Consumer insights are changing fast—here’s how to stay ahead

What do consumer insights look like in 2025 and beyond for CPG and QSR brands?

The convergence of technology, behavioral science and artificial intelligence (AI) is rapidly reshaping consumer insights. The rise in AI, big data and other advanced technologies (such as eye tracking) are giving companies access to a continuous stream of nuanced consumer insights. And the rise in these technologies has put pressure on CPG and QSR brands to anticipate, , not just react to,, consumer needs and preferences. 

In 2025, consumer research is no longer fixed and linear — but continuous, predictive and highly actionable. The “new consumer insights” gives CPG and QSR brands access to real-time, democratized consumer data that shows them not just why consumers think, feel and act how they do, but also predicts what they’ll want from brands and how they’ll behave next.

In this post, I’ll explore current trends as well as the future of consumer insights for CPG and QSR brands and show you how you can implement them. 

Read on for five macro consumer insights trends for 2025-2026. 

1. The integration of real-time, continuous feedback loops

Traditional research models are inflexible, fixed and limited. They only provide a snapshot into consumers’ perceptions, needs and wants. But what’s true of consumers six months ago is often not true of them today. 

Forward-looking CPG and QSR brands know this. 

Many of these companies are now relying on a stream of continuous consumer insights to build better brands, products and customer experiences. Whether that’s weaving concept testing into their product journeys to engaging consumer feedback throughout the development of their ads, agile CPG and QSR companies are integrating continuous feedback loops built on real-time data into their development lifecycles. 

Brands are relying on several different research methods alongside AI to automate and collect real-time consumer data such as focus groups, surveys, interviews, user testing and on-site polls.

Steve Phillips, our founder and Chief Innovation Officer, says,

“By leveraging AI throughout the entire product-development journey, we’re making it easy for insights teams to bring the consumer’s voice into every strategic decision. It’s all about reducing time-to-market and increasing the relevance of new products.”

At Zappi, we’re all about helping brands stay connected to consumers as they create, test, analyze and optimize their product and marketing ideas — making sure their brand, marketing and product decisions are guided by ongoing consumer feedback. Read up on our ethos here. 

2. The rise of emotional and subconscious measurement tools

"A snap judgement… The song that runs through your head every time you step into an elevator…. The desire to drink Coke instead of Sprite or drive a truck instead of a car. Your dislike of roses but love for tulips. The expression on your partner’s face that makes you feel either angry or amorous (or, the perplexing reasons you even married this person in the first place?). Welcome to your subconscious! While each of these events is seemingly unrelated, they all reveal a rich, inner life outside of conscious, rational thought." - Beth Kendall, Sleep Coach

Implicit research is used to pick up on the subconscious, unbiased associations consumers have toward a product, brand, product or category. 

Implicit research mainly measures this by observing how quickly consumers make their selections,capturing instinctive reactions. The two main types of research used in implicit research include Single Implicit Association Tests (SAT) and Multiple Implicit Association Tests (MAT). 

In the SIAT test, consumers evaluate a single piece of stimulus, such as a brand logo, in isolation. This measures the strength of consumers' associations between the stimulus and a range of attributes like "good" or "bad." While the MIAT test asks consumers to evaluate multiple items (such as design features, brands and products) at once, determining which of these has the strongest association with different qualities or emotional goals. 

In addition, newer technologies are now being used across consumer research to understand the subconscious, emotional motivations of consumers. The latest technologies include EEG (electroencephalography), which measures electrical activity in the brain via electrodes on the scalp and eye-tracking tools — tools that can observe consumers' thoughts and feelings by tracking and analyzing their eye movements. 

“[Research] suggests that what we think of as free will is largely an illusion: much of the time, we are simply operating on automatic pilot, and the way we think and act — and how well we think and act on the spur of the moment – are a lot more susceptible to outside influences than we realize.”

― Malcolm Gladwell, Blink: The Power of Thinking Without Thinking

Read our post on implicit research in marketing to find out more.

3. Data privacy is reshaping insights collection methodologies and data protection approaches 

New data privacy regulations are profoundly reshaping the way brands approach consumer research. New laws, such as the General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) in the United States, are demanding greater transparency, explicit and informed consent and more responsible data handling. 

Across research approaches, insights teams are now prioritizing explicit opt-in consent, greater transparency and clarity when it comes to privacy policies, and providing easier and faster ways for consumers to withdraw their consent at any time.

While new data privacy regulations have moved many CPG and QSR brands away from third-party data brokers with unclear consent origins and approaches to data privacy that they can’t control. Instead, many companies are now favoring first-party data collection alongside qualitative and hybrid approaches such as focus groups and interviews.  

And while AI offers a number of benefits to consumer research, from extensive automation to in-depth analytics, the rise in the use of AI has also brought with it challenges for data privacy. Automated systems that centralize and analyze huge consumer datasets have made it harder to track data processing and ensure data privacy. 

Many brands looking to leverage the benefits of AI are adding additional data protections. Privacy-focused AI techniques like differential privacy, in which teams add carefully calibrated "noise" or randomness to their datasets before they analyze them, can go a long way in helping to maintain data privacy. 

Homomorphic encryption is another technique that brands are applying to help ensure greater data privacy. Homomorphic encryption is an advanced cryptographic technique that allows teams to perform computations directly on encrypted data — without the need for decryption. 

As an example, you may think about a company that stores consumer data on the cloud and directly accesses it for their personal analysis. In this case, the unencrypted data never needs to be shared with their cloud provider. 

Many companies are also prioritizing algorithms that are fair and unbiased — taking additional measures to ensure their data isn’t inadvertently supporting harmful stereotypes. 

Find out how you can address data quality issues in our past post. 

4. Hyper-personalization powered by predictive analytics

"Technology is reshaping fast food, making personalisation scalable. AI and machine learning are making customisation scalable, helping restaurants tailor meals while streamlining operations. For fast food chains, this isn’t just about convenience – it’s about survival in an era where consumer expectations are shifting faster than ever." - Jodie Shaw, Kadence

Consumers crave hyper-personalized brand and service experiences. 72% of fast food customers say they prefer restaurants that offer personalized ordering, while a third of customers have ditched a restaurant that failed to provide it. 

Research in the CPG market also found that the use of AI to personalize consumer journeys can lead to a 300% ROI in retail media. 

Hyper-personalization, powered by predictive analytics, represents a significant evolution in consumer research. Hyper-personalization is when brands take consumer data and use it to create experiences that are completely unique to each consumer. With the help of predictive analytics, companies can take huge amounts of consumer data and use machine learning techniques to anticipate their future needs, behaviors and preferences. 

Hyper-personalization typically uses AI to combine a variety of granular datapoints such as purchasing history, social media engagement, preferences and browsing behaviors to deliver individualized experiences and highly-customized customer interactions that help consumers develop deep, longer-lasting connections with a brand. 

In the consumer research space, hyper-personalization powered by AI has shifted the focus away from traditional research methods where companies look at past consumer behavior to understand why something happened — instead, putting the emphasis on what consumers will do next and how the brand can influence them. 

Hyper-personalization is moving brands towards tracking and understanding the entire customer journey, breaking down the micro-moments that make up the whole and giving brands countless opportunities to act on this data. 

How is this being applied in the QSR industry as well? 

Machine-learning capabilities currently support QSRs to deliver customized menus to consumers. By tracking and learning from data on past orders and consumers’ unique dietary preferences, QSRs are providing customized digital menus to each consumer. 

Right now, the biggest tools in consumer research are AI-based tools that combine qualitative and quantitative research capabilities. Let’s review some of the best and take a look at how they can help you benefit from the latest consumer insights trends.

Zappi 

With Zappi, you can test ideas and content early and often, create a learning loop across your insights, craft automated AI-generated reports and gain deep insights into your audience with real-time analytics and flexible benchmarks. 

You can also use our AI Agents to measure immediate consumer sentiment — supporting your implicit research efforts. 

"For a new shake flavor, I analyze the drivers of interest & purchase in all the shakes we’ve tested before. I can see how consumers play those concepts back, & what they want us to do differently. There’s a lot I can do easily with the data set."

- Matt Cahill, Senior Director of Insights Activation at McDonald's

Our agile market research platform is used by brands like PepsiCo, McDonald’s and SoFi to name a few, and we currently have over 1000+ customers in over 50 research markets. 

🚀 Learn more about the Zappi platform 

Suzy 

Suzy’s consumer insights platform breaks down silos and offers a fully-integrated approach to consumer research. Suzy supports both quantitative and qualitative research methodologies, integrates proprietary audiences and provides AI-enabled tools to support automation and conversational research.

Quantilope

Quantilope offers over 15 automated research tools and methodologies for researchers in the consumer insights space. With a world-wide panel network of over 300 million and AI technologies that immediately turn consumer feedback into insights, Quantilope is a great platform for researching your customer base. 

Hotjar 

Curious to find out more about how consumers experience your website, product page or other digital offerings? Hotjar is a product experience (PX) insights platform that allows you track and analyze users' experience of your website and digital products. 

With Hotjar, you can access a range of qualitative and quantitative data. For example, you can use Hotjar's heatmap feature (quantitative data) to track users' movements across your website — from how quickly they scroll down the page to where they linger or click the most frequently. 

You can combine these quantitative-data features with features like on-site feedback, interviews,and surveys, giving you direct access to the real-time thoughts and feelings of consumers as they use your site and engage with your content. 

Mixpanel 

Mixpanel is a product analytics tool you can use to get insights into the features your users value most and how they typically use your product. You can use the platform to visualize user paths, segment and analyze user cohorts and see how users use your product in real-time with product replays. 

Sherry Shih, Product Manager at KKday explores how the brand uses Mixpanel to understand their user journeys: 

“Before Mixpanel, we didn’t have the complete map of our user journey. Now that we have full visibility, we can segment our users according to their behavior and better target them. We used to think that our time to conversion was between one to three days but after looking at the data in Mixpanel, we realized that 85% of the time, people were completing their booking process within just 50 minutes. This informed us to better design our user engagement to fit within this time window, instead of optimizing it for one to three days."

How are CPG and QSR brands taking on these trends? Let’s take a look at some of the brands leading the way. 

KFC 

KFC regularly undertakes in-depth quantitative and qualitative consumer research. 

Here’s Kantar on some of their customer behavior research for the brand: 

"Regular KFC customers are more likely to hold more progressive views in a number of areas. For example they are significantly less likely to believe that there is too much concern with the environment (26% agree with this notion, compared to 34% of users of other chicken outlets) and less likely to be willing to sacrifice family time in the name of work (24% would willingly do this, compared to 39% of other chicken restaurant customers). They also show a greater spirit of adventure, being less inclined to go for holidays where the activities are pre-organised for them."

In response to their customers’ demands for more sustainable fried chicken, KFC set out to reduce their GHG emissions by 46% by 2030 and aim to reach net-zero emissions by 2050. The brand has also moved to more circular packaging — designing out waste, scoring more sustainable packing materials and focusing on recycling and reusing. Over in the UK, they’ve also incorporated AI into their sustainability efforts, sharing:

"In our restaurants, we’re using automated demand forecasting software to tell kitchen staff how many units of each item to prepare at any given time. Some of our UK restaurants are currently working with Yum! Brands, our parent company, to trial AI technology to improve the forecasting of how much chicken we need to cook, which will help us reduce overproduction waste even further." 

KFC is also currently using consumer data to better personalize the customer experience. The fast-food chain uses hyper-local menu customization to draw in customers — testing localized items like spicy or regional seasoned chicken in different regions of the U.S. to meet the preferences of local diners. 

💡 Takeaway: KFC has built one of the most successful QSR brands by listening to consumers and personalizing the customer experience. Be like KFC, implement ongoing consumer research initiatives that combine quantitative and qualitative methodologies and use these insights to better personalize the customer experience and drive customer loyalty. 

Mooyah 

Texas-based fast-food chain Mooyah used eye-tracking technology to help understand their customers’ brand experience, making it the first fast food company to use the innovative new technology to understand consumers. 

The tech uncovered how long store guests kept their eyes focused on specific brand elements, as well as what they looked at first, second and third after entering the store. 

Mooyah president Alan Hixon said: 

"The thing that I think helped the most was when I could hear their comments along with where they were looking. This helped me better understand what they were thinking. For example, as someone looked around the restaurant, and you could see where the crosshairs were focused, it was great when they would say things like "pretty cool" or "feels much nicer than the other location that I have been to before."

He also noted how the technology has helped the company confirm previous suspicions or gut insights: 

"You get to see your operation from the customer's perspective and that's hard to do. It confirmed some things we hoped to confirm."

💡Takeaway: Companies like Mooyah are accessing deeper insights into their customers by being one of the first QSR companies to use subconscious measurement tools. You’ll likely gain a significant competitive advantage by experimenting with these tools in your consumer research. 

Coca-Cola

"The magic of AI lies in combining its capabilities with human creativity and judgment. In industries such as consumer packaged goods, AI is optimizing supply chains, personalizing marketing, and helping companies anticipate consumer behavior shifts, embrace sustainability and unlock new revenue streams."

- Ashley D'Souza, Chief Digital Officer at Coca-Cola

Coca-Cola was one of the first brands to use AI and predictive analytics in its consumer insights and product development initiatives. 

Greg Chambers, global director of digital innovation, said, “AI is the foundation for everything we do. We create intelligent experiences. AI is the kernel that powers that experience.”

Coca-Cola Freestyle, an AI-based soda machine, allowed customers to combine and mix any beverages from the company’s inventory via the touch-screen display. Based on real-time data collection and AI analytics, they found that Sprite and Cherry was one of the most popular mixing patterns — leading the brand to launch Cherry Sprite. 

While the continuous collection of real-time consumer data also allows venues to predict consumer wants and personalize their selections accordingly. Lance Concannon at Meltwater says: "Each individual machine conducts real-time analysis of consumer data, responding in various helpful ways to improve customer experience. The AI algorithm means every establishment can use their machine to promote unique, bespoke beverages and trending flavors in relation to their consumers."

💡 Takeaway: Coca-Cola embodies the power of the “feedback” loop, consistently learning from their consumer base and combining these insights with predictive analytics to improve customer satisfaction and loyalty. Look at how you can use big data, AI and predictive analytics to preempt what consumers want and need from you next. 

If we look ahead to consumer insights for 2026 and beyond, I predict we’ll see a growing focus on iterative, agile models supported by AI and other emerging technologies. With the ability to create surveys in minutes, access and analyze huge amounts of consumer data and give us unique insights into the subconscious workings of consumers’ minds, AI will become an even more essential part of the research process. 

Democratization will also become commonplace within consumer insights. By giving every stakeholder access to the consumer data they need, organizations will be built on faster, smarter, data-informed business decisions and will be able to become fully customer centric. 

What to do next as a marketing or brand leader

Start future proofing your strategy by looking at how you can bring AI into your research and data analysis, looking at how you can democratize insights and integrating real-time, continuous feedback loops into your consumer research approach. 

The right consumer insights partners can help you build a forward-thinking strategy. How do you choose the right partner? I recommend running through this list of questions with them: 

1. What research approaches and methodologies do you use? 

2. Which data sources do you use (e.g. first, third, a mix)? 

3. What is your data privacy policy?

4. How do you ensure the quality of your data? 

5. Can you show me your processes? 

6. What is your consumer insights philosophy? 

7. What analytical techniques do you use?

8. Do you have specialist expertise in a particular market?

9. What tools do you use for data collection, analysis, and visualization?

10. How do you deliver insights and business recommendations?

11. What kind of consultancy or support do you provide? 

12. Can you demonstrate ROI for past clients?