Using Lifecycle Scores for Marketing Optimisation

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Measurecamp - March 2014

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Using Lifecycle Scores for Marketing Optimisation

  1. 1. Using Lifecycle Scores for Marketing Optimisation Carmen Mardiros @carmenmardiros Friday, 28 March 14
  2. 2. @carmenmardiros Customer’s cognitive decision process, not YOUR marketing funnel. Post-decision evaluation Need Recognition Option Evaluation Shortlist Interest (research) Decision (... Some loopbacks and optional steps, but some form of it always exists ) Friday, 28 March 14
  3. 3. @carmenmardiros Where your path crosses that of the customer... Post-decision evaluation Need Recognition Option Evaluation Shortlist Interest (research) Decision ... there’s just one goal - Move them to NEXT stage Friday, 28 March 14
  4. 4. @carmenmardiros Need Recognition Option Evaluation Shortlist Interest (research) Decision See category pages Actively interact with category pages See product pages Actively interact with products Discovery behaviours The One Goal Find a contender product, to buy now -- or later. (success measure = “Add to basket” ) Friday, 28 March 14
  5. 5. @carmenmardiros See category pages Actively interact with category pages See product pages Actively interact with products Engage with curated product lists Read pre-purchase help, tools and features Add to wishlist .... Intuitively, valuable behaviours but many and varied... Can we aggregate them all in a single “discovery score”? Organic PPC 30 350 4 7 21 7 3 13 99 460 7 34 1 1 = Propensity of channel to deliver valuable discovery visits. Friday, 28 March 14
  6. 6. @carmenmardiros Step 1. How much is each discovery behaviour worth? Users that interact with category pages Out of theses, users that ALSO add to basket A B Discovery score = B/A * 100 (... or the conversion rate for this type of discovery behaviour) Friday, 28 March 14
  7. 7. @carmenmardiros Step 1. How much is each discovery behaviour worth? Smoothen out fluctuations by averaging over weekly cohorts Caveat: Would need to split by other dimensions to find the true “value” of a behaviour. Tedious work until API supports visitor-level segments. ( Better yet, use median or confidence ranges ) Friday, 28 March 14
  8. 8. @carmenmardiros Step 1. How much is each discovery behaviour worth? Behaviours closer to “Add to basket” tend to have higher discovery scores ( duh! ). Channels that drive a mix of high-score visits are better at moving people to NEXT stage in the decision process. Friday, 28 March 14
  9. 9. @carmenmardiros Step 2. Calculating discovery scores when channels bring a messy mix of visits score1 * ratio1 +score2 * ratio2 .... Discovery score = Why this formula? It evens the playing field (e.g. channels driving more lower-score visits ~ channels driving fewer higher-score visits) Friday, 28 March 14
  10. 10. Use cases: - Validate intended response from campaigns and messaging - Uncover true channel purpose - Identify time-wasters (high engagement, wrong kind of engagement) - Identify marketing opportunities (low volume, high discovery score) Friday, 28 March 14
  11. 11. Not just for channels... Functional overlay for landing page groups to understand flows. (see Gary Angel - Functionalism) Friday, 28 March 14
  12. 12. Not just for channels... Function of content seen and interacted with. Friday, 28 March 14
  13. 13. Progression through decision process Not just for channels... Friday, 28 March 14
  14. 14. @carmenmardiros Yet to do, cross-reference with Multi Channel Funnels Friday, 28 March 14
  15. 15. Thank You Carmen Mardiros @carmenmardiros Friday, 28 March 14

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