AI-based video analytics can improve the customer experience for online retailers by gathering valuable customer data from video feeds. This includes information on how customers move through physical stores, what products they look at, and who is visiting. Retailers can use sensors and CCTV cameras to collect data points on customer demographics, dwell times, queue lengths, and returning visitors. This data provides actionable insights like optimizing product placement, targeting promotions, and improving the overall customer journey through facial recognition.

1. How can AI-Based Video Analytics
improve the customer experience?

3. Online retailers knows everything about their customers
Information?

4. How are people moving in your stores?
What are your customers looking at?
Who is visiting your stores?
How many visitors do you have?
Returning customers?
Conversion rate?
Examples of information requested

5. Sensors?
Connected devices – 75 Billion
What data points can be used?
Video – investments?
Actionable analysis?
IoT?

6. How are people moving in a store?
Using the CCTV infrastructure of
the shop
Camera feed
By customer type (demography)
Learnings from historical trends
Dwell times
Number of visitors
Number of checkouts open
Number of people queuing
Counting
Real-time alerts to open new
checkouts
Reporting for staff scheduling
Reporting dashboard on visitors
Queue management
Customer’s age & gender
Demography

7. • Takeaway #1 goes here
• Takeaway #2 goes here
• Takeaway #3 goes here
Actionable Takeaways from this session:

8. • Gather information based
on customer interest
• Promotion optimization
• Attractiveness of product and
placement
What is being touched?
What is your customer looking at?

9. • Re-Identification
• Returning customer
Who is visiting your store?

10. Customer journey with face recognition at BUD airport
(retail)

11. Simple customer journey (enter)

12. Simple customer journey (POS match)

13. Simple customer journey (exit)

14. Gender analysis (with POS matching)

15. Age analysis (with POS matching)

16. Returning customers with Facial Recognition

17. Number of persons entering in the showroom daily
Age and gender statistics of entering persons to showroom daily
Average dwell time (average time customers spend in the showroom)
Dwell time for more areas (time one customer spends within a defined
area)
Age and gender statistics of the customer in an area
The time between entering in each area and the first interaction with the
sales consultant
Statistics about returning customers (reidentification of the same person by
the next visit or visits
Infiniti Middle East – Optimize sale and customer
experience

18. Thank you!
And please visit us at
stand #6145
www.ultinous.com
business@ultinous.com
linkedin.com/company/ultinous/