Life in the restaurant business can be one of the most rewarding around. It can also represent something of a struggle, as the need to boost restaurant sales in the face of growing customer demands, increased competition, and rising costs of keeping a restaurant afloat are common issues surrounding today’s establishments.
Leading chains like Starbucks are tapping into a resource which can solve a range of issues around profits, experience, satisfaction and more. We’re talking about data and how it can transform the way a restaurant attracts and retains a customer base.
Example: Burger Chain Increases Check Size by 10% with Data-Driven Marketing
New technologies now enable the collection of huge amounts of data within a restaurant’s four walls; information that can be used for everything from marketing to product trials and franchise management.
Even before any type of investment, it’s likely that your POS system already contains a goldmine of information about every existing customer transaction, including past purchases, preferences, and full order history.
Of course, having all this information is worthless if you are unable to analyze it and use it proactively. In order to make the most of your data, you must be able to understand it correctly.
Six Ways Data Boosts Restaurant Sales
1. Find growth opportunities
A big advantage of using data to boost restaurant sales is the ability to analyze performance across your operation. Data-driven restaurant chains use insights to monitor restaurant locations and take action on opportunities for growth or cut back on wasteful activities.
When you add a customer engagement solution into the mix, you can funnel that data back into a campaign which aims to drive traffic to a specific location. For example, you can target nearby customers with personalized coupons or special offers to bring them into that location.
2. Promote specific products
Data creates the opportunity to conduct analysis in granular detail. Moving away from assessing the performance of whole restaurants, we can drill down into the popularity of menu items.
By accurately analyzing the data collected data via your POS, you can find out which products are the most popular and offer special related deals. This helps promote new items and renew enthusiasm around existing ones. An example could be an offer which pairs a leading item with a less popular one, enabling you to see whether your promotional efforts were at fault.
3. Maximize customer value
No customer is built the same; each requires a unique incentive to help get them engaged with a product.
Thankfully you can now segment your ideal customers into groups and analyze their value according to a range of factors. For example, how recently they visited, how frequently they visit, and how much they tend to spend.
From here, you might want to offer customer loyalty rewards to your premium customers. Some restaurants report that as much as 70% of their revenue come from their VIP diners. Nurturing those relationships could be crucial to the success of your restaurant.¹
In addition to that, you might look into ways of incentivizing your less frequent customers to encourage their return. Encourage repeat business by issuing special offers on products you know a customer will enjoy. That could be anything from a new veggie burger for vegetarians or a discount for families that dine together.
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. By using data to identify what days and times draw the least traffic, you can start to build a communication strategy which focuses on driving business around quiet parts of the week.
Some restaurants have taken to using personalized incentives to attract customers during specific periods. An obvious example would be to offer a special price on two products that a customer really likes during a certain time of day or the week.
5. Predict customer behavior
Forecasting can reveal insights on future purchases, consumer behavior, and average spend, shedding light on what businesses can expect and what they need to be prepared for.
Having that insight allows the business to not only plan for the future, but also to 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 your success
Within marketing specifically, you can use data to analyze where your efforts have been successful and replicate those past successes.
It might be that a campaign launched over the holidays helped drive many families to your restaurant. Data will allow you to identify where these success stories are happening and how you can repeat them for a similar outcome.
Turn Data Into Action to Boost Restaurant Sales
So now we know that data is essential to boost restaurant sales, but how do we measure and analyze that data? Customer management toolsets, like COMO, use POS integrations to draw actionable insights and create automated campaigns.
Restaurant campaigns can be adjusted according to your business’s needs, whether that’s driving loyalty program membership, boosting repeat sales, bringing back dormant customers, or making visits more frequent.
Como Sense, 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, Como provides restaurants with the most in-depth analytics and data insights.
Easy to understand and even simpler to pull reports, restaurant chains are amazed with their sheer volume of possibilities the Como platform offers.
Find out how you can leverage your data to drive sales and loyalty by contacting us today for a free demo.
Check out the slideshow below to get a glimpse of how the leading chains are using data to their advantage.
As Como's Data Group Manager, Adam lives and breathes machine learning algorithms and advanced analytics. He's currently busy developing and perfecting Como's insights and recommendation engine.