Expert columnists
March 9, 2022

Examples of Successful Loyalty Programs

Mindbox’s founder Ivan Borovikov explores how well-known companies work with loyalty programs, and how they have the potential to make up to half of their revenue. We’ll be taking a look at the cases of Burger King, the Kant sports store chain, the Rigla pharmacy chain and United Colors of Benetton.

A loyalty program is like an iceberg. The part that is visible to the customer is made up of discounts, bonus points, and different loaylty levels (we’ll refer to this as the public part of the mechanics).

The purpose of this “visible part of the iceberg” is not to earn money for the store, but to spend it on obtaining the customers’ personal data and linking it to customer purchase information, website and app visits etc. In this case, the money facilitates the processing of personal data obtained with the help of the mechanics described below.

A loyalty program is a complex marketing tool. It can show high economic efficiency and provide up to half of the company’s revenue. That being said, misunderstanding this tool could result in a mountain of problems. However, not using it would risk disappointing customers.

In this article I’ll be exploring what we mean by “a successful loyalty program”, and I’ll be analyzing the ideal process for developing a loyalty program using United Colors of Benetton's example.

A Successful Loyalty Program’s Elements: Expenses and Profit

A successful loyalty program consists of:

  • The “visible part of the iceberg” that represents the collection of customer personal data and information about their behavior and purchases at retail points of sale. This is achieved by authorizing (i.e., recognizing) the customers when they make a purchase using any identification mechanics such as a plastic card, a digital wallet, a personal promo code, or a mobile phone number.
  • We combine this data with information obtained from other sources, such as a mobile app.
  • The collected data helps us apply the multifaceted approach for working with our customers that is ultimately aimed at increasing LTV (Lifetime Value).

Therefore, we believe that the loyalty program is made up of two crucial components: data collection and the construction of targeted marketing.

Data collection is an expense. When customers log in online or via their phones, the business is able to understand customer behavior as opposed to the order value. No such approach exists in retail, which means companies either have to invest or sacrifice part of their profit margin in order to incentivize customers to authorize themselves, i.e., show their loyalty member card at the point of sale or give their phone number to the cashier.

When building up an accurate representation, it is important to stimulate the customer to specify their data in other points of contact, for example, on the website, and on the app.

Various public mechanics such as cashback for purchases, gifts, or accumulating bonus points are used to collect data. No matter how creative and complex these mechanics are, it’s challenging to assess their impact on the business. It is possible that customers could have made purchases without any additional incentives.

By default, it would be better to see this part of the loyalty program as an expense. In other words, it is an investment made to obtain customer personal data that will be used in the future.

Burger King collects data from loyalty program members in exchange for discounts of up to 50% and an increasing cashback percentage.
Burger King collects data from loyalty program members in exchange for discounts of up to 50% and an increasing cashback percentage.

Targeted marketing brings profit. It can be used alongside personalization to motivate customers to take certain actions, for example, to make a repeat purchase. With this data, we can get to know the customer at different points of contact, determine their interests and interact with them directly through communication channels such as email, SMS, mobile and web push notifications.

Complete information about the client helps us reasonably assume what kind of discounts they may be interested in, what product should be offered, and when we can expect the next purchase. In other words, it helps us understand the Best Sending Time when it comes to sending relevant personalized offers to the customer.

Burger King email
Burger King email with a list of all current promotions for customers who have not ordered anything on the app in the last 10 days. This is aimed at increasing purchase frequency.

According to our clients’ statistics, the personalization of email mailings alone increases company revenue by an average of 13.9%. The highest rates are in the fashion industry (24%) and cosmetics (25%):

Our clients' stats

Personally, it was a revelation to me that this approach worked even in real estate. One of the leading real estate companies, PIK Group, directs customers through the funnel automatically, using a complex scheme of automatic mailings that support the customer’s decisions at various stages. We can therefore assume that the personalization of other channels – i.e., website, mobile app, SMS, and messengers – will produce the same increase in revenue.

As a result, targeted marketing can generate at least 20-30% of sales. For the fashion and cosmetics industry, this figure can account for up to half of the company’s revenue.

Here’s a very illustrative example: 49-72% of purchases in large pharmacy chains as Rigla, Zhivika, and Bud Zdorov are made by members of loyalty programs, and their average order value is 61% higher than that of ordinary customers. This happens due to the fact that loyalty program members have personalized offers on frequently purchased drugs.

Another benefit of targeted marketing is that it helps us save on paid customer acquisition. This is especially true for companies where the majority of customers come through paid channels, for example, contextual advertising or targeting on social networks.

Target marketing makes it possible to redistribute the advertising budget, i.e., spend less on paid acquisition and more on developing different promotions. Promotions allow you to reach the customer and achieve repeat sales, an increase in the average order value, or, for example, recommendations to other customers.

The example of the Kant sports store chain illustrates this principle. The loyalty program was launched in April 2020 and at the height of the pandemic, the average order value with the use of bonus points increased 1.7 times, and the retention rate increased by 33%.

The loyalty program made it possible to reach out with personalized offers to a loyal audience that made large purchases and gave them great rewards during that period. The customers liked the targeted offers so much that Kant’s call center couldn’t cope with the large flow of orders. In a successful loyalty program, the profits exceed the costs of data collection.

To sum up, a loyalty program should ideally consist of:

  • costly but effective public mechanics to collect contacts;
  • targeted marketing that results in revenue.

Data collection is only the first step and it makes no economic sense without targeted marketing. The company must have a dedicated employee who’ll be dealing with this data. Ideally, this employee should be hired before the loyalty program launches. Involvment at the project’s initial stages is crucial.

A similar approach works when it comes to choosing the technical solution. Without a ready-made infrastructure and integrated software, the loyalty program simply won’t “take off”.

What a successful loyalty program looks like in practice. The case and experience of United Colors of Benetton

In recent years, United Colors of Benetton’s priority has been the digitalization of the brand’s interactions with customers, getting a clear picture of what attracts them and what repels them. The omnichannel loyalty program has become a tool for obtaining customer data.

Once Benetton’s marketers had drawn up the basic rules of their loyalty program, it was time to find the technology to launch it. Finding and selecting the technology took just over a month, followed by three months, which saw the entire integration, pilot launch, and error correction completed.

Six months later, the company strengthened its marketing staff with a CRM manager. The CRM manager is responsible for launching personal offers and promotions, guided by an e-commerce director.

The terms of the loyalty program allow you to create a range of personal offers for different customer segments
The terms of the loyalty program allow you to create a range of personal offers for different customer segments, for example, double bonus points for the churn segment

The Color Club loyalty program operates in 19 offline outlets and an online store. Digital wallets for Android and iOS are used for convenience and to communicate with customers.

In the first year, the main KPI was engagement, i.e., the number of loyalty program members in the database. We reached our goal of 200,000 customers in the first 12 months, doubling the number of members in the next year. We now expect to reach half a million members by mid-2021.

The company is very happy with these figures because they see the main purpose of the loyalty program as collecting information about customers: what they buy, how often, and which product categories are more popular.

Accumulated customer data makes it possible to personalize your communication with them. As a result, the email and SMS channels help United Colors of Benetton earn ~20% of total online and offline revenue, while the share of total online revenue reaches ~32%.

I would like to emphasize the role of direct communications for loyalty program members. In this segment, the added online revenue relative to the control group amounts to several million rubles per month.

In addition to money, Benetton also looks at the “health” of loyalty programs, for example:

  • how the balance of bonus points received by loyalty program members affects their involvement regarding purchases and the growth of the company’s turnover. If customers receive but do not spend bonus points, this should act as a wake-up call. Fortunately, Benetton does not have this issue;
  • how the loyalty program affects the average order value. It is evaluated in relation to promotions, bonus points, and discounts. With these indicators, Benetton can see how the loyalty program affects the overall profitability of a particular store.

Dashboards for analysis are built on the basis of Power BI. They give the client a breakdown on the efficiency of the loyalty program:

One of UCoB's dashboards
One of the Power BI dashboards of United Colors of Benetton within the loyalty program. Data has been changed.


A loyalty program should ideally consist of two key components:

  • costly but effective public mechanics to collect contacts;
  • targeted marketing that drives revenue.

A successful loyalty program is one in which the profit from personal promotions exceeds the cost of data collection.

Benetton is a good example of what a loyalty program looks like in an ideal world. In the next article, I’ll be sharing with you what mistakes to avoid in order to repeat this experience.

Source: RB

The following case study is from Mindbox, the original brand behind Maestra’s technology