IBM Case Study Agility & Analytics

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IBM Case Study Agility & Analytics

  1. 1. IBM Case Study Agility& Analytics Pam A. Evans Marketing Consultant pam@pamevans.net Bob Slaker IBM NA Demand Programs Lead & WW Project Director - SPSS
  2. 2. 2 Agility and Analytics Agenda • CMO Priorities on Data and Social Media • Engagement, Branding and Segmentation • How IBM Tracks the Health of Its Business ─ SPSS Experiences ─ SPSS Story ─ Customer Stories ─ Thoughts Social Networking Sites and Communities
  3. 3. 3 CMO's Top 2 Issues: Data Explosion and Social Media Source: Q8 How prepared are you to manage the impact of the top 5 market factors that will have the most impact on your marketing organization over the next 3 to 5 years? n=149 to 1141; Q20 To what extent will the opportunity to collect unprecedented amounts of data require you to change? n=1629 to 1673 Under preparedness Percent of CMOs selecting as “Top 5 Factors” Data explosion 71% Social media 68% Channel & device choices 65% Shifting demographics 63% Financial constraints 59% Decreasing brand loyalty 57% Growth markets 56% ROI accountability 56% Customer collaboration 56% Privacy considerations 55% Global outsourcing 54% Regulatory considerations 50% Corporate transparency 47% Need for change to deal with data explosion Percent of CMOs indicating high/significant need Invest in technology Understand analytics Collaborate with peers Validate ROI Address privacy Integrate insights Rethink skill mix 73% 69% 65% 64% 52% 49% 28%
  4. 4. 4 From the HBR Blog … Marketers Flunk the Big Data Test • “Most rely too much on gut” • “A majority struggle with statistics” – 44% got four or more answers wrong on a five question aptitude test; – Only 5% of marketers even own a statistics text book • “Some are dangerously distracted by data” – Over react to “blips” in dashboard data – Focus on response-metrics vs customer loyalty or lifetime value • “The best focus on goals and filter out noise – But that is only 10% – Need to reiterate critical business goals, and teach to put data front and center Read the article at: Harvard Business Review Blog Network
  5. 5. 5 The point … – You will need to develop or acquire the expertise to use analytics – Short term, there are not enough “data scientists” to go around – Marketers will need to be able to “speak data” to help ensure successful outcomes
  6. 6. 6 Agility and Analytics 1. Set Measurable Goals 2. Ensure KPIs align to goals 3. Understand the results in terms of actions
  7. 7. 7 Creating a system of engagement.
  8. 8. 8 What is the speed at which you can get data for decision-making?
  9. 9. 9 Full Landscapes rely on timely and usable data
  10. 10. 10 Data Mining Social Media Analytics Statistical Analysis Social Network Analysis Analyze Relevant Customer Data Sentiment Analytics
  11. 11. 11 Are your tools and methods enablers?
  12. 12. 12 IBM Digital Dashboard: An Agility Project • Key performance metrics defined to understand and act – Importance of connecting marketing data to sales  Two -week status checkpoints on new enhancements – Analysts recommend actions based on a series of factors and trends
  13. 13. 13 Worldwide analytics for Smarter Planet • Total visits continue to climb, with 30% more visits in 2011 compared to 2010 • WW Dashboard by Smarter Planet topic to understand visitor behavior – Reach and Engagement – Daily and monthly visits trends – Top pages and page types – Traffic Sources • Top Domains • Organic Search and Paid Search • Social Media – PDF downloads, Video plays and Top Solution pages
  14. 14. 14 Web Analytics investigates Customer Navigation Funnel Analysis • What % of customers are reaching their destination? • What % of initial customers completing the form? Path Analysis • What % of customers are leaving the site? • What are the most popular links for this path?
  15. 15. 15 Social Impact Metrics* SiriusPerspective: The shift away from traditional brand metrics (reach, sentiment, share of voice) is critical to show impact. 28% 8% 16% 34% 14% Traditional brand metrics Customer satisfaction/loyalty Analyst influence Demand increase Revenue What are the top metrics you use to measure impact? *Copyright by Permission of
  16. 16. 16 IBM SPSS … our own case
  17. 17. 17 While we sell analytic software…
  18. 18. 18 …we were the cobbler’s kids.
  19. 19. 19 “Membership” has its advantages„
  20. 20. 20 Analytics provides the ability to understand each step in the waterfall
  21. 21. 21 Predictive factors to get that win! Firmographic Psychographic Buying cycle Sales Cycle Demographic Marketing cycle
  22. 22. 22 Buying Cycle Interactions 22 A I C E P CA ED CV N T A B Marketing Cycle—CA > ED > CV = Create Awareness > Educate > Convince > Offer Buying Cycle—A > I > C > E > P = Awareness > Interest > Consideration > Evaluation > Purchase Sales Cycle—N > T > A > B = Need > Timing > Authority > Budget Marketing Cycle Buying Cycle Sales Cycle O
  23. 23. 23 Consistently capture and analyze interactions developing a digital thumb print
  24. 24. 24 Synchronize marketing processes to create a closed loop and global view of the customer Synchronize marketing processes to create a closed loop and global view of the customer
  25. 25. 25 Embed predictive capabilities to drive personalized campaigns and micro-targeting
  26. 26. 26 Gain real-time intelligence
  27. 27. 27 Combine attitudinal and survey-based data with social media sentiment to anticipate and target new segments
  28. 28. 28 What did it take? Give up old views Better alignment with sales Recognize that it takes more than great creative to get results Understand that we no longer control the message “Radar” has to go out further Organizational behavior affects individual behavior
  29. 29. 29 Quick Case Studies
  30. 30. 30 Meteolytix Hidden influences
  31. 31. 31 Meteolytix – uses analytics to build sales forecasts for retail and service sector clients The Challenge: Develop improved ability to make precise sales predictions at branch locations for bakery chain The Process • Client bakeries had observed that purchase types varied with weather • Combined data from multiple sources … – Historical sales figures – Vacation and holiday dates – Local competitive environment – Marketing activities – Weather • Provides sales forecast to identify how much of what to produce at local bakeries – Drizzle is typical cake weather – Heat wave associated with higher sales of grilled sandwiches – Continuous rain increases sales in some locations, and decreases in others • Beginning to apply microforecasts to other industries … hairdressers, energy producers etc.
  32. 32. 32 Meteolytix The outcome … – Improved availability of exactly the right products – Reduces returns/spoilage by 33% – Reduces waste and environmental impact – Increases customer satisfaction The Point … What hidden influences do you have that affect your business? Are you taking advantage of available data about them? Learn more at: meteolytix case study
  33. 33. 33 Rabobank Real time for real results
  34. 34. 34 Rabobank – financial services leader The Challenge: To Better understand individual customers to create strategic offers for cross, up and deep selling The Process … • Combined data from three types of interactions: outbound campaigns, “event” driven (like birth, marriage etc.) and incoming activity • Added in knowledge from market research and data mining. • Identified product clustering and sequencing – Customer with savings account, responsive to investment offers – Transfer of large sum to account indicates potential immediate interest – requires rapid response – trigger lead or offer • Identified customer channel preferences for contact by an advisor directly or through a direct marketing channel • Target campaigns by identified groups, using the appropriate channel • Using analytic software, able to deploy predictive models immediately • Synchronize customer data with analytics in real time – daily updates to branches on who to target and how
  35. 35. 35 Rabobank The Outcome … – Contact channel optimized for each customer – Marketing campaign launch cycle reduced by at least four weeks – Just in time identification of leads for quick response to customer opportunity – Campaign costs reduced, and success rates increased The point … Are you integrating analytics into your normal work stream to increase agility and success? What can you do to make that happen? Learn more at: Rabobank case study
  36. 36. 36 UNICEF No more “not you again”
  37. 37. 37 UNICEF – child rights organization of the UN The Challenge – increase funding from contributions, with minimal resources - outbound direct mail had lost growth potential and CRM system with operational data had limited analytical capability The Process … • Combined third party lifestyle data with millions of house records • Incorporated results data from marketing activities over the years • Applied analytics on massive data to identify who to include and who to exclude from campaigns
  38. 38. 38 UNICEF The Outcome … – Identification and mapping of contributors identified clear-cut donor segments – Analysis and results easily put in visual presentations to improve insights – Doubled response on neighborhood level campaigns – Yield became predictable, so campaigns became more effective and efficient – Minimized “irritation” of mis-targeted campaigns The Point … Use of analytics enabled not only improved campaign results, but minimized negative reaction from off-target recipients. Who you don’t market to can be as important as who you do market to. Do you know who to leave out? Learn more at: UNICEF case study
  39. 39. 39 Telerx Listening to the voice of the customer
  40. 40. 40 Telerx – contact center • The Challenge – transform to gain competitive advantage in evolving market • The Process … • Analyze unstructured and structured data • Unlock value in thousands of daily voice recordings • Support advanced predictive modeling • How … – Incorporated data from social media channels, such as FB, Twitter, blogs and forums – Automatically transcribed voice recordings – Consolidated into data mart along with call center notes and CRM data – Mined text data – Presented as a series of intuitive graphical reports
  41. 41. 41 Telerx Outcome … – Incorporating voice transcription yielded twice as many insights as social media or notes alone • Analysis identified areas of interest that the call center scripted questionnaires would not have captured – Able to identify “hot topics” in social media and prep call center for volumes and scripted responses even before calls begin coming in – Automated dashboard report highlight patterns and trends in consumer behavior so can act The Point … Are you taking advantage of what your customers and prospects are literally telling you? Or are you forcing their feedback into what you think they are talking about? Learn more at: Telerx case study
  42. 42. 42 Some additional thoughts …
  43. 43. 43 Thoughts … • Ready or not, analytics is part of marketing • Nothing has changed, everything has changed • Look for data in places you may never have considered • Agility is essential • Need to focus on the right data • Fast is good; faster is better
  44. 44. 44 Thank You! pam@pamevans.net bslaker@us.ibm.com

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