Part Two of our Series “Demystifying A Restaurant CDP”
In our last blog post in the “Demystifying A Restaurant CDP” series, we talked about what a CDP (Customer Data Platform) is. The next steps are determining how you might leverage a CDP platform to make crucial decisions and decisive actions critical to your business.
Most people think of data as 1’s and 0’s, long spreadsheets with letters and numbers, and an overwhelming amount of knowledge that is difficult to organize and eventually use. You may even find yourself knowing the action or outcome, but the information you need is buried within those endless rows of information. However, data is like language, you put pieces together to create a sentence, a paragraph, and eventually a story.
In the restaurant industry, we have a unique overlap between consumerism, generating experiences, nurturing social relationships, and meeting basic human needs. This creates a stage to tell a story about your customers and their behavior using the data that you have gathered.
Lets outline the path from sitting at home, feeling hungry, and all the steps before and after dining in your restaurant.
The first step in understanding customer behavior is to understand who your customers are outside the restaurant. Over the decades Personica has researched key demographic factors which determine like-behavior between restaurant customers. The three critical indicators of dining behavior are:
- Marital Status
- Number of Children
This may feel overly simplified, but how you group these three attributes together creates distinct customer personas. Personica has defined the eight main demographic personas in a restaurant as:
Personica, like all proven customer-centric CDPs, will create and house these core audience segments as a starting point to micro-target or add additional complexity. For all of these segments, simply adding three fields on your join page (Birthday Year, Number of Kids, Marital Status) provides restaurants robust segmentation very quickly.
It is sometimes difficult to get inside the heads of all of your customers, but carving out a section in your CDP for survey responses, guest profiles, propensity for discounting, and other dining behaviors will help you identify key motivators. These will be the triggers for your marketing efforts to drive motivation-based decisions, even before customers identify they are hungry. Understanding the step for a customer to get off the couch (or stay and order online) is to identify what is motivating them to choose your brand to fulfill their need-state at that moment. Some examples of motivations and driving actions include:
- I want an amazing place to celebrate my birthday. <- Send Email Near Birthdate
- I need to feed my large family on a fixed budget. <- Offer Free Kids Meals
- I want to feel seen and have a good relationship with the wait staff. <- Remind of your “Cheers” Environment
- I have dietary restrictions which prevent me from dining at some restaurants. <- Send Message About Dietary Options
- I want to feel as if I am getting a good deal. <- Send an Enticing Discount
Now here is where having both a solid system of data storage meets a robust data processing center. Preferences can either be known or inferred. Sometimes it is difficult to get truthful, complete information from a customer about what they like, so we have to make some inferences about their preferences. Within your CDP you should have a clear silo of the known and the inferred preferences, because both can balance each other out. Since you never want to override a customer’s clear response of what they like with what you perceive they like, having both data points is critical for behavior changes over time.
One mistake restaurants sometimes make is that giving a coupon for an item means that the customer loves the item and is excited to receive the discount. However, research shows that people may order an item just for the discount, but may not actually enjoy it. If we were to perceive preference on this behavior, we would miss that the discount is the preference; not the item being discounted. Your data transformation process should include a score-based methodology to determine preference – not a yes or no.
This is where a CDP can really shine. When choosing a data storage platform, you really want to factor in being able to store all of your data and be able to process it quickly and efficiently. At Personica, we have built our CDP platform on a leading cloud database management platform, which allows for inexpensive storage of data and power house analytical processes. You don’t want to be stuck making the decision of only looking at subsets of your data because of technical limitations.
Purchases are the best bellwether of are you telling your story correctly. Did you understand the guest’s motivation correctly? Did they dine how you expected they would? Did customers try something new when you wanted them to? Was that discount a mediating factor to entice a lapsed guest to return?
Here is another example of how creating segments for starting points is a great idea. At Personica, we use a RFM (Recency, Frequency, and Monetary) segmentation model to provide brands with easy-to-understand and usable purchase segments.
How was your customer’s experience? Did they create new motivations to dine? Maybe they changed their preferences – were you able to track those changes? This is as critical a place in your story as the dining experience itself: understanding what type of customer left your restaurant vs. the type that came in. Your CDP should include a place to intake post-dining surveys, social and website reviews, and most importantly, checking to see if they make a return visit. Remember:
70% of Guests Try A Restaurant And Never Return
Telling Your Story
The first use cases of your Customer Data Platform should be identifying the customer stories you want to tell, and making sure you have the data to back it up. To tell great stories, start with this checklist:
- Add the three key demographic collection fields to any customer sign-up page (Birthdate Year, Marital Status, Number of Children).
- Create standard customer surveys that are repeatable for long periods of time to understand what motivates your customers. Don’t create one-off surveys for highly specific data points, create consistent data collection results.
- Clearly define areas in your database that are Known vs. Perceived identifiers and give a score to the perceived values.
- Identify the types of customers who are visiting and grouping them into activation segments.
- Continually monitor review sites, post-dine survey responses, and brand perception.
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