How Loyalty Programs Can Build Customer Trust and Retention
A decade ago, DBMG built the Safeway/Von’s Pavillion ‘just for U’ loyalty program with customer retention, increased engagement, and building the average customer spend/frequency in mind. This highly customized program considered each shopper’s personal purchasing habits, resulting in the capability to adjust and minimize markdowns based on the consumers recency, frequency, and spend levels. Unlike the traditional markdown, the approach helped us move away from the “one discount fits all” concept, and allowed us to create segments of customers based on their level of interaction with the brand. After analyzing the data, we then created tailored experiences for each individual customer with personalization and convenience as the highest priority.
“Some of the points of differentiation that set Safeway’s Just for U loyalty program apart is the level of personalization, the level of predictive analysis of a shopper’s needs with the segmentation of products a consumer buys regularly from products that a consumer might buy regularly.” – Steve Burd, previous CEO.
With the advancement of technology, and AI and marketing databases growing significantly, we are able to design individualized efforts towards any given customer, at any given time to drive increased transaction sizes and visit frequency. Ultimately, this helps to build a personal relationship between the retailer and their customers.
An effective loyalty program not only drives increased loyalty with your existing clientele but can also be used as an acquisition tool. So, what does it take to build a successful loyalty program that engages participating customers and boosts revenue?
Have you ever downloaded a mobile app with high expectations, only to be let down because it was impossible to find what you’re looking for? You are not alone. A common statistic within the retail industry found that 90% of users stopped using a loyalty app/program due to poor performance. But, why did they fail?
When building their apps, businesses often want to add feature after feature. This way, mobile apps can quickly become cluttered, and users won’t know how to use it, let alone receive its benefits. Herein lies the key to a successful program: Keep it simple. Users should be able to quickly understand how and when to use the loyalty app/program and see the benefits immediately. The rewards system should also be kept simple. Make it easy to see immediate gains, allow for ease of engagement, and encourage redemption. Not only will this motivate your customers to utilize it during their visits, but it could result in increased frequency of sales. An easy-to-use loyalty program will have your customers excited to earn and redeem valuable rewards in no time.
User Data and Segmentation
When it comes to loyalty programs, there are two steps to using your data that can make a significant impact on overall program performance.
- Analyze User Data
- App/Digital Portal Metrics: How much time are users spending on the app/web pages? What do your email/notification rates look like? How are the downloads, deletes, and user counts?
- Purchase Habits (both increases and decreases): How often are customers visiting? What is their basket size and what items are they selecting? Are there any repeat purchases or cross-shopping patterns? Does there appear to be a correlation between purchase times?
- Location-Based Information: Which store locations do they visit, and which in-store offers do they redeem?
- User Feedback: Engage with your audience and ask what improvements/features they would like to see in future versions. Then, evaluate the feedback, test, and implement.
- User Data Segmentation
- By using AI and machine learning algorithms, your user data can be analyzed to glean actionable information. Use this data to develop consumer scoring models, or segments. A good place to start for retailers would be with different value categories:
Data Insights for Retention and Acquisition
Customer value is just one insight that AI and machine learning can provide from analyzing your user data. Once you’ve established your consumer scoring models, you should be using this data to create customized communication that features different levels of campaign aggressiveness, messaging, offers, cadence, and channels to effectively reach that specific consumer segment. Monitoring, testing, and analysis of these segments over time will become the controlled variable when testing how well your loyalty program is working.
Today, consumers expect a true 1:1 personalized experience when interacting with your brand, and there is no better place to showcase that ability than with an effective, easy-to-use loyalty program with custom messaging and offers tailored specifically for them based on their shopping habits/user data.