Abundance of Data in Restaurant Groups
It comes to no surprise that Restaurant groups have a huge amount of data throughout their organization. It’s important for these organizations to leverage this data in order to optimize their offerings and effectively target consumers. Here are some ways to leverage data sharing in restaurant groups.
Firstly, restaurant groups should be looking at a holistic view of their purchase data. Silo’ing data within one business unit or specific restaurant brand decreases the overall value of the data to the organization. As an example, Darden Restaurants is a group which owns, among many other restaurants, The Capital Grille & Eddie V’s in Boston. Although different branding and locations, the two customer bases overlap. As a result, Darden gains significantly through combining the two datasets. We spoke about the restaurant industry making data driven decisions for delivery apps, but the same can be said for even high end restaurants. Customer profiling & predictive analytics can help restaurants optimize their menu or forecast demand.
App / Loyalty Data
Restaurants that leverage mobile / app ordering and rewards systems get a slew of valuable data in return for the convenience that the app offers. The first bit of information that the app collects is mobile location data. Users often share their location with restaurant groups for the ability to quickly locate and order from the closest location. As a result, the marketing team has a huge potential to capitalize on media attribution from not only in app purchases but also driving in store / drive through purchases. Similarly, the metadata that is collected by a restaurant group’s app allows for increased customer analysis. Restaurant apps present an opportunity to be able to tie purchases back to a specific user. As such, predictive modeling and customer clustering allows for these restaurants to better understand their customers and act on these insights.
Sharing Data with External Partners
We’ve spoken about external data monetization plenty of times, but what exactly does it mean for those in the restaurant industry? Better yet, what does it not mean? It doesn’t mean selling valuable data to competitors or others in the industry. Instead it focuses on strategically sharing data assets with partners for increased value or overall efficiency. As an example, sharing sales data with suppliers allows for better demand forecasting and decreased costs. Suppliers can pass these cost savings back to the restaurant. Similarly speaking, restaurants can share insights with their brand manufacturers to better leverage joint marketing efforts to drive product consumption. As an example, sharing foot traffic data or transaction data with Pepsi to inform marketing campaigns is beneficial to both Pepsi and the end restaurant the drink is being consumed in.
Value of External Data
Capitalizing on external data doesn’t necessarily mean sharing data to other partners. It can also mean leveraging the data that other companies have to offer. Data Marketplaces like Snowflake allow for organizations to easily access this data and append it onto their own data. With regards to the restaurant industry, here are a few examples of valuable external data.
Weather is often a great business indicator of performance for restaurant groups. It’s easy to grasp that if it heavily rains over a restaurant, that particular restaurant may experience a lack of sales due to the outdoor patio. That said, for a restaurant group of hundreds if not thousands of locations, weather conditions can also play a real time part in forecasting sales data based on previous performance under similar conditions. It can do this down to the specific location for a restaurant group. That level of insight is within reach using the tools set in place by data marketplaces.
Mobile Location Data
There are several use cases for external mobile location data. Of which, one of the most interesting is the ability to leverage this data for foot traffic attribution. As previously mentioned, this data can be used to better understand the effectiveness of marketing campaigns. External data takes it a step further and can show the incrementality beyond the core restaurant’s app users. Similarly, these datasets can even show the lift in net new downloads from campaigns.
As we previously wrote about in our article about leveraging data in the food delivery industry, external transaction data can be a huge asset for major restaurant groups. Restaurant chains can better understand how their customers are engaging with their restaurants relative to competitors or collaborative businesses.
How we can help
Highland Math specializes in helping businesses create revenue from their data. This means leveraging data to grow revenue internally and sharing that data to create a company “data dividend”. Similarly, we help companies manage the complexities of the external data ecosystem, helping them source external datasets to improve business processes.