Product Insight

Loyalty: The New Wealth for Businesses

How Loyalty Programs Can Build Customer Trust and Retention

Author

Scott Uchiyama

Director of Research & New Product Development

Monday, March 16, 2020

Replace

A decade ago, Database Marketing Group built the Safeway/Von’s Pavillion ‘just for U’ loyalty program with customer retention, increased engagement, and building the average spend/frequency in mind. This highly customized program considered each shopper’s personal purchasing habits, as well as being able to adjust and minimize markdowns based on the consumers recency, frequency and spend levels. This approach vs. the traditional mark down helped us move away from the “one discount fits all,” 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 top of mind.

“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, AI and marketing databases growing significantly, we are able to create individualized efforts towards any given customer, at any given time to drive increased transaction sizes and visit frequency, as well as build a personal relationship between the retailer and their customers.

An effective loyalty program can be a driver for not only 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 to engage participating customers and drive revenue?

Simple UI/UX

Have you ever downloaded a mobile app on your phone having high expectations, only to be let down because you couldn’t understand how to use it or find the information you were 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. So, why did they fail?

We often work with clients that want to add feature after feature, but then it starts to become so cluttered that the users don’t know how to use it, let alone receive its benefits. 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 and easy to see immediate gains and ease to engage and encourage redemption. Not only will this motivate your customers to utilize it during their visits but it could result in increased frequencies of sales. An easy-to-use loyalty program will have your customers excited to earn value and redeem 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 in improving your overall program performance.

  1. Analyze User Data
    • App/Digital Portal Metrics - time spent on app/webpages, email/notification opens, downloads, deletes, user counts
    • Purchase Habits (both increases and decreases) - visit frequency, basket size, item selection, repeat purchases, cross shopping patterns, time of purchases/visits, etc.
    • Location-Based Information – store locations they visit, in store offers/CTAs redeemed
    • 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.
  2. User Data Segmentation
    • By using AI and machine learning algorithms, your user data can be analyzed to glean actionable information. We recommend using the customer data to develop consumer scoring models, or segments. Partnering with our clients to define these scoring algorithms, we can feed the user data into different value categories:
    • Consumer Scoring Model

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 feature 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 are expecting 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.

Learn more about how to segment and glean your database in our next blog: Waste Management