ULA Retail

VIDEO ANALYTICS FOR RETAIL

Typically, 40 to 60% of your customers participate in a loyalty program. Therefore, retail chains receive information about buyers only from the transactional data of checks.

Computer vision algorithms get data about all customers, not just those who have loyalty cards. Video analytics provides the following information about the client:

  • icon

    time spent in the store (entry and exit times)

  • icon

    real gender and age

  • icon

    people they come to the store with (family or friends)

  • icon

    choice of a cart or a basket at the shop entrance, etc

The obtained data will help to segment customers better and to improve marketing activities. As a result, your marketing department will reduce communication expenses and increase share conversions.
carret

AIMS OFTHE SALES NETWORK, WHICH CAN BE ACHIEVED WITH ULA:

  • Increasing the LTV of customers with loyalty program
  • Increasing the number of loyalty program participants
  • Increasing the loyalty of visitors who are not registered in the program
  • Implementation of new channels of interaction with clients

The technologies of the analytical system help to create a detailed portrait of 100% of visitors, regardless of the presence of a smartphone and security settings in it. Other technologies which use IoT: BLE (Bluetooth Low Energy), Wi-Fi and UWB (UltraWideband) are able to find out information about only 30-50% of the audience.

IMPLEMENTATION SEGMENTS:
  • SUPERMARKETS
    SUPERMARKETS
  • CONSTRUCTION SHOPS
    CONSTRUCTION SHOPS
  • SHOPPING CENTERS ETC
    SHOPPING CENTERS ETC

ULA MARKETING RESEARCH:

To optimize marketing activities, you should turn anonymous receipts into personal ones. Thus, it is possible to perform a comprehensive monitoring of the audience mood. Such research will make it possible to create a database of customers and send them personal offers, which will increase the level of loyalty.

ULA MARKETING RESEARCH
INFORMATION THAT CAN BE FOUND THANKS TO THE SYSTEM:
  1. Indoor Movement Routes.
  2. Most Popular Zones: A list of departments that are popular and rarely visited.
  3. Visitor dynamics: new or return visit, increase or decrease of the number of return visits.
  4. Customers without loyalty cards: new and return visits.
  5. Marketing professionals will be able to work with regular visitors to enroll them in a loyalty program.
INFORMATION THAT CAN BE FOUND THANKS TO THE SYSTEM
CURRENT STATISTICS BASED ON THE PORTRAIT OF THE VISITOR
CURRENT STATISTICS BASED ON THE PORTRAIT OF THE VISITOR:
  1. Age and gender.
  2. Moving alone or in a group of people (family).
  3. Use of self-service scales.
  4. Use of Price checker technology in the hall.
  5. Use of carts or baskets while shopping.
INTEGRATION OF THE ULA RETAIL PROGRAM WITH THE CUSTOMER'S CRM:

As usual, the customer's CRM finds out that the customer is in the store only at the checkout when it is too late to send personalized offers to customers. ULA can send notifications to CRM about the client appearing at the shop entrance, which will make it possible to send a personal offer at the right time, thereby increasing the conversion of marketing activities.

Additionally, CRM will receive information whether clients came alone or with family, friends, and whether they took a basket or a cart.

A camera installed in the store department will detect the buyer's interest in a particular storefront and report this to CRM.

INTEGRATION OF THE ULA RETAIL PROGRAM WITH THE CUSTOMER'S CRM

SECURITY OF THE ULA SALES NETWORK:

The security of a retail space can be improved by the process of visitor identifying. The system creates several groups of people: visitors, VIP visitors, violators or thieves, employees.

SYSTEM CAPABILITIES:
  • icon
    Detection of customer`s elevated temperature with a thermal imager.
  • icon
    Detection of crossing the entrance line in the opposite direction not by a shop employee.
  • icon
    The entry of suspicious buyers into the area of expensive goods and goods with a high probability of being stolen.
  • icon
    Notification about cases of fraud or a buyer`s mistake if the product is weighted under the label of another product.
  • icon
    Detection of the cases when a buyer from the list of those who are suspicious goes to a certain checkout.
camera

* The correct performance of the scenario depends on the quality and location of the cameras.

HAVE YOU GOT ANY QUESTIONS?

If you have any questions or something remains unclear, our specialists will find answers even to the most difficult questions.

Contact us