Chapter 7: Applying AI for Innovation – Restaurants Deep Dive

The restaurant industry is notoriously difficult. It's a highly competitive space with slim profit margins, and these challenges have only been exacerbated during the COVID-19 pandemic, in which restaurants are subject to more stringent guidelines than ever before.

The average cost of opening a leased restaurant in the US is $275,000, and only about 20% of new restaurants survive past their first five years. This means that there are many failures, but also many opportunities for those willing to take risks and try new things.

In this chapter, we'll discuss how artificial intelligence (AI) can help overcome some of these challenges. We'll look at how AI can be used to improve operations and increase revenue, all while reducing costs and increasing profits. We'll also discuss how AI can be used to create more engaging experiences for guests in the restaurant industry.

In this chapter, we are going to cover the following main topics:

• Understanding the challenges of restaurants
• Analyzing product data for restaurants
• Using Commerce.AI for restaurants

Understanding the challenges of restaurants

The restaurant industry is one of the most staid and stagnant in retail, with little appetite for change. Think about it: historically, restaurants have had a tough time competing with other forms of entertainment such as TV and movies, or even just socializing with friends. Why would you go out when you could stay at home, order in from Seamless or Just Eat, and watch Netflix?

Traditional brick-and-mortar retail is struggling mightily to reinvent itself as consumers shift their spending habits online. Meanwhile, the restaurant industry has remained largely unchanged since its inception – there's not much innovation that can occur once a business model becomes so ingrained in society.

But times are changing. In recent years, data has become democratized – accessible to anyone with an internet connection and a computer – allowing companies to make better decisions than ever before based on evidence rather than gut feel or guesswork.

To better understand how and why to use data and AI in the restaurant industry, let's explore some of the major challenges in this industry today.

Profitability

The first major challenge is generating enough revenue to break even. While the end goal is to become (or to stay) highly profitable, this starts with matching the break-even point. While profitability is a universal challenge for businesses, this is particularly true for the restaurant industry, which faces notoriously slim profit margins.

It is estimated that the average profit margin of a restaurant is approximately 3% to 5%, with many restaurants struggling to break even. This has led some to call the restaurant industry a low-profit business. So, what does it take to generate enough revenue to break even? And more importantly, how can you increase your revenues in order to achieve profitability?

We have broken down this topic into four key areas: customer acquisition costs (CACs), menu innovation, pricing strategy, and marketing tactics. Each of these areas will be covered in detail in the following subsections.

Customer acquisition costs

This first area of focus deals with all of the costs associated with acquiring new customers – or CACs for short. These include advertising costs (both online and offline), as well as any discounts or incentives you may offer existing customers in order to bring them back into your business on a recurring basis.

In other words, if you are relying solely on word-of-mouth referrals to acquire new customers, then you will need to invest heavily in marketing efforts so that people know about your location and offerings.

It is also important here not only to consider your customer acquisition costs but also those of your competitors; if there are heavy discounts being offered by other businesses at nearby locations, then it may be wise for you to match or beat those offers.

You should also be aware of any local or state incentives that may be available to help offset the costs of your restaurant. For example, if you are in the process of opening a new location, then there may be grants and tax breaks available that can reduce your CACs.

However, all of this is just a starting point, and using data from the restaurant industry as a whole can help you to refine your marketing and acquisition strategy. In other words, industry-wide CAC data can be used to improve your own CACs, and ultimately your profitability.

Menu innovation and product development

The next major factor impacting profitability when running a restaurant is actually changing what you serve in terms of food. If you are currently serving the same old dishes night after night while hoping for an uptick in sales, then the chances are things aren't going according to plan.

As such, making sure that your menu remains fresh and exciting from month to month is paramount here; offering items beyond basic American fare can help ensure that people continue returning again and again.

Menu innovation is the process of developing new and exciting food and beverage offerings for existing or new customers. It's an essential tool in the restaurant industry, enabling restaurants to stay relevant in a crowded marketplace by offering something different from their competitors – something that will make them stand out from the crowd.

In order to understand how to improve your restaurant menu, we need to step back and look at how this concept of the customer experience has taken over our lives. Many people these days are living their lives online, on social media platforms such as Facebook and Instagram. They're also sharing their thoughts about restaurant dishes and menus, and tapping into this data can provide valuable insights into menu engineering, as we'll explore later in this chapter.

Pricing strategy

The third area of focus when it comes to increasing profitability pertains to the pricing structure of your business – and more specifically, the why behind what you are charging for your products or services. If you are currently charging too little for your offerings, then the chances are that this is resulting in lost revenue and a decreased overall bottom line.

To put it simply, if people aren't willing to pay enough for what you have to offer, then they probably won't be returning for future purchases – no matter how good those previous purchases were. You can increase profits by raising prices on selected items that are in high demand while simultaneously lowering prices on other items that may not be as highly sought after. This will help ensure that the balance between the sales volume and average ticket price remains favorable over time.

Be sure to also take into consideration any promotions or discounts being offered by competitors (or possibly even by yourself in the past) as well as any tax implications associated with any such changes. There may be opportunities here to further increase profitability based on tax laws or certain government incentives currently in place. Most importantly, however, is analyzing pricing and demand data at scale to calculate the optimal pricing strategy.

Marketing tactics and social media

Leveraging social media effectively is an increasingly important aspect of marketing efforts today – particularly within the restaurant industry itself. Facebook has become a powerhouse when it comes to reaching potential customers, with over 2 billion users worldwide.

Organic traffic refers to traffic that a company would have gotten absent of paid advertising. Paid ads can actually drive organic traffic as a secondary effect by leading to word-of-mouth referrals. Using Facebook ads can help drive foot traffic into your restaurant through organic means, which will ultimately result in higher customer counts – especially when you consider that nearly one-third of visitors who come into brick-and-mortar establishments do so via word-of-mouth referrals from friends or family members first.

By leveraging Facebook ads along with other paid social media campaigns (for example, on Twitter or Instagram), it is possible to reach a vast audience while driving significant increases in sales over time. Just keep in mind that spending money on paid social media campaigns alone may not necessarily result in increased revenues, as there are many other factors to consider.

Changing guest preferences

Understanding and anticipating consumer behavior is perhaps the most important aspect of maintaining a competitive edge in today's dynamic restaurant marketplace.

The hospitality industry has been through many changes over the past couple of years, and while innovations such as augmented reality have brought new excitement and appeal to dining out, we believe that consumers are looking for more than just a new gimmick. In order to create long-term value for brands, they need to understand what guests expect from their experience – and how those expectations are changing.

Restaurant customer preferences have changed dramatically. Just a couple of years ago, the focus was on aspects such as the taste of the meal, the variety of the menu, the wait time, and the restaurant ambiance. Today, rigorous health and sanitation measures are foremost on customers' minds, and many customers will complain if standards are slack.

These changing guest preferences impact profitability and forecasts as well. For example, there's a new reality of smaller dine-in sales overall, as well as decreased check sizes. As a result, restaurants have to look for new ways to bring in revenue, in addition to satisfying customers based on their new preferences. For example, restaurants can consider changing their menu or even implementing technology to better help them adhere to social distancing protocols (for example, contactless payment options and QR codes for menus).

Preferences come down to context. What do guests see? Who are they with? How hungry are they? Where are they dining? And what else are they doing during their visit (for example, shopping at nearby stores)? These contextual factors play an important role in determining whether an experience will be memorable or not, and whether guests will want to share it with others or not (hence why engagement metrics on social media become so important).

The key takeaway here is that every guest has different needs based on their individual situation, which means that no two experiences will be exactly alike. To stand out amidst today's crowded landscape requires both creativity and innovation: you need something different that your competitors don't have – access to massive amounts of product and service data.

Creating profitable menus (and pricing)

The restaurant industry has been through a lot. Pre-COVID-19, the industry saw decent growth, which plummeted dramatically in 2020, putting many small restaurants out of business. The response of federal governments flipped the switch, driving an increase in discretionary income among consumers and a desire for people to eat out more frequently post-COVID-19. As a result, many new restaurants were opened across the country, and there was an explosion of innovation in terms of technology, design, and food quality.

In order to find success in this tumultuous environment, restaurants must adapt and evolve in order to stay relevant to today's consumers.

Menu engineering

Menu design is crucial to the success of a restaurant. A well-designed menu will increase customer loyalty, build brand identity, and enhance overall revenue growth. Unfortunately, many restaurants struggle with menu design. There are a number of reasons for this, but one of the most common is that menus often contain outdated information.

Restaurants relying on legacy technology – whether it's paper menus, tablets, or mobile apps – won't be able to keep up with today's pace of change in the restaurant industry. In order for restaurants today to compete effectively in an increasingly competitive landscape, they need new ways of communicating with their guests and creating engaging experiences around what they eat.

Taking it to the next level, restaurants don't only need to design menus, they need to engineer menus that are loved by consumers while maintaining high profitability. Menu engineering is one of the most complex and challenging strategies for creating profitable restaurant menus. To do it right, restaurants must be innovative in both product development and marketing.

Innovation in product development is critical because it's the only way to keep up with changing consumer demands, while still providing variety and ensuring customers are satisfied. As consumers become more health-conscious, they're looking for more natural ingredients in their food – and they'll pay a premium for these products if you include them on your menu. This means that you need to invest in developing new products that have a real chance of becoming best-sellers.

Maintaining online reviews and social media marketing

Online reviews and social media have become an essential part of the consumer's decision-making process when choosing where to dine out. However, with the growth of online review platforms and social media channels, restaurants are finding it harder to maintain their online presence. Online reviews and social media posts are no longer just a matter of informing consumers about a business; they have become a way for consumers to interact with brands on their own terms.

Online reviews and social media posts can be powerful tools that help differentiate a restaurant from its competitors – or can backfire if not handled properly. For example, negative reviews or bad press can damage a brand's reputation and could lead to customers avoiding the company in the future.

The advent of online review platforms has made it easier than ever for people to voice their opinions about businesses, but maintaining an online presence is no easy task – especially when competition is high and there are so many other options for dining out.

Now that we understand some of the major challenges facing restaurants, including profitability, maintaining online reviews, and social media marketing, let's explore how restaurants can analyze product data to overcome some of these challenges.

Analyzing product data for restaurants

The restaurant industry is a highly fragmented market with an enormous variety of products and services available to consumers. As a result, it can be difficult for restaurateurs to understand the data they need to drive meaningful innovation in their businesses.

This section introduces several different ways that data can be used as a tool for innovation within the restaurant industry, including predicting food item success, predicting competitor performance, new profile discovery, and more.

Predicting how food items are likely to perform

One big way to use data for restaurant innovation is to predict how food items will perform in-market. By analyzing the performance of food items in the restaurant industry at large, restaurateurs can identify which food items are likely to be most popular with consumers. This information can then be used to inform business decisions about menu items, pricing, and marketing campaigns.

Traditionally, restaurants would rely on their experience to make business decisions. However, with more data to hand, restaurateurs can use data science to gain insights into how customers are likely to respond to food items. For instance, a restaurant might use Commerce.AI to automatically monitor social media sentiment surrounding its dishes and adjust its menu accordingly.

In the last few years, we've seen increased investment in data science and AI across a wide variety of industries. However, in the restaurant industry, the use of these tools has been relatively slow to develop. The main reasons for this are that it is difficult to predict how individual consumers will respond to new trends or innovations in real-time and that it is costly and inefficient for restaurants to collect large amounts of consumer data.

However, with rapidly advancing technology, we now have the ability to overcome both of these challenges. And as a result, more and more restaurants are starting to leverage data science and AI in their operations.

Predicting how competitors will perform

Another way that data can be used is by taking a look at historical sales information for similar products or service offerings from competitors. This information can then be analyzed to determine the most promising market niche for a new food or beverage offering, or a new product or service more broadly.

For example, if one of a restaurant's competitors has recently launched a new dessert item that seems to be selling well, the restaurant may consider introducing a similar dessert item as well. This approach allows restaurateurs to learn from their competitors and take advantage of what they perceive as untapped opportunities within their industry space.

Competitive intelligence is an important tool for any business, but it can be especially valuable for those in the food and beverage industry. The competitive landscape within this space is constantly changing as new competitors enter the market, and existing ones adapt their offerings to remain competitive.

In order to stay on top of these changes, restaurateurs need to have a strong understanding of what their competitors are doing so that they can make informed decisions about how best to position themselves in the market.

Predicting customer needs based on previous purchases

Further, data can be used to help make informed predictions about what customers want based on their previous purchases. For example, by looking at where people buy different types of wine or beer, it's possible to determine which types of wine or beer are likely to be most popular within certain markets/regions/sectors (for example, reds tend to sell better than whites in the US).

Using this information along with other consumer data, such as age group and purchasing patterns, can help restaurants develop more targeted marketing campaigns that appeal directly to customers who have shown a propensity toward certain types of products or brands before.

Data collected from previous purchases can also provide insights into what motivates certain customer segments within each market segment (for example, millennials prefer beer over wine). By understanding how different customer segments react differently depending on the context of their purchase decision (such as whether they're buying for themselves or as part of a gift basket), it's possible to create more tailored promotions.

New profile discovery

Many of the products and services available in the restaurant space are relatively new. For example, many consumers have never eaten a sweet yogurt bowl before, or they've never tried a high-protein food that is baked instead of fried.

In order to create meaningful innovation, restaurateurs need to be able to understand their customers' behavior and preferences across a variety of dimensions (such as food type, experience type, and price point) in order to find opportunities for improvement and growth.

Data can uncover new insights about the profile of consumers who visit a restaurant. For example, data analysis may find that sweet-toothed guests are more likely to spend more money on average than those with a savory appetite. This insight could be used by restaurateurs to understand which dishes or products within their menu are performing well and why, potentially leading to new product development or service offerings.

Ultimately, data can be a powerful tool for restaurant innovation. From predicting food item success and competitor performance to new profile discovery, data can enable meaningful competitive advantages. Next, let's look specifically at how restaurants can use Commerce.AI for boosting innovation.

Using Commerce.AI for restaurants

In previous chapters, we've looked at how to use Commerce.AI for various product-oriented industries, including luxury brands in Chapter 4, Applying AI for Innovation – Luxury Goods Deep Dive, wireless networking brands in Chapter 5, Applying AI for Innovation – Wireless Networking Deep Dive, and consumer electronics brands in Chapter 6, Applying AI for Innovation – Consumer Electronics Deep Dive.

As we'll see, Commerce.AI can be used in the service industry as well, including for restaurants. This is because the service industry is highly data-rich, as customers leave large amounts of both implicit and explicit feedback.

In fact, so much data is generated, largely in the form of customer feedback, that it would be impossible to manually sort through and analyze a meaningful amount of it. That's where AI comes in, which automatically finds trends in customer reviews and can make predictions about the future.

Let's look at five main ways Commerce.AI can be used in the restaurant industry:

• Analyzing restaurant customer data
• Mobile surveys
• Gauging customer sentiment response based on marketing campaigns
• Staying connected with customers
• Restaurant trend analysis

Finally, we'll look at a case study of how a French pizza chain used Commerce.AI for restaurant innovation.

Analyzing restaurant customer data

As one of the leading players in the restaurant technology space, with over 1 trillion data points processed through its platform (from tens of thousands of products and services), we've seen firsthand how companies leverage our platform to get insights into their restaurant businesses. This experience has helped us develop some best practices on how restaurants can effectively leverage our services when doing business analytics projects.

Analyzing restaurant customer data is no different, and most restaurants can benefit from taking a deep dive into their data to understand their customers. It is also useful for understanding how your food and beverage consumers create value that you can leverage in your business – whether it's managing operations, developing new products, improving marketing campaigns, or all of the above. But before we dive into how to do it, let's take a look at some of the challenges that most restaurant businesses face when doing analytics in their businesses.

When you think about analytics in your restaurant business, you might begin with company-wide reporting – think revenue by unit or revenue by shift – or product improvement such as finding the optimal inventory levels (including position) for each item on a menu board. Both are great uses of an analyst or manager's time because they're actionable insights that impact decision-making immediately.

Unless the goal is to find further correlations between elements within your existing dataset(s), these kinds of reports won't provide much insight into repositioning products or changing spending behaviors.

That's because they use pre-existing patterns without challenging those patterns in any way; therefore, there's very little beyond correlation/causation found, and nothing gained from putting things into more meaningful context through analysis (such as combining all shift information). It feels like just throwing more irrelevant detail onto an already complex pile that nobody understands but everybody has to deal with.

Commerce.AI solves these issues by combining internal, existing data with large amounts of external market data and summarizing findings in quick and snappy insights.

Mobile surveys

Mobile-based surveys have become an essential tool for understanding consumer behavior in relation to your restaurant products and services.

Mobile surveys are a great way to understand how consumers use your restaurant, as well as what they like and don't like about it. They can also be used to understand how consumers feel about the quality of your food, whether you're keeping them happy with their experience, and if you need to make any changes.

In the restaurant business, the customer is king, and with mobile surveys, you can have an intimate look at what your customers want.

Mobile surveys can be completed quickly and easily in Commerce.AI. They're a great way to understand your consumers in real time, as well as to set up regular health checks on the quality of your food or service.

The data from these surveys can also be used to inform more traditional forms of marketing such as print ads, social media posts, and organic search engine optimization (SEO). You could even create a custom survey for specific audiences via email and put it in front of them when they come into your restaurant.

Gauging customer sentiment response based on marketing campaigns

Marketers spend a lot of time and energy on developing and executing initiatives to increase brand engagement with our customers. The question they often ask themselves is does this effort pay off?

We can measure engagement, sales lift, and other metrics to determine if the investment was worth it, but there are many factors that influence customer behavior that make it challenging to accurately predict how a campaign will perform. One data source that can be immensely helpful in understanding how an initiative will play out is sentiment analysis.

Sentiment analysis uses machine learning algorithms to identify whether the written content is positive, negative, or neutral in nature. Since social media posts are generally longer than traditional marketing campaigns, they give us more information about what types of things our customers like or dislike about our products and services.

This allows us to quickly understand the overall sentiment of a campaign and make adjustments as necessary before investing too much more money in an initiative.

Commerce.AI provides powerful tools for sentiment analysis because it integrates with popular third-party services such as Google Analytics and Facebook Insights, two widely used tools when measuring customer engagement with online businesses. These integration capabilities let you analyze customer sentiments using the same data sources that you use for your marketing analytics programs, which means you can begin making smarter decisions about how to build your business from day one, instead of building it after the fact based on feedback from existing customers.

Stay connected with your customers

Social media has become an important channel for staying in touch with customers. Companies are engaging with their followers on Twitter, Facebook, Instagram, and other platforms in real time so they can learn what matters most to them as consumers. This knowledge helps brands make smarter decisions about their products and services, grow sales, improve customer loyalty programs through personalized offers, and increase engagement across all channels.

Monitoring social media conversations around a given brand or competitor is a great way to stay connected with your customers. This means that you can hear about any emerging issues before anyone else does and respond quickly when something goes wrong or needs fixing. It's also a great way to get alerts when potential new customers show interest in your brand or product category.

You've probably heard the phrase social media return on investment (ROI). It means measuring the benefits of social media campaigns, whether it be through likes, comments, shares, or other interactions on your company's social platforms. With social media as a platform for customer engagement, brands can listen in on what their customers are saying and learn from their feedback.

If you have a customer service team that is consistently answering questions from customers using social channels such as Facebook Live or YouTube Chats, you should be able to track how many people watch the live stream and interact with the content. A similar approach can be taken when listening to comments that customers leave on your website or blog posts. By tracking comment data, you can see who is engaging with your brand and what they are saying about your company and products.

The key takeaway here is that companies can use real-time data analysis tools such as Commerce.AI to stay connected with customers across multiple channels so they can understand what types of content resonate most with them and why. This allows companies to create targeted content marketing campaigns that keep their audiences engaged and ultimately drive more revenue for their businesses.

Finding and predicting trends in the restaurant business

As part of your innovation strategy, you should be constantly looking for new ways to add value to the business. The restaurant industry offers many opportunities for innovation and growth – but you need a way to find those opportunities so that your team can execute on them.

Innovation teams can use Commerce.AI to identify potential trends in the restaurant industry and potential innovations that can add value for your customers.

The goal of any good analysis is not just to spot interesting trends, but also to make predictions about what will happen next based on those trends. For example, if there's been a recent increase in the number of reservations made for Sunday brunches, then it might be a good time for an innovation team within your restaurant chain to release a new menu item specifically targeted at these types of high-value bookings.

If you can predict what people want before they know they want it themselves, then you have a competitive advantage. This is why innovation teams need to be data-driven. They need to know what their customers want so that they can build and market products or services that are designed to meet those customer needs.

In order for innovation teams to create the products and services that will bring customers flocking, they need a thorough understanding of how people behave when they eat out. This requires them to look at trends in the restaurant industry, which has been experiencing an unprecedented amount of change over the past decade.

A case study – how a large French pizza chain used Commerce.AI

A leading French pizza chain used Commerce.AI to analyze customer feedback at scale and evaluate both store service and product quality. This French pizza chain evaluated over 100,000 customer reviews across 385 stores to analyze metrics including the following:

• Overall review sentiment
• Store leaderboard – best and worst stores
• Top attributes
• Comparing stores across attributes

Let's dive into each of these areas.

Overall review sentiment

Restaurant reviews are a huge part of the online journey for consumers when considering where to eat. In fact, consumers spend a significant portion of their time researching restaurants before deciding where to eat.

But this also means that businesses need access to reliable data on how their customers are engaging with their content. And nowhere is this more critical than in the world of online reviews, where an average consumer checks out several reviews before making a decision about which restaurant or experience to engage with next.

The good news? There's now an open standard for measuring the sentiment on all sorts of review platforms – and it's called using Commerce.AI. Traditionally, businesses only had two options when it came to using customer feedback: ignore negative sentiments or respond quickly and personally (often using bots).

This has resulted in a lot of conflict on review platforms – negative sentiments coupled with personal replies from business owners who feel compelled to defend themselves against unfair accusations. In essence, businesses have been fighting fire with fire rather than using data insights from customer feedback as a tool for improving their products and services.

With Commerce.AI, brands can quickly and easily measure the overall review sentiment. The French pizza chain was able to gain immediate insights into the overall review sentiment, informing them how their customers were feeling at any given time.

Store leaderboard

Large restaurant chains often have hundreds of stores and millions of customers, making it difficult to track performance at an individual level. By applying sentiment analysis and AI to data collected from social media platforms such as Twitter, the pizza chain innovation team was able to identify the top-performing stores by measuring how happy customers were with their service and food quality, as seen in Figure 7.1:

Figure 7.1 – Leaderboard of top stores by sentiment in Commerce.AI

Similarly, this data and AI analysis indicate the worst-performing stores, as seen in Figure 7.2, allowing them to quickly address areas for improvement. The goal is to learn from the stores leading the way and apply those lessons across the board while pulling up the stores that are faltering, improving brand image and customer satisfaction from both sides. After all, each and every store plays an important role in your overall brand.

Figure 7.2 – Leaderboard of worst stores by sentiment in Commerce.AI

By using this approach, the team is able to identify which stores are underperforming or have opportunities for growth. They can then invest in these locations, providing resources such as new Point of Sale (POS) systems and training for employees, which can help turn around performance at these locations.

Using this data-driven approach also allows the chain to set goals for itself over time. For example, they might decide that they want to double their number of store champions by 2025; if they achieve this goal, it will be clear that they've made significant progress in improving their network of stores and increasing customer loyalty over time.

Top attributes

Understanding the specific attributes of a particular location and how to improve them is the Holy Grail for many companies. If used correctly, data can be a powerful tool to gain an edge in competition.

Using AI to measure store attributes such as price points, product quality, or customer service can give retailers and restaurants an advantage over their competitors.

However, this requires gathering large amounts of data from multiple channels. The pizza chain used Commerce.AI to analyze data across hundreds of its locations and tens of thousands of customer reviews to measure and analyze specific attributes for each individual store, highlighting areas for improvement for a ground-up innovation approach, as seen in Figure 7.3:

Figure 7.3 – Analyzing store attributes in Commerce.AI

In this case study, most attributes are in French, as we're analyzing data from France. We can see that positive attributes reference things such as price, quantity, and the professionalism of the delivery person, while top negative attributes reference things such as order delays and missing items.

Comparing stores across attributes

Each of the 385 stores analyzed by the pizza chain had a unique attribute profile, with varying sentiment across attributes such as price, quality, professionalism, and cleanliness. Using the Commerce.AI data engine, we were able to compare each of these attributes between stores in order to find specific areas for improvement for any given store, as seen in Figure 7.4:

Figure 7.4 – Comparing multiple stores for multiple attributes

We can see, for instance, that Store 31754 has particularly intense chatter for the French word retard, or delay, indicating that measures need to be taken to make processes more efficient at that store.

With the power of data and AI, the pizza chain was able to gain unparalleled insights into the sentiment of their stores and competitors' stores, as well as discover opportunities to meet consumer wants and needs.

At a high level, these insights can be consolidated in the form of data-driven reports, which provide a quick overview of the data for innovation teams to understand the hearts and minds of their consumers. In Figure 7.5, for instance, we can see a mockup of what this dashboard may look like for a pizza chain, the data of which would be populated by the specific brand and stores selected.

Fig 7.5 – A Commerce.AI mockup of a high-level consumer insights dashboard

We can see quick summaries of the data from thousands of reviews, such as Staff was OK but delivery was awesome, highlighting an opportunity to improve teams and market their excellent delivery processes.

In conclusion, Commerce.AI is a versatile tool that restaurants can use to analyze customer data, deploy surveys, gauge customer sentiment, analyze trends, and more. By implementing these kinds of AI use cases, restaurants can get ahead of the competition that's stuck using traditional analytical methods (or even worse, little-to-no analysis at all).

Summary

In this chapter, we've explored how data is a critical tool for restaurant innovation teams. Using data to inform your restaurant strategy is an essential part of being successful in this evolving industry. The right data, at the right time, can save you countless hours of trial and error, help you make smarter decisions, and even help determine what food and beverages to sell or services to offer in the first place.

AI isn't just about automating repetitive tasks; it's also about providing insights that no human could have come up with on their own. These tools are perfect for the unique challenges faced by restaurant owners, from managing inventory across multiple locations to understanding consumer behavior on social media platforms such as Instagram.

As consumers engage with food in new ways through digital channels – apps such as Instagram or Pinterest – restaurants have an opportunity to reach them directly with offers or content that they find interesting or engaging enough to share with their friends on these channels.

In the next chapter, we'll go through one more industry deep-dive, and look at how consumer goods businesses can apply data and AI for innovation. Like restaurants, consumer goods businesses are facing stiff competition, and they can use data and AI to overcome key challenges.