TDP Case Studies

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The Data People Case Studies from Nestle to Alliance & Leicester

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TDP Case Studies

  1. 1. Case Studies<br />
  2. 2. Nescafe Ultra Premium<br />
  3. 3. The Brief <br />A major development in the Nescafe UP’s brand strategy was to narrow the target audience that all marketing communications were aimed at.<br />Extensive work by the brand team had re-defined the audience that Nescafe UP would target.<br />Two target audiences called Roast & Ground Dippers and Instant Dippers had been identified – c1.7m HH’s<br />The brief was how, from a data perspective, do we find this audience to allow a major dm sampling campaign to take place<br />
  4. 4. The Solution<br />Nescafe did not have marketing data of their own<br />There was not sufficient volumes of external data to purchase that identified ‘dipping’<br />In order to get the quantity and quality of data needed we proposed data modelling<br />In simple terms, this meant creating a profile of the people we wanted and then finding lookalikes.<br />The secret lay in having the most accurate profile at the start<br />We recommended using Tesco Clubcard data to create the profile that the data model would be built around<br />The model would then be applied to external lifestyle data sources <br />
  5. 5. The Model<br />TGI DATA<br />VALUE DATA<br />£<br />Build Data Model<br />Matched to Claritas database<br />Audience<br />Characteristics<br />
  6. 6. The Results<br />The data model used in the direct marketing campaign proved to be highly successful<br />The mailing delivered £280k uplift in the first three months alone<br />The mailing had an impact on customers behaviour resulting in sustained change over a year – once customers had tried it they remained loyal<br />Customers moved from the targeted product areas of Freeze Dried and R&G proving the model’s accuracy<br />At a brand level customers were most likely to have moved from Kenco Ultra Premium and other Premium freeze dried coffees<br />
  7. 7. Loctite<br />
  8. 8. The Brief<br />Historical events and staff changes had led to there being a number of different unlinked customer and prospect databases<br />Whilst these were being used as a growing repository of new leads as they arose, the following operations were not routinely performed:<br />company name & address validation or cleansing<br />identification of “gone-aways”<br />linking multiple records for the same company<br />tracking the progress and outcome of leads received<br />Loctite required help in formulating the requirements for a consolidated ‘single view’ customer database<br />
  9. 9. The Solution<br />We conducted a short, intensive consultancy exercise:<br /> to review in detail the business requirements that should drive the future database system<br />to identify the functional and information requirements of key decision-makers and members of staff within the business<br />to critique the current databases in more detail and document their strengths and weaknesses<br />to recommend a database solution going forward:<br />proposing the most appropriate database software solution<br />retaining and building on the strengths of the existing systems<br />
  10. 10. The Solution<br />Proposing a single company view that links and makes available all information relating to an individual company<br />defining a closed-loop approach which tracks leads from outset to outcome<br />defining rigorous data capture, cleansing and maintenance processes<br />proposing a suite of reports tailored to the needs of key decision-makers <br />identifying staff training needs and suggesting an appropriate programme<br />addressing questions of core data fields and standardisation of data formats<br />
  11. 11. The Solution<br />In-bound<br />Leads <br />Dashboard<br />Management Reporting<br />Single Customer<br />Database<br />Data Capture<br />Data Appending<br />Data Cleaning<br /> De-Duplication<br />Sales Force<br />Lead Generation<br />Marketing<br />Sales Outcomes<br />Sales Tracking<br />
  12. 12. The Results<br />The consultancy was completed within 3 weeks of being agreed<br />As a result of this work a comprehensive brief was developed to appoint the database solution provider<br />Continued consultancy was provided to assist the tendering and appointment process<br />
  13. 13. Yorkshire & Humber Strategic Health Authority (NHS)<br />
  14. 14. The Brief<br />Coverage rates in the cervical screening programme in the Yorkshire and the Humber were in rapid decline<br />If nothing was done to address this decline then Primary Care Trusts would struggle to meet the national coverage targets<br />A social marketing intervention will be undertaken to halt the steady decline in coverage rates amongst 25-34 year olds<br />Our brief was to profile this age group to get a clearer understanding of which sections of society non-attendance of cervical screening is greatest so that a targeted research programme could be undertaken<br />
  15. 15. The Solution<br />The first challenge was to ascertain whether we could access data on non-attendees.<br />We were able to access full post code data on non-attendance for each of the 14 PCTs in the SHA but no other data would be made available to protect patient confidentiality<br />Working in partnership with Yorkshire & Humber Public Health Observatory we profiled the non-attendance data against 5 geo-demographic classification systems<br />We analysed the data at regional and PCT level and split the age bands into 25-29 and 30-34 sub age bands<br />We also profiled the general female population for the above to allow for indexing<br />
  16. 16. Comparing Non-attendance Volume 25–34 Years of Age with Eligible Population Volume 25–34 Years of Age<br />As a percentage, Group N (Struggling Families) is over-represented when compared against the Eligible population, which means that this group is ‘non-attending’ far more than it should<br />
  17. 17. The Results<br />The data profiling clearly showed Group N (Struggling Families) to be the dominant target audience when it comes to non-attendance<br />This group is consistently prevalent amongst all PCTs profiled<br />High incidence of young single mums appear to be a key feature after further analysis<br />This key audience comes out through all the classification systems<br />This will be a difficult group to influence but we now need to understand ‘why’ they are not attending their screenings and what messages and service offerings will positively influence their behaviour<br />
  18. 18. Holmes Place<br />
  19. 19. The Brief<br />Like many of its competitors, Holmes Place concentrated on acquisition during the unprecedented growth phase of the industry<br />Customer retention and improved targeting for acquisition were recognised as important business drivers as:<br />competition increased <br />cost of acquisition increased<br />attrition rates exceeded 50% per annum<br />Little was known about the customer, and no estimates of customer value and what drives it had been evaluated<br />The brief was to understand the customer better to allow for smarter and more efficient marketing activity<br />
  20. 20. The Solution<br />The first step was to take the client’s membership and transaction databases and combine them<br />Append demographic and lifestyle information<br />Identify valuable customers – including length of membership and additional spend (e.g. personal training)<br />Profiles for each club by value band were compiled<br />In addition, value groupings by type of membership and by number of visits to clubs were made<br />
  21. 21. The Solution<br />Key variables – transactional and lifestyle - for predicting closure of membership were identified<br />The resulting model was applied to the customer base to predict the likelihood of attrition <br />Although there are many factors affecting renewal of membership (such as moving away from the area), many members do not renew because of their lack of usage of the facilities available<br />The models allowed us to identify the probability of each member renewing, and allows communication strategies to be put into practice for valuable but potentially disloyal customers<br />
  22. 22. The Results<br />Targeting for new customers has been revitalised <br />After years of reducing returns from marketing targeted by demographics only, the new models coupled with data cleaning processes have resulted in a five-fold increase in response rates<br />Costs per new member have been reduced<br />Average value of each new member acquired was increased<br />Early indications are that the modelling of likely defectors, coupled with communications designed to retain them, is starting to reduce churn rates<br />
  23. 23. Alliance & Leicester<br />
  24. 24. The Brief<br />Alliance & Leicester had been using cold contact lists to direct potential customers to their web site, with limited success<br />Registered users of the site were segmented by answers to basic financial questions only upon registration<br />Communications to registered users had minimal tailoring<br />With results from nearly 2 years’ activity now available, our brief was to optimise results – <br />Increase visits to the site from dm activity<br />Maximise the potential value of visitors to the site<br />
  25. 25. The Solution<br />The first step was to take the client’s database of registered users, plus a sample file of non-respondents, and append lifestyle and demographic overlays to the data<br />CHAID modelling based on each set of overlays was carried out and gains charts compared to improve targeting<br /> The client’s registered user base was segmented in terms of their long-term behaviour in relation to the site<br />The resulting 6 clusters were profiled in terms of their likely financial requirements and long-term value potential<br />The rules for optimum allocation to segments were modelled using discriminant analysis<br />
  26. 26. The Solution<br />A series of new questions at registration were identified to give the client data to allocate the new user immediately to the appropriate segment<br />
  27. 27. The Results<br />There was an immediate increase of over 100% in site visits generated from direct mail through the improved targeting<br />Value models within the segmentation allowed the client to estimate long-term potential value<br />Thus determining the products advertised and marketing investment for each segment<br />In addition, extra information about customers’ potential value are being added to the model as experience gives us more accurate information about the web-site’s longer term usage patterns and sales values<br />
  28. 28. Jordans Cereal<br />
  29. 29. The Brief<br />Jordans needed to increase its market share in a very competitive marketplace<br />Research showed that the client suffered from low levels of heavy purchase customers relative to the competition <br />Also many of its existing customers did not purchase more than one product in the client’s range<br />Apart from general research the client knew little about its customers<br />The brief was to understand the customer better and to address the above issues<br />
  30. 30. The Solution<br />The only customer data was contained in a file of entrants to promotions and competitions, most of them off-pack<br />The recommendation was to build a customer database from which to run a CRM strategy<br />It would attract new and existing customers by offering free sampling and trialling of the client’s products in return for information on purchasing <br />This would enable us to: <br />understand better the customer base<br />improve targeting of all advertising, both above the line and below the line<br />identify cross-selling and up-selling opportunities<br />evaluate all marketing activity on ROI basis<br />
  31. 31. The Solution<br />Prior to any analysis, the client’s data was cleaned, enhanced and de-duped, and compiled into a relational database<br />Segmentation using appended demographics, lifestyle and attitudinal data was undertaken<br />Several down-market segments of “coupon clippers” rather than existing customers were identified and excluded<br />A re-specified database was compiled to record mailings, coupon redemptions, purchasing data, demographics and lifestyle data<br />
  32. 32. The Results<br />Mailings and door-drops have attracted more “tasters” than was anticipated, most of whom have volunteered information on the brands they buy and how often <br />Purchasing information is now being used as a vehicle for cross-selling purposes, and to identify customers who may be persuaded to buy larger packs more regularly<br />The database now forms an integral part of the client’s knowledge base, and is helping to drive above-the-line activity as well as traditional direct marketing<br />
  33. 33. NTL<br />
  34. 34. The Brief<br />NTL, suppliers of TV, telephone and BroadBand services via cable, had experienced a significant reduction in acquisition rates from their direct marketing – for new BroadBand services as well as their more traditional fare of Analogue and Digital TV and Telephone services<br />With little understanding of the types of customer which were responding to different product offers, they had resorted to mailing everyone with generic offers, and hoping that “something would stick” <br />Of course, less and less was sticking and they need help to market smarter<br />
  35. 35. The Solution<br />Initially, demographic and lifestyle data was matched and appended to the company’s customer and prospect base<br />Profiles were built of customers with each product combination (analogue or digital TV, telephone, BroadBand – the latter at different speeds) and compared with the company’s defined catchment area<br />Within each product combination, cluster analysis identified different groups with different requirements and different lifestyles, identifying opportunities for targeted creative treatments and offers<br />As a result, CHAID analyses for each product combination were carried out<br />
  36. 36. The Solution<br />The models allowed us to rank every prospect and existing customer in terms of their likelihood to respond to each product offering<br />Customers were further classified into segments using cluster analysis, so we were able to:<br />rank all customers and prospects in terms of their likelihood to respond to each product offering<br />identify the best product offering(s) for each customer or prospect<br />use appropriate creative treatments and offers for each customer or prospect<br />use different approaches and compile different offers for existing customers and prospects<br />
  37. 37. The Results<br />Testing of the models against control groups have verified the efficiency of the modelling as well as providing additional information for segmentation<br />Significantly improved response rates have resulted, enabling the client to obtain more new customers and additional cross-selling for the same budget<br />In addition, all new residents in the client’s catchment area can now be scored and the appropriate product offering and creative treatment assigned to them as soon as fresh data is received about the customer or prospect<br />
  38. 38. South Western Electricity<br />
  39. 39. The Brief<br />In the de-regulated electricity market, there has always been a perceived danger of utilities “cherry-picking” profitable customers and using price to deter poorer customers<br />Higher fuel prices for prepayment customers were seen as penalising poorer customers, based on the assumption that only those poorer customers used prepayment methods<br />The Government put pressure on utilities to introduce pricing regimes for prepayment fuel to reduce the incidence of fuel poverty<br />The client wanted to test the assumed relationship between prepayment methods and fuel poverty to enable it to respond to regulatory pressure regarding prepayment fuel charges<br />
  40. 40. The Solution<br />Segmentation and profiling of the utility’s prepayment customer database with appended lifestyle data, identified several discrete clusters of customers who take advantage of the prepayment facility<br />Simplistically, they can be divided into two groups:<br />the relatively poor, who use prepayment out of necessity e.g. for fuel budgeting purposes<br />those who choose the prepayment option because it suits their lifestyle e.g. young professionals, perhaps renting privately<br /> A section of the former are estimated to be fuel poor, but very few of the second group are classified as such<br />
  41. 41. The Results<br />The client used the results of this research to convince government bodies and charity organisations that prepayment fuel purchase and fuel poverty are not necessarily related <br />Subsidising prepayment costs would be wasteful since it would have the by-product of also helping much more wealthy sectors of the community.<br />The analysis of prepayment customers differed significantly between areas of the country, with many more relatively wealthy prepayment fuel purchasers in London and the South East than in more rural areas of the UK<br />So a national prepayment price regime would help the poor more in some areas than in others.<br />
  42. 42. South Western Electricity<br />
  43. 43. The Brief<br />Loyalty to existing fuel suppliers is an important element of utilities’ marketing strategy in the de-regulated market and paramount to continued profitability<br />We were asked to identify likely defectors – to and from the utility, in each catchment area and by combination of fuel – to enable an appropriate communications strategy to be implemented<br />
  44. 44. The Solution<br />Segmentation and profiling of “switchers” (those customers who have already switched their fuel supplier) identified discrete groups of people, with different reasons for switching<br />Discriminant modelling of the separate groups of switchers allowed us to predict switching by an average of 3 times greater accuracy than chance alone<br />
  45. 45. The Results<br />The client was able to develop communications strategies with their creative agencies aimed at the most “vulnerable” customers, both inside and outside their catchment areas <br />Each target group received a different message depending on their profile and likely reasons for switching<br />As a result, customer acquisition costs have been reduced dramatically, and communication strategies for potentially disloyal customers have shown extremely positive returns on investment<br />
  46. 46. Cif<br />
  47. 47. The Brief<br />Jif had been in the market place for 28 years (since 1973). Housewives had literally been using it for years.<br />In January 2001, Jif changed its name to Cif because of Global Realignment<br />The challenge was to migrate as many consumers as possible from Jif to Cif<br />Extensive research had identified considerable resistance to any change of name amongst Jif's core audience<br />Our brief was to Identify the most valuable Jif Cream users who would be resistant to the change<br />
  48. 48. The Solution<br />There were approx. 400k over 55yr. old Jif Cream consumers on Cif’s database. <br />To find more users, we used external data sources.<br />In addition we needed to identify the most vulnerable and valuable consumers - ‘The cream of the Cream users’<br />To find these 'change resistors' we used Social Value Groups (which groups consumer according to their values, beliefs and motivations)<br />Three Social Value Groups (SVGs) - Social Resistors, Survivors and Belongers - were overlaid onto 55+ Jif Cream users<br />SVGs also gave us the flexibility to be able to tailor messages to a particular group's 'hot buttons'<br />
  49. 49. The Solution<br />The three SVG data sets were then run against TNS tracking information to enable us to identify the most valuable consumers<br />There were 200k consumers who were identified as most valuable and vulnerable – ‘Cream of the Cream users’<br />There were also another 800k Jif consumers who formed the next layer in terms of value and vulnerability - ‘Heavy Cream users’<br />The 200k most valuable and vulnerable consumers were targeted with a two stage mailing <br />The 800k heavy cream users received a simple one stage mailer<br />
  50. 50. The Solution<br />
  51. 51. The Results<br />Contrary to the fear of losing sales the brand value has in fact increased by 9% overall <br />The first ‘Cream of the Cream users’ mailing achieved a 32% coupon redemption rate and the follow-up mailing generated a staggering 58% response<br />The sophisticated targeting undertaken to identify the target audience was used in future communications to these groups<br />

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