply dropping them onto the Profile window and it's also possible to compare two profiles side-by-side. There's a simple wizard for this but it's barely necessary.

The third and final function of the main window besides profiling and selection building is a cross-tab function that can handle two or even three variables. Like the rest of the package, this is simple but elegantly implemented and very fast. Again, you simply drag and drop the variables you want onto the window, while the cross-tab values can be dragged straight into Excel.

Two- or three-dimensional crosstabs are the work of seconds.

There's a good data browser that can handle up to a million records on its own. Showing its list management roots, the package also offers decent tools for splitting out lists, for example, into males and females or to create test cells or 1 in N selections. Another good idea is to be able to flag a record as part of a test cell on the database.

Reporting is minimal. Clicking the Audit function on the bottom window gives you a tabulated report of the current count process, but further charting and manipulation would have to be done within Excel. For this, you can simply drag and drop selections into Excel with a single click rather than having to set up an export. Further connectivity employs ODBC to access databases, though no native connectors for the likes of Oracle appear to be available. Text files for import and export are another option.

Another notable feature of Listknife lies in how it is built around the use of URNs rather than holding customer names and addresses. In this age of corporate concern over data security, it means that losing a laptop full of customer data doesn't necessarily put your company on the front page of next morning's papers.

It also gives a way for the package to easily match lists without having to get into full-blown name and address processing. For example, if you have the URNs of a list of respondents from a campaign, you can easily import them and match them to the original target list by using URNs.

When it comes to production, one restriction could be its lack of remote access capability. Though the vendors say that remote access is possible, there are speed implications and no current customers use it in this way. Listknife does have an up-to-date .NET platform so there should be a way around this, but it's an isolated batch tool as it stands, and as such, a tad lacking in today's connected world.

Dedicated functionality makes splits and control cells easy to set up.

Like almost all fast counting tools, Listknife has a proprietary, highly-indexed database structure and requires a pre-load import stage to convert data into this format. Both of these may well deter a company's IT department, but it's par for the course in this area. A standalone utility is used for the import, with five million records claimed to take an hour's processing. No "trickle feed" updating is possible; the whole database has to be rebuilt to incorporate any changes.

Focused on lists
For end user marketers who run a few big monthly campaigns around a monthly database update cycle, Listknife would do most jobs perfectly well. Where one person has only, say, half their time allocated to handle mailings, they could easily jump in front of Listknife and sort out that month's selections. The main competition comes from other straightforward fast-counting tools like Minotaur or a low-cost standard application like SQL Server running on fast hardware. Many tools today can do much more, often as part of a wider suite that takes in stats, web-published reports and campaign management functionality. Something like FastStats Discoverer is a much more capable package.

But if running lots of counts and generating lists is where it's at, then Listknife could well be for you. The name is something of an indicator: it's perfect for list owners and managers. In fact, consumer data specialist The Trading Floor liked the tool so much, it bought the company.

Costs and specification
Listknife pricing is by annual fee with a nominal set-up charge. The fee tends to be from £14k to £20k depending on the number of users and database size/complexity. Listknife only runs on Microsoft operating systems. www.thetradingfloor.co.uk

(Database Marketing: Software Review – March 2008)

Fill The Pool

2008-03-15T16:03:00.003Z

Once you've decided to build a prospect pool, how should you select the data to put in it? James Lawson investigates.

Working with a prospect database is increasingly acknowledged as the most cost-effective way for serious direct marketers to acquire new customers. Farming a semi-permanent file rather than hunting and gathering lists every time you want to send a campaign out of the door takes marketing up the evolutionary chain, and learning can be fed back to a central point for future application too.

So the argument is over and a prospect pool is on the horizon. But what are you going to put in it?

What's in the pot?
The initial attraction of a prospect database for many is the opportunity to save money when buying data by negotiating terms in advance. There no doubt that buying all the data you need for the year up-front is a lot cheaper than ad hoc list purchasing. However, many companies tend to maximise the size of their discount by doing a deal with a single data provider and so sticking to a single source. Does this lead to a lower performing pool?

Opinions tend to be split on the route to take, with some advocating simply selecting a tranche of lifestyle data or geodemographically-coded Electoral Roll data that matches your customer profile, while others would take a more traditional route in bringing together tens of lists and updating them quarterly thereafter while testing new sources. The middle way is to use some sort of base file and pull in valuable extra sources if they will really make a difference.

"You need to use a base file with other information added to it;' says Richard Higginbotham, head of marketing at CDMS. "On top of that, you can layer your response data and other elements of prospect tracking like how many times a contact has been mailed."

Multisourcing a file may make the task of building a pool more complex but has a number of benefits. For a start, even if all you are doing is adopting worst practice and carpet bombing the Electoral Roll- the approach used by US credit card companies over the past decade to build their UK market share - maximum coverage will come from multisourcing different versions of the Electoral Roll. If the aim is to whittle down a UK base file to match your needs, having the biggest possible footprint to start with has to be a good idea.

In a study by The Customer Partnership in 2005, Julian Berry and Paul Rowson found only a 75 per cent overlap between two competing replacement Electoral Rolls. So the consequence of going with just one Electoral Roll supplier is either a 25 per cent loss of mailable volume, or having to mail parts of the file that are much lower down your propensity models' gains charts, with a consequent drop in response rates. As the opt-out level has risen by nearly ten per cent since that study, the figures would be even more compelling now.

You need to be able to process quickly and accurately - Rob Salmon, managing director, meta-morphix

Using multiple fIles should also give more variables to use for predictive modelling. Berry and Rowson found that the four separate sources they used were all involved in each of the five propensity models they built. "We could not have scrapped any of them without seriously weakening our models;' says Julian Berry, managing director of The Customer Partnership.

Multisourcing will also help reliability by providing multiple instances of the same individual or household, and so multiple examples of critical variables like date of birth or insurance renewal date. Based on the reliability of each source, the data processor can choose to pick one piece of data from a record, merge other fields or simply ignore it.

"We currently take 38 different feeds to build our own pool and we have a hierarchy of data survivorship rules which govern which source takes precedence;' explains Zoe Vine, head of Data Services at The Trading Floor. "Multiverification helps increase confidence in many areas, particularly residence:'

Set against these benefits is the extra work and therefore cost involved in the initial build, then the ongoing maintenance cost plus the liaison work with each supplier: the more sources a file has, the more complex it will be to refresh. Each data supplier will supply updates at different intervals, and each one will have a different idea of what "update" means, so you could be processing the same data over and over again.

Building a model may also be slightly problematic if, despite a lengthy search, variables are not populated or consistent across the whole data set. However, there are ways around this.

"You may have to build separate models for individuals that appear on one source but not on others;' says Berry. "But usually have 80 to 85 per of them across your main sources so it's not as had as it sounds."

Test your files
How to choose the size and composition of the base file, and which lists to layer on top is the heart of the challenge. Tim Beadle, managing director of Marketing Improvement, says that paring down the size of the "addressable target universe" should be the first step.

"Take a brutal and pragmatic view;' he says. "If you are selling Jags, then you don't want high-rise council block tenants. Far too many people try to make their prospect database as large as possible which carries a massive cost."

Just as in classic profiling and targeting, understanding which are the key attributes of your own customer base will help inform which other files might help improve prospecting performance - though restricting a pool solely to the profile of your existing customers could limit growth.

The desirability of extra files will obviously vary for each sector: car insurance renewal dates will be top of the list if you are marketing car insurance, while indicators of a propensity to go on foreign holidays will attract travel operators. Co-op data showing multibuyers is a likely purchase for a mail order company and mortgage providers may be attracted to some of the warm lead-to-purchase data aggregated by the likes of The Trading Floor.

Some marketers may have their heart set on using a certain set of lists that have worked for them in the past. Alan Thorpe, commercial and operations director at G2 Data Dynamics, gives the example of a financial services company that wanted to employ lists of readers of financial magazines to drive its contact programme during the ISA season.

"But they could only get a couple of hundred thousand names from those' he says. "By imputing variables from the lists across a larger EuroDirect base file, they got the volume for roll-out along with the accuracy they needed:'

Far too many people try to make their prospect database as large as possible - Tim Beadle, managing director, Marketing Improvement.

However, it's possible to go too far in adding response-built lists, and Beadle advises caution. "Sure they responded, but do you know why?" he asks. "Or why they purchased? It's ok if the list is precisely right but the overwhelming majority of lists don't have the information on them to help you make that decision."

He states that it can often be best to stick to a simple base file along with a few highly predictive variables like age, gender, location and income. Targeting can then be based on those in combination with geodemographics.

"Using the most comprehensive sources to get the right footprint and selecting rigidly on tight geodemographic values works very well;' Beadle argues. "Where people live is the most highly predictive variable out there:'

So when it comes to deciding which selection of sources will work best in a pool, the only really accurate way to do it is, as ever, to test in advance. No discount is worthwhile if the data involved doesn't work.

"You need to get your short list of potential data suppliers to match up their data to your model development data sets, and then let the statisticians tell you which data items you need, and how much you need any particular piece of data;' advises Berry. "No-one can tell you which are the right variables until you model and test, but very few people do that. If the data item is very expensive and the least important variable in your propensity model, you could decide to drop it and save the money."

No-one can tell you which are the right variables until you model and test - Julian Berry, managing director, The Customer Partnership.

But having to think two or three years ahead and set up a testing programme can be rather daunting when the priority is to get the pool built. No wonder so many companies listen to the sales pitch and sign up with a single data owner.

"It is very hard to test the pool components with different timings and creative," says Vine. "It's a different thing to classic DM list testing. But if you're going to licence up front for three years then you simply will have to do it:'

One option that holds out the promise of cost and time savings is to employ pre-merged pools. Why reinvent the wheel? This encompasses products like CACI's Ocean and Alchemy's AMS pool and also includes Ai Data Intelligence's pooling proposition.

"We have a large merged database as standard;” says Ai's managing director Jon Cano-Lopez. "We can build client-specific views based on which supplier data they want to buy."

The company has recently added credit data to its merged file and also offers Pipeline, a web-based pay-as-you-go list sales service that pulls records from the same central database.

"This might not necessarily be the whole answer but it has to be better than a single source;' comments Berry.

In all cases, it's well worth checking that the company building your pool will be able to source all the data you might need from the major owners. In some cases, it has been known for data owners to refuse to supply some service providers and not just because they threaten their own prospect pooling business. For example, one major data owner has previously refused to supply its file to a third-party provider because the terms of the proposed contract meant that the provider would have had unlimited use of the variables when transformed into scored values within a pool.

Hosting a large prospect file with a specialist supplier rather than holding it in-house is one of the classic decisions in direct marketing. Marketers have always used bureau services to run the complex merge/purge routines needed for list building, and the initial and ongoing data processing required for a permanent pool is no different.

We take 38 different feeds to build our own pool - Zoe Vine. head of Data Services, The Trading Floor.

Unless your technical staff, systems and applications are up to the job, then forget going in-house. There's also the time and effort involved in maintaining the reference files required to update and suppress the prospect data that mitigate against doing much of this work yourself.

"You need to be able to process quickly and accurately," says Rob Salmon, managing director of meta-morphix. "We have 240m records to match to and make sure that are up-to-date. There's a proliferation of reference data and there's a huge physical overhead to manage and update it. Compared to that, a ten-million record database is quite small."

Retain control
In filling up the pool, the decision is more about whether you should you buy your data from and host your database with the same provider or use an independent broker along with a hosted specialist. Another wrinkle on this is where the hosting company not only brokers data but is also a data owner itself. Can a data owner really be independent?

"You can be independent and a data owner," insists Experian's Colin Grieves. "Our base data sets are where we start." He declines to comment on whether he is under any internal pressure to sell his company's own data as part of a hosted prospect pool.

"The large data owners will have an axe to grind," states Salmon. "They will definitely be under pressure to use their own data."

Or maybe you're happy with the data suppliers but not the service you get from your hosting provider or bureau - this can present real dilemmas. The advice here is to make sure that your data pool is portable rather than in some format known only to your incumbent supplier.

You'll have more power over your bureau and should get a better service as a result. If a prospect pool is indeed a long-term commitment, taking the time to pick the right range of suppliers will pay dividends in future - just like the data.

(Database Marketing: Prospect Data Management - March 2008)

Adapt Or Die

2008-03-15T15:00:00.004Z

In an industry traditionally addicted to volume, is tighter targeting good or bad news? Robert McLuhan looks at how consumer data suppliers are catering for smaller, precise campaigns and a growing demand for richer, lead-to-purchase data.

For years, direct marketers have been besieged by public concerns about unwanted mailings, intrusive home calls and misuse of data - and have mostly escaped unscathed. Now they have found themselves in the firing line over fears about global warming and the environmental damage caused by waste. With volumes in bulk consumer mailings already on the wane, how does this new world order affect the outlook for suppliers and users of consumer data?

Sitting duck
Together with newspapers and magazines, direct mail is estimated to account for 14 per cent of household waste. When dumped in landfills, paper creates methane, a gas that is 23 times more polluting than carbon dioxide. All this makes direct marketers an easy target for politicians: in January the environment minister Joan Ruddock warned that a mandatory opt-in for commercial mail is "still on the table".

Marketers can justly retort that the days of blanket mailings are over. These days much more effort goes into profiling to ensure that mailings are properly targeted and that waste is avoided by using more deceased/goneaway suppression amongst other initiatives. As for environmental concerns, by 2006 the industry had boosted the amount of mail going to recycling to 30 per cent, as agreed between DEFRA and the DMA, and is on track to meet its commitments of 55 per cent by 2009 and 70 per cent by 2013.

But the agreement also commits the industry to reducing volumes through a mixture of better targeting and hygiene. If that starts to happen, then presumably companies will need to source less data, and that in turn could impact on the data industry. With bulk prices arguably already at rock bottom at around £80-90 per thousand records for the most generic data, smaller volumes could make it hard for many suppliers to generate the revenues they need to stay in business.

For the moment, suppliers claim that mailing volumes have yet to fall significantly. "If anything, volumes have been going up, a sign that direct mail really works," argues Richard Webster, commercial director at DLG.

"Companies are not going to hold back on a successful medium as long as it continues to bring good returns, and if they can demonstrate that it is not leading to waste;' he says.

However some agree that a decline in the quantity of commercial mail is a logical outcome of current trends. "Over time, the industry will be selling less data overall," predicts Peter Lupa, sales director for data at Acxiom.

We are at a watershed - Annette Holmes, managing director, Prospect Swetenhams.

What is clear is that the consumer data market is undergoing a seismic shift. Annette Holmes, managing director of Prospect Swetenhams, points to the need to reduce overall volumes but argues that more spend will be needed to support better targeting.

"We are at a watershed, as suppliers and owners start to wake up to the need to control waste and change their business model;' she says. She then identifies the nub of the problem for suppliers: reducing volumes cannot lead directly to less revenue, because if it did the whole industry could collapse.

In Holmes's view, in future, it will not just be the lists themselves that will be driving the market so much as the in-depth analysis, profiling and modelling required to identify targets. It is precisely because clients are now looking for greater return on investment from their data that they have a greater appreciation of the need for quality. Instead of flogging large quantities of shallow data for poor returns, suppliers will increasingly be supported by the demand for the extra services that they can provide.

A sense of what can now be achieved with this sort of data/analytics packaged approach is provided by a recent campaign by Eurodirect on behalf of the DVLA, persuading drivers to pay annual road tax online or by telephone instead of going to the post office. Eurodirect first profiled and segmented online customers to help identify prospects who would most likely convert to online registration. From this pool, it used GIS software to identify drivers who lived further than 30 minutes away from their nearest post office.

It then filtered prospects against tax disc renewal dates in order to slice up the audience into monthly mailing flies. This preparatory work paid huge dividends, with a response rate of over 36 per cent, a far cry from the one or two per cent that satisfied many companies as little as five years ago.

John Regan, CEO of Ai, says: "Focusing much more closely on targets makes campaigns more efficient, with fewer non-responders. It doesn't mean that the numbers of customers that companies are acquiring via direct mail will reduce. So clients accept there is value to be had from those services, and that keeps the spend up."

There is a growing feeling that the costs and pricing model has had its day. Certainly there is a shift away from commoditised data purchase. Regan adds: "The pricing model should be based on the recognition that profitability comes from efficiency, not from driving the price of data through the floor."

If pricing is based solely on short-term economy, he points out the data will soon cease to exist: it will become old, because owners can't afford to refresh it, or it will be poorly maintained. "We have to stand firm on the value of our proposition," he says. "It consists not just of so many records, but also the result of the analysis we carry out before we even think about sourcing."

Pooling for prospecting
As a sign of changes in the market, Regan says consumer data suppliers now often walk away from a prospective deal because they can't make money from it. This is hurting those brokers who specialise in sourcing data at the cheapest price, as they can no longer fulfil their unrealistic promises. And companies making tenders are starting to realise that firms offering rock-bottom prices can't follow through.

All this heralds a shake-out, with the "cheap and cheerful" merchants most likely going to the wall. But there will be a positive knock-on effect, Regan suggests: consolidation among data suppliers will result in the pooling of data sets, and this will help bring about higher quality.

Clients will be able to choose from more than one record of a particular consumer, as they did when they went to multiple sources for their data. But these days, instead of picking the cheapest for the sake of economy, they are opting to pay for two or even more versions of the same record, in order to have as much relevant data as possible.

"It can be valuable to know that someone has appeared on more than one database;' Regan says. "But also the information will be slightly different and that is useful for targeting as well. So we will see hybrid data pools where data sources combine together, which doesn't happen much at the moment."

Webster too is enthusiastic about the benefits of pooling information. Data is becoming harder to source in the conventional ways: consumers are much more protective of their information, and certain methodologies such as printed surveys, the bedrock of lifestyle marketing ten years ago, have become much less responsive than they were. Instead his company is relying more and more on tightly linked networks of data contributors.

"There is as much data as you could possibly want out there, but it is not necessarily in the right place," he says. "So one has to be cleverer in how one collects and distributes data. Our goal is to try to establish a rapport with our clients, looking at their prospect databases, and helping them utilise their information, while they use ours in a multifaceted way, via a whole network of companies and suppliers."

One has to be cleverer in how one collects and distributes data - Richard Webster, commercial director, DLG.

Another way in which suppliers can help generate better responses is by speeding up the delivery of data. "The more recent it is, the better the conversion:' says Lupa. "Online we can do that in real time, and with post the gap is little more than a day. So clients can act on the consumer information far quicker, which makes the offer more timely and relevant."

With the growth in popularity of rich data and sophisticated targeting techniques comes a greater interaction between buyers and sellers. "In the past, data suppliers were kept at arms length, but these days they are developing closer relationships with their clients," Holmes says. "It's about sharing the objectives and also the responsibility if the responses are not there,"

Could that mean companies paying for the leads that a list generates rather than for the campaign data? Unlikely, since a sale depends as much on the creative and the offer, over which data suppliers have no control. Lupa says he does not know of any attempt to implement "pay-per-response" that is working.

"It sounds tempting but the supplier can't sell the proposition at the point of sale," he says. "We can deliver consumers who are about to renew their policy to an insurance client, for instance, but to actually convert that is the job of the offer itself."

Companies might still prefer to invest in small numbers of certain prospects rather than taking potluck with a large volume of cheap data. "It's a reasonable way to go if the industry is serious about targeting better and causing less waste," says Holmes.

"If you can't buy 100,000 names and only pay for those who convert, it makes sense to buy 30,000 that have a high likelihood of converting. That way you will still save loads."

Of course there is a cost attached: once a list has been winnowed down to likely responders, investment is needed to verify the details. This will normally be done by cross-referencing through different transactional information sources. Business-to-business companies will often use the telephone, but this can also be worth doing for high value consumer items too, such as cars, jewellery or luxury holidays. "Once you have narrowed the list down, it becomes cost effective to invest more," Homes says.

This approach is still quite new but it is starting to gain critical mass, she adds. "It has a logic you can't argue with. It's a question of finding companies that are prepared to test it and then stick with it. If they do they should find the return on investment improving over a period of time." Of course it is up to suppliers to convince clients that this is the way forward.

"There will always be the innovators and people who follow the crowd," she says. "We choose clients who are ready to take that on board and work with us in partnership, and fortunately there are plenty of those around right now."

Volume versus value
Quality of targeting is not the only way to respond to environmental concerns. Another is to shift from postal to email marketing, and this is definitely a major trend, says Zoe Vine, head of data services at the Trading Floor. And it will become even bigger when the acquisition rates increase, she adds; these are as yet relatively low, because marketers have not yet acquired the same level of expertise that they have in mail. But it does not imply a falling-off in demand for data.

Focusing much more closely on targets makes campaigns more efficient - John Regan, eEG, Ai.

"Marketers are still looking to get more value from their existing customer base, appending variables to take them into different markets or to give them different contact methods for different customers, only by email instead of post:' she says.

Any decline in demand will hit large aggregated data sets, while niche lists will continue to bring good revenues, Vine predicts. This is one reason why her company prefers to specialise in particular sectors, mainly insurance and financial services, as well as some travel and charities. It also aims to keep response rates up by limiting the number of contacts for its data.

For instance, insurance lists only go to four different users, which makes them far more productive than if they went out to twenty, as happens all too often. Any revenues that are lost by this voluntary constraint are more than made up for by the premium the supplier can charge for data that is more responsive and niche to buyers' needs.

Any decline in demand will hit large aggregated data sets - Zoe Vine, head of data services, The Trading Floor.

There's no doubt that direct marketers' skills have been improving by leaps and bounds, and that new approaches enable them to avoid much of the waste that so upsets the public. But will this be enough to stop the government imposing legal constraints?

Some feel it won't matter how much mail gets pumped out as long as it is recycled afterwards. The real driver here is the return on investment. "If response increases as a result of better targeting, companies would possibly use us more, and volumes would stay up," says Webster.

But he concedes that perceptions are everything, and direct marketers will not necessarily be given credit for tightening up their act. "Politicians are driven by their own agenda. It's very easy to use us as a whipping boy to demonstrate to voters that they are taking action," he says.

Regan shares that worry, concerned about what steps the government might take in the future to meet fears about global warming. Given the emergence of carbon tax and trading, it would be a logical step to tax other resources such as paper, he suggests. Even if the politicians don't intervene, pressure on suppliers could come from clients responding to public concern. For some time, their contracts include a clause committing suppliers to ethical employment policies, and they are now also requiring similar undertakings to avoid undue waste.

As things stand, this is little more than lip service. Regan says. "What is undue waste? If a company wants to send out a million records we will supply them." But that may not continue indefinitely, and suppliers, especially those who supply the bigger banks, could find themselves having to sign up to some quite specific targets. That may be some way in the future, but one thing that suppliers can be sure of: the pressure is unlikely to let up.

(Database Marketing: Consumer Data - March 2008)

An Appealing Prospect

2008-01-25T15:30:00.003Z

Fake Manchester United replica shirts were the target of a Trading Standards swoop on Oxford Street in the first week of the New Year. The football club had initiated a complaint about its intellectual property being ripped off which led to the seizures.

It could be argued that the club might just have been looking to divert consumer attention. MUFC has been found guilty in a case brought by the Office of Fair Trading of being in a cartel with shirt manufacturer Umbro and leading retailers to keep prices high. Anybody who bought the club’s shirts in 2000/01 from certain outlets can now get a refund and the club has had to p[ay a substantial fine.

Football shirts and prospect pool data may not seem to have a lot in common. Yet when it comes to protecting the value of an intellectual property, there is no difference. And it is as easy to find data users who feel ripped off over the price of data as it is to find football fans who think they pay too much for shirts.

At the heart of both issues is the way in which third parties build prospect pools. For data owners, there is a constant fear that their files are either given a falsely low position in the de-duplication hierarchy or that prospect pool operators imply do not pay the royalties which are due.

“Six weeks ago, one of our telemarketing team came in and asked about our costing on a complicated prospect pool job. A competitor had given a price which, if they were paying royalties as they should, would have given them a gross profit of just £80,” reports Jon Cano-Lopez, managing director of Ai Data Intelligence.

While acknowledging the possibility that the price was a loss leader, Cano-Lopez says this is a common complaint. Ask around and you will find a couple of suppliers regularly named as offering impossibly cheap prices. One of these suppliers is no longer able to licence data from two leading providers because it does not pay out the expected level of royalties.

“We have got to do something as an industry. That is why a company like ours would be happy to undergo an audit at short notice,” he says. Ai has one of the largest commercial prospect pools on the market, so it has to be perceived as an honest broker by data owners.

The consequences fro data owners, prospect pool builders and data users of non-compliance with intellectual property rules is higher prices – but only for those who play fair. BT has had to increase the rate for its OSIS file because it has not been getting the royalties it expected and which are appropriate to its cost base, for example.

“The people who do play the game end up having to charge more than the people who don’t, says Cano-Lopez. Surprisingly low prices quotes during a pitch can only mean one thing – royalties are not being paid. But proving a prospect pool operator has done something wrong is another matter entirely.

Data owners are wary about signing up to prospect pools, especially where the proposition is entirely new and doubly so if the data is derived from client-side activity. The Trading Floor faced a particular issue when trying to build its insurance enquirer pool.

“In the early days, there was definitely an issue about setting up the pool and its benefits – trust was the biggest hurdle,” says Zoe Vine, head of data services at the company. “We’re just coming to the end of our second financial year so we have a bit of a track record behind us now.”

To counter this, her company had a culture of openness and transparency about the way it operates and puts data together. A new data owner will be taken through a very detailed briefing about each stage of the process.

Vine says this serves two purposes – demonstrating transparency and conditioning expectations. “If somebody has a file of 30,000, only 17,000 may make it into the pool, because 10,000 may be internal dupes, 3,000 goneaways and deceaseds,” she points out.

When the royalty cheque arrives, it is important that the data owner does not feel let down. Prospect pool owners may also9 be able to provide tips on ways to improve data quality and value, for example by using online PAF verification at point of entry.

One of the biggest concerns for data owners is that a prospect pool may take a variable off their file without paying for it. Vine says: “We have data ownership rules which we fully share with our suppliers. We give them scenarios for everything that might happen.”

Each prospect pool involves sophisticated matching and merging rules. Recency ought to be the most heavily-weighted factor, but it is easy to believe that cost is given prominence.

Just how those rules are drawn up and applied is the intellectual property of the prospect pool operator, so they are very unlikely to give too much away bout how it is done. That leaves the sense of a black box approach in which explanations about individual decisions can not be given.

That should not preclude being able to provide proofs of how much data has been used and the revenue it has earned, however. “It doesn’t just come down to trust,” says Annette Holmes, managing director of Prospect Swetenhams.

“There is a way of establishing an audit trail because data owners are concerned about their revenue and people may think they’re getting ripped off, but they don’t know how to prove it,” he says.

Her company sits on both sides of the issue as a data owner, with sources such as Market Monitor, as well as a prospect pool operator with its Business Universe. That has driven an emphasis on correct business practices. “We’re trying to establish a process that should overcome those questions,” says Holmes.

That means detailed reporting of how variables have been picked. While critical to establishing trust and proving royalty levels, this approach does have other consequences – for example, if a data source that routinely sits second in the hierarchy becomes unavailable, the selection programmed needs to be over-written to look for the next available source.

“The reason we are doing this is data quality. We have long-term relationships with end clients. Our aim is to develop their return on investment over time as we refine the model. That only works if the data quality is right,” she says. Unless data owners are earning revenues that allow them to invest in data quality, everybody loses.

Tri-direct has adopted a similar approach. “The client has to report on exactly how they have ended up using the data and what they put into the pot to get to that,” says data director Barry Leeson-Earle.

His company requires a double verification from data users. The client must sign-off on a report about the volume and source of data used, while the mailing house must provide a certificate for the final mailed volume. “Clients have got be willing to sign that off and they take it very seriously because it could be used as evidence in court,” he says.

Getting data users to accept the principle of this process was not difficult, although implementing the process can present challenges. Keeping track of the incoming data sources, the hierarchy used and the way different variables are picked off each list is a more detailed requirement that has been place of them.

Nonetheless, it is critical if data owners are to continue to provide their data and invest in its quality. “They have to be happy in the way their data is being used, so we have put this process in place to ensure they can follow the trail. If they have a q2uestion, they can audit us and the end client,” says Leeson-Earle.

As individual suppliers start to adopt solutions to the question of trust and royalty payments, it should create the impetus for change across the industry. Getting agreement on a common standard is unlikely, but it could make open books and audit trails the standard. Something certainly needs to be done because the current fear and uncertainty is not productive or conducive to data quality. With all other aspects of direct marketing becoming more closely accountable and auditable, data will have to follow suit.

“Unscrupulous practices have been going on for years in various forms and largely as a result of the growing pressure to pay less for data,” says Lisa Neville, operations director at EDM Media UK. “We are in an environment where data processing and manipulation is becoming increasingly sophisticated, while at the same time response rates are down compared to what they used to be. The natural reaction is to do anything possible to reduce the cost per response.”

She adds: “The truth is that data owners know very little about what happens to their pooled data. And sadly it’s inevitable that working practices are subject to unscrupulous behaviour because of some obvious market factors. However, it’s something that can be and needs to be changed.”

Data owners have the ultimate sanction by withdrawing their datasets. They are often unwilling to do this because it reduces their revenue. When those revenues do not match up to expectations, it can trigger an alarm.

Unfair processing is against the Data Protection Act as it relates to data subjects. Increasingly data owners are demanding that they are shown the same respect, and prospect pool operators will have to respond.

(Precision Marketing - 25th Jan 2008)

Trading Floor Expansion Driven By Credit Crunch

2008-01-18T15:36:00.000Z

Data trading company The Trading Floor, of Sowerby Bridge , is expanding – and it is all down to the credit crunch.

“As the markets have become more difficult, our strength is the fact we supply transactional data that is accurate.”

“And as companies squeeze marketing budgets they are looking to us for a product that delivers results,” said managing director Chris McDonald, who with financial director Harry Cummine, established the business two years ago.

The company, which collects data to sell principally to the financial and insurance industries, has offices at the Warehouse and Calder House and employs more than 30 people locally. In December it opened a southern office at St Albans, in response to an increasingly high level of inquiries from within the City.

“A lot of our major clients are southern based, although it is not critical we are anywhere,” said Mr McDonald.

Last year The Trading Floor was the inaugural winner of the Evening Courier New Business of the Year Awards with sales of more than £6 million. This year Mr McDonald said he was confident of achieving £8 million.

“We are looking for organic growth through some strong partnerships we have already established, but also keeping an eye on potential acquisitions,” he said. “We don’t go out and look for companies to acquire, our organic growth is sufficient to give us our target”, he said.

The southern office will be run by Peter Mayne as head of agencies and he will be joined by two others in the south of England while maintaining the stronghold in the north.

“The Trading Floor is an exciting young company that is making a big impact in the data industry,” he said.

(Halifax Evening Courier - 18th Jan 2008)

Yorkshire Business Insider - Chris McDonald

2008-01-15T15:10:00.001Z

Chris McDonald, 41 - Managing Director, The Trading Floor and www.thecomparisons.com

After many years working for some of Yorkshire’s top law firms in a sales capacity, McDonald found himself working for a company that specialised in internet lending. He quickly realised that much of the data such companies collected was wasted. McDonald felt there had to be some use for this. “After all, much of the data industry is based on incorrect information,” he says. The result was the formation of Sowerby Bridge based The Trading Floor, a company which specialises in collating “wasted” data and selling it on. “We take the data for nothing, and if we successfully sell it on we share back half the proceeds with the original owner,” he say. The company has over 500 clients, including Barclays, Norwich Union and Asda.

Its success spurred McDonald on in 2007 to launch www.thecomparisons.com, a price comparison site that McDonald says sets itself out from the opposition by charging all companies who want to be featured the same flat fee. He’s already in discussions about customising the site for clients including football clubs and airlines. “It’s exactly how MBNA launched themselves in this country.” he says. “They were producing affinity cards for other people for years before they launched any of their own.”

(Yorkshire Business Insider - Jan 2008)

Time To Beef Up Security?

2008-01-11T15:34:00.002Z

It couldn’t happen here. That was the common reaction across the direct marketing industry to the high profile data losses which so embarrassed the Government at the end of 2007. For a business which relies on personal data flowing between the key operational and execution points in the marketing chain, it seemed unthinkable that large databases could be allowed to go astray.

Which only goes to prove what short memories data practitioners really have. Last year started with the news that a marketer within Nationwide Building Society had taken home a laptop containing 11 million customer records. Following the theft of the computer, the bank was ultimately fine £1m by the Financial Services Authority.

Press those in the know and few would deny that the exposure of personal data in this way is by any means unusual. Data has to be moved around and it has to be worked on. Each of these stages opens up a vulnerability which at best can lead to human error and loss and at worst to exploitation by criminal elements.

Jon Cano-Lopez, managing director at Ai Data Intelligency, says honestly that, “we try to insist with clients that they treat data in a particular way, but sometimes it is not as secure as it should be. Some do just want to send data to us on a CD. We tell them not to”.

The reality is that a two-speed industry exists. Suppliers are moving fast to embrace the highest levels of security, but clients are often much slower to implement necessary measure. They routinely insist that their data services partners work to a higher standard than they themselves embrace.

“The gold standard is secure FTP. That is much better than physical media. And never, ever email.” Says Cano-Lopez, before adding that, “people do. I have seen instances of emails with Zipped files and password protection, but they send the password in the same email.”

Some clients sending data files by email think that using a separate message to provide the password is more secure. But if an intruder has gained access to an individual’s inbox, they will see both messages. Set against this is the tight security applied within database bureaux’ data centres. “Nobody can access any data at all unless they are working in our centre. Even I can’t access and upload files. The data keys are walled off and there is a secure firewall between me and the production sit,” he says.

The issue of access rights is one which is likely to cause a lot of argument across the data industry in the coming year. To keep personal data secure, it should only be available to a handful of individuals who need to carry out specific actions. That means marketers should not be able to download databases onto laptops, disks or portable hard drives for offsite access. That is contrary to the existing culture in which data flows freely and risks are not considered to be high.

Cano-Lopez argues that what is needed is a cash handling culture. “The Government’s problem is both good and bad for us. It is bad because the public becomes aware that we are sending their personal data around and consumers would have a heart attack if they knew. It is good for the industry that people are becoming aware of the issue.”

Solutions to the problem of sustaining data led marketing without exposing data controllers to risk do exist. If recent experiences do nothing else, they are likely to drive greater interest and adoption in new encryption and data management applications.

One of these is LogicBox, which was recently acquired by The Trading Floor. Its ListKnife solution was specifically developed to allow non-technical users to carry out counts and analyses on laptops without creating any risk of data losses.

“The application uses unique reference numbers, not actual names and addresses,” points out Stephen Church, head of business development at The Trading Floor and co-founder of Logicbox. “If you leave your laptop behind, the data remains secure.”

Moving onto systems like this is likely to become widespread on the client side as marketers catch up with what data services providers have been doing. “I’m used to it from working at Equifax where data security was critical. It would be a very naive client and an inconsiderate data services providers that did not bring the issues to attention,” he says.

Church acknowledges that physical media transfers are still a fact of life within the data industry. Disks are still routinely used to send databases to a supplier using courier services. These are assumed to be more secure than the regular mail, but they have just as much propensity for loss and theft, possibly more.

He doubts that it is likely that increased data security concerns will lead to the end of physical media. For databases containing multiple million records, secure FTP is not yet quick or reliable enough. Errors in the transfer could corrupt whole parcels of data and make processing significantly more complicated.

Critically, Church points out that the data industry is not usually dealing with bank account details and certainly never National Insurance numbers. That ought to be seen by consumers as a major reason for having greater trust in commercial data owners than they place in the public sector.

“You can’t say to HM Revenue & Customs that you will not provide them with the data they need or that you will stop dealing with them. But if I lose a client’s data, they would stop using us.” Says Church.

Many bureaux are aware of the vulnerable points in their business and also the limitations in the various methods of transferring data. Part of their proposition is the secure methods they can offer to ensure databases are moved without risk and without exposing either the consumers or the clients to potential loss.

“At Celerity, we always aim to go beyond government best-practice guidelines,” says managing director Jason Lark. “For example, data transfer to and from our clients happens over a multi protocol label switching network, in essence a UK-wide VPN that allows clients to connect directly to our network in a secure and controlled manner.”

The network offers three-tier encryption coding which gives extremely secure data transfers. However good the technology might be that is applied to data transfers, the major vulnerability remains the human factor.

Lark points out that, “finger print and iris recognition technologies are the way forward for data protection on the move. We currently use finger print recognition within our business and it’s an area we’re looking to develop”.

He notes that there is a reluctance among staff to accept iris recognition. This stems from fears about the potential long-term effects on the eye of being exposed to pure light sources. For those working most frequently with data, this could be a latent health problem.

What is not in doubt is the good faith that exists among database bureaux around data security. As Sue MacLure, head of marketing and business development at EHS Brann Discovery, says: “It is almost unbelievable our industry is having this conversation. Having dodgy data practices is like stealing money from grandma’s handbag – it’s unacceptable.”

She adds: “It is unlikely that the direct industry would commit bad data practice out of malice. Mistakes are probably made due to a deadly combination of time and cost pressures, naivety, and failure to take responsibility.”

Processes for keeping data secure take considerably longer than just copying a file onto a disk, zipping it and giving it password protection. Instead, the data has to be properly encrypted and the keys kept entirely separately from the file.

For secure FTP transfers, names and addresses are replaced with codes which are transmitted separately. All of that requires more attention and more time than marketers have been used to giving to their data.

“The industry’s offenders are probably seeing data handling as a process, rather than understanding what the data is, i.e, not just a list of records, but people, with characteristics, behaviours, spend patterns and history. Perhaps thinking of a dataset as a collection of personal diaries would give people the tendency to be a little more careful with how they dealt with it, “says MacLure.

Probably the greatest threat to the data industry is simply that of complacency. It is very easy when data management has become routine and risks seem remote to cut corners or fail to follow correct procedures. This is what is essentially happening every time a marketer loads a database onto a laptop.

What tends to increase security is any extra layer of regulation that might apply. In financial services, for example, there is much more awareness of the need to protect data and to ensure that all parties are compliant.

As Richard Webster, commercial director at DLG, notes: “For companies operating within the financial sector, there are APACS accreditations that can only be obtained with compliance to strict criteria and testing.”

But he adds: “For those operating in consumer data, there isn’t a benchmark at this moment in time. It is a case of businesses operating in accordance with codes of conduct and best practices – and within the Data Protection Act – a position which it is in our interests to evaluate.” That is a thought which many more in the industry are likely to share this year.

(Precision Marketing - 11th Jan 2008)

The Drum - Stuart Watt

2007-12-15T15:43:00.003Z

Stuart Watt, Head of Sales, The Trading Floor

1. What attracted you to the position?
The pace of growth and the fact that they have such a strong reputation for ‘doing things the right way.’

2. What company did you last work for?
Experian Integrated Marketing.

3. What was your first industry job?
Ten years ago as a corporate account manager for Datel Computing.

4. How did you find your new position?
The Trading Floor had been a client of mine for the last 18 months. We had a great working relationship and I finally decided to join them after a couple of ‘invites’.

5. What would you like as your epitaph?
Winner! Sometimes cheesy.

6. What’s your oddest habit?
I am a fully fledged member of the OCD Club. How about eating cheese sandwiches, every work day for five years? When in the office, always wearing my jacket until noon.

7. Who was your favourite teacher at school and what did they teach?
No idea, I remember going to school and that’s about it.

(The Drum - Dec 2007)

Data Strategy Awards - The Trading Floor runner up

2007-12-15T13:48:00.003Z

Against some stiff competition from the likes of DLG and the ReaD Group, The Trading Floor were awarded the runner-up prize for Data Provider of the Year at the recent Data Strategy Awards.

"Running a very close second in this category, The Trading Floor brought a revolutionary new data set to market in October 2005 by enabling insurance companies to exchange and trade their dormant enquirer data through a central, independently-managed data pool. The data is pooled, cleansed, modelled and then traded in the full commercial market. For contributing clients, the company has delivered over £1m in data sales revenue in the last 12 months. Since launch, the company has grown substantially and is currently trading over 10 million names per month. At the same time, clients have been able to improve their cost per response significantly."

Data Is Knowledge And Knowledge Is Power

2007-12-14T17:11:00.000Z

Data interrogation - what data you hold on each customer, what information can be deduced from each piece, how it can be harnessed for future sales prospects. Without reliable data, you can do little to build your strategies.
Segmentation - identifying groups of similar customers. A variety of clustering and profiling techniques can be adopted to identify customers with similar behaviour patterns and demographic trends.
Hypothesis - once the segmentation is complete and you have robust statistical data sets, with a clear model of the customer life cycle, you can start to generate a variety of predictive models for cross and up selling purposes to existing datasets.

Peter is Trading Places

2007-12-10T14:10:00.011Z

Leading database management and prospect pool specialists, The Trading Floor, has appointed Peter Mayne as Head of Agencies. Following an intensive period of growth, the newly created role will focus on optimising opportunities within the agency sector.

Peter has over ten years experience in the data sales industry and has previously worked at LBM, IPT, Prospect Swetenhams and Mokrynski International. He has worked in both list broking and data sales roles and will use his extensive experience to build The Trading Floor's presence in the South of England whilst maintaining their strong hold in the North.

Peter adds: "The Trading Floor is an exciting young company that is making a big impact in the data industry. I'm delighted to be joining the highly reputable team and I look forward to being a part of the next stage of the company's rapid expansion."

Based in St Albans in Hertfordshire, Peter will be reporting to Stuart Watt, Head of Sales at The Trading Floor. Stuart comments: "Peter brings with him a great deal of knowledge to our business through his many years of experience within the data industry. Specialising in the agencies market, Peter's skills will be an asset to The Trading Floor and our ongoing expansion programme."

Merging And Matching

2007-12-06T15:52:00.000Z

The story of UK consumer data supply has traditionally been one of innovation. Whether building and maintaining niche lists, introducing complex stats to build modelled Electoral Roll-based files or offering third-party-supplied names with transactional data attached, this market rarely stands still.

Head to head?
The latest entrants to consumer data sourcing have continued to seek out new sources. The Trading Floor has made insurance application data from the web available for marketing use, while companies like Transactis or Abacus with its Publishing File have brought data that would traditionally be restricted to closed co-ops out to a wider market.

The availability of transactional information on real buying behaviour plus proprietary UK-wide merger databases are the two biggest innovations of the last few years. Now these files are maturing and, with the grater volume and selectivity, are ready to take on lifestyle.

“The pools created by people like Alchemy and Transactis are emerging as alternatives to lifestyle databases,” says Michael Smith, senior account manager at Prospect Swetenhams. “You get plenty of selectability plus the transactional data shows what people really buy. With credit data and many charities contributing, there’s some really interesting stuff on there. It’s used across the board and works well in most sectors.”

Many UK marketers still stay loyal to one data supplier, often choosing to simply licence a large chunk of lifestyle data. Matching the variables to customers, running profiles and then constructing ongoing campaigns is much more straightforward when you only have to deal with one type of data. So are these pools or “open co-ops” really a valid alternative to lifestyle data?

“The majority of proprietary pools still do not remotely have the depth or the selectability or lifestyle,” says Richard Webster, group communications director at DLG. “The source of contributed transactional data also tends to be anonymised so it’s hard to test one source against another. With lifestyle, you can test on 400 separate variables. And there’s also sponsored client questions that simply aren’t possible with a third-party co-op or pool.”

Traditionally, there has been skew on both lifestyle and transactional data. The former because surveys have historically been more attractive to older women, the latter because they are composed of mail order buyers who also tend to be older women: great if you are targeting though the post, otherwise perhaps not so desirable. There’s also a question mark over lifestyle’s reliability though this can easily be addressing by testing.

“You do get a really skewed sample of the population on lifestyle,” says Zoe Vine, head of data services at The Trading Floor. “They tend to be female and over 40, or students. Also, people filling in insurance applications tend to tell the truth.”

“Because of multi-channel collection, the female skew simply isn’t true anymore,” argues Webster. “We take a third from the net and gather the majority of the rest over the phone.”

In fact, with multisourcing and merging now accepted as the best way to get optimal prospect coverage and depth, it’s becoming apparent that lifestyle and transactional data are far more effective working in harmony than posing as alternatives to reach other, whether the merging work is done by the data end user or offered as a proprietary service.

The success of this approach was borne out in the classic 2005 study by consultancy Tank where a multi-sourced file built from two Electoral Rolls (ER) and a third source outperformed individual Rolls on both coverage and predicted response. Specifically, coverage was up 25 per cent with the merged file and 6.63 per cent of its top decile were predicted to respond, the highest figure of all files tested.

Chasing transactional
Collecting data via transactional means in some form and adding it to their base file is becoming very desirable for many data owners. It allows targeting based on actual behaviour rather than what has been claimed in a survey and the continuing customer relationship also serves to periodically validate the data. It’s also a lot cheaper to collect and collate than traditional or even online surveys.

“It’s becoming less and less viable to manufacture data with surveys,” says Chris Morris, managing director of Transactis.

With much of the UK’s data becoming ubiquitous due to multiple licensing deals, merging and modelling work is becoming more of a differentiator in campaign performance, and being able to offer transactional data is very desirable. But it’s not all that easy to get hold of – there are only so many high-volume UK mailers. As in the suppression market, stringing deals to source these files from home shopping or travel companies is conducted in great secrecy in case the competition get wind of it and try and corner that feed for themselves.

For example, Transactis doesn’t pass on transactional indicators to third parties, partly due to the fact that much of the company’s data is only permissioned for analysis and enhancement rather than for list usage. “We keep these for ourselves,” says Morris.

DLG has already moved some way toward this third-party approach by signing up Friends Reunited as a contributor. Though this is not transactional data, customer details are continuously reverified as registered users enter the site.

We’re coming from the other side,” says Webster. “We’re looking to draw other data onto lifestyle as part of our consumer data hub. We’d like to p0artner or acquire a significant owner of transactional data.”

The drive to build multisourced data products is far from new. Companies like Experian have long since used a mixture of their own and external data to build geodemographic segmentations while other suppliers happily employ data from third parties to fill in the gaps in their national coverage. For example, Transactis supplies AcXiom with data to help fill the gaps in the ER base file it used for its modelled Infobase Lifestyle Universe product.

For its part, EuroDirect’s Data Exchange has to be the granddaddy of the open consumer prospect pools and the company could fairly claim to have been well ahead of the game when it launched it almost a decade ago. Claimed to be the UK’s largest prospect pool, it is built from a mixture of every type of consumer data on the market: compiled response lists, credit, lifestyle, contributed transactional information, public register and more.

“We have transactional data that is typically sourced from mail order,” says EuroDirect’s database solutions director Tim Pottinger. He says that the transactional data is more typically used as an indicator rather than being used at a more detailed level to drive offers.

“We use that information at individual level to model out to the rest of the population,” he says. “If someone is mail-order responsive then we’ll use that as an indicator of channel preference. It’s our intentional to gather more transactional data and put it into Data Exchange at a lower level with greater details.”

Beyond the data owners, data-independent companies have been building merged UK files from license third-party data for some years now, with products like CACI’s Ocean and Alchemy’s AMS pool bringing many of the benefits of multisourcing to straightforward “per-thousand” rentals. But to realise the most from multisourcing, some form of data set bespoked to your own requirements is the way to go, bringing together the most relevant files that may not be available in “pre-merged” form.

For the largest mailers, building their own pool in this way has long been the most controllable and efficient way to run prospecting. Over time, more and more marketers have started to take this route, attracted by the results it offers and also by the savings to be made by efficient long-term usage. Pay-as-you-go deals, introduced by Experian and now taken up by a number of other suppliers, have helped ease the upfront costs, but financing a bespoke database build is never cheap.

Accessible pools
Now more suppliers are coming up with a lower-cost route into merged prospect pools by offering their clients access to their master pre-merged database and then adding bespoke data on top rather than starting each project from the ground-up each time. Ai was one of the first to go down this route.

“We have a large merged database as standard,” says managing director Jon Cano-Lopez. “We can build client-specific views based on which supplier data they want to buy. There’s not much transactional data in there as standard, but we will add anything a client wants us to add that is available.”

The company has recently added credit data and also offers Pipeline, a web-based pay-as-you-go list service that pulls records from the same central database.

“This gives access to a multi-sourced pool for smaller users,” says Cano-Lopez, who notes that each client’s view of th4e data in Pipeline has to be set up in Advance depending on how many sources they want access to.

More data owners are now starting to do something very similar to the data-independent Ai, building out from their base data sets by adding in third-party data from other owners and offering them as a richer base for a bespoke pool (and spinning out subsets of the data as list rental sources too). Here, multi-sourcing improves selectability, reduces skew in the original data and crucially makes much large volumes available to sell to their clients.

Transactis has used CACI’s Ocean as the base file for its consumer data from its earliest days and adds in Equifax credit data for pre-scoring prospects, plus Council Tax Band information to help with household and neighbourhood- level targeting.

It labels its Vision service as an “off-the-shelf solution that includes every key data component used in today’s targeting arena”.

“Prospect pools aren’t just a solution for the big mailers anymore,” says Morris. “Prohibitive de-duplication costs from bureaux and poor access to their data are holding companies back. The pre-built element of our solution lowers the cost and we’d add any data set the client wants to mix.”

The Trading Floor has hung its data on a third-party data skeleton since day one (CACI’s Ocean again). With around 8.5 million of its own records, it is now adding more data to the mix to improve volume and details. “We can have fantastic information for one transaction, but might need more behavioural or life stage detail,” says Vine. “We partnered to bolster these aspects. Now we’re adding EuroDirect’s Cameo Financial overlays and merge in more insurance date renewals from external sources.”

With its pre-merged file as a base, the company has recently launched a database management division offering bespoke pool building and online access to hosted prospect databases. However, simply gaining volumes is not what it’s about.

“Anyone can build a UK reference file,” says Vine. “We’re more interested in accuracy. It’s not so much about volumes, it’s the value of the records that are in there.”

The increasing number of merged files and pooling services can make it very hard to tell the difference between the competing suppliers. More and more databases are on offer with most records being the same data license from the same original owners. And where you are dealing with the data owner, there will inevitably be pressure on sales staff to sell their own data rather than that of a third party simply because of the grater margins.

As to how any pool is built and run, any supplier mentioned here should be happy to do it all for you including hosting, or to work with your incumbent data processor if they are doing some or more of the work. With the newest data pools offering cost reductions over bespoke builds due to their pre-merging work, how the lowest “total cost of ownership” matching up with performance during testing looks like the equation to solve. More and more vendors are offering packaged deals rather than volume-based pricing, and the cost-per-acquisition route to pricing we mentioned by all commentators as an option.

Merging the most
So rather than the latest data sources taking over from lifestyle as top dog, the direction is the other way: merging lifestyle data with everything else and seeking out ways to tap transactional data sources that haven’t already been ring-fenced by competing suppliers. A series of “super-merged” UK universes have emerged that, when combined with some specialist files, have performance comparable to the best bespoke prospect pool.

We can see these rich pools becoming the base for a new range of products and services. For example, EuroDirect has long since used Data Exchange as a base for its classifications and now has an alerting service based on new incoming data. If an individual’s income or address changes, they are flagged up for potential contact.

“There’s no getting away from testing in direct marketing, but the combination of transactional, Electoral Roll, credit and lifestyle data has to be the way to go,” says Morris. “Now it’s coming down to two key sources: lifestyle and transactional.

(Database Marketing - Dec 2007)

Karting Rivals To Join Forces For New Year

2007-11-16T16:15:00.001Z

Two young karting aces have put their on-track rivalries aside to join forces in 2008 as they continue to follow their dreams of becoming professional racing drivers.

Harrogate’s Adam Parsley and Knaresborough’s Myles Collins have battled each other tooth and mail at racks all over the UK this year, the pair competing in the Northern Karting Federation (NKF) championship.

Collins eventually came out on top, finishing fourth overall, while mechanical problems denied Parsley the chance to compete on equal terms at the last two rounds, finishing the series in sixth.

But, despite the fierce on-track competition, a healthy respect developed between the two young drivers.

And it looks like the pair will be racing out of the same stable, with both in talks with seasoned racing outfit S8 Racing of Sheffield.

“At least we’d have no worry about these two ending up like Fernando Alonso and Lewis Hamilton in F1,” said Parsley’s father, Steve.

“They fight hard on the track were there’s no quarter asked or given, but once they’re back in the paddock, they’re back to being mates again. “

Collins’ father Chris added: “It helps that they have similar temperaments; when one has a hard race the other commiserates as they know how it feels. But it would be great to see them driving each other on at the front with an experienced team like S8.”

Both Parsley, 13 and Collins, aged 12, plan to move up a category to the 70 mph Junior Rotax class, after spending 2007 in Minimax.

S8 hopes to enter drivers in both national and regional championships, although which series Collins and Parsley will race in has not yet been decided.

“Thanks to sponsorship from Yorkshire Water and York’s indoor circuit F1 Racing, Adam also did the ten round televised Motors TV Karting Challenge this year and finished 11^th overall. It was good experience and we learned a lot about racing at national level – but it’s too early to say where we’ll be in 2008,” said Steve.

Chris added: “We’ll have to see how we get on in winter testing; we have to remember neither Myles nor Adam have raced a Junior Rotax yet so we don’t want to commit ourselves to anything too soon.

“Our two sponsors – The Trading Floor and thecomparisons.com – have committed to work with us again in 2008 which is a great vindication of the work Myles has done to get back to being competitive after a big accident early last year.”

(Harrogate Advertiser - 16th November 2007)

The Trading Floor at Connect Awards

2007-10-05T17:29:00.007+01:00

The Trading Floor were pleased to sponsor the category for the best Direct Mail Pack at the recent Connect Awards, held at the Dorchester Hotel, London.

The Trading Floor drives a data deal with GMAP

2007-08-15T17:59:00.003+01:00

Rapidly expanding data trading firm, The Trading Floor, has signed an exclusive two year contract with GMAP Consulting, which is part of the Skipton Information Group, to provide automotive prospect data for its innovative new cameo driver product, Motorvision.

Following an intense selection process, GMAP, which is a leading market analysis and network planning consultancy, chose The Trading Floor – now the largest multi channel list manager in the UK - as its core dataset supplier for the construction of the new customer profiling product.

GMAP currently provides a large number of motor dealers and vehicle manufacturers with a range of complementary new and used car services including customer and vehicle profiling and verification, prospect management, local market analysis as well as sales planning and stock profiling.

(Precision Marketing Magazine - Aug 2007)

Maximise Results From Previous Marketing Campaigns...

2007-08-01T17:43:00.001+01:00

Zoe Vine, Head of Data Services at The Trading Floor, says:-

Profiling databases and campaign results can be complex and most marketers leave it to the boffins, number-crunchers and analysts. However in reality, results analysis is only as complicated as you make it.

It’s important to work out what sets an individual apart as a buyer, an enquirer or neither so firstly separate your campaign results into responders and non-responders.

In addition to understanding and unlocking your customer base, it is just as important to examine those people who did not respond to establish any identifiable trends or reasons why. You don't need the richest data set to run a profile and segmenting these individuals by the information you already hold in your database will provide an insight into any emerging trends.

Even basic information such as geography, gender, age or income will enable you to sharpen your data segmentation. Alternatively, by matching against a lifestyle database you can gain a detailed lifestyle profile analysing further financial and demographic information such as newspaper readership, charity donations and interests.

This means next time you buy data you can instantly tighten your selections by utilising these prime drivers from your responders whilst actively deselecting and screening out key variables from the non-responder file.

Then, working on Pareto's principle that 80% of business comes from 20% of your customers, you can hone your data selections further still by breaking down your responder file into percentiles based on the amount of business generated from each individual against the initial cost per acquisition. Again, look to identify any emerging patterns or trends and utilise these in your data planning.

Once you start evaluating your campaigns and factoring in external issues such as timing, pricing and product offering, you can be confident that your data is working to its full potential.

(Direct Response: Ask The Experts - Aug 2007)

My Passion - Harry Cummine

2007-05-08T17:39:00.003+01:00

Harry Cummine is Operations Director of insurance prospect data firm, The Trading Floor.

Even though I only picked up a tennis racket for the first time six years ago, the sport has quickly become a huge passion of mine that I now play several times a week.

My 20 year old daughter has played the game to a high standard since she was five. We have always supported her and she now plays in the first team at Loughborough University. It was on a family holiday that she challenged me to a game and taught me to play and I’ve been hooked ever since.

I am now a member at Thongsbridge Tennis Club near Holmfirth where I play at least three times a week, all year round, as well as regularly competing at mixed doubles in weekly box league competitions. The sport keeps me extremely fit and active and I find it a great way to relax.

There’s also a great social side to the sport and I have made some very good friends since I started playing. We even holiday two or three times a year at the famous La Manga Sports and Leisure Resort which has an internationally renowned Tennis Centre with 28 floodlit courts so you can play day or night.

The club has playe d host to a wide range of prestigious events as the Davis Cup and the Fed Cup, as well as numerous ATP tournaments. It is now the official winter training base of Britain's Lawn Tennis Association and the official training centre of the Bavarian Tennis Federation. For any tennis fan, it’s great to be able to follow in the footsteps of some of the world’s greatest players and play on these courts against people from all over the w orld.

Even though Mrs Cummine doesn’t play I am lucky that she is a huge fan of the game and a keen spectator so when I’m not playing we will regularly be watching tournaments on television. Tennis is home to some of the world’s biggest sporting giants with the likes of Roger Federer and Rafael Nadal who are both stunning to watch, highly skilful athletes and most importantly, they are great winners.

Although it’s been a while since UK tennis has won any major events in recent years we still have some great ambassadors of the game and the future looks very encouraging. Tim Henman always plays with huge amounts of determination and will always keep fighting whilst remaining controlled and composed. He’s a great role model for young people watching how sports people act and behave.

In addition to this Andy Murray is making a big impact on the world stage and all the signs suggest that he has a promising career ahead. Again he seems to have his feet on the ground and has a supportive family that will help to nurture his talent.

The future of UK tennis now looks exciting as the Lawn Tennis Association is investing heavily in sponsoring coaching programmes for children at tennis clubs throughout the country. At Thongsbridge Tennis Club for example children as young as three years old are already being coached.

When talents are identified as early as this it should lay the foundations for a promising future and help to lift UK tennis back into the world’s spotlight. If only I’d have realised 30 years ago what a great game it is, maybe things could have been very different!!

(Yorkshire Business Post - May 2007)