Restaurant life is pretty rewarding, but it can also represent struggle due to increase competition, high expectations from guests and increasing cost related to keeping the restaurant afloat.
Thanks to the advancement of technology, we are now able to collect great amounts of data from just one restaurant store. This information can be used for the purpose of marketing and product enhancement. Your POS system probably already consists of a lot of data such as a customer’s purchases or their favorite dishes, but all this data is worth nothing if you don’t analyze and utilize it to the best of its ability. In order to make correct use of your data, it is crucial to first decode and understand it.
1. Find growth opportunities
Restaurants that are driven by data use insights to monitor restaurant locations and take action on opportunities for growth or cut back on wasteful activities. Adding a customer engagement solution, the data gathered can be put back into the campaign and drive traffic to this particular restaurant store. One way to do this is to target nearby customers with personalized coupons or special offers so they want to visit the store.
2. Promotion of specific products
How can you know which dishes are the most popular among your customers? Using your POS, you can track all your clients’ behaviors and detect the most popular items…or the least appreciated. Once you mark down the popular dishes, you can offer special deals and not only promote them to new customers but also keep the existing ones coming back.
3. Maximize value of customer
All customers are different which means as a business, you need to incentivize them differently in order to keep them engaged to your company’s products. If this could seem impossible to do in the past, now you can segment your customers into groups of similarity, depending on their purchase frequency, the average amount spent, etc. Thanks to data analytics, you can target them differently. You can offer them different customer loyalty rewards, especially to VIP customers as they usually represent 70% of the restaurant’s revenue.
It is also important to provide incentives to customers that aren’t frequent clients either, to avoid losing them: you can, for example, offer special discounts on products that you know they will enjoy (because they already ordered these items).
4. Increase foot traffic during slow periods
Slow periods are a pain point for most restaurants, but they don’t need to stay that way. You can use data to track what time of the day there is least traffic in the store and offer special discounts during that time to attract customers.
5. Customer behavior prediction
By forecasting customer behavior, you can get access to insights on what the customer will purchase in the future, what will be their average spend, etc. This way, the business can see what is expected from them and they can prepare accordingly. Please note that it does not only concern the future, restaurants can also find ways of boosting restaurant sales from certain customer segments using a proactive approach. An example of this could be targeting a group of customers that typically order the same predictable items and creating a promotion to get them to explore new options.
6. Replicate success
Every business has efforts that have been greatly successful and what is better than to replicate those successes? You can set up a campaign over the holiday season to help drive families as that has worked for you in the past. Repeat similar outcome using data gathered.
How do we measure and analyze the data collected?
Using customer management tools like Wefee1 helps draw actionable insights and create automated campaigns. These campaigns include loyalty programs, ringing back dormant customers, or making visits more frequent. Wefee1 is a customer management tool that enables restaurants to offer personalized customer experiences by targeting people based on their profiles, preferences, purchase history, and much more. Unlike other POS integrations, Wefee1 provides restaurants with the most in-depth analytics and data insights.