How Technology Helps to Slay Discounting Demons

Restaurants recognize that a major key to success is repeat business from loyal customers. Using a loyalty program is often an excellent way to drive customers back to the business regularly. However, some restaurants fear that a successful loyalty program relies heavily on discounting, eating into company profits. In this exclusive Q&A, Michelle Tempesta, head of product, Paytronix, reveals that loyalty programs can be used for much more than just discounts. When used effectively, loyalty programs provide restaurants with a wealth of invaluable data, can incent lapsed customers to visit again, and can reward customers in more sophisticated ways than just a hard discount.

There is a wealth of customer data available through loyalty programs, how can restaurants avoid data paralysis and make smart decisions on promotions and ways to engage customers? 

TEMPESTA: Loyalty programs enable restaurants to drive incremental revenue. A program can be thought of as a big lever with the marketer at the controls. When optimized, the marketer can pull the lever to produce a predictable outcome – sales and visits. 

Once the brand has reached a critical mass of loyalty checks versus non-loyalty checks – let’s say at least 20%, it can then implement a strategy to move less frequent guests to more frequent behavior. For instance, moving them from 3-4 visits per quarter to 5-6 visits per quarter. Messaging, offers, and ultimately engagement start with a clear objective, “I want to move this group of guests to the next tier of visit behavior.” 

With an established objective, segmentation is clear and offer testing, the scientific approach to marketing, begins. What messages and offers are most effective at causing this segment to take the action I’m asking them to take? Testing is critical. Timely, accurate test results, inform the marketer of the message and offers that are most likely to achieve the desired outcome.

Thinking on an operational level, what are some ways technology can provide managers with actionable insights to make smart business/operational decisions? 
TEMPESTA: Getting accurate data in the hands of the operations team is critical. Operations needs to know that discounts are being strategically employed. If the operations team believes marketing is discounting full-priced checks, they will discontinue driving guests to the program. 

Instead, demonstrating the impact of the use of discounts in attaining incremental visits is paramount. With the use of target and control data that shows the behavior of guests who were presented with an offer versus those who were not incented to visit, marketers can clearly address the perpetual operational challenge: “Why are we discounting, when those guests would have come in anyway?” 

Getting this intelligence into the hands of organizational stakeholders is why Paytronix is testing various methods for delivering critical program information to the field. At this year’s Paytronix Users’ Experience, we demonstrated the use of Amazon Alexa, a convenient delivery mechanism for accessing insightful data. I can imagine a day when operators will be able to say, “Alexa, how many incremental visits did we have today?” and Alexa would respond, “You had 3,452 incremental visits today that produced $67,314 in sales.” This data is easily accessible in our system today via data visualization tools. Delivering it through Alexa is on the innovation horizon for us.
 

What is an effective way for restaurants to target lapsed customers and incent their return? 
TEMPESTA: Start by gathering data from the loyalty program. While there are several reasons for lapsed behavior, we typically see guests reengage with the brand for several months post win-back promotion. The others may have experienced a change in lifestyle, moved, or switched jobs. Around 5-10% of all members will move each year causing their traffic patterns to change. 

Getting the "win back" timing right is essential. The best way to address lapsed customers is to minimize the number that actually lapse. This strategy includes having a clear understanding of customers’ normal visit patterns. When that visit pattern is interrupted, custom, relevant messages should be deployed. Some may include offers.

With our convenience store customers, for example, we have identified a 7-day refueling pattern. When customers are approaching the 7-day visit, messages are deployed to ensure that the brand is top of mind when the consumer is making that purchase decision. Timing is everything. 

Once the guest has lapsed, targeting them with relevant, timely messages and offers can help win them back into a visit pattern. Testing offers and timing is essential for finding the right mix of offer, message and timing. Using expiration dates with the offer provides a sense of urgency – expiring offers within a week, versus a month can be a valuable activity driver. 
 

A common complaint for operators is how to win at loyalty without having to “give away the farm” in discounts. How can restaurants partner with loyalty providers to avoid this trap?
TEMPESTA: There is certainly discounting associated with a loyalty program. The types of discounts come in two categories, both quite different than discounting through FSIs or general email or social programs: 

Earned Rewards. These are discounts given to customers who are identifying themselves with each visit and earning either surprise rewards or published rewards. These discounts deliver value to the brand by incenting visit and spend behavior and rewarding customers for it. The program acts as a tie breaker between brands during the customers purchase decision. The second benefit is in the data. Once the brand understands the guests’ purchasing behavior it can leverage the data to expand and perpetuate that behavior – driving sales. 

Layered Offers. Using the data collected through the core program, marketers can segment and then use discounts with precision. In other words, use discounts where and when they need to nudge the guest to partake in a specific behavior – new menu item trial, new day part, new brand, new location, or increase visit cadence, and more. With our technology, the marketer can remove cannibalization from campaigns by using predictive analytics. A common application is to remove those guests who are likely to visit anyway from a campaign – why discount full priced sales, when you don’t have to? 
 

What are some loyalty “bad habits” that restaurants should “unlearn?” How can technology help? 
TEMPESTA: Restaurateurs have seen success in using their ‘gut instinct.’ In fact they’re darn good at it. I was just visiting one of our customers the other day. He said he sees a loyal customer sitting at the bar every other day enjoying rewards from the program. That guy at the bar may be making his decision to sit at your bar every other day because the loyalty program is present. The program is in fact acting as a tie breaker and thanking him for his loyalty toward the brand. 

Making program decisions based on this individual experience is a mistake. It’s only in the program data that you can see the impact it’s having from a macro level. In the macro program data, operators can see large movements in behavior from guests who visit infrequently moving up through to high-frequency segments. That’s where the program generates results. While there may be a few outliers one can witness at a micro level – trust the data from macro level and make decisions from that perspective.