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Personalization Strategy Workshop - Los Angeles

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See examples of personalization in action

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Personalization Strategy Workshop - Los Angeles

  1. 1. Personalization Strategy Workshop Los Angeles August 18, 2016 Travis Bryant, Vice President of Sales, Optimizely Ian Thiel, Head of New Products, Optimizely Matty Wishnow, Founder & CEO, Clearhead +
  2. 2. Agenda 2:30 PM Registration & Refreshments 3:00 PM Open/Welcome Travis Bryant, Vice President of Sales, Optimizely 3:15 PM Personalization Capabilities Overview & Demo Ian Thiel, Head of New Products, Optimizely 3:45 PM Break & Networking 4:00 PM Personalization Strategy Best Practices Matty Wishnow, Founder & CEO, Clearhead 5:00 PM Group Discussion, Networking & Happy Hour
  3. 3. Welcome and Opening Remarks Travis Bryant, Vice President of Sales, Optimizely Travis Bryant Vice President of Sales Optimizely
  4. 4. Personalization Strategy & Demo Ian Thiel, Head of New Products, Optimizely Ian Thiel, Head of New Products, Optimizely
  5. 5. What are my peers doing? 2016
  6. 6. Behavioral retargeting produces 4x ROI Personalized campaign Used behavioral targeting to show buy-one-get-one tire promotion to customers who had viewed tires. Results • 21% increase in overall site sales • Sold out of tire stock 2 months before expected • 4x return on investment in Optimizely and solutions partner services
  7. 7. Paywalls Targeted offers Account Based Marketing (ABM) Product recommendations Category affinity What are my peers doing? Recap
  8. 8. Demo! 2016
  9. 9. How does Optimizely personalize?
  10. 10. Personalization Strategy Workshop Matty Wishnow, Founder & CEO, Clearhead Matty Wishnow Founder & CEO Clearhead
  11. 11. August solving problems with personalization an introduction to PSM
  12. 12. 2 problem / solution mapping A unifying framework for continuously optimizing around a common set of goals, problems & solutions, researched & validated with data. 
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pS ps problems 
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 4 hypotheses prioritized by data 
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 experiments validated by data outcomes UX product merchandising marketing
  13. 13. 3 it’s still an 
 experiment everything is an experiment promotions + campaigns merchandising changes new features & functions UX + IA changes new SaaS additions personalized experiences everything if everything is an experiment, 
 then these are questions to live by What problems are the 
 changes solving? 
1 How will you know if the 
 change was successful? 
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  14. 14. 4 what is personalization? The customization, targeting or adaptation of content and/or experiences for end users based on implicit or explicit attributes of more refined segments. what is a/b testing? A method of comparing a variation to a control to determine if the differences observed in the sample are statistically likely to survive in a larger, general population or data set. 
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  15. 15. 5 sizing the prize large segment effort opportunity small segment algorithmic manual target smart phone users with ability to send cart to their desktop people who bought this long tail item also bought this target un-authenticated people who come from pinterest with an email opt-in modal
  16. 16. 6 “A good archer is known not by his arrows but by his aim.” -Thomas Fuller
  17. 17. 7 increase mobile conversion rate by 10% by the end of 2016. ask yourself: • target set? • clearly understood? • time based? • realistic?reduce mobile bounce rate by 15% by the end of 2016. increase mobile revenue per visit by 5% by the end of q3 2016. improve mobile net promoter score by 10% by the end of q1 2017. goals
  18. 18. 8 “If I had one hour to save the world, I would spend fifty-five minutes defining the problem… and only five minutes finding the solution.” -Albert Einstein
  19. 19. 9 increase mobile conversion rate by 10% by the end of 2016. problems ask yourself: • is it a root problem? • who does it impact? • where and when does it impact them? • how do you know it is a problem? users find it hard to click on our filter & facet functionality on their smart phone. it is challenging for users to look at alternative product shots on our mobile PDP because the thumbnails are so tiny. we frustrate mobile phone users with two extra steps — interstitial cart and account options — before getting them to checkout. goal
  20. 20. 10 “Determine the thing that can and shall be done, and then we shall find the way.” -Abraham Lincoln
  21. 21. 11 solution hypotheses ask yourself: • I believe that… • If I am right then… • could a designer/ developer/analyst reasonably begin work based on the hypothesis? I believe that if we skip the interstitial cart page for smart phone users and redirect them to checkout once they add something to their cart, they will be less likely to waver in their journey and bounce. If I am right, then, mobile conversion rates for for smart phone users will increase by 5%. I believe that if we eliminate the “sign up”
 option at the beginning of check-out for all unauthenticated users on smart phones, they will be less intimidated by the prospects of filling out extra form fields and will be more likely to purchase. If I am right, then mobile conversion rates for for smart phone users will increase by 10%. we frustrate mobile phone users with two extra steps — interstitial cart and account options — before getting them to checkout. problem
  22. 22. Consistently require all changes to be mapped to problems & hypotheses. Determine if additional problem research is needed. hypotheses experiments outcomesproblemsgoals Determine what should be researched or tested vs “just do it” Review & iterate regularly. 2 4 5 3 Agree to the “Problems Worth Solving.” 1 what do you do once you’ve got your map?
  23. 23. goals problems hypotheses outcomes 13 define clear success metrics, that include targets, time basis & exceptions reporting. 1 capture business & end user problems.2 organize all problems into clusters.3 research & prioritize problems.4 agree how much to invest in “problems we want to solve.” 5 develop solution hypotheses for “problems we want to solve.” 6 prioritize solution hypotheses.7 ux, product & stakeholders plan for feedback & experiments. 8 solutions are tested at various stages.9 experiments analysis & data stories around specific solution hypotheses. 10 ongoing measurement of KPIs related to goals. 11 qualitative tracking of “problems worth solving” 12 expand investment in those solutions that worked! 13 move on to new hypotheses if old ones proved invalid. 14 use data to regularly re-align around problems & solution hypotheses. 15 mapping details
  24. 24. 14 segments: let’s get real where should we start? how do you get from qualitative personas to definable 
 data segments? is predictive segmentation
 a real thing? anybody doing amazing
 omni-channel personalization? for problem 
 research for hypothesis development should we just randomly explore segments?
  25. 25. 15 When you are personalizing, you are still experimenting. Don’t personalize just because you can. Endeavor to solve problems that relate to critical goals. Key considerations for personalization • Segment size • Segment value • Manual v algorithmic key takeaways Segment definition and exploration takes time. There’s no magic button (yet). Experiments come with risk and investment. Multi-channel customer data layers are increasingly a practical reality! 
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  26. 26. Thanks! +

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