M&S Digital Labs: Lean product development, fast feedback & leopard print dresses
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M&S Digital Labs: Lean product development, fast feedback & leopard print dresses
- 1. M&S Digital Labs Lean product development, fast feedback (& leopard print dresses) @hemalkuntawala
- 2. • About M&S Digital Labs • One of our products 5 minutes 15 minutes
- 3. About M&S Digital Labs Lean startup techniques… …kick-start products and experiences… …our customers wouldn't expect to see from M&S
- 4. About M&S Digital Labs * Online Desktop, tablet, mobile Ops Marketing Digital Trading, fulfilment Marketing Ops Branding, campaigns Supply chain Stores Marketing Ops High Street, Simply Food, Outlet Offline Stock, forecasting * Not to scale, or very accurate
- 5. Lean startup (& product management) Value proposition Customer segments Business model canvas Marketing channels Customer development Validate assumptions Design thinking Insight & assumptions Learn UX Build Autonomy User testing Activation Data Product Revenue Extreme programming Retention Behaviour Split tests Developers Designers Vision, instinct & obsession… Acquisition IA Referral Product/market fit? Measure Continuous deployment MVP
- 6. Insight & assumptions Our brands confuse Would our customers create and view outfits? What happens to conversion if we remove models? What happens if we remove our brands? Data Can’t outfit Our models alienate Product One of our products
- 7. Product The product: Style Board Would our customers create and view outfits? What happens to conversion if we remove models? What happens if we remove our brands?
- 8. Product Would our customers create and view outfits? Data The data Let’s have a look… What happens to conversion if we remove models? What happens if we remove our brands?
- 9. 5000 Traffic 3750 Sign ups 52% conv. 2500 Boards 39% conv. 1250 Month October November December January February
- 10. The data Data Product Would our customers create and view outfits? • • 52% visitors signed up 39% users created a board What happens to conversion if we remove models? • Traffic from Style Board converts 36% higher What happens if we remove our brands?
- 11. The data Data Product Would our customers create and view outfits? • • 52% visitors signed up 39% users created a board What happens to conversion if we remove models? • What happens if we remove our brands? Traffic from Style Board converts 36% higher Let’s have a look…
- 12. Brand mix
- 13. The data Data Product Would our customers create and view outfits? • • 52% visitors signed up 39% users created a board What happens if we remove our brands? What happens to conversion if we remove models? • Traffic from Style Board converts 36% higher • Brands are mixed and matched More data! Category mix Product relationships
- 14. Category mix
- 15. The data Data Product Would our customers create and view outfits? • • 52% visitors signed up 39% users created a board What happens if we remove our brands? What happens to conversion if we remove models? • Traffic from Style Board converts 36% higher • Brands are mixed and matched More data! Category mix • Some popular categories could be better sold Product relationships
- 18. The data Data Product Would our customers create and view outfits? • • 52% visitors signed up 39% users created a board What happens if we remove our brands? What happens to conversion if we remove models? • Traffic from Style Board converts 36% higher • Brands are mixed and matched More data! Product category mix • Popular categories could be better sold Product relationships • Relationship data could produce better product suggestions
- 19. What’s next? Version 1 • Isolated app (mandsstyleboard.com) • Login via Facebook • (Minimal) engagement mechanics • Deep links • Responsive • Shipped in 4 weeks • Traffic from M&S Facebook Version 2 • Increase engagement • Increase quality • Increase conversion • Lick of paint • Use as a marketing channel • Wherever else the data takes us…
- 20. What else you can expect from us Online Desktop, tablet, mobile Stores High Street, Simply Food, Outlet
- 21. Food High Online aided by offline Mainly online Frequency Tops Lingerie Shoes Bottoms Women’s wear Shirts Underwear Handbags Dresses Men’s wear Flowers Suits Low Sofas Slow Homeware Kitchen ware Purchase-cycle speed Fast
- 22. Thanks! @mnslabs