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How business can unlock value from its customer data.


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How business can unlock value from its customer data.
Provides examples of customer acquisition, customer retention, using behavioural analysis, customer segmentation and mapping technologie

Published in: Business, Technology
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How business can unlock value from its customer data.

  1. 1. Data2dollars<br />How business can unlock value from it’s data<br /><br /><br />1<br />
  2. 2. Agenda<br /><ul><li>The problems facing Sales and Marketing in today’s organisation
  3. 3. The Situation
  4. 4. The Solution, how it works and what it changes
  5. 5. Case Studies
  6. 6. Next Steps</li></ul><br />
  7. 7. Have you ever felt like this?<br />50% of my ad budget is wasted, I just don’t know which 50%<br />My business is a mess of silos of unconnected data<br />I can’t get unique customer profiles<br />If I need access to data for a marketing decision, I have to wait in line for an IT report<br />I send the same direct mail to all of my customers<br />External Data is never taken into consideration<br />I have to use assumptions to drive my analysis<br />I need to know that the right customers are available in the new market<br />My factory sells products to major retailers, but I have no idea what they do with it<br />I don’t understand what type of people my previous buyers were<br /><br />
  8. 8. What we need to do: Convert Data to Dollars<br /><ul><li>How can business unlock value from its customer data?
  9. 9. IT is seen as a cost but data represents untapped business value.
  10. 10. Typically, databases are only used to measure $ historically – sales, revenue and profit.
  11. 11. Databases that work can also help business to:
  12. 12. Attract new customers
  13. 13. Retain existing customers
  14. 14. Identify opportunities for them to spend more
  15. 15. Develop existing customer relationships
  16. 16. …… and thus generate dollars </li></ul><br />
  17. 17. Dollars <br />(Attract– Retain – Grow Customers)<br />Customer Communications<br />Knowledge<br />Data<br />The Data to Dollars Model<br /><br />
  18. 18. Solution: The IT Solution<br />Single Customer View<br />Desktop Applications (All Desktops anywhere)<br />Office<br />Document Management<br />Email<br />Specific Business Applications<br />Analysis<br />Financial System<br />Sales Tracking<br />Product<br />Servicing<br />Warranty System<br />Web Site<br />Databases<br />FINANCIAL<br />DATABASE<br />SALES<br />DATABASE<br />CUSTOMER<br />DATABASE<br />WARRANTY<br />CLAIMS<br />SERVICING<br />INFORMATION<br />CUSTOMER<br />ENQUIRIES<br />EXTERNAL<br />DATA<br /><br />
  19. 19. The Typical Business Environment<br />Dollars<br />Retain<br />Customers<br />Acquire<br />Customers<br />Develop<br />Customers<br />Grow<br />Retain<br />Attract<br />Customer Touches<br />Service Centre<br />Website<br />Call Centre<br />Sales Force<br />Social Net<br />Marketing -- Sales – Service to Repurchase – Upgrade -- Depart<br />Knowledge<br />Market<br />Knowledge<br />Customer Segment& Profiles<br />Customer<br />Behaviour<br />Customer<br /> Relationship <br />History<br />Data<br />Finance System<br />Sales Leads<br />External<br /> Industry Data<br /><br />
  20. 20. The Goal<br />Dollars<br />Higher - Leads, Conversion Rate, Average Sale Value, Margin, Transactions, Lifetime Value, Referrals<br />Retain<br />Customers<br />Acquire<br />Customers<br />Develop<br />Customers<br />Grow<br />Retain<br />Attract<br />Customer Touches<br />Web Site<br />Call Centre<br />Sales Force<br />Service Centre<br />Give the customers that YOU want the experience that THEY demand <br />Marketing -- Sales – Service to Repurchase – Upgrade -- Depart<br />Knowledge<br />Market Knowledge<br />Customer Segment& Profiles<br />Customer<br />Behaviour<br />Customer<br /> Relationship History<br />Ensure the RELEVANT KNOWLEDGE is given to the RELEVANT PEOPLE in the organisation<br />Data<br />Finance System<br />Sales Leads<br />External<br /> Industry Data<br />Transform your existing data into a single view of the customer <br /><br />
  21. 21. How it Works<br />Dollars<br /> Strategic sales programmes designed and built around preferred customer buying process – time, place, opportunity!<br />Retain<br />Customers<br />Acquire<br />Customers<br />Develop<br />Customers<br />Grow<br />Retain<br />Attract<br />Customer Touches<br /> Customer insights provided on desktop viewer power superior decisions & effective customer communication<br />Web Site<br />Call Centre<br />Sales Force<br />Service Centre<br />Marketing -- Sales – Service to Repurchase – Upgrade -- Depart<br />Knowledge<br />Market Knowledge<br />Customer Segment& Profiles<br />Customer<br />Behaviour<br />Customer<br /> Relationship History<br />Delivery of customer insights in a Simple Desktop Viewer<br />Analysis of unified database including external data<br />Data<br />Finance <br />System<br />Sales Leads<br />External<br /> Industry Data<br />Customer <br />Database<br /><br />
  22. 22. Case Study: Fernwood Fitness<br />The Issues<br /><ul><li>Fernwood franchisee applicant looking for funding to open a franchise in a particular franchise area
  23. 23. Government funding agency wanted compelling market data on the viability of the franchise in that area</li></ul>The Solution<br /><ul><li>The ideal profile of Fernwood members was known
  24. 24. Demographic information was analysed to identify the number and location of ideal customers in the franchise area
  25. 25. This was compared with the number and location of ideal customers in other franchise areas
  26. 26. Analysis of this information provided compelling evidence as to the likely turnover of a franchise in the chosen franchise area
  27. 27. Further analysis of the data, using models such as 8 and 10 minute drive time analysis, identified the most appropriate location for the franchise in the franchise area </li></ul>The Result<br />The funding agency minimised its lending risk, the franchisee received the funding and opened the franchise. The franchisee chose the most attractive store location based on the findings of the report and was able to maximise its marketing spend by limiting mail drops to households who fitted the ideal customer profile<br /><br />
  28. 28. Case Study: Health Services Provider<br />The Organisation<br /><ul><li>Provides services to 30,000 mostly elderly customers across Melbourne
  29. 29. Fundraising a major revenue stream
  30. 30. Operational information in 10 different databases across three software systems, managed by different departments.</li></ul>The Issues<br /><ul><li>Same person occurs in different roles in different databases and the organisation cannot tell
  31. 31. The relationship between donors and service recipients or their contacts can’t be established
  32. 32. Change of detail in one system cannot be updated in the other systems
  33. 33. The information cannot be used to understand the customer base better</li></ul><br />
  34. 34. Case Study: Health Services Provider (cont’d) <br />The Solution<br /><ul><li>Set-up a simple software routine to take names and addresses from existing systems on a weekly basis, convert them to new format and add them to a new database. This found about 80,000 people in various databases.
  35. 35. Provided a simple search screen for the new database to find where the same or related clients and their contacts exist in the various existing databases.
  36. 36. Used the results to clean/correct the existing poor data entry practices. (i.e. addresses of “As above”)
  37. 37. Mapped the household locations of the whole community against external data like Census to segment and understand the client base and growth potential
  38. 38. Used this to more effectively communicate with existing and potential clients/donors.</li></ul><br />
  39. 39. Case Study: Major Retailer<br />The Organisation<br /><ul><li>Major Australian Retailer
  40. 40. Single club database of over 500,000 customers receiving direct mail regularly
  41. 41. Provide a range of different products that suit different stages of life
  42. 42. Main customer base is young families</li></ul>The Issues<br /><ul><li>A young single, expecting mother and retiree sent the same type of communication/offer
  43. 43. Specifically households with babies vs. teenagers not segmented
  44. 44. The database not used to help the organisation better understand their customers</li></ul><br />
  45. 45. Case Study: Major Retailer <br />The Solution<br /><ul><li>Customers segmented using their previous spending patterns (RFM analysis)
  46. 46. Outcomes used to predict who would respond to a direct marketing piece
  47. 47. The potential annual savings of not writing to those who wouldn’t respond was $1 per club member
  48. 48. Segmentation tested against the complete mail out and found to have high accuracy
  49. 49. By comparing RFM analysis outcomes and running test communication pieces it is possible to make communication highly effective and relevant to the customer by both understanding what type of person they are and where they are in their spending cycle
  50. 50. People with changing needs identified and communication adjusted accordingly
  51. 51. The results used to analyse the profitability of each of 200 houses across Victoria
  52. 52. The spend compared to total sector spend per 200 houses to allow competitor analysis and better understand market penetration
  53. 53. The profit per communication piece per 200 houses was calculated to fine tune general mail drops and growth areas for NEW customers</li></ul><br />
  54. 54. Case Study: Hardware Manufacturer<br />The Organisation<br /><ul><li>Organisation’s product distributed all over Australia and offered by all the major hardware retailers
  55. 55. Many of the larger stores hold no stock and make few sales, but smaller stores of the same brand have high stock/high sales levels
  56. 56. The only information the company has is through the receipts in their financial system
  57. 57. The sales are made with no co-ordinated sales strategy or information system</li></ul>The Issues<br /><ul><li>No understanding of the split between sales to new houses and the renovation industry
  58. 58. No understanding of the market penetration in different geographical areas and thus the potential to grow the market
  59. 59. No way of knowing how many potential smaller retailers might sell the product
  60. 60. No sales forecasts to give new potential market channels</li></ul><br />
  61. 61. Case Study: Hardware Manufacturer<br />The Solution<br /><ul><li>Sales data extracted from financial system and restructured by geographical area
  62. 62. External data obtained to show the total spend on renovations and new houses in each area
  63. 63. A market share was calculated for each major part of Australia
  64. 64. The top 25% of sales regions were identified
  65. 65. Modeling showed that if the top 25% market penetration was repeated for the rest of Australia then sales would triple.
  66. 66. Lists of all potential retailers were obtained and put against existing sales
  67. 67. Information used to work out different distribution strategies for different parts of Australia</li></ul><br />
  68. 68. Case Study: Residential Developer<br />The Organisation<br /><ul><li>Organisation sells residential housing estates in suburban and holiday areas
  69. 69. Each display house has its own database and sales function
  70. 70. All of the existing advertising above the line</li></ul>The Issues<br /><ul><li>No measured understanding of the household make up of buyers
  71. 71. Potential buyers who visit two display homes are in two parallel sales processes
  72. 72. No strategy to directly target potential buyers
  73. 73. No way of separating dreamers from buyers
  74. 74. No understanding of the sales potential in different geographical areas</li></ul><br />
  75. 75. Case Study: Residential Developer<br />The Solution<br /><ul><li>Sales data extracted from the various systems and formats and combined into a single database
  76. 76. The buyers and visitors database was mapped to understand where they come from
  77. 77. The database was segmented into different household profiles and compared to the general population. One of the identified segments was the “Dreamers”
  78. 78. Sophisticated modeling software was used to rank each group of 200 houses across Sydney from 1 to 10 by their likelihood to visit a display home
  79. 79. The likelihood of each type of visitor to buy was checked
  80. 80. The different types of buyers for different estates was modeled
  81. 81. The results were tested against actual buyers and visitors for the following 3 months
  82. 82. The reliability of the model was:
  83. 83. 38% of the visitors came from the top 10% of the houses
  84. 84. 58% came from the top 20% of ranked houses
  85. 85. 83% came from the top 50% of the houses
  86. 86. This virtually eliminated half the population as not being potential buyers and identified a group four times more likely to buy
  87. 87. This information is being used to both better understand the potential buyer and develop direct marketing strategies</li></ul><br />
  89. 89. Sales per CCD (200 hundred houses)<br /><br />
  90. 90. WHERE DO PEOPLE SHOP ??<br /><br />
  91. 91. Survey respondents by segment<br /><br />
  92. 92. Segments by location <br /><br />
  93. 93. The D2D Proposition<br /><ul><li>We know that to deliver a Memorable Business Outcome you need to build five pillars:</li></ul>IT Infrastructure<br /><ul><li>Most businesses have this in place</li></ul>Meaningful Data Requirements<br /><ul><li>Understanding what we need to know</li></ul>For decision support<br />For performance metrics<br />For strategy<br />Standards, Processes and Business Rules<br /><ul><li>So that there is consistent interpretation – One Version of the Truth</li></ul>People and Organisation<br /><ul><li>Who can access the data and why</li></ul>The Customer Environment<br /><ul><li>External factors data (including web data)
  94. 94. The last four are in addition to most “IT” projects.</li></ul><br />
  95. 95. The D2D Proposition (cont’d)<br /><ul><li>We build a system that meets these criteria in any organisation, along with our recommendations.
  96. 96. We undertake all phases of the system build in parallel.
  97. 97. No silos
  98. 98. Outcomes are demonstrated and tangible benefits delivered very early in the project.
  99. 99. No threat to existing systems
  100. 100. co-ordinatation of systems to deliver the outcomes.
  101. 101. minimisesorganisational change.
  102. 102. Rapid prototyping checks all data, standards and organisational issues that may affect the project, as well as the very early demonstration of results
  103. 103. The system can subsequently operate as a bureau service or as an in-house system</li></ul><br />
  104. 104. First Step: Proof of Concept<br />Customer Interviews to provide information on the existing environment, systems, data, knowledge etc<br />Review the Existing Environment and write a Short Report outlining:<br /><ul><li>The benefits of a Single Customer View to the business
  105. 105. The steps required to obtain the benefits
  106. 106. Time and Cost</li></ul>Build a prototype that uses real data and delivers some real answers:<br /><ul><li>Take a copy of each database
  107. 107. Put into a temporary analysis database
  108. 108. Run some basic analysis to demonstrate potential outcomes</li></ul>Evaluate business value and agree to proceed to full project. <br /><br />