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A Pragmatic Approach to Analyzing Customers


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The business market is different today than it was 20 years ago when BI got started. We're just beginning to grasp how to work within the new economic and communication models. Companies can't rely solely on financial and operational metrics any more, and need to analyze customer behaviors in more detail.
 The big change in analysis is a move from mass market metrics to individualized data, no longer analyzing or managing by averages. The stream of events and observations available from applications today combined with new platforms for collecting and processing data enables (relatively) easy analysis.
 Despite this, many companies struggle to analyze customer data. This talk will describe a handful of customer metrics and models that are (relatively) easy to do, yet are often not done. It's often easier to succeed by stringing together a handful of simple techniques rather than applying advanced techniques.
 Expect to come away from this session with:
- a little history of customer data use by marketing and how that has changed in the last 10 years.
- the most common behavioral data sources you have available.
- some of the basic questions that often go unanswered, and data that is not assessed in the proper context.
- some basic analyses you can perform.

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A Pragmatic Approach to Analyzing Customers

  1. 1. A Pragmatic Approach to Analyzing Customers Mark Madsen @markmadsen
  2. 2. What happened in the overall market?
  3. 3. © Third Nature Inc. The Internet happened and companies are still reacting The internet is unlike all prior media channels: it allows for two- way communication, enabling entirely new practices.
  4. 4. © Third Nature Inc. From the brand as controller of messages in a channel…
  5. 5. © Third Nature Inc. …to the brand as participant in interactions in an arena.
  6. 6. © Third Nature Inc.© Third Nature Inc. Bad news if you want to reach people via advertising Number of prime-time 60 second TV commercials required to reach 80% of 18-49 year-olds ▪ In 1965: 3 ▪ In 2002: 117 People with DVRs watch 12% more TV  90% of them skip the ads 
  7. 7. © Third Nature Inc.© Third Nature Inc. The obvious solution hasn’t worked very well.
  8. 8. © Third Nature Inc.© Third Nature Inc. One-to-One marketing concepts fared little better.
  9. 9. © Third Nature Inc.© Third Nature Inc. Changes to Communication Channels Old model: ▪ One-way ▪ Outbound ▪ Interrupt-driven marketing ▪ Messaging New model: ▪ Two-way ▪ Inbound, outbound and between peers ▪ Event-driven marketing ▪ Messaging and listening
  10. 10. © Third Nature Inc.© Third Nature Inc. Social Software Affects Buying Behavior for Business
  11. 11. © Third Nature Inc. Everyone is a Direct Marketer Now
  12. 12. © Third Nature Inc.© Third Nature Inc. The (mass) Marketing Process This is designed for a mass market where you create a few to dozens of stable segments, with hundreds of thousands or millions of members in each. Analyze and segment the market and/or customers* Create offer Execute campaign Record results Feedback *or not
  13. 13. © Third Nature Inc.© Third Nature Inc. Hard because measuring results is hard ? The assumption is this: What happens in the middle is largely a mystery because of the nature of mass communication and transaction channels. Mass marketing treats people similarly, but with slightly more refinement owing to segments associated with channels.
  14. 14. © Third Nature Inc.© Third Nature Inc. Direct Marketing is Not Mass Marketing Responses differ, so craft offers for segment-specific goals. More offers, segments, faster feedback, constant resegmenting. Many segments, and most often derived from behavior. Individuals uniquely identified. Create customized offers Execute campaign Record results Feedback
  15. 15. © Third Nature Inc.© Third Nature Inc. Better, but more complex, result measurement ? The assumption in direct marketing is this: There is more visibility into which campaigns best lead to actions and which customers are best* but still a visibility gap. Direct marketers still treat people similarly, but with more refinement owing to direct response visibility. ? ?
  16. 16. © Third Nature Inc.© Third Nature Inc. The Obligatory Funnel Diagram Most of marketing’s efforts today are in the area of customer acquisition. Marketing tries to generate awareness within an audience, some of which become prospects. When prospects are interested they become sales opportunities. When they are interested enough to consider your product they are leads. If they take action (purchase or donate) they are customers. Satisfied (happy) customers can become proponents. Audience Prospect Opportunity Lead Customer Proponent
  17. 17. © Third Nature Inc.© Third Nature Inc. Conversion Rate: Where linking to the DW becomes important Most marketing to sales metrics (particularly with web analytics) track back to a single core transaction metric: conversion rate. Rates usually bounce around between 1% and 5%, depending on industry.
  18. 18. © Third Nature Inc.© Third Nature Inc. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Bounce rate Take rate Qualification rate Abandon rate Online conversion Viewing Conversion Rates Properly Mis-targeted Opportunites Leads Losses Customers
  19. 19. © Third Nature Inc.© Third Nature Inc. The funnel concept is too narrow It ignores non-transactional marketing. It ignores the customer’s post-acquisition interactions with the organization. After spending money to acquire a customer, attention must be paid to service aspects of the relationship, and there are multiple feedback loops. Marketing analysis for brand campaigns and customer acquisition. Analysis for customer retention and customer lifecycle management. Audience Prospect Opportunity Lead Customer Proponent And these areas are not normally marketing’s responsibility so not in their customer repository.
  20. 20. © Third Nature Inc. Post-purchase data is needed for experience measurement You need to get post-purchase data and support tracking of marketing activities for the post-sale period. ▪ 60% of consumers of facial skin care products research more after purchase. ▪ 20% of evaluated CPG purchase decisions are made differently at the point of purchase You have to look at data from the perspective of customer phases of activity: Useful beyond marketing: product features, design, sales experience (store, web, phone), service Consider Evaluate Purchase Post-purchase
  21. 21. © Third Nature Inc.© Third Nature Inc. It’s a Multi-Channel World There isn’t one funnel, there are many small funnels that combine to form the big picture. Each of these new channels has measurement data coming from different sources, often external and out of your control.
  22. 22. © Third Nature Inc.© Third Nature Inc. High Level View of Common Primary Channels Communication Channels Radio TV Print Online Web site Email IVR Social networks SEM Display ads Mobile Games Each of these has individual metrics, some of which are standardized in the traditional channels but only for some online.
  23. 23. © Third Nature Inc.© Third Nature Inc. Communication channels are not transaction channels. One drives people to the other. ▪ Measuring communication channels is about the communication process and the expected outcomes in transaction channels. ▪ Measuring transaction channels is about the performance and processes of those channels. TransactionCommunication Marketing Measurement = Channel Measurement Online Print Radio TV Online In-person Phone Campaigns can cross communication channels. TX channels overlap and cannibalize each other.
  24. 24. © Third Nature Inc.© Third Nature Inc. The Online Channels Have Advantages The online channel can provide realtime feedback where old marketing channels sometimes have a data lag of months. Messages and offers can be tested while a campaign is running, rather than between campaigns. This requires that you collect the data to manage the process, while the process is running.
  25. 25. © Third Nature Inc.© Third Nature Inc. Customer data is usually functionally aligned Each function has specific applications and processes, usually supported by local reporting and BI. Sales automation Audience Prospect Opportunity Lead Customer Proponent Customer master Marketing automation Call center automation Sales BI Marketing BI Call center BI Unifying customer information and contact processes was something CRM was supposed to do for us. Web? Social media? Mobile?
  26. 26. © Third Nature Inc.© Third Nature Inc. What Marketers (and Organizations) Say They Need Individual, cross-channel, lifetime history: 360o
  27. 27. © Third Nature Inc. The customer experience is of supreme importance …and it’s missing from the 360o view.
  28. 28. © Third Nature Inc. People do not experience the world in channels. “Online” is just part of everyday life. They see one organization with multiple touchpoints, not fragmented channels. This is how you have to view your organization’s interactions. Your view of them Their view of you
  29. 29. © Third Nature Inc. Customer experience has fuzzy definitions A measure of quality, the total of all interactions a customer has with your organization’s product or service. ▪ Utility ▪ Quality / reliability ▪ Ease of use / usability ▪ Aesthetics An attempt to measure how good your product or service is. The basic thing being measured is (quality of) interactions.
  30. 30. © Third Nature Inc.© Third Nature Inc. Experience is about integrating individual interaction preferences
  31. 31. © Third Nature Inc.© Third Nature Inc. Customer Experience Experience drives other metrics Loyalty and satisfaction have a direct impact on financials (revenue, profitability, market share), so the goal should be to improve experience, which means (a) fix problems (b) make things better Utility Quality Usability Aesthetics Loyalty Satisfaction Likelihood to: Repurchase Discontinue Defect Recommend
  32. 32. © Third Nature Inc.© Third Nature Inc. What about Word of Mouth? People talk about experiences. Online measurement and social software allows for watching something which could only be surveyed for in the past: what people say. ▪ Awareness ▪ Sentiment ▪ Reputation ▪ Buzz ▪ Feedback But these things are harder, fragmented across multiple external channels and sources.
  33. 33. © Third Nature Inc. Measurement? What measurement? forrester
  34. 34. © Third Nature Inc. Kinds of customer analysis questions: acquisition, management, retention, reactivation What are the characteristics of our customers? Who are our most profitable customers and how do we retain them? How to improve customer satisfaction? How do we reactivate lost customers? Attract new customers? Increase sales? Make our less profitable customers more profitable? Manage high -risk customers? Reduce acquisition or customer management expenses? Dubai April 28th, 2013
  35. 35. © Third Nature Inc. There’s a lot of hype related to big data and analytics
  36. 36. © Third Nature Inc. Closed loop process to monitor marketing Create an offer (promotion, call to action, thing of great beauty) Publish it Monitor it React to it Make adjustments (push it, tweak it, fix it) Stop it or move on Unlike older media models, online/digital allows for rapid adjustment. We’re interested in the monitor/publish part, which is more complicated than the usual BI work
  37. 37. © Third Nature Inc. Why is this more complicated? The data sources ▪ Often (usually) not a DB ▪ Frequently want to see up-to-date results ▪ Many different sources / elements for one campaign The data ▪ Need to see data for elements as well as the aggregate (which might mean different/missing data for different elements, e.g. video, twitter) ▪ Reaction / adjustment may change data collected ▪ Implies multiple, possibly changing data models ▪ Adjustments should be annotated, this is text on a timeline ▪ May throw it all away at end of a campaign Create an offer (promotion, call to action, thing of great beauty) Publish it Monitor it React to it Make adjustments (push it, tweak it, fix it) Stop it or move on
  38. 38. © Third Nature Inc. 3 common customer measures Only sales taken into account. No valuation of differing product margins, service costs, lifetime value of customer. (Average Revenue Per User) Revenue minus the cost of the product / service (Average Margin Per User) Average across users, not an individual metric Total revenue revenue over the time the person has been a customer to date (LTV) and forecast to an expected date when they will stop being a customer (pLTV) Averages are easy to calculate in BI, but these are usually an average, e.g. sum(customer sales) / count(customers). They are not often calculated for each individual in the database and they are missing important information that would change how they are served. Revenue (ARPU) Profitability (AMPU) Lifetime value (LTV)
  39. 39. © Third Nature Inc. It’s always better to start simple, e.g. RFM RFM: Table-based statistics without the stats >40 year old technique used in direct marketing Recency: Recent transactions indicate a customer is more likely to transact again Frequency: More frequent customers are more likely to respond to an offer Monetary: Customers who spend above average are likely to spend more this time The model assumes that R > F > M in importance. This may not always be true. 43
  40. 40. © Third Nature Inc. RFM: Technique Based on N quantiles for each attribute, where N is commonly 5 but can vary. Sort the data by recency, defined as the last time they transacted with you on a voluntary basis (i.e. paying a phone bill isn’t a good example) and assign each record a quantile number This numeric label is the recency column in the table and is their recency “score” 44 Record Set 1 2 3 4 5
  41. 41. © Third Nature Inc. RFM: Technique Now do the same sort and assignment for frequency, where frequency is by some meaningful time period for your organization and customers. Then repeat with monetary, e.g. avg order size, total lifetime spend, etc. The same row will have three numbers now. Record Set 1 2 3 4 5 Record Set 1 2 3 4 5 Record Set 1 2 3 4 5 Recency Frequency Monetary
  42. 42. © Third Nature Inc. RFM: Technique You can think of this is constructing a cube and assigning one index value along each axis. In this model, the cells will having varying numbers of customer records corresponding to their RFM score. Recency Monetary 1-1-1• Test a representative sample. • Record the response rate by cell. • Based on this and p(r) * v you can now calculate breakeven by cell and identify the ones to mail to or avoid.
  43. 43. © Third Nature Inc. Why is RFM Used? 1. It’s better than random. 2. It’s simple. 3. It’s fast. 4. It’s cheap. It’s usually not as good as other models – until you factor in the above points. You can do several campaigns with RFM for 1 run of a complex scoring model.
  44. 44. Why simple might be better: Video Store case Key Figures: ▪ 200 stores, 200.000 transactions per week ▪ Appr. 1 million active customers, 1.3 million inactive ▪ Average frequency 8-10x per year Adapted RFM Model: FMR ▪ 'F' determines 'M', 'M' class influences 'R' class ▪ M = Revenue in 52 weeks prior to last visit ▪ Less than 52 weeks of data: weighted total Assumptions (tested): ▪ No visit in last 52 weeks : inactive customer ▪ First 12 weeks: new customer Similar model results, 2 minutes vs 2 days, SPSS consulting and licenses and server vs 0 recurring external costs, better overall result
  45. 45. © Third Nature Inc. Analyzing the entire customer base another way Pareto analysis of the share of buyers who make up 80% of sales volume for products. Data source: CMO council
  46. 46. © Third Nature Inc. What makes these customers different? How does this affect a new product launch, or line extensions? The idea of a mass market is not really true. More a set of small markets within the mass. This is as true of commercial supplies as it is consumer goods. Data source: CMO council
  47. 47. © Third Nature Inc. Customer metrics today should all be individual Metrics go through periods of being fashionable. Average customer metrics were fashionable in the 90s. Today it’s all about measuring the individual. But can you? Probabilities assigned to groups are not an individual predictor. Both of those rank each individual rather than providing averages.
  48. 48. © Third Nature Inc. Survival Analysis, Key to Lifetime Value Calculations Based on a hazard function (mortality model). Things survival analysis tells you: ▪ When a customer is likely to leave ▪ When a customer is likely to move to a new segment ▪ When a customer is likely to broaden or narrow the relationship ▪ The factors in the relationship that may increase or decrease tenure ▪ The quantitative effect of various factors on customer tenure Why it’s worth it: predict churn, risk of defection, predict places to intercede to make things better,
  49. 49. © Third Nature Inc. Lifetime Value Calculations Customer Value (CV) – the actual amount to now Lifetime Value (LTV) – the predicted value to the date determined from the mortality calculation (or actual value in the case of inactive customers) ▪ Can be calculated based on Revenue or Margin* ▪ Can be absolute or discounted to current dollars Customer Acquisition Cost (CAC) – the variable and fixed costs to acquire the customer Comparing any two customers requires knowing their start date and expected tenure. LTV = (CV – CAC) * Tenure
  50. 50. © Third Nature Inc. Satisfaction, Loyalty: CSI and NPS
  51. 51. © Third Nature Inc. LTV misuse There was a flawed article about 5 years ago in a business magazine with the idea that you should “fire your worst customers.” First, find the LTV, then get rid of the ones who are unprofitable.
  52. 52. © Third Nature Inc. GETTING STARTED
  53. 53. © Third Nature Inc.© Third Nature Inc. Evolution of the Customer Master Demographic • Your customer master • Geography • Group memberships • Social network profiles • Syndicated data Psychographic • Clickstream (visits, views, timing) • Communications • Content (blogs, tweets, comments, ratings) • Transactions • Syndicated data Socialgraphic? • Profiles of connections • Communities of interest • Connection likes and dislikes • Syndicated data The detail and breadth expand as collection improves
  54. 54. © Third Nature Inc. Individual profile Metrics (LTV, Satisfaction, loyalty, influence, etc.) Product preferences Brand preferences Price preferences Seasonal preferences Communication preferences Service preferences Transaction preferences What we need to build: the real customer master, not a customer dimension A lot more than just demographics. Includes every transaction, interaction, observation about the customer. Not built all at once. Household Household profile Transaction history Service history Outbound marketing contact history Inbound marketing contact history Social networks*
  55. 55. © Third Nature Inc. The Advanced Companies Are Integrating Social Data into Customer Databases Do you have a process to record and integrate data from social interactions with customers into existing customer databases? Source: Survey for Social Media Program Managers, conducted by Altimeter Group (Q1- Q2 2011) 143 respondents, all over 1000 employees
  56. 56. © Third Nature Inc. Measuring customer interactions State of practice: ▪ Limited customer master, in a silo. Partial customer contact histories, outbound only. State of the art: ▪ A system to gather data about any customer interactions, inbound or outbound, from marketing to service. Sources are extensive: ▪ web analytics, CRM, sales automation, lead scoring, marketing automation, email providers, online advertising, call management, IVR, bug reporting, warranty, service management, enterprise feedback mgmt, decision automation, sentiment analysis, conversation management, dynamic case management, VoC, social media, surveys, focus groups, syndicated market data… Many types and structures, not all relational-friendly, may require new storage and processing platforms.
  57. 57. © Third Nature Inc. Different Data and Different Usage Patterns Be prepared for changed assumptions: ▪ Marketing campaigns and tactics change frequently, particularly online marketing. ▪ This means data sources change frequently, as well as reporting needs. ▪ Much of marketing is like experimental science, and unlike the read-only BI usage model.
  58. 58. © Third Nature Inc. Value 1. Web alone, not that much 2. Web plus transactions, big increase 3. Web plus email plus transactions, bigger increase But the real goal in customer analysis is a full picture, which means an interaction master for everything: online ads, mobile app use, inbound & outbound call center, physical point of presence, direct mail contacts. i.e. You have to say yes to all new data requests…
  59. 59. © Third Nature Inc. The data warehouse has to evolve to support these kinds of uses. This means a more complex data platform Transient data Raw data Infrastructure layer: Store and manage Refine and deliver Application layer: Analyze and consume The new model encompasses data at rest and data in motion Multiple access methods Standardized data Multiple ingest methods BI, data extracts, analytics, applications The platform has to do more than serve queries; it has to be read-write.
  60. 60. © Third Nature Inc. Define the goal Decide how to measure it Baseline Plan your actions and monitor outcomes Iterate Define goal-driven actionable metrics as the starting point, don’t boil the ocean
  61. 61. © Third Nature Inc. Getting started You can’t build everything at once, so don’t try. 1. Build out the convenient: for a few channels that are important, assemble the raw interaction data for each. 2. Store that data in a place where it can be be easily refined from its raw state, and hopefully further linked to DW data on TXs (which will show you outcomes). 3. Add some inexpensive tools to explore the data with. 4. Do some simple modeling to understand a few key customer channel interactions. 5. Keep extending the data and capabilities.
  62. 62. © Third Nature Inc.© Third Nature Inc. “The future, according to some scientists, will be exactly like the past, only far more expensive.” ~ John Sladek
  63. 63. © Third Nature Inc. Creative Commons Thanks to the people who made their images available via creative commons: Outdated gumshoe.jpg – Card catalog – Book of hours manuscript2.jpg – Royal library san lorenzo.jpg –
  64. 64. © Third Nature Inc. Image Attributions Thanks to the people who supplied the images used in this presentation: outdated gumshoe.jpg - laptop face.jpg - anne hathaway.jpg - desert ibex - michael polizia wheat_field.jpg - Open air market - child workers - whack-a-mole_door.jpg - uniform_umbrellas.jpg - train_to_sea.jpg - riot police line small - changing of the guard.jpg - pyramid_camel_rider.jpg - chinatown little color gate.jpg - teapot.jpg - motionless in crowd.jpg - well town hall - febo amsterdam.jpg - cadillac ranch line.jpg - Slide 77
  65. 65. © Third Nature Inc. CC Image Attributions Thanks to the people who supplied the creative commons licensed images used in this presentation: Veyron - unrecycle.- wheat_field - Open air market - riot police line small - Sandblaster - subway dc metro - fast kids truck peru - well town hall - Tokyo forum -
  66. 66. © Third Nature Inc. About Third Nature Third Nature is a consulting and advisory firm focused on new and emerging technology and practices in information strategy, analytics, business intelligence and data management. If your question is related to data, analytics, information strategy and technology infrastructure then you‘re at the right place. Our goal is to help organizations solve problems using data. We offer education, consulting and research services to support business and IT organizations as well as technology vendors. We fill the gap between what the industry analyst firms cover and what IT needs. We specialize in strategy and architecture, so we look at emerging technologies and markets, evaluating how technologies are applied to solve problems rather than evaluating product features and vendor market positions.