Traffic, paths and dwell time By Olivier Delangre [email protected].

Traffic, paths and dwell time

By Olivier [email protected]

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

Easy for online retailers...

No longer “Mission Impossibl

e” for “brick & mortar”

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

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

For who?Food Non-food

Small Large

Let’s illustrate

1. Remodeling

2 key hints from OUR data

1.Wider aisles in different areas =

more traffic and dwell time

2.Sales and time spent are correlated

Client’s decision

•Wider aisles

•Created universe by regrouping sportswear and equipment

•Added changing rooms (universe)

2. A supermarket

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

3. Another remodeling

Turnover

Clients (purchased

something in this department)

Basket

-2,1%

-19,4%

+21%

Visitors (people who entered the department)

Conversion rate

(Clients/visitors)

Dwell time intra

department

+11,2%

+26,6%

+1,4%

Recommendation

•Even if sales data are disappointing…

•…. traffic data show remodeling is OK

•Work on product offering, merchandising, pricing to improve sales

4. Impact of promotions

Exposure

+27%

5. Going beyond “numbers”

“Typical” paths

Qualified traffic

Contributionto

turnover

Y =Traffic, X = Sales

Focus on comparisons and evolution !

•Compare shops

•Compare shop over time

•Cross with sales data

OK, now, how does it work ?

Real time analytical tool

Want to know more?

Contact us !www.amoobi.com

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

• 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…