Chapter 11: Delivering Insights with Market AI

The marketplace for everything is here and now. Every possible good or service that can be imagined is listed on an online marketplace, from flights to real estate, to concert tickets to old-fashioned manual labor.

It's not just something we read about in the news – it's a new reality. All around us, people are buying and selling goods and services as never before. The same forces of digitization that have democratized access to information also enable marketplaces to become ubiquitous.

It used to take companies years of investment and millions of dollars in revenue before they could even dream of creating a new, profitable product line; now, it takes weeks or months. The barrier for entry into many markets has fallen so low that competition is at an all-time high.

To succeed in this new market landscape, product teams need to be able to identify trends and patterns in their products' data that can inform them of more strategic decisions. The ability to analyze data in new ways can help product teams improve their products and offerings – and ultimately, increase revenue.

In this chapter, we'll explore how to use AI to gain actionable insights to succeed in the market. In particular, we'll cover the following topics:

• Analyzing trends and white space discovery
• Connecting market shifts to brands, products, and services
• Understanding market DNA

You'll learn how to identify new product and market opportunities, uncover and act upon market shifts, and tap into the concept of market DNA to read the voices, hearts, and minds of your customers.

Analyzing trends and white space discovery

First, let's discuss how to use AI to find megatrends in commerce through the lenses of product innovation and market intelligence.

Historically, product teams have relied upon a variety of methods to identify innovative products or features. These methods often include customer interviews, focus groups, and extensive market research. In recent years, due to the availability of additional resources and technology, product teams have been able to leverage AI-based techniques to complement or even supplant these traditional approaches.

In particular, trend analysis and forecasting have come into their own as important tools for product managers, enabling them to identify fads, up-and-coming trends, and potentially lucrative markets.

Improving product idea generation with white spaces

Idea generation starts with market research – but it doesn't end there, not by a long shot. Once a team has identified what people want through market signals, they should be able to go deeper into the data and AI, including to find so-called market white spaces. White spaces refer to those product segments that are not currently being served but could be if a product team can figure out how to operate in them.

In the following diagram, we can see a mockup of how white spaces are discovered by looking at data across all areas – products, services, brands, markets, consumers, and more:

Figure 11.1 – A mockup of Commerce.AI white spaces analysis

By combining insights from data sources such as digital channels, along with qualitative information about people's actual behaviors across channels (things such as what people search for or what features they like or dislike about a particular product), product teams can develop highly predictive models that will help them create more effective products or services.

Using this concept of finding market white spaces, Commerce.AI has uncovered 10 megatrends across over a trillion market data points. Let's dive into these megatrends, which have important implications for product teams today.

The virtualization of everything (VE)

Virtual reality (VR) is the digital environment of the future for several reasons, including its immersive nature and top-of-the-market performance in terms of both hardware and software adoption. The number of VR headsets sold globally has grown over 50% in the first quarter of 2021 (https://thejournal.com/articles/2021/07/01/virtual-reality-headsets-see-explosive-growth.aspx), and the technology is finally starting to reach an installed base large enough to be noticed by many consumers. VR will continue to gain traction in the coming years as more people are exposed to it, driving up average revenue per user (ARPU).

These figures can only increase, especially as costs continue their downward trend while simultaneously increasing computing power per dollar spent on a device.

While VR may not seem like a mainstream phenomenon just yet – it's something you have to try before you believe – the infrastructure is mostly in place and adoption rates are rising fast. It wouldn't be surprising if a billion people or more started using VR at some point within our lifetimes (even though that seems unlikely today).

Furthermore, large businesses such as Facebook are putting massive resources behind VR, including billions of dollars and hundreds of employees dedicated to working on the technology, so it's not a flash in the pan – it's an investment that will pay off.

There are many opportunities for product teams who want to leverage this new technology for their business. Let's highlight a few areas where companies should start thinking about how they might use virtual reality today:

• Immersive experiences
• Transforming existing industries
• Branding and reputation

These three areas are prime targets for VR-based experiences and products. The opportunities are wide open but will require companies to think about entirely new forms of business models that leverage the technology's unique capabilities. We'll explore each of these areas in detail next.

Immersive experiences

Companies that offer immersive experiences will likely see the most success with VR. The main benefit of virtual reality is that it allows people to be somewhere else, whether it's a game, a movie, an exhibit, or even another country. But it goes beyond entertainment.

Companies can use VR to train their employees, put customers in touch with experts, show off products and services, and much more. As a result, companies are finding exciting ways to engage users through new channels and formats – all while offering them something they couldn't get from regular old 2D screens.

Transforming existing industries

In the past couple of years, we've seen companies use VR for aircraft design prototyping, virtual showrooms, and more. These projects demonstrate how companies are looking at older industries and finding new ways for people to engage with them using technology – in this case, virtualization.

Branding and reputation

Getting people to notice your brand is hard. That's why companies spend so much money on advertising – to reach the few people who see their ads. Virtual reality can change all of that because once integrated into a company's ecosystem, customers will want to engage with the brand. No one will want to miss out on new virtual experiences in the future; instead, everyone will want to be part of it (especially if their friends are there too).

Augmented reality

The augmented reality (AR) market is growing incredibly quickly as more consumers become aware of its possibilities. As with most new tech trends, AR initially targeted a niche audience – specifically, gamers looking for more immersive and realistic experiences – but as time goes on, it will continue to expand beyond this initial group.

There will be increased accessibility across multiple demographics, such as enterprise users seeking better collaboration tools, or parents who want an extra set of eyes while supervising children playing outside without fear of accidents happening.

AR will also benefit from the fact that it can be seen as an extension of VR since users are essentially living inside a digital world. The two technologies complement one another since they both provide users with new ways to interact with their surroundings – in this case, digitally augmented ones – providing them with an entirely new experience altogether.

This interaction is especially useful for those who work in industries where physical locations need to be shared with others. It's also worth noting that Facebook has recently been on an acquisition spree of AR firms, such as Scape Technologies, Daqri, and Mapillary.

Just as product teams can use VR, there are many creative uses for AR. For example, product teams can use AR to showcase new features or functions to educate users about how new features work, and even for brand engagement. Similarly, a restaurant could overlay real-time orders on top of customers' tables so that they can see how long it will take for their meals to arrive.

To give a few more examples, a real estate developer could create an AR model of a property and show it to potential buyers, while a homeowner could use AR to add virtual furniture to their homes. Consumers are even using AR to try on makeup, clothes, hairstyles, and accessories. Considering all of these possibilities, it's no wonder that companies are investing in AR to help them engage with their customers and prospects in new ways.

E-commerce

Online shopping is becoming more and more commonplace as e-commerce continues to experience massive growth. The Commerce.AI data engine saw 10 years' worth of e-commerce growth in just a few months in 2020, leading to tremendous e-commerce penetration all over the world.

E-commerce will also benefit from the fact that younger consumers are less attached to traditional methods of shopping or purchasing products; they see buying things online as no different than going to a mall and buying something there.

For physical stores, the biggest challenge is the so-called friction of travel. If you live in a rural area and you want to go in-store shopping, there's no other option but to get on a plane and go to a different city for your shopping trip. On the other hand, online retailers don't have this problem – all you have to do is hop on your computer or turn on your smartphone, and you can be anywhere in the world where people are willing to buy from you or send their money to you.

This shift toward online retailing has been a long time coming. A couple of decades ago, it was virtually impossible to buy anything online besides books or office supplies; today, thanks largely to e-commerce platforms such as Amazon and Alibaba, which dominate their respective markets, anyone can easily purchase almost anything with just a few clicks of their mouse.

The rise of social commerce

Social commerce has grown significantly over the past several years and shows no signs of slowing down anytime soon either, especially with the likes of Instagram and Tik Tok becoming increasingly popular as platforms for brands to connect with customers.

On the other hand, traditional media outlets such as newspapers or television ads might alienate some potential customers who aren't interested in what's being advertised at any given time (besides perhaps if it's pizza). This is, in part, why social commerce is dramatically taking over.

Currently, social media is most popular among Gen Z; however, its penetration rates have been increasing rapidly among older age groups such as Boomers and Gen Xers over the past couple of years as well. Social media has become such an ingrained part of our daily lives that it's unlikely anyone will stop spending time on these platforms – and brands that can leverage this trend will see their sales increase dramatically.

The rise of influencer marketing

Influencer marketing is another example of social commerce that has seen significant growth in the past several years. Influencer marketing spending will continue growing in parallel for the foreseeable future, especially as consumers become more comfortable with buying products based purely on someone's recommendation rather than due diligence that's been conducted by themselves.

Influencer marketing has grown alongside social commerce; both have benefited tremendously from each other as they both rely heavily on word-of-mouth recommendations among customers.

If there's one thing we've learned from the age of social media, it's that online peer pressure is often extremely powerful when it comes to influencing people and convincing them to buy something, whether they need/want it or not.

The gamification of everything

Gamification is a hot topic in terms of both commerce and marketing, with both brands and consumers alike being interested in how they can leverage the concept to increase engagement. This trend has been around for over a decade now – even Facebook was using gamification techniques since its origins – but recently the amount of attention it's been getting has increased exponentially as competition increases to grab people's limited attention spans.

The idea behind gamification is to make something that would be considered mundane or uninteresting by itself – in this case, things such as shopping experiences – into something that people look forward to doing.

For example, suppose you're selling a pair of running shoes. You could create an app for runners and turn the act of running into something interesting and enjoyable – such as competing with other people to see who can run the furthest or in the fastest time. You could also build a community around your brand and create an experience where people are encouraged to share their workout results with others, encouraging others to join them in their workouts.

This even applies to physical stores. Let's say you run a pizza restaurant. Instead of just having a pizza oven on display, you could have a game where people play to deliver pizzas to others in the community within 15 minutes. The person who gets to the top of the leaderboard wins a free pizza!

The possibilities are endless when it comes to using gamification techniques in both commerce and marketing.

The rise of the mass affluent

In financial terms, the mass affluent is often described as someone with liquid financial assets between $100,000 and $1,000,000.

The mass affluents are the new power brokers in global business and economy as they continue to grow in importance both economically and socially. This group of consumers is made up primarily of people who fall somewhere between upper-middle class and upper class, depending on which parameters are used to define their social status (wealth, education level, purchasing power, and so on).

Their purchasing power has grown tremendously over the past few decades as companies have been leveraging the internet to reach them and they have been able to compare price points, quality levels, and service from various consumer goods/services across many different providers. This trend has made it nearly impossible for companies in most industries to ignore these consumers – especially since they now have money to spend.

When you add all of this up over the past few years, it's no wonder that we are starting to see several trends emerge with regards to how brands interact with this group, primarily through immersive content and influencer marketing.

The rise of authenticity

With social media platforms such as Instagram, YouTube, Twitter, Discord, and so on having amassed billions of users who are interested in self-expression through self-captured content (whether its videos or still images), we're seeing a lot more authentic content being produced by users.

In addition, some of the largest brands in the world today first got their start on social media platforms before evolving into household names. This was thanks largely to their ability to connect with consumers at an authentic level.

Social platforms are not going anywhere anytime soon, so it's no surprise that many brands are trying to leverage them to create more authentic connections with their consumers. In short, consumers today are far more likely than ever before to trust and interact with brands on these platforms.

Gen Z

Generation Z (born after 1997) are the first truly digital natives and the largest generation of digital consumers. The sheer size of Gen Z is often overlooked due to their youth, but they will be entering the workforce at a time when both technology and service industries are experiencing unprecedented growth.

Gen Z has demonstrated an innate ability to understand how brands should interact with them based on their unique needs. For example, they appreciate authenticity much more than previous generations.

Demand for sustainable products

Lack of access to clean water, food, and energy in many parts of the world is pushing consumers toward buying products that have a smaller environmental impact, while also providing valuable benefits such as improved wellbeing or performance.

While this has always been an important aspect of what brands should be focusing on, Gen Z has led the way in demanding more sustainable products from brands they are interested in. These customers want to buy products that do not harm the environment but are also beneficial to them rather than compromising between both.

Companies such as Unilever have recognized this trend and created sustainable product lines with less toxic ingredients that are still effective in delivering the desired results.

To summarize these 10 megatrends, we can say that they are an inevitable consequence of the rapid evolution of many different spheres of human activity, from business to government to science. They are here to stay and will continue impacting how our lives are lived daily.

That said, understanding market shifts isn't enough – to capitalize on them, companies must be able to connect these shifts to their strategy and existing assets, as well as identify where they can innovate to better meet demand.

Connecting market shifts to brands, products, and services

Now that we've looked at ways to analyze and interpret market shifts from commerce data, let's learn how to connect market shifts to brands, products, and services. We'll look at this connection across two main areas:

• Gauge positive and negative changes in your product and product category, and respond with speed and efficiency.
• Recognize, manage, and resolve product risk areas and escalations and develop solutions proactively.

Gauging product shifts

Gauging shifts in the market is hard. How do you know what's happening and how to act on it?

It's not enough to be aware of shifts in consumer demand. You have to be able to act quickly, anticipating what those shifts will mean for your product or service offerings and how you might capitalize on them. By doing so, you can turn an opportunity into a competitive advantage that positions your company for success in the long term.

Let's look at three key ways that companies are using AI to better understand these shifting markets: identifying opportunities, gaining insights into competitors, and making changes based on data analysis.

Each of these areas is critical – and each requires AI technologies such as sentiment analysis and natural language processing (NLP). Of course, there is much more to consider than just being able to identify market shifts – but if you can leverage NLP technology as a starting point, it can unlock new possibilities for your product team.

How market shifts can help you find opportunities in the market

So, what does it mean when consumers switch from consuming water straight from their taps at home to buying pre-bottled water? Or when consumers go from buying bottled water for picnics and outdoor activities to buying it for everyday consumption? These are shifts in consumer behavior, and they're worth measuring.

How do you know what those shifts mean? And how can you leverage them to your advantage as a company – whether that means finding new ways of connecting with customers or identifying where they might be switching from your competitors?

Whether it's bottled water, electronics, or something else entirely, NLP can help us understand how consumer sentiment and interests are shifting.

This information could give us a good idea of which brands consumers plan on purchasing in the future, and this insight can then be used by product managers or marketers to create new campaigns aimed at these specific users. In essence, we would have been able to identify an opportunity in the market before anyone else.

Predicting market shifts and understanding what those shifts mean for brands and products is not just important for identifying opportunities – it's also key to creating new ones. By knowing which consumers may be interested in your product or service, you can start building out community content around that topic – all while creating a potential opportunity for your brand to attract new customers.

Gaining insights into competitors can help you create a competitive advantage

The customer experience (CX) is the new competitive advantage in e-commerce. And that makes sense – in today's world, consumers are more likely to make decisions about which brands they do business with based on how those brands treat them.

As such, companies in every industry need to pay close attention to what their competitors are doing so that they can learn from and react to what their customers want. By gaining insights into competitors through NLP technologies such as sentiment analysis, you can better understand how your brand is being perceived by consumers.

In the case of bottled water, we might be able to see a positive shift toward premium bottled water brands as people become more concerned about health and wellness. But this could also mean that there is a potential market shift away from other products in a product line, such as soda.

This information could then be used by product managers within any given company – whether it's Coca-Cola or some other consumer goods company –to determine how best to adapt their product offerings accordingly.

Making changes based on data analysis can help you adapt to shifts in the market

Data is everywhere, and more than ever, companies are using it as a way of gaining insights into their markets. As a result, it's never been easier for brands to access data on everything from consumer behaviors to competitors' sales trends. And when used effectively, this information can be a valuable tool for taking action and making informed decisions about how you should operate within any given market.

NLP technology is just one piece of the puzzle when it comes to identifying market trends and making changes based on data analysis. But no matter what industry you work in or what your role is at any given company – from marketing manager to CEO – being able to leverage NLP technologies can help you spot emerging opportunities faster than your competitors, gain deeper insights into your customer base so that you can create more meaningful connections with them, and make smarter decisions.

Recognizing product risk areas

Product risk areas are the manifestation of shifts in customer needs and behaviors that cause a product to fail or underperform. When these areas are better understood, they can be addressed proactively through design and development changes. By anticipating change, market conditions, and even competitors' strategies, product teams can develop products that meet changing customer needs.

To manage these areas effectively, product managers need to understand their customers – who they are and how they behave – so that they can anticipate what features customers might value most highly. When developing new products or services, this knowledge should inform you of how features will be designed internally and what problems/opportunities for innovation exist externally in the market.

To reduce the risk of failure, product managers should also have a strong understanding of their organization's capabilities and constraints to ensure they are building products that can be successfully delivered within their budget and timeline. They should consider how competitors are approaching similar problems, what technology will likely be used to solve those problems, and what capabilities they may lack internally but could leverage from external partners or vendors.

This kind of proactive approach allows you to identify potential risks early in the design process. It also provides you with the opportunity to build flexibility into the product roadmap by incorporating some level of experimentation, along with certain features, strategies, or business goals.

Risk mitigation should extend beyond product managers to include the entire product development team, who can work together as a cohesive unit to identify and address any potential issues that might emerge.

Product risk management with AI

The ability to proactively anticipate risk and design products that are more likely to succeed is a valuable asset for product managers, but it can be difficult for teams to manage on their own. This is where artificial intelligence can help. AI can provide a comprehensive understanding of the market by analyzing numerous data sources in real time, including social media posts and online conversations, as they pertain to the product under development.

This analysis can identify emerging trends earlier than traditional approaches through its capability to uncover patterns that may otherwise go unnoticed. The AI-generated insights that are gained from these data sources can then be continuously refined and updated over time to provide even more detailed information on the state of the market situation – all things that a proactive product manager would find useful when trying to develop an innovative product within a competitive environment.

As part of this ongoing process, new opportunities or risks can be identified and acted upon before they become full-blown problems, providing additional benefits beyond just identifying potential issues before launch or reducing failure rates once launched.

This kind of strategic intelligence could give companies an advantage in creating new value propositions that customers will want to pay for – something that was not possible when those same companies were operating without the benefit of AI technology.

To conclude this section, the use of AI technology has helped companies identify opportunities and risks in the market, as well as improving their ability to anticipate changes coming at them from all angles. Using AI in this way can help companies gain a competitive advantage by better understanding their customers and developing products that meet those needs. To succeed in a competitive market, let's explore the concept of market DNA.

Understand market DNA

Market DNA is a set of attributes and characteristics that define a market. For example, a market might be defined by the attributes of its participants – such as how many users it has or their experience level – or the attributes of what they buy and sell, such as in a subscription model.

Market DNA is essential in understanding how a product should function and what features it should have. In particular, market DNA includes key product features. For example, if you're in the smartwatch market, a key feature is battery life. So, you may want a smartwatch with long battery life to capture the attention of consumers.

The following screenshot shows the features that contribute to market DNA in the case of men's wristwatches. Innovation teams can dive into dashboard sections around Products, Ratings, Reviews, Attributes, Consumer Wishlists, and more. Each feature illustrates one dimension in the multi-dimensional space of market characteristics:

Figure 11.2 – A screenshot of Commerce.AI's market overview for men's wristwatches

Product teams often struggle with this, as they're tasked with defining the product's purpose and building features that meet those needs. But it's rare for product teams to have data on how customers use their products – especially in early-stage companies where feature sets are still being defined. This is where Commerce.AI can help.

Commerce.AI helps product teams find patterns in market data from customers, which can uncover key product features faster than by conventional means, such as customer interviews or focus groups.

Commerce.AI also helps you understand how customers are using products, which can help product teams fine-tune their feature set and product strategy. For example, if a large percentage of users are using your product for one-off use but not regular use, this is a red flag that you might want to rethink the purpose of your product or its target user. Let's dive into these ideas more deeply by understanding market attributes, user wants and needs, finding new use contexts, and more.

Finding market DNA attributes

In this section, we will discuss how market data from Commerce.AI can help product teams find key features in the context of market DNA – including surfacing specific attributes that define the market. We'll dive into examples of key features that have been surfaced by merchants on our platform and how these insights can inform product teams' decisions.

As with many new product strategies, there's often a temptation to try and build everything for every possible user. This approach can quickly lead to feature creep and delays in shipping features as you need to add support for more use cases.

More importantly, it's not always clear which features are critical to success in a particular market. For example, is it critical for your product or service to have a long usage lifetime?

Marketers often think so, but customers may not be so attached to this. Research suggests that people generally prefer long-term products over short-term ones; however, there are exceptions – such as when the customer experience of switching is prohibitively expensive or inconvenient (for example, moving homes).

So, understanding whether customers want one-time purchases or expect their purchases to last longer might be an important insight into defining your product strategy.

Commerce data from our platform has helped merchants understand how customers respond to different pricing structures and offers on their site – which has led them to adjust their prices more efficiently while increasing revenue per customer interaction.

Through insights from Commerce.AI, these merchants have also been able to identify key features on their site that are helping drive conversion rates and increase purchase frequency among visitors.

These findings could help inform product teams about what types of features should be prioritized during development efforts, or even enable teams at other companies that are using our platform to find inspiration around what types of features they should consider building into their products/services.

Finding user wishlists and emerging needs with AI

Consumer demands are changing. People are using their smartphones more, and now they're using them non-stop for shopping. Today, we have more data than ever before about people's needs and wants – but the challenge is figuring out how to turn that information into products that people want and need.

To get there, product teams need a new way of thinking about user research. Traditional user research methods such as focus groups or one-on-one interviews often result in too much noise: lots of details that don't tell you much, if anything, about your users' underlying motivations or goals.

This can make it difficult for product teams to develop meaningful hypotheses about how to design products that meet users' needs better than existing options do. These insights will help you improve the ways your teams both start new products and evolve existing ones.

Product managers and executives have long understood that user research is essential to product development – but they've been challenged by limited access to users in the past. The best-laid plans often go awry when those plans require more human subjects than you have access to.

Today, however, advances in technology are making it possible to do what was once considered impossible: truly understand who your users are, where they are in their life cycles (compared with whom), how they think and feel about your product or service currently or potentially (compared to other options), and how you can design a product that keeps them engaged over time.

As the world's first company to design and build a platform for conducting deep market research at a global scale, we have seen firsthand how daunting this problem can seem at first glance – but also how solvable it can be once you start thinking about it in new ways.

AI and consumer-generated content

Our customers can understand their audience in more granular detail than ever before by exploring and interrogating any number of consumer-generated content (CGC) sources, such as video clips, product images, sound bites, and comments on social media posts – even contact center data, data lakes, and more.

And with our platform that connects market research teams with target audiences across all major social platforms at scale, they gain immediate insight into emerging needs and unmet desires among the people they want to influence.

In short, when you ask your customers what they want now AND what they might be interested in down the road – combined with insights gained from CGC sources such as videos and pictures posted publicly online – you're able to gain a clearer understanding of your audience's underlying needs and desires, which are often not articulated by them yet. And the more you can understand what those unmet needs or latent desires might be, the better positioned you are to create products and services that serve their long-term interests over time – whether they realize it at the time or not.

This is where we believe AI comes in: by combining CGC insights with AI technology, you're able to uncover patterns in users' behavior that you might not otherwise be able to see. For example, our customers have used our platform to identify emerging trends among specific groups of customers – such as millennials who love Android phones but hate iPhones – which can then be used for market research.

Finding new use contexts with AI

Commerce.AI uses advanced machine learning to identify the most relevant and useful use cases for a product, based on the user's prior behavior and other contextual factors. For example, if you are selling a new pair of shoes, one customer may want to wear them for exercise, while another may want to use them for weekend shopping, and yet another may just want to show them off at the club.

To successfully market and sell these shoes, you'll have to overcome the challenge of understanding how your product can be used by different users in different ways.

Product teams can then design new products with those specific contexts in mind. Product managers can also leverage this data to help prioritize features or changes within their product backlogs – prioritizing features that are likely to be more useful across multiple use cases rather than simply focusing on what is the most important for a single user or group of users.

Let's look more closely at one example: smart home products. A smart home product could be used for many different things: an energy monitoring product, a security product, a panel for your next house addition, and so on. To create the best possible experience across these use cases and to attract the most customers as a result, you'll want to design your product with some important context in mind: how will others in your user community use it?

For example, if you're creating an energy monitoring product for homes that are more expensive than average – say, $1 million or more – you may want to consider not only whether people will use your product for conservation or efficiency purposes but also whether they might be investing their money into building out other aspects of their home (such as another bedroom) – potentially increasing the demand for your product among wealthier users.

By analyzing product reviews, social media comments, and more, Commerce.AI can help you understand the context of why people are buying your product – and what other potential use cases might bring in new customers based on this information.

Summary

In this chapter, we've learned how to use AI technologies to gain strategic insights into the market, identify opportunities and risks as they emerge, anticipate shifts in consumer preferences, and reduce the risk of failure. In some cases, market shifts can be good for your business – but they can also present new challenges if you aren't ready for them.

We've explored how Commerce.AI helps firms take advantage of market shifts to create new value propositions and improve the overall health of their businesses. Using AI to gain strategic insights into the market can help companies anticipate change, identify opportunities, manage risks, and even predict how consumers will respond to products before they are launched.

Commerce.AI goes beyond simply validating hypotheses to help teams find product-market fit more quickly by identifying underserved needs in emerging markets and areas of white space within incumbent markets. Enabling product teams to better understand these dynamics enables them to invest time early on in building a viable product-market fit while mitigating the risk that comes from trying to figure out what customers want once feature sets have been defined.

In the next chapter, we'll discuss how voice surveys can be used to build an understanding of how customers think about a product or service, as well as how teams can use this information to inform innovation decisions.