This question was asked during our Office Hours - Session #2 where we covered the topic of Customer Segmentation for Restaurants.
As a QSR (Quick Service Restaurant) specializing in salads, bowls, and sandwiches, what metrics do you recommend we look at to segment customers based on their attitudes about health-conscious takeout options?
from Sasha Bartashnik, Director of Data Products, and Nick Lanoil, Sr. Business Development Manager.
Defining Goals and Metrics
Depending on your goals, the actions you take might be different. For example,
Acquisition - Your target is a strongly health-conscious takeout customer and you are looking to understand where or how you can find more customers like this to acquire.
Retention - You want to identify those really health-conscious customers within the existing customer base, so you can engage them more directly.
Although your goals might be different, you can start the segmentation process using the following steps.
First, you need to define what you mean by "health-conscious." Perhaps there are certain menu items that your brand considers to be healthy. Then rank customers by that volume or proportion and select, for example, the top 25% or top 10% of customers who've purchased those items. You can also apply this approach to specific ingredients or add-ons.
Some examples of options you might consider as "health-conscious":
Customers who add avocado
If you have these as options in your menu, you can track that data. Generally through, ingredient-level or modification-level data might be a little harder to track. Such options are not commonly a part of restaurants' standard menu options and ordering. The data could be less trustworthy if you're not categorizing it.
Instead of thinking about which menu items are actually purchased and considered as "healthy", you might actually be thinking about this a little more broadly. Maybe you truly want to know the attitudes, not the purchase behavior. Attitude is a little different. It is more about the intent, rather than what a customer already did.
Consider serving your customers an email survey. It might go to all customers or just a segment that you identified by one of the prior metrics above. You can ask them questions you have about their interest in healthy cuisine.
Maybe you don't have a lot of menu items that you would consider health-conscious and you're trying to explore. Not everyone will answer, but likely those who really care about this topic will. And then you found yourself a really strong health-conscious segment that you can work with.
Using Your Data
When thinking about customer segmentation, it's important to consider how you're planning to apply that data back to your goals. You really don't want to be creating or capturing data if you don't have a goal for how you're going to apply that work.
For customer acquisition, you can create targeting via lookalike audiences based on those groups that over-indexed on health-conscious purchasing or behavior. Also, think about identifying not just customers who over-index on that kind of behavior, but also those who score highly on metrics like lifetime value and retention so that when you're creating a lookalike audience, you are creating it based on a really strong customer group that you actually want to keep attracting.
You also might want to understand what characteristics those strong health-conscious customers share. Then look for ways to attract customers based on those characteristics.
For example, let's say you found out that many of those health-conscious customers were acquired from an in-store promotion at a specific location, or through specific types of ads. Once you see what's working for new customer acquisition, you can do more of it.
On the retention and engagement side, once you've identified a segment you can target that group with personalized messaging, such as special emails promoting relevant menu items. You can also use more health-branded messaging that you maybe don't want to send to the rest of your customer base.
Brightloom is an AI-powered customer segmentation engine that helps restaurant brands scale by understanding their customers and sending personalized campaigns. It recommends personalized marketing content and strategies focused on improving customer loyalty metrics such as visit frequency and customer lifetime value.