1. Traffic, paths and dwell time By Olivier Delangre Olivier.delangre@amoobi.com

2. Why ? Action needed ! Complement/challenge intuition/experience Improve understanding of sales numbers Validate efficiency of remodeling Understand promotion effectiveness Match in-store communication with traffic

3. Easy for online retailers...

4. No longer “Mission Impossible” for “brick & mortar”

5. We need information Characteristics and evolution of traffic Dwell time in each department Frequent vs. non-frequent visitors Most likely paths Typical paths Cross sales data with traffic data

6. Specs for new technology Provide actionable insights vs. masses of data Sampling, not counting Transparent for shoppers Fairness, no privacy issues Affordable and scalable Autonomous, no IT integration Easy install, relocation

7. For who? FoodNon-food SmallLarge

8. Let’s illustrate 1. Remodeling

10. 2 key hints from OUR data 1. Wider aisles in different areas = more traffic and dwell time 2. Sales and time spent are correlated

11. Client’s decision Wider aisles Created universe by regrouping sportswear and equipment Added changing rooms (universe)

13. 2. A supermarket

14. After 4 weeks of observation… 64% of shoppers came only once over the 4 weeks, 17 % twice, 7% 3 times, etc. Over 50% of shoppers paths/time is spent in 4 departments. Over 50% of visitors spend less than 15 min in the store (check-out included) on weekdays

15. 3. Another remodeling

17. Turnover Clients (purchased something in this department) Basket -2,1% -19,4% +21%

18. Visitors (people who entered the department) Conversion rate (Clients/visitors) Dwell time intra department +11,2% +26,6% +1,4%

19. Recommendation Even if sales data are disappointing… …. traffic data show remodeling is OK Work on product offering, merchandising, pricing to improve sales

20. 4. Impact of promotions

22. Exposure +27%

23. 5. Going beyond “numbers”

24. “Typical” paths

25. Qualified traffic Contribution to turnover

26. Y = Traffic, X = Sales

27. Focus on comparisons and evolution ! Compare shops Compare shop over time Cross with sales data

28. OK, now, how does it work ?

34. Real time analytical tool

35. Want to know more?

36. Contact us !www.amoobi.comwww.amoobi.com

37. In other words… A reliable independent and « mobile » sampling and analysis/reporting system, with the spotlights on shopper’s path and traffic/dwell time « Enriches » ticket and loyalty data when available Helps improve comparisons between shops and over time Helps to test validity of strategies/recommendations Provides actionable conclusions both for quick (very) local action (and/or deep global re-thinking) to improve conversion and sales

38. Maze of failsafe wirelessly interconnected detectors collect data Permanent wireless transfer to (nodes and) servers « in the cloud » via 3G Data treatment by proprietary SW Authorized access to results via login & PW, secured site, Internet Permanent remote monitoring of every installed component, « on the fly » replacement if fault No connection to Client’s ITC Technically …