Blog > Tervolina decreases loyalty expenses without losing efficiency

Tervolina decreases loyalty expenses without losing efficiency

TERVOLINA owns one of the largests shoe and accessory retail chains in RF. Stores are located in 9 regions of the country, from Northwest to Uralian federal regions. In the beginning of 2020 the retailer decided to transfer to the new loyalty management system – RS.Loyalty&CRM.

Transition process

The transition to the new loyalty management system took a bit more than two months. The active phase of the project started in the middle of March 2020. TERVOLINA specialists set up casheers and product movement management integration with their system on their own. ASTOR implementation team provided consultation for this stage, then trained TERVOLINA personnel to use the system. 

By the end of May the system was tested by the personnel of the pilot store in Belgorod. After three days of operation the retailer decided to apply the system to the entire chain. System implementation took one week and by Jun 1 RS.Loyalty&CRM was launched in every store of the chain.

How changes affected customers

For retailer’s clients the transition process was imperceptible. Balances of loyalty program participants and active reward systems were transferred to the new system:

  • Threshold cumulative bonus program
  • Discounts based on receipt sum threshold
  • Discounts based on the amount of products on the receipt
  • Two products for the price of one
  • Cupon mechanics
  • Gift certificates

Benefits for retailer

RS.Loyalty&CRM helped to decrease customer reward system operation expenses. Increase in the number of clients and transactions will not increase operation expenses:

  • Push notifications are free for the audience of any size.
  • Data storing and processing for all clients (cardless included) is not tariffed
  • API access for shares import/export require no additional payment
  • Call center services are free as a part of the anti crysis policy
 With RS.Loyalty the retailer kept all of the effective loyalty management instruments while decreasing overall expenses of operating the cloud loyalty system. 
Mark Tartakovsky, CIO of Tervolina

It’s worth mentioning the quality of the support- the project team was always in touch.  Technical support is available on every day of the week, 24/7. ASTOR specialists deal with unexpected situations quickly and provide qualified assistance to my colleagues.

Solution development

One of the key criterias for choosing the new system was the ability to transfer to the new customer loyalty management model based on Big Data for decision making.

RS.Analytics Loyalty module gathers information on sales, reward system, customers, and the content of their baskets. The system presents the data to the user in the form of convenient dashboards and reports. This presentation allows to identify hidden correlations and make informed and strategic customer management decisions. Analytical module implementation is planned for the end of summer 2020.

RS.Analytics Loyalty has more than 40 analytical tools preset to evaluate the effectiveness of marketing promotions, segmentate the client base, perform A/B testing, etc. 

Classic loyalty management goals are increasing check’s sum and depth, increasing sales for special products, introduction of new products into the range and removing them from it. To achieve that it is more profitable to work with segments of customers rather than with the entire customer body. 

For example, with RFM analysis the retailer can identify “leaving” customers and send them special deals with push notifications. With RFM analysis it is also possible to identify big spenders.

For example:
With RFM analysis the retailer can identify “leaving” customers and send them special deals with push notifications. With RFM analysis it is also possible to identify big spenders.

Сohort analysis can help identify clients who bought a specific product to send them offers for similar products. For example, sending them personal discount coupons for new winter shoes to clients who bought winter shews two years ago.

Client base can be segmented by reward system participation, loyalty to specific brands, frequently bought products, etc. Set of identifiers is not limited — retailers identify them on their own, depending on their goals.

RS.Analytics Loyalty allows to evaluate reactions of specific customer groups on marketing events. The system allows users to understand correlations between actions taken in the loyalty system and monthly KPI dynamic.