Richard Simtob is the President and co-owner of Zoup! Fresh Soup Company, a 100-restaurant chain of fast casual soup, salad and sandwich restaurants. It is his belief that, in the restaurant industry, you live and die by how many repeat customers you get and how many new customers you get. When he wanted to track new and repeat guests he turned to Upserve for restaurant analytics.
Restaurant Analytics Shouldn’t Be A Guessing Game
Before Upserve’s restaurant management platform, Richard recalls what a nightmare it was to manage multiple locations and get insight into guest data.
“It was absolutely impossible. It was a guessing game. We always guessed. I wonder how many people are coming in and how often are they coming in?”
Richard needed brand-level and store-level insight into new versus repeat guests, restaurant analytics that Upserve’s platform delivers seamlessly.
“This store has been around 18 years. In the last 28 days, it still had 1,500 new customers come in, which is just phenomenal, first time people. We have Upserve in this particular location for over two and a half years now. 59% repeat.”
And the best part, he says? You can go back as far as you want to compare data. You can start to compare and see are the changes that we’ve done, thanks to Upserve, he recalls.
“We know that there’s an opportunity there that we lost customers, they’re not coming back and we’re going to have to work hard on bringing them back again.”
“It makes me really proud to see that I know that if I go back, let’s see if we go back to 2016 and I go back to January. Now, let’s go back further. Let’s go to 2015 and go January. Here, we could see our repeat customers then were 45% and our new was a little higher.
We’ve done management changes there, we’ve done other changes. Just last year, we’re at 53% repeat and you saw when I did the last 28 days, it went up to 59%. I could tell you just by looking at these numbers, that the actions and the things that we’ve done with our management and training have worked. That we’re getting increased repeat customers.”
Brand Level Restaurant Analytics At The Store Level
Managing over 100 restaurants means you need brand level restaurant analytics, but sometimes you also want to look at each store on it’s own, Richard says.
“One of the things that we’re able to do is we can look at our stores and you can sort them over here, where I’ve got stores with the highest repeat number. Stores like the Renaissance Center and Huntington Center are two stores that are in downtown office buildings. When I see 76%, no matter what the customer surveys and all that says, it means customers are coming back. 76% of every customer that’s coming into this place, is coming back over and over again because they work in that same building.
When I do see stores at the bottom here, it’s either new store or the stores that are not being run that great. I have to take out the new ones because the new ones haven’t been around a while but I see Avenir, this store has been around over a year and Avenir, it’s in Milwaukee and it only has a 43%. We know that there’s an opportunity there that we lost customers, they’re not coming back and we’re going to have to work hard on bringing them back again.”