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Tutorial: Customer Clustering 101
- 1. Tutorial Customer Clustering 101 Dhruv Bhargava Director Analytics, AgilOne dhruv.bhargava@agilone.com
- 4. Let’s talk clustering! • Your customers are different à Clustering reveals these different personae • Understanding clusters à personalization • Personalized campaigns à better marketing ROI
- 5. What is customer clustering? Athletes Chronic Returners Doting grandmothers 5 Creating homogenous groups of customers and identifying personae to drive marketing actions
- 6. Then: Broad strokes Basic retro-active segmentation Now: Clear picture Clustering drives relevancy & personalization • • What products do they need? • 12 month file versus 12+ month file • What brands do they prefer? • Buys best selling brands • What offers will compel them to buy? • 6 1x buyer versus 2x+ buyers Has loyalty membership? • What’s the right channel & frequency of contact?
- 7. 3 clustering models available • Behavioral: Spending, channel, order interval, discounts, returns,… • Product based • Brand preference • Clustering done mathematically via unsupervised learning • • • • • Let data drive what clusters you have in your customer base No guesswork or leaning on intuition Multi-variable, not based just on revenue, or a single product Optimized for stability Data refreshed daily
- 8. Example: behavioral cluster DNA Long term, frequent buyers, medium sized orders High value, fewer orders, big spend on 1st order $99 average order $2,261 total revenue 24 days between orders 24 total orders 57 total items $76 first order revenue 1.7 products in first order 6% of orders on clearance +10 more $124 average order $595 total revenue 67 days between orders 5 total orders 14 total items $164 first order revenue 3.3 products in first order 3% of orders on clearance +10 more
- 9. Use the DNA to personalize Long term, frequent buyers medium sized orders High value, fewer orders, big spend on 1st order Goal: increase order size (AOV) Goal: decrease time to rebuy Campaign: Give double points if they spend 50% more than usual Campaign: Give double points that expire sooner than usual with purchase Result: 125% increase in AOV Result: Time to next purchase reduced to 2 months from 4 months
- 10. Example: product clusters Product Clusters Developed Cluster #1: Sweaters • Based on what products customers buy Cluster #2: Stylish Men’s Wear Cluster #3: Active Wear Cluster #4: Gift Certificates/Family Cluster #5: Elegant Ladies Cluster #6: Kids Wear Cluster #7: Underwear Cluster #8: Accessories 10 4 March 2014 • Once clusters are created, this reveals the natural groupings of products
- 11. Example: product cluster DNA 11 4 March 2014
- 12. Example: Brand clusters DNA Cluster 1 Brand Scale Least Interest Pleasure Doing Business Wow Couture Desigual 6126 L*Space Preferred Brands Tahari Arthur S. Levine Calvin Klein Eliza J Adrienne Vittadini Nine West Preferred Brands Cluster 3 Brand Scale Least Interest Collective Concepts Wow Couture Max and Cleo Rene Rofe Steve Desigual Dzhavael Couture Custo Barcelona Smash Wear Salvage Rock’N’Rebel
- 13. DNA for each cluster drives relevancy in campaigns Cluster 1: Sweaters Cluster 3: Active Wear Goal: Drive customer engagement Goal: Increase customer value Campaign: Target cluster with all main product related campaigns (E.g. New sweater arrivals) Campaign: Offer bundles of related products from same cluster at discount Result: 100% increase in AOV Result: Improved email open rate by 25% and click rate by 66%
- 14. info@agilone.com Ÿ (877) 769 3047
Hinweis der Redaktion
- IN THIS video, I will talk about customer segmentation, what it is, when and how it is used, what are different types of segmentation and what to watch out for when segmenting customers.