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Measuring customer behaviour
in-real-life
1
0
10
20
30
40
50
60
70
80
90
100
09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00
Evolution over an average day
undef.
Women65+
Women35-65
Women15-35
Womenchildren
Men65+
Men35-65
Men15-35
Menchildren
The challenge
Understand trends and patterns
in the behavior of customers in the store
How many people come in on an average day? What’s the peak
hour? Where are the hot zones? How long do they stay? How
often do they come? What is the first place in the store they go to?
What’s the percentage of visitors watching my media? For how
long? What best attracts their attention?
How does the profile of visitors evolve over time? Do people
behave differently depending on their gender and age?
How do the various locations compare one another? And to global
benchmarks?
2
Proposed Solution
3
• Alt64 delivers a full turnkey service along with Quividi and its
technology partners to:
– Provide an advanced in-store measurement solution/methodology
– Validate the branches chosen for the deployment of this solution
– Install and setup the solution in stores
– Monitor/manage the technology 24/7 to establish best quality of results
– Establish meaningful KPI and produce the data reports that help you
optimize the experience in the stores
– Plan technically and commercially a solution across branches to provide
the dashboards that can be used to monitor/optimize store performance
and customer experience
The technologies used
4
• Amoobi WiFi/Bluetooth sensors for smartphone radio tracking
• Quividi VidiCube, a robust hardware plaform that allows
– Automatic processing of video for movement and flow detection
– Face detection, tracking and classification
• VidiCenter: a back office in the cloud that allow the management of
sensors in the field, the storage of sensors data, data coherence and
analysis of data measured to produce customized reports
Those solutions are completely anonymous and respect customer
privacy as they never store images or any data that can be traced
back to a single person.
A robust and discrete solution
5
• Ability to use store internet or standalone 3G router solution
• Robustness: works 24/7, automatically reinitialization in case of
power shutdown. Remote monitoring and automatic IT notification
in case of hardware issue
• Discrete cameras (3x8x2cm) and easy to install/hide hardware
(VidiCube 12.5x12.5x3 cm et Amoobi 20x11x6 cm) that can be fixed
on walls or installed in the branch ceiling
The measurements
Number of visitors and demographic categories (gender and
age categories: child, young adult, adult, senior)
 Presence depending on time of day/period (day, week,
month,….)
 Average dwell time in branch
 Traffic dans l’agence et ses départements
 dwell and attention time to a measured point (digital
signage, poster, windows, shelf … etc.)
 Conversion Rates (entrance to aisles to shelf to product..)
And any combination TBD !!!
6
Wave Division deliverables
7
 Optional : Help to select statiscally relevant
sample of branches to be measured
 KPIs (totals, averages, ratios, …) as reports on frequency
TBD adapted to the graphical charts/logo requirements
from customer
 Study of customer flows/paths in store
 Comparison by period, by site, by demographic group
 Analysis of trends (average days /weeks,…)
Other Possible analysis
8
 Benchmarking between location/industries/period of time
 Data-mining and correlation (sales number, wait tickets, demographics, playlist of
played media on digital screen etc.)
 Customer loyalty and customer satisfaction (using satisfaction kiosks)
 Comparison of various branch layouts (before/after, concept stores …)
 Study on the impact of windows and any promotional media (digital screens,
posters…)
…
About Quividi?
 Pioneered Ananymous Face Detection in 2007
 The leader of OOH (Out of Home) audience measurement
 Date Measurement, management and analytics for 200 clients
dans 43 countries with 2.5 B+ faces detected
9
www.alt64.com www.quividi.com
www.medicionaudiencia.com

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Shopper intelligence by Alt64

  • 1. Measuring customer behaviour in-real-life 1 0 10 20 30 40 50 60 70 80 90 100 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 Evolution over an average day undef. Women65+ Women35-65 Women15-35 Womenchildren Men65+ Men35-65 Men15-35 Menchildren
  • 2. The challenge Understand trends and patterns in the behavior of customers in the store How many people come in on an average day? What’s the peak hour? Where are the hot zones? How long do they stay? How often do they come? What is the first place in the store they go to? What’s the percentage of visitors watching my media? For how long? What best attracts their attention? How does the profile of visitors evolve over time? Do people behave differently depending on their gender and age? How do the various locations compare one another? And to global benchmarks? 2
  • 3. Proposed Solution 3 • Alt64 delivers a full turnkey service along with Quividi and its technology partners to: – Provide an advanced in-store measurement solution/methodology – Validate the branches chosen for the deployment of this solution – Install and setup the solution in stores – Monitor/manage the technology 24/7 to establish best quality of results – Establish meaningful KPI and produce the data reports that help you optimize the experience in the stores – Plan technically and commercially a solution across branches to provide the dashboards that can be used to monitor/optimize store performance and customer experience
  • 4. The technologies used 4 • Amoobi WiFi/Bluetooth sensors for smartphone radio tracking • Quividi VidiCube, a robust hardware plaform that allows – Automatic processing of video for movement and flow detection – Face detection, tracking and classification • VidiCenter: a back office in the cloud that allow the management of sensors in the field, the storage of sensors data, data coherence and analysis of data measured to produce customized reports Those solutions are completely anonymous and respect customer privacy as they never store images or any data that can be traced back to a single person.
  • 5. A robust and discrete solution 5 • Ability to use store internet or standalone 3G router solution • Robustness: works 24/7, automatically reinitialization in case of power shutdown. Remote monitoring and automatic IT notification in case of hardware issue • Discrete cameras (3x8x2cm) and easy to install/hide hardware (VidiCube 12.5x12.5x3 cm et Amoobi 20x11x6 cm) that can be fixed on walls or installed in the branch ceiling
  • 6. The measurements Number of visitors and demographic categories (gender and age categories: child, young adult, adult, senior)  Presence depending on time of day/period (day, week, month,….)  Average dwell time in branch  Traffic dans l’agence et ses départements  dwell and attention time to a measured point (digital signage, poster, windows, shelf … etc.)  Conversion Rates (entrance to aisles to shelf to product..) And any combination TBD !!! 6
  • 7. Wave Division deliverables 7  Optional : Help to select statiscally relevant sample of branches to be measured  KPIs (totals, averages, ratios, …) as reports on frequency TBD adapted to the graphical charts/logo requirements from customer  Study of customer flows/paths in store  Comparison by period, by site, by demographic group  Analysis of trends (average days /weeks,…)
  • 8. Other Possible analysis 8  Benchmarking between location/industries/period of time  Data-mining and correlation (sales number, wait tickets, demographics, playlist of played media on digital screen etc.)  Customer loyalty and customer satisfaction (using satisfaction kiosks)  Comparison of various branch layouts (before/after, concept stores …)  Study on the impact of windows and any promotional media (digital screens, posters…) …
  • 9. About Quividi?  Pioneered Ananymous Face Detection in 2007  The leader of OOH (Out of Home) audience measurement  Date Measurement, management and analytics for 200 clients dans 43 countries with 2.5 B+ faces detected 9