Data based segmentation @ vsco
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The document outlines VSCO's user segmentation strategy, highlighting their audience demographics and engagement metrics, such as their 41 million monthly users and the tools available for both marketing and design purposes. It details a six-step process for conducting clustering analysis to understand user behavior and improve targeting, including choosing inputs, log transforming data, and programmatic cohort tracking. The approach integrates insights from marketers, designers, and analysts, emphasizing the importance of behavioral data for effective segmentation.
Data based segmentation @ vsco
- 1. VSCO→CONFIDENTIAL→DONOTDISTRIBUTE Data Update - 01/27/2016vsco.co/blevishkin Data Update - 03/17/17vsco.co/prazakj 06 APR 2017 RUBEN KOGEL ( VSCO ) RUBEN@VSCO.CO @CHILICONDATA Data-based User Segmentation
- 2. VSCO→CONFIDENTIAL→DONOTDISTRIBUTEVSCO→CONFIDENTIAL→DONOTDISTRIBUTE What is VSCO? → tools for expression → a community to share, learn, and discover vsco.co/mikelyon
- 3. VSCO→CONFIDENTIAL→DONOTDISTRIBUTEVSCO→CONFIDENTIAL→DONOTDISTRIBUTE Who are VSCO users? → 41M monthly audience → 12B images served monthly → 70% of daily audience create → 73% under 25 → 76% female → 81% international • North America (22%) • Southeast Asia (20%) • China (16%) • Europe (14%) vsco.co/curtsaunders
- 4. VSCO→CONFIDENTIAL→DONOTDISTRIBUTE Segment iOS client Android client App Store Prod Database VSCO Web 3rd party (AppAnnie..) SQL client Mixpanel SDK Product Design Engineering Finance Analysts Content Investors Leadership (everyone) periodic delete Data Stack at VSCO as of 3/31
- 5. VSCO→CONFIDENTIAL→DONOTDISTRIBUTE Cantor iOS client Android client App Store Prod Database VSCO Web 3rd party (AppAnnie..) SQL client (Presto/ Spark) Mixpanel SDK Events Analytics Deep AnalysisKafka Data Exploration Dashboarding New Data Stack at VSCO (in-progress)
- 6. VSCO→CONFIDENTIAL→DONOTDISTRIBUTEVSCO→CONFIDENTIAL→DONOTDISTRIBUTE Why segment? → marketing: who should we target? → design: what usage do we design for? → product / officers: how do we grow usage? vsco.co/evanhundelt
- 7. VSCO→CONFIDENTIAL→DONOTDISTRIBUTEVSCO→CONFIDENTIAL→DONOTDISTRIBUTE Why segment? vsco.co/evanhundelt method insights goal Marketers interviews persona define target audience Designers interviews intention design intuitive UI Analysts data behavior track usage, conversion
- 8. VSCO→CONFIDENTIAL→DONOTDISTRIBUTE the theory meat consumption dairyconsumption paleo German dietFrench diet mediterranean diet usage frequencymilesdriven commuters taxi driversweekenders greenies
- 9. VSCO→CONFIDENTIAL→DONOTDISTRIBUTE where do you draw the line?? 0 20 40 60 80 100 0102030 editing usage number of actions numberofpeople(inthousands) the practice 0 20 40 60 80 100 01020304050 sessions number of actions numberofpeople(inthousands) 0 20 40 60 80 100 010203040 publishing usage number of actions numberofpeople(inthousands)
- 10. VSCO→CONFIDENTIAL→DONOTDISTRIBUTE → k-means find the dimensions with the most separation and use that information to form “clusters” • each additional dimension will change the output - but does it add information? → eliminate unnecessary input variables • use intuition and data exploration → segment only on the things that matter: • age on the platform • sum of past behavior • current behavior - what we want to model → this is an iterative process: re-do this step after running the clustering algorithm step 1: choose the right inputs
- 11. VSCO→CONFIDENTIAL→DONOTDISTRIBUTE step 2: 0 20 40 60 80 100 0200004000060000 0 1 2 3 4 010000200003000040000 → otherwise your model assumes the gap between people editing 1 and 2 photos counts the same as between people editing 101 and 102 photos → log transform so that the gap between few actions gets blown up and the gap between large numbers get shrieked • log(2) - log(1) = 0.69 • log(102) - log(101) = 0.01
- 12. VSCO→CONFIDENTIAL→DONOTDISTRIBUTE step 3: choose the number of clusters that make sense balance: → sparseness → interpretability • does it match intuition?
- 13. VSCO→CONFIDENTIAL→DONOTDISTRIBUTE step 4: deliver the insights in an intuitive way 1 2 3 4 5 6 dimension 0.0 0.0 0.0 0.9 2.8 0.5 dimension 0.0 0.0 0.0 0.6 1.9 0.3 dimension 0.0 0.0 0.0 0.5 1.5 0.3 dimension 0.2 0.1 0.1 8.5 18.4 2.5 dimension 0.2 0.1 0.1 3.1 3.9 1.4 dimension 0.3 4.8 27.1 2.1 20.5 22.7 dimension 0.3 2.5 7.6 1.3 7.7 6.9 dimension 0.3 1.9 3.3 1.1 3.4 3.3 dimension 0.2 3.6 21.4 0.3 3.4 7.3 dimension 0.1 0.2 0.1 2.7 13.0 10.5 dimension 0.1 0.1 0.1 1.6 6.5 4.1 dimension 0.1 0.1 0.1 1.3 3.2 2.5 dimension 0.0 0.0 0.0 0.5 6.4 0.1 dimension 0.0 0.0 0.0 0.4 4.2 0.1 dimension 0.0 0.0 0.0 0.4 2.5 0.1
- 14. VSCO→CONFIDENTIAL→DONOTDISTRIBUTE step 5: use programmatic rules to track cohorts → what happens if we re-compute the clusters every month? • the algorithms will find different cohorts with different centers with every new dataset • a user that was classified as a “super editor” one month might, with the same behavior, be classified as a “casual editor” the next month → instead deduct the boundaries between the different groups from the initial cluster analysis and design programmatic rules to classify users on an on-going basis • more stable • easier to explain
- 15. VSCO→CONFIDENTIAL→DONOTDISTRIBUTE step 6: deliver dashboard or on-going classification segmentation, over time source of the “green” segment, in each month
- 16. VSCO→CONFIDENTIAL→DONOTDISTRIBUTEVSCO→CONFIDENTIAL→DONOTDISTRIBUTE Summary → marketers, designers, and analysts use different but complementary segmentation approaches → data-based segmentation is useful to track usage; should be based on behavioral data only → most usage data is exponential so need algos to identify cluster boundaries 6 steps to doing a clustering analysis 1. choose the right inputs 2. log transform (almost) everything 3. choose the number of clusters that make sense 4. deliver the insights in an intuitive way 5. use programmatic rules to track cohorts 6. deliver dashboard or on-going classification vsco.co/sannalinn
- 18. VSCO→CONFIDENTIAL→DONOTDISTRIBUTE → → 06 APR 2017 RUBEN KOGEL ( VSCO ) RUBEN@VSCO.CO @CHILICONDATA