Agile Consumer Analytics

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Different Approaches to Analytics for the 21st Century.

Five Takeaways
1. You must move beyond conventional analytics to be disruptive (Sophisticated Analytics = Disruption)
2. Consumers have increasingly high expectations. How will you meet them? (Increasing consumer expectations)
3. Consumer analytics must focus first on value to the consumer, then on value to the business (Consumer value first)
4. Analytics is the engine, the consumer experience is the car (A car and engine glyph maybe?)
5. The best analytics are found in solutions to interesting solutions to real problems

Different approaches to agile analytics and customer engagement.
Retail as we've known it for the past 50 years is dead. As the population becomes increasingly diverse and the baby boom generation wanes, retailers can no longer simply "stack it high and let it fly". Consumers want to shop whenever and however they prefer and the notion of a single point of sale is obsolete. Therefore the conventional retail analytics of the past 20 years such as segmentation, profiling, wallet share, lifetime value analysis, etc. are also becoming obsolete. Join Ken Collier as he examines the convergence of factors that are leading to a sea change in retail and how retailers might benefit from advanced analytics to enhance the shopping experience and strengthen the retailer:consumer relationship.

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  • A Geofence is a layer of intelligence that allows you to make decisions or take some action based on a geographical area. It can circle anything/ any area you like – a retail store, a stadium, a neighborhood. You can build an App-based Geofence that, as the name suggests, requires you have an app to access GPS data. Or you can build a Network-based Geofence that uses carrier-grade location data and is not app dependent.

    http://www.chieflocationofficer.com/demystifying-geofencing/
  • Who is ambitious and disruptive?

    This slide is a subsection slide that may be eliminated. The next several slides are case stories about ambitious consumer analytics.
  • Agile Consumer Analytics

    1. 1. AGILE CONSUMER ANALYTICS Different Approaches for the 21st Century
    2. 2. Ken Collier, PhD Director, Agile Analytics ThoughtWorks @theagilist kcollier@thoughtworks.com
    3. 3. THE 21ST CENTURY CUSTOMER SOME ANALYTICS STORIES WHAT TO THINK ABOUT today
    4. 4. Marketing analytics A brief history
    5. 5. “…there has been no other point in history when so many aspects of disruptive change have collided and conspired to wreak havoc on the retail and consumer packaged goods industries.” “Who the customer is, what customers want and how to give it to them are completely up for grabs.” Doug Stephens The Retail Revival
    6. 6. The Great Unwind is a horizon where consumers…take back control of their behavior, holding themselves and the companies they do business with to higher business and social standards. Consumers long to return to a time when they could actually like the places they shopped and feel good about spending their money there. John Gerzema, Spend Shift
    7. 7. “The brands that secure their place in the future will ultimately have to be trusted and loved— and above all, remarkable.” Doug Stephens, The Retail Revival
    8. 8. What do consumers want? TRANSACTIONS ANYWHEREAND ANYTIME
    9. 9. What do consumers want? RADICAL PERSONALIZATION
    10. 10. What do consumers want? REMARKABLE CULTURE
    11. 11. What do consumers want? HI-FIDELITYOR HI-CONVENIENCE
    12. 12. What do consumers want? HONESTY ILLUMINATION IMMEDIACY
    13. 13. PERIL LIES AHEAD RELIANCEONBROAD CONSUMERSEGMENTS
    14. 14. And how are they doing it WHO IS DOING THIS WELL?
    15. 15. user preferences social influence user location Source: “Mobile Advertising, Clustering Algorithms, and Your Ticket for a Free Ride” Lillian Pierson, Smart Data Collective
    16. 16. WHAT TO THINK ABOUT
    17. 17. PARTNER WHO CARES DIFFERENTIATING PARITY marketdifferentiation mission critical Business Intelligence Static Reporting Executive Dashboards Operational Analytics Consumer Analytics Marketing Analytics
    18. 18. SOLUTIONS THINKING VS. ANALYTICS THINKING
    19. 19. DATA AS CURRENCY
    20. 20. takeaways 1SOPHISTICATED ANALYTICS =DISRUPTION
    21. 21. takeaways 2CONSUMER EXPECTATIONS AREINCREASING
    22. 22. takeaways 3PUTCONSUMER VALUEFIRST
    23. 23. takeaways 4ANALYTICSPOWERS THECONSUMER EXPERIENCE
    24. 24. takeaways 5THEBESTANALYTICS AREFOUNDIN AMBITIOUS SOLUTIONS
    25. 25. THANK YOU For questions or suggestions: Ken Collier Director, Agile Analytics - ThoughtWorks kcollier@thoughtworks.com @theagilist

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