Handling Loyalty liability

Our team was responsible for POS Loyalty program. During exploratory UX research many users shared their concerns about Loyalty Program liability and its effect on their business. They communicated the need to control the amount of Loyalty in circulation, to manage Loyalty liability. We built loyalty expiry feature, a solution that helps merchants control their loyalty liability, adjust it to their business requirements and customer shopping habits. The expiry feature was launched in May 2023, and allowed to expire more than $0.5 M in Loyalty dollars during first 3 months of its operation.

My role: In close collaboration with PO and tech lead, I prepared and participated in user interviews, mapped current user journeys, defined the pain points and formulated the HMW statements. I performed a comparative analysis of the three different expiration methods and conducted additional user research (surveys) to confirm our approach. I mapped the future user flow and designed wireframes and hi-fi mocks for the final solution.

Uncontrolled liability – what can be done?

Based on UX research results, I mapped the current user journeys and main workarounds merchants used to solve for the liability control issue. We got a good understanding about the reasons merchants might want to enable Loyalty expiry.

I followed with the ideal conceptual user journeys, journey not related to any interface. They helped to understand how the solution could work and what flexibility users might need to manage liability effectively. Based on these journeys, I formulated How Might We (HMW) statements. After sessions with the Product Manager, stakeholders and design team, we had a set of finalised HMW statements to address the problem of loyalty liability.

Getting control – Loyalty expiry base on last purchase date

We knew that the problem can be solved by introducing loyalty expiry, this solution was very prominent. The challenge was to determine the expiry type. I carried out a comparative analysis of three loyalty expiry types. Several criteria were selected to compare the expiry methods, such as “How many merchants can benefit from this method?”, “For how many merchants will it be sufficient?” “How will it influence customers behavior?”, “How easy is it to understand for customers?” “How feasible is it for our dev team?” etc.
Taking into account all these considerations, Loyalty expiry based on last purchase date seemed to be a winner.
To verify our choice of expiry method, we conducted an email survey with the users. We also wanted to get more information about expiry parameters our merchants would need to consider for their business model and customer’s life-cycle.
The survey results were very encouraging. They confirmed our choice and proved that our vision of the problem and its solution reflected the user’s needs. Moreover, the reasons our users gave to support their choice were very insightful. They helped us better understand the way merchants view Loyalty, their motives and goals.

Three HMW statement, three solutions

Results

The expiry feature was launched in May 2023, and had a very good adoption rate. It allowed to expire more than $0.5 M in Loyalty dollars during first 3 months of its operation.

Takeaway

To organize the user interview for this project, I gave our team members a brief introduction to Dovetail. We registered, arranged, transcribed, and tagged the interviews in Dovetail. Using this software, we were able to define the most commonly cited difficulties and issues and conduct an effective analysis of the findings.
Dovetail provides excellent tools and raises the bar for customer research considerably. Since we first used Dovetail, it had become a “must have“ research tool for our team.

Due to company policies and confidentiality agreements, I do not share all visual materials for this project. If you want to know more about the problem discovery approaches or solution design methods and tools, please explore other projects or reach out to me directly.