Data A La Carte: Restaurateurs Can Use Big Data to Make Offers Guests Can’t Refuse
3 Min Read By Walt Taylor
Today’s consumers respond well to personalized suggestions. Amazon, Netflix and Facebook were the first to recognize this tendency and cash in on it.
Their secret tool?
It’s no longer a secret. It’s a process called data mining.
They use powerful computers to scoop up each and every data footprint that a customer leaves after an online purchase. Special algorithms then compare them with those of other buyers in order to find those with comparable tastes.
Once analyzed, they act on the data, using it to suggest additional books, films, or articles the customer may also enjoy.
Today’s savvy restaurateurs have taken note and are trying their hand at creating personalized offerings to their diners.
And like these three online giants, they are using data.
Data a la Carte
No longer do restaurant owners tally up their cash register receipts and either celebrate a busy night or sigh and say, “maybe tomorrow will be better.”
They look at that bottom line and weigh the factors they can control, like the menu offerings, the specials, or the staff on duty that night, against the uncontrollable ones, like the weather or the Super Bowl was on that night.
But they’re proactive too; gathering the data their customers generate so they can leverage it to get a more detailed picture of their dining habits.
Data on the Ground
Even owners of small dining establishments have tremendous amounts of data to sift through.
And managers of multi-location restaurants with multi-year data can easily accumulate a terabyte of data. Day by day, data accumulates about each customer, mined from sources like:
- Point of sale systems (POS) that yield payment, check, and item-level information about each customer
- Loyalty programs and cards
- Email campaign coupons
Then there are public data sources that yield information about customer’s experiences such as:
- Yelp pages
- Twitter posts
- Facebook pages
- Instagram posts
Sorting It All Out
The goal of gathering all this data is to use it to gain practical insights that can be used for more effective marketing and decision making.
Difficulties arise stemming from the fact that since all these data points reside in different silos, they cannot be easily combined.
And to compound matters, they are all in different formats. Email is unstructured. POS data is structured. Social media is streaming.
Until recently, the available technology to sort all this data was extremely expensive, with costs running as high as seven figures.
But restaurants today are fortunate in that internet pioneers like Google, Yahoo, and Amazon, have overcome these challenges, choosing to make available a version of the analytical tool they’ve developed to do so.
It is called Hadoop. It’s an open source framework that restaurant managers, or in most cases, the data management companies with whom they work with, can incorporate into their marketing platforms to help them make guest analytics the foundation of their marketing tactics.
Using Data Analytics in Marketing
A common practice that has proved useful in devising marketing campaigns is to use analytics to create segments among the clientele.
Segments are filters that divide customers into subsets without altering the underlying data.
Three segments particularly useful for restaurants are recency, frequency, and monetary value, or RFM.
The ways segments can be used to create irresistible marketing campaigns are virtually limitless once you know your customers.
- High-value spenders can receive an immediate thank you in their emails and be entered into a points program that earns a free entree
- Customers who show high-frequency visits can receive an offer for a free appetizer or dessert if they spend a chosen minimum
- Recent visitors who do not fall into either program can receive news of upcoming special menu items or entertainment
- If POS data reveals that a high-frequency visitor usually chooses a particular entree, she might receive a discounted offer for the next time she orders that item
However, dependent as today’s marketing may be on data analysis, it’s not the technology that determines success. It’s the ability to mine the data in a way that delivers actionable insights and the resolve to read it on an ongoing basis.
Use Data Analysis to Drive Profits and Save Energy
Keep in mind there’s also a lot of data in your utility bills that warrants analyzing. Using this data, you can drive down your costs each month and increase profits.