Why Traditional Consumer Insights Aren’t Enough in the AI Era

• Consumer & Market Insights

In a world where consumer trends can go viral in hours, waiting days and weeks for survey results is like driving by looking only in the rear-view mirror.

For years, quarterly reports, surveys and focus groups were gold mines for extracting consumer insights. They gave an idea to brands about what people wanted, how they behaved and why they chose a specific brand or product over another.

However, those tools were built for a slower marketplace, one where it took months for trends to spread, competition was predictable, and “data” was organised neatly in rows and columns.

That world ceases to exist now.

Today, consumers are generating massive streams of unstructured data in every second, from Instagram Reels and TikTok videos to product reviews and customer service chats. Trends are becoming global overnight, and it is difficult for traditional insights to keep up in this environment.

Here’s why.

The Speed Gap

It takes weeks for surveys and focus groups to run and analyse. By the time their results reach the senior executives, they are already outdated.

Consider TikTok’s “quiet luxury” and “mob-wife” fashion trends. These trends exploded in a matter of days, while traditional survey cycles would have only caught up after the moment had passed.

AI here can flip the script. Real-time sentiment analysis tools can scan thousands of reviews, posts, and conversations every minute to detect unusual shifts as they happen.

Zalando, a European online fashion retailer, is using AI to produce imagery quickly enough to respond to short-lived fashion trends spread on social media. This enabled them to cut campaign production from 6-8 weeks to just 3-4 days.

Bias and Blind Spots

Another limitation of traditional surveys is that they often tend to capture the loudest voices, either the delighted or the disappointed ones. The silent majority stays unheard.

Furthermore, pre-set questions are unable to capture new themes that consumers might want to bring up on their own.

AI closes this gap by analysing unstructured text like app reviews, forums, or support logs.

Experts analysing EV charging station reviews trained AI models to classify nuanced sentiments with 91% accuracy – insights far richer than a simple “satisfied vs unsatisfied” scale.²

The Scale Challenge

In today’s era, brands are collecting gigabytes of data daily, from clicks, call centres, IOT sensors, and social platforms. Traditional tools cannot cope with this flood of data.

AI can thrive on scale. Machine learning models can digest billions of data points to spot weak signals and continuously refresh forecasts.

UK Grocer Sainsbury’s has entered a strategic partnership with Microsoft, which will enable the supermarket group to use its rich data to enable AI-powered insights to guide both online personalization and in-store operations. This will help staff to act faster, and customers shop smarter.³

Personalization at Scale

Modern consumers don’t want to be considered as a part of a demographic. They want to be seen as individuals by brands.

Traditional insights, which are based on averages, cannot deliver that.

Generative AI can make personalization for brands practical. It can generate images, copy, and product recommendations tailored to customer segments within seconds.

Fintech firm Klarna is saving $10 million annually by using GenAI to run marketing campaigns and generate images on a weekly basis for key events such as Valentine’s Day, Mother’s Day, summer sales etc.,^{4 4}  while IBM’s pilot with Adobe Firefly delivered 26x higher engagement than traditional campaigns.

Trust is Non-Negotiable

Like every good thing, AI isn’t perfect. It sometimes hallucinates, reflects biases in its results, or makes certain decisions that might be too opaque to explain.

In this digital age, consumers are deeply concerned with transparency and fairness. They want to know how their data is being used and they expect brands to act more responsibly.

Bain & Company found that while AI can dramatically improve customer experience, trust can collapse quickly when biases or errors go unchecked.⁶

The bottom line? AI needs to be used with human oversight, ethical guardrails as well as clear communication.

The Way Forward

Traditional insights aren’t obsolete yet, as they are still useful for consistent tracking, benchmarking, and grounding strategy.

However, on their own, they are not enough.

AI does not replace human intuition it enhances it.

• From lagging to leading – moving from history to foresight.
• From averages to individuals – replacing generalizations with personalization.
• From anecdotes to evidence – turning billions of scattered and messy data points into clarity.

The brands that can win will be those that combine tried-and-tested traditional methods with AI’s ability to act fast, scale insights, and capture nuances.

In the AI era, consumer understanding is not just about keeping up, but about staying ahead.

Traditional tools give us the foundation, but to thrive in today’s fast, dynamic, fragmented, and data-rich world, leaders need to embrace AI responsibly, not just for listening but for truly understanding.

That’s the promise of C5i’s Synthetic Audiences – a powerful service designed to help leaders to test concepts and simulate behaviours using intelligent synthetic data models.

C5i’s Synthetic Audiences are AI-generated virtual consumers built for modern research. Fueled by demographic, behavioral, and social listening data, these synthetic respondents replicate real-world attitudes and reactions — without the lag or cost of traditional methods. Seamlessly integrate them into your workflows to simulate surveys, test concepts, assess brand health, and more. From virtual personas and synthetic concept testing to sample augmentation and pricing simulation, our AI-powered solution delivers fast, privacy-safe, and statistically robust insights. 

Sources:

1. Zalando uses AI to speed up marketing campaigns, cut costs – Reuters
2. Generative AI for Consumer Behavior Prediction: Techniques and Applications – MDPI
3. British grocer Sainsbury’s partners with Microsoft to use AI for data insights – Reuters
4. Klarna using GenAI to cut marketing costs by $10 mln annually – Reuters
5. IBM tests Adobe’s Firefly for personalized marketing at scale – Axios
6. Generative AI’s Potential to Improve Customer Experience – Bain & Company

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