In today’s world of discerning consumers, vast amounts of data, proliferation and increased accessibility to artificial intelligence (AI), having a “me too” loyalty program with a mass communication approach is no longer cutting through the competitive clutter.
At the same time, unfortunately, too many Canadian retail loyalty programs do not leverage their unique assets, including customer data. Instead, they all offer the same features whereby members earn points for every dollar spent, which can then be redeemed for dollars off their future purchases or store gift cards.
As a result, retailers get into a complacent manner of thinking wherein points and cash back are the only possible currencies and means of value we can offer to our consumers in exchange for their spending at our stores. But this kind of thinking limits our ability to leverage our data to drive better consumer insights and deeper relationships with our shoppers.
Relevance and personalization are no longer just possible: they are mandatory to compete effectively and retain consumers. Mass programs are not just “safe”: they risk costing retailers as consumers are voting with their wallets:
Only 14% of consumers are satisfied with the level of personalization they receive according to Bond Brand Loyalty 1; and 41% of consumers said they ditched a company because of “poor personalization and lack of trust” according to Accenture2.
The truth is that many organizations would like to have more relevant loyalty programs and customer communications, but they do not know how to get started. In fact, 61% of companies say the lack of a clear roadmap is the biggest barrier to personalization, according to the Boston Consulting Group3.
Utilizing data is key
I believe that the key lies in utilizing your data: the best asset that makes your organization unique. The big question then becomes how do you unleash such data within the organization to help create the one-to-one relationships, programs, and dialogues with your shoppers?
We see the following common gaps in terms of analytics:
1. Companies either have unmanageable amounts of data or have vendors that manage their data and have to pay for access.
2. Consolidating data across all the data sources, especially with respect to providing a single view of the customer, is extremely complicated and therefore not always performed.
3. Reporting is available but is disjointed across organizations and uses many visualization tech solutions, which makes it difficult to consolidate.
4. The ability to come up with insights is light and sharing those insights across organizations is difficult.
5. The biggest issue facing companies is coming up with actionable steps to capitalize on the insights and seize the opportunities, closing the gap between companies’ current and desired states highlighted in the reporting.
To overcome these challenges, you need the right kind of partner with the right kind of experience, people, and tools.
Loyalty program data is particularly rich in providing valuable insights and should be included in such analysis. Your data could, for instance, help you create more differentiated rewards, such as experiential rewards that would help balance out your near-cash redemptions. Experiential rewards can be priced to bring down your cost per point, can be targeted to be relevant to each member or group of members, and are quite popular and highly valued by program members.
Loyalty data-driven successes
With our expertise in loyalty and data science, we helped a retail client noticeably gain more from their program. We accomplished this through:
1. RFM (recency, frequency, monetary) segmentation to identify the most valuable members;
2. Top product index analysis to identify the most popular products among the best members; and
3. Basket analysis to identify the products most likely to be added to the shopping carts.
We delivered key insights that helped both the marketing and merchandising teams to:
1. Enhance product offering in-store and online;
2. Understand what products to feature and offers to display and increase relevancy and response;
3. Better allocate the loyalty budget and resources toward the right customers; and
4. Direct the right bonus incentives to encourage more products to be added to the members’ baskets.
Here are my recommendations for unleashing the power of your data:
1. Start with strategy (the what and the why) rather than with marketing technology (the how).
2. Create a flexible program with relevance and personalization at its core instead of being strictly points or cash-back based.
3. Use your data to create a dialogue with your customers, customize communications with each customer and communicate with them in a unique way, to truly care about them and their opinions. Connect with them in a meaningful way: that provides your customers with the value they can’t get anywhere else. Value can be in the form of money, but better yet, the value should be in the form of customer experience.
4. Use what you learn to continuously adapt and evolve. Continue using new insights to innovate your business; continuous innovation will have your competitors always trying to catch up and never quite succeeding.
5. Worry about satisfying your customer (retention is key!) and not about what competitors are doing. Their customer is different and so are their insights. Stop looking around and look within.
Can any marketer afford to lose 41% of our consumer base to companies that are able to better understand and serve our consumers’ needs? Would you as a consumer rather participate in a program where you are one of the multiple millions of members or a customized program with a communication plan that speaks directly to you?
I believe the choice is simple. Retail “me too” programs are no longer cutting it. Data absolutely needs to be at the heart of any program design/redesign, and we can help you get there.
1 Bond Brand Loyalty, “The Loyalty Report 2017”, report, May 23, 2017.
2 Robert Wollan, Rachel Barton, Masataka Ishikawa and Kevin Quiring, “Put Your Trust in Hyper-Relevance”, Accenture, Global Consumer Pulse Research, December 5, 2017.
3 Mark Abraham, Steve Mitchelmore, Sean Collins, Jeff Maness, Mark Kistulinec, Shervin Khodabandeh, Daniel Hoenig and Jody Visser, “Profiting from Personalization”, Boston Consulting Group, article, May 8, 2017.