Providing EPOS solutions to the hospitality sector for over 20 years

How a Data-Driven Approach Can Enhance Your Restaurant

22/03/21

Modern-day restaurants rely on certain fuels to power their operation. A data-driven approach can enhance your restaurant.

Modern-day restaurants rely on certain fuels to power their operation. Find out your way to success with a data-driven approach. Some of the more obvious examples are customers, cash, and stock—each of which enables the business to succeed. But data is more than worthy of its status as a source of power for all manner of objectives.

We’re talking about the kind of insight that can offer the lowdown on customer behaviour, experiences, popular menu items, and much more. For example, information on someone’s purchase history is helpful when targeting them with products you know they’ll be interested in. We also have information on customer preferences, like the time and day that people choose to visit a restaurant, the items they typically order, and how they pay for them.

Data-driven Approach Strategy

Used effectively, this information can provide clues for driving more customers, improving their satisfaction, future-proofing the business, and successful product development.

Here are five ways you can leverage business and customer data to maximise your restaurant sales:

1. Product-level targeting

If you’re collecting data on purchase history, you can easily see how some products are more popular than others. With those which are lagging behind, you might need to develop a strategy to give them an extra push.

Marketing special offers for the items in need of promotion will soon reveal whether they can reach the required heights of performance or if they need removing entirely.

There’s also a case for promoting items that you know will drive the highest margin. Though applicable to restaurants, it’s a tactic commonly used by online retailers that want to sell more to people that are already buying with them. By highlighting complementary items that will drive a good level of revenue, any business can significantly enhance their opportunity to earn.

2. Catering for VIP customers

Over the last couple of years, you might have heard a bit about customer lifetime value (CLV). It’s a metric that enables you to see how much a given customer is worth to you, based on their frequency of visits and average spend. Expand your knowledge about the data-driven approach.

Once you have that data, you can make plans to nurture and strengthen the relationship even further. For example, if a customer spends a certain amount of time or visits your restaurant enough times, you can offer special rewards that will make them feel valued.

Some restaurants gain as much as 70% of their revenue from VIP customers. If you’re to succeed in the long term, you need to keep them on your side.

Marketing off the back of CLV also helps re-engage people that perhaps don’t spend as much with your establishment. If you have data on customers that aren’t buying much or haven’t visited in a while, a simple ‘ We miss you ’ sent via a push notification, SMS or email could help turn things around.

3. Driving footfall  

As well as pinpointing the customers in need of attention, data can also be used to identify the times and days that your business is flagging.

This is a great example of how data flows within a restaurant and the ways in which it helps turn things around. In this instance, data on slow periods can be collected by the EPOS, thus identifying where the business could be doing more.

Customers submitting that information could be linked to a loyalty programme or an email database, where they can be targeted with special offers for specific times of the day. Chain establishments can even look into sales by location and incentivise customers to head to a place they wouldn’t usually consider.

In these instances, you can see how data has a direct impact on revenue and customer visits.

4. Personalised marketing

Are you aware that 59% of customers believe marketing personalisation can have an impact on where and what they buy?

Once you know the details around each customer, such as their preferences, history and demographic, you can start to build audience segments which enable a more personalised method of communicating with them. That in turn creates loyalty around your brand and keeps people coming back again and again.

Let’s say that a group of your customers regularly turn up to your restaurant and consistently order meat-free items from the menu. If you have a new vegetarian meal option or wish to offer discounts on similar meals, you’ll know exactly who to target. Check out the right way to use the data-driven approach.

For years, marketers have been able to customise their communications by adding a name to any messages they send, but times are changing. Customers are more demanding than ever, which is why personalisation should be applied to the content of your messages and the offers they carry.

5. Finding (and repeating) a formula for success

If you already check your finances, you’ll be able to see how well you did in a certain month or week. Dig a little deeper; did a specific event or new product help drive that bright period?

Successes happen around the business all the time and these should be repeated whenever it’s possible and appropriate to do so. Analytics and reporting can help you identify where your marketing paid off and provide clues as to where you might want to repeat it in the future.

It’s key to think about attention to detail when examining your data for trends. It might be that you ran a Christmas promotion offering discounts for people dining with their families. This could have been a strong period for revenue—one that you’d love to repeat—but how much of that was down to an increase in family visits?

If you’re prepared to dedicate time and money into marketing, be sure that you’re measuring each campaign’s direct impact on the business.

Data-driven approach to increase restaurant Customer Lifetime Value

It's crucial for restaurants to not only attract new customers but also retain existing ones. One way to achieve this is by focusing on customer lifetime value (CLV), which is the total amount of money a customer will spend at your restaurant over their lifetime. Before we dive into how restaurants can use data to optimise their CLV, let's first understand what CLV is and why it's important.

What is Restaurant Customer Lifetime Value?

Customer Lifetime Value is a metric that measures the total amount of money a customer will spend at your restaurant over their lifetime. It takes into account factors such as the frequency of visits, average spend per visit, and the length of time a customer remains a patron.

Why is CLV Important?

CLV is important because it helps restaurants understand the value of their customers and how much they should invest in retaining them. By focusing on increasing CLV, restaurants can improve their overall revenue and profitability.

Using Customer Analytics to Optimise CLV

Now that we understand the importance of CLV, let's explore how restaurants can use customer analytics to optimise it.

Collecting and Analysing Customer Data

The first step in using a data-driven approach to optimise CLV is to collect and analyse customer data. This can include information such as customer demographics, purchase history, and feedback. By analysing this data, restaurants can gain insights into their customers' behaviour and preferences, which can then be used to tailor marketing efforts and improve the overall customer experience.

Personalising the Customer Experience

One way to increase CLV is by personalising the customer experience. By using customer data, restaurants can create targeted marketing campaigns and promotions that are tailored to each customer's preferences. This can include personalised offers, loyalty programs, and special events. By making customers feel valued and appreciated, restaurants can increase their likelihood of returning and spending more money.

Upselling and Cross-selling

Another way to optimise CLV is by upselling and cross-selling. By analysing customer data, restaurants can identify which items are frequently purchased together and use this information to suggest additional items to customers. This not only increases the average spend per visit but also exposes customers to new menu items, potentially increasing their overall satisfaction and likelihood of returning.

Improving Customer Retention

Customer retention is a key factor in optimising CLV. By using customer analytics, restaurants can identify which customers are at risk of churning and take proactive measures to retain them. This can include targeted promotions, personalised offers, and improved customer service. By focusing on retaining existing customers, restaurants can reduce the cost of acquiring new ones and increase their overall CLV.

Leveraging Technology for Revenue Optimisation

In addition to using customer analytics, restaurants can also leverage technology to optimise their CLV and increase revenue. This can include using customer relationship management (CRM) software to track customer data and interactions, as well as using revenue management systems to optimise pricing and inventory.

Data-Driven CLV Optimisation

Data analysis is crucial for restaurants to increase profits. By analysing customer data and segmenting them based on preferences, restaurants can create targeted marketing campaigns, maximising their effectiveness and increasing customer engagement.

Calculating customer lifetime value (CLV) is essential for understanding long-term profitability. By considering factors like average spend per visit, frequency of visits, and customer acquisition cost, restaurants can determine the value of each customer. This helps prioritise marketing efforts and allocate resources to retain high-value customers.

Restaurants can optimise CLV by leveraging email marketing. Personalised offers, promotions, and updates on new products or services nurture customer relationships and encourage repeat business. Tailoring email marketing campaigns to specific customer segments increases engagement and conversion.

Social media platforms play a vital role in engaging with customers and building strong relationships. Active presence on platforms like Facebook, Instagram, and Twitter allows restaurants to interact, respond to feedback, and showcase their offerings, fostering loyalty and attracting potential customers.

Analysing the customer journey identifies pain points and areas for improvement. Implementing engagement platforms or live chat features enables real-time feedback and prompt assistance, enhancing the overall experience.

Data-driven decision-making informs marketing strategies, menu updates, and promotional campaigns. Regular analysis of customer data identifies trends, preferences, and growth opportunities, enabling restaurants to deliver personalised experiences.

Email marketing remains a powerful tool for communication with existing and potential customers. Building an email list and segmenting it based on preferences allows sending targeted messages, including personalised offers, exclusive discounts, and updates. Leveraging email marketing keeps customers engaged, encourages repeat visits, and increases CLV.

Conclusion

From the above we can see that data is helping restaurants perform better across a range of different functions.

However, you shouldn’t just collect data for the sake of it. Whether it’s used to drive footfall around slow periods, re-engage customers that don’t visit often or strengthen relationships with those that do, data can impact a business in an ever-growing number of ways.

Restaurants have become a hotbed for information that floods into their systems on a daily basis. By integrating a customer engagement platform with your EPOS, it’s easier than ever to understand exactly what people are buying, and the reasons behind their every decision. With a solution like Como Sense, you can instantly take action based on that data and create targeted, personalised campaigns that fuel significant results.

Remember that you can always request a callback for more information about the data-driven approach.

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