Benefits of a Targeted Data Strategy

What are some critical considerations and benefits of a targeted data strategy that truly targets the right segments?

Restaurants should be looking at all available insights and data to best understand changing consumer patterns and trends affecting their business. These insights and data can enable and inform strategic decisions that drive growth and increase market share. An effective data strategy considers the critical value of third party, unbiased data sources such as human movement and audience data, that allows restaurants to get insights into consumer behavior they don’t get from their first party data. 

What are some examples of critical customer insights and KPIs? 

Restaurants must be able to answer questions like: Who's dining at which location? What time of day are they dining? Are my customers going to my competitors across the street? How can I make their experience better? Having these important data sets and insights answered in order to make better strategic decisions in regard to how a restaurant operates is paramount. Additionally, restaurants also need to obtain insights with their customers in regard to what they are doing when they're not engaged with their brand, like where else are they eating, shopping and visiting, as well as what that greater audience looks like.

Do restaurants need help understanding who their true competitors are? (E.g., a hamburger chain may think McDonald’s is their biggest competitor when in fact it’s the burrito place around the corner.)

As well as gaining an insight into the visitors to your own stores, a targeted data strategy can leverage real-world analytics to monitor other retail locations and understand what your competitors are doing. Inaccurate assumptions and second-guessing become a thing of the past when you can compare your competitors’ footfall data with your own to see where you are leading and where you perhaps need to put in more effort. You can discover what engages your competitors’ consumers and use this data to enhance your own offering. One marketer recently told me that access to real-time competitor insights is like having a “cheat-code for my favorite game.”   

How can a data strategy seamlessly bridge online and off-line data from a variety of sources?

Unifying online and offline data sets is important and requires access to large repositories of varied data types and a robust technical architecture to analyze these datasets at scale. Going omni-channel (online and offline) provides even greater value as it expands the amount of information available to say restaurant chains and gives them access to deeper insights into their customer base.

For example, let’s say as a restaurant chain, you know from online data that “Diner A” searches for “pasta in my area” on a particular day in the morning and does the same in the evening from home. Combining this knowledge with offline data, you can start to build a deeper profile: a professional, interested in Italian food, in the 25–35 year old age bracket, and visits specialty grocery stores on the weekends. With this information at your fingertips you can now engage in some clever marketing, such as showing Diner A tailored food offerings on an internet-connected device when he is seen at your competitors’ restaurants. First-party data makes this possible, so it is imperative that you collect and utilize it to its full potential.