Case Study: Increasing Restaurant Revenue by 97% by Connecting Email and POS

How did we increase revenue by 97% in fast-casual dining simply through the email channel?Spoiler alert, the answer is email engagement and point of sale data.

Email remains the only channel with a clear, trackable ROI. The right strategy transforms it to the most effective channel for maintaining customer loyalty and increasing revenue. The combination of E-commerce and retail creates a unique opportunity to correlate email metrics with online sales and POS data. This is especially true for retailers utilizing targeted segmentation strategies with personalization and sending at the optimal time.

So how does a restaurant build customer loyalty, increase customer traffic and grow revenue by utilizing the same tactics? How can they track ROI on email when the goal is to get people into a location vs. an online purchase?

Restaurants, especially the small ones, have small marketing budgets and HAVE TO demonstrate ROI immediately. Like any other business, they rely on repeat customers, so creating that brand loyalty is critical.

When they focus on data driven email marketing and segmentation they can achieve similar success to that of the retail space.

Connecting POS to email…

All restaurants are different.A deep dive analysis of the POS data reveals some loyalty trends. Customer loyalty is different depending on the type of restaurant. For a fast-casual restaurant in a high traffic business area, loyalty might begin on the 3rd or 4th visit in 30 days. For fine dining, this might be the 4th visit in 60 days.

Recently, we ran a data analysis for a fast-casual restaurant brand. For this brand, we determined that loyalty started on the 4^th visit within 30 days and that people become less loyal if they hadn't purchased in 30 days. We built a segmentation strategy to quickly engage first time customers moving them to the 4^th visit. By targeting first time customers, we saw a 28% increase in visits for this segment.

The goal is customer loyalty, and we achieved that very quickly, but there is more juice in the lemon. Once they are loyal, the focus is retention and the POS data reinforces this objective.When tying POS data to email intelligence, fifty percent of email revenue came from the most loyal segment for this fast-casual restaurant. When they started to email on a more frequent basis (previously emails were sent very ad-hoc) they were able to increase transactions rates by more than 150% for this group.

The restaurant wanted to take it a step further and truly understand how to increase the number of visits, retain customers and win-back lapsed customers.

In Comes Audience Optimization

We just discussed how POS data can help identify the most loyal customers. But what about lapsed customers? Yes, restaurants have them too! Are the same "win-back" strategies as effective with fast-casual dining as they are with retail brands? Do customers respond to time of day and day of week targeting, like their retail counterparts? The answer for restaurants is an emphatic YES!

By combining email behavioral data with POS data, the restaurant could determine if subscribers were lapsed customers or just no longer engaged with the email program. If they were still customers, they needed to be better engaged with email and if they were engaged with email but not customers, they needed to be converted.

Loyalty programs with an incentive definitely help to achieve this. However, not all restaurants have an incentive based loyalty program. We first attempted to determine the best day of the week and the best send-time. There are many tools within email platforms that can help you determine the best day to send email to your subscriber list. However, we chose to go a different route by using Audience Optimizer. I already knew of the success with Audience Point's Send-Time Optimization tool and wanted to see if similar results could be achieved by driving people into a location.

Through Audience Optimizer, we were able to pinpoint the day of the week that someone was most likely to engage, which allowed the restaurant to win back 10% of lapsed customers. This approach actually accounted for close to 50% of the revenue from email. New customers saw a 26% transaction rate.

The most significant result was when we compared total revenue from the previous emails to the email utilizing Audience Optimizer. By utilizing this tool, the email generated a 97% increase in revenue from email. The restaurant was also able to see a cost savings by determining who was no longer engaged with marketing messages.

What's next…

Email is complex and data plays a critical role in developing a good solid strategy. Small changes to a program can achieve big results. Far too often I see companies that don't really take advantage of the tools that are out there or utilizing customer data. Nearly doubling revenue from one small change shows the power that email marketing can have, even for a small business.