Session 6: Managing the Data - Fabrizio Vigo

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Session 6: Managing the Data - Fabrizio Vigo

  1. 1. 1 Data and model to support TransPromo communication Fabrizio Vigo CEO Consodata SpA European TransPromo Summit Brussels, 6-7 October 2009
  2. 2. 2 Agenda Direct Mail & Trans Promo communication: Overview The approach to an efficient 121 communication – Customer Table enrichment – Target selection – A “tailor made” communication Some real examples
  3. 3. 3 Direct Mail over view • In 2007 the Western Europe postal services processed 18 billion items. (*) • Direct mail in Western Europe has grown up, and it has been valued at 40 Billion € and accounted for 32% of spending traditional media.(*) • In Italy the Direct Mail is the 5% of the Below the line communication, which represents the 49,5 % of the advertising market. (**) (*) Source: “Mail Trends Update” – Feb. 2008 (**) Source Eurisko Search - Oct .2008
  4. 4. 4 Direct Mail in Italy In Italy per month: • the 91% of household receives direct mail communication and the average number of postal objects received is of 7,8. • The 53% of household receives an addressed direct mail communication and the average number of addressed postal objects received is of 2,8. Average reading time dedicated to addressed direct mail is around 4 minutes, slightly less for un-unadressed communication. (**) Source: Eurisko Search - Oct .2008
  5. 5. 5 Trans Promo: features As we know, the Trans Promo communication consists in shipping transaction documents, such as statements, invoices and notifications to an existing customer. Research stated that the 95% of transaction documents are opened and read. Trans Promo communication becomes part of the customer experience and can be used to established a long term relationship with the end customer.
  6. 6. 6 Trans Promo: plus • Direct marketing cost reduction • Cross selling/up selling improvement • Strengthening the Brand • Improving customer retention • Increasing number of client reaction to a specific call to action & promotion • Increase loyalty
  7. 7. 7 A succesfull Trans Promo • Is strictly based on the full understanding of what consumers wants. • Consumers has shown to prefer an addressed mail as a way to receive promotions • By studying purchasing customers experience it’s easier to drive marketing strategies towards each customer need. The fact is: how to enrich and profile the customer base to fully understand needs, habits and “taste” to make with transpromo a direct and effective promotion with high redemption.
  8. 8. 8 The approach to an efficient 121 communication Kn Qu ow ize ali an fy O rg h r ic En E AS E R B G” T OM ETIN U S AR K C M “ Communicate Improve loyalty
  9. 9. 9 The approach to an efficient 121 communication Data Treatment & “Tailor Made” Profiling Enrichment Communication To qualify a To identify the best To act personalized customer base and sales strategies: promotions by get useful cross/ best/up selling, target, product and information to by product and sales channel select and profile define the most target receptive target to a specific promotions.
  10. 10. 10 Data Treatment & Enrichment The Data Treatment consists in performing all necessary operations to make a Customer Base able to efficiently support CRM and 121 Marketing DATA QUALITY ENRICHMENT ORGANIZATION AND MANAGEMENT of the available info
  11. 11. 11 Data Treatment & Enrichment In details, Data Treatment allows to: – Save cost in direct communication – Improve efficiency in elaborating process – Get better quality and insights into customer database analysis
  12. 12. 12 Data Treatment & Enrichment The steps to be followed: Useful activities for the following phases Normalization, geocoding and data deduplication Necessary activity for the enrichment phase Matching with qualified data base Basic activity for profiling Enrichment of the matched data with Consumer e Business information.
  13. 13. 13 Normalization & geocoding Normalization is a process which re-allocate addresses to official denomination, it is an essential activity for posting, matching different database and improving the database quality. Geocoding allows to place addresses on territory at house numbers level and to enrich data with statistical information of the census block in which each data is located.
  14. 14. 14 Data Cleaning This process permits to eliminate double data from different database or from a single one, assuring a saving in communication cost besides the shipping of correct messages (no double messages), as guarantee of company reliability.
  15. 15. 15 Data Enrichment Matching and Enrichment This process compares, recognizes and matches data from different archives accordingly to an assigned criteria to enrich the customer data base with available and additional info, both individual or statistical info (micro-territorial). It enables to know and highlight main characteristics of the customer DB to better understand their needs, habits and behavior.
  16. 16. 16 Data Enrichment: Which info collect? Consumer – First and Last Name Personal data – Address Behavioral data – Telephone number – email – sex Lifestyle data (ex: credit – age cards usage, hobby, Socio-demo – Income level reading, travels.) info – Job description – School level – Household members
  17. 17. 17 Data Enrichment: Which info collect? Business – Company name Company data – Legal Form Product – Fiscal code Segmentation data – VAT Number – Address – macro/product – Telephone # category – url – Logical grouping – Market type and area – Employees number Structural data – turnover – import/export amount
  18. 18. 18 Target Selection: profiling Target group selection Qualified info availability permits to define CUSTOMER specific target into the Customer Base and BASE identify profiling variables (personal and enriched territorial). Models Estimation The methodology generally used is based on Logistic / Decision logistic regression and decision tree, by using Regression Tree Models just personal data (Individual model) or jointly Estimating Target territorial and individual info (Mixed Model). affinity to individuation belong to a rules target
  19. 19. 19 Target Selection: profiling Validation Models The double approach (Individual and Mixed) permits Training set to understand and “see” variables and scoring rules able to discriminate the belonging of single data to a specific Target, directly on the training Validation set set and to approve its efficacy. (Validation set). Target rules Inference A scoring model availability is useful to qualify the customer base data and to evaluate the target CUSTOMER affinity level. BASE enriched
  20. 20. 20 A “tailor made” communication The Customer base profiling with the enrichment of all available info, is more complete and it helps in defining and planning a better and more efficient direct promotion using the most appropriate media. A communication act is effective if “straight”, in content and creativity, to the addressed customer profile
  21. 21. 21 A “tailor made” communication Trans Promo communication is, by its nature, “a tailor made” communication, joining the transactional messages with the promotional ones. Customer Base Profiling supports at its best the Trans Promo communication, besides “exalting” its own features.
  22. 22. 22 …a virtuous cycle CUSTOMER Direct and BASE personalized enriched Profiling messages “Osmosis” and continuous feed Mailing Returns analysis
  23. 23. 23 Some real examples 100,0% 10 0 , 0 % target Cumulative % Decile Mailing % Index number intercepted distribution 90,0% Line of perfect equality 9 0 ,0 % Lorenz curve 80,0% 8 0 ,0 % 0 25.000 22 1,23% 1,23% 12 74 , 4 % 70,0% 58% 70 , 0 % 1 25.000 56 3,12% 4,35% 31 60,0% 6 0 ,0 % 2 25.000 94 5,21% 9,55% 52 56 , 5% 3 25.000 98 5,43% 14,99% 54 50,0% 50 , 0 % 4 2 ,3 % 4 25.000 129 7,19% 22,17% 72 40,0% 4 0 ,0 % 3 1, 7% 5 25.000 171 9,55% 31,72% 95 30,0% 3 0 ,0 % 2 2 ,2 % 6 25.000 189 10,55% 42,27% 106 20,0% 2 0 ,0 % 15, 0 % 30% 7 25.000 256 14,26% 56,53% 143 10,0% 10 , 0 % 9 ,6 % 4 ,3 % 8 25.000 321 17,90% 58% 74,43% 179 0,0% 0%% ,0 1, 2 % 0% 10,0% 20,0% 30,0% 40,0% 50,0% 60,0% 70,0% 80,0% 90,0% 100,0% 9 25.000 459 25,57% 100,00% 256 250.000 1.795 100,00% The last decile of the model is able to The achieved concentration level, enables intercept the target more than twice to contact more than 58% of prospect with respect to the average value with 30 % of mailings

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