When closing the say-do gap, real-time product usage data matters
Editor’s note: Nihal Advani is founder and CEO of QualSights. This article was updated on Sept. 25, 2025.
For decades, survey research has been the backbone of consumer insights. From tracking brand health to testing new products, marketers and researchers have relied on asking people what they think and what they do. Despite advances in methodology and analytics, one persistent issue continues to undermine accuracy and impact: the say-do gap.
The say-do gap refers to the discrepancy between what consumers claim they do and what they actually do. It isn’t usually intentional deception; instead, it arises from the natural limits of memory, the influence of social desirability and the complexity of everyday life.
In the CPG industry, this problem is costly. Industry analysts estimate that up to 85% of new CPG products fail, often due to inadequate or misleading consumer research.
The pitfalls of recall-based research
Traditional surveys rely heavily on recall. Respondents are asked to remember what they used, when and how often, sometimes stretching back weeks or months. This introduces multiple problems:
- Overstatement of intentions: Consumers often express stronger commitment to products than their actual behavior reflects. A customer may claim to use a product daily, when in reality they only use it three to four times a week.
- Faulty memory: Most people don't remember how often they used a particular cleaning spray or opened a snack pack. Memory is biased, approximate and influenced by what respondents think the “right” answer should be.
- Fragmented routines: Usage is rarely consistent. A product may be part of a morning ritual one week and forgotten the next – or substituted depending on travel or mood. Traditional surveys struggle to capture this nuance.
These pitfalls mean that recall-based insights often provide a blurred, backward-looking view of consumer life. Even when recall-based data is collected, it usually arrives weeks after behavior occurs, too late for agile decision-making. In fast-moving categories, such delays can result in missed signals and flawed assumptions.
The case for real-time insights
To address these shortcomings, a new generation of methods is capturing actual behavior in real time. By combining passive detection of product use with triggered engagement at the moment of consumption, researchers can observe not only what consumers say, but also what they do.
At the Quirk’s Event – New York, QualSights, a Chicago-based provider of consumer insights technology, and a CPG client shared one approach using a real-time, in-context research method. The process works in three steps:
- Observe behavior passively. Real-time, always-on, cloud-connected sensors capture how often and when products are used, recording objective frequency and timestamps.
- Trigger engagement instantly. At the moment of use, consumers receive a short survey, video or audio prompt asking why they used the product, how they felt and what else was happening in that context.
- Analyze patterns over time. AI-enabled dashboards connect behavior with context, surfacing trends and barriers invisible in recall-based data.
This approach sheds light on the “black box” of usage between purchase and repurchase. A consumer may buy a facial moisturizer but only use half the jar, and traditional sales data can’t explain why. Real-time methods provide the missing “why,” whether it’s forgetfulness, unpleasant smell or packaging that discourages routine use.
Real challenges vs. aspirational claims
A CPG client faced exactly this challenge. Surveys suggested consumers were building routines, but use and repurchase rates told a different story.
Through real-time trigger surveys, the client validated what was truly happening. The company could track exactly when consumers used the product and how often they didn't.
For example, there may be contexual barriers. In-the-moment prompts revealed the obstacles behind lapses in product use, including disrupted routines while traveling, difficulty opening packaging.
The insights weren’t just interesting, they were actionable. Marketing could address real compliance challenges rather than making aspirational claims. Research and development could test packaging durability at the moment, and innovation teams could identify unmet needs to feed the pipeline.
A broader CPG imperative
While the case above centered on wellness, the same principles apply across categories:
- Personal care: Are consumers using shampoo as frequently as they report, and how does that differ by household size?
- Household products: How much detergent is dispensed per wash cycle compared to what consumers say they use?
- Food and beverage: Do consumers open and finish snack packs in one sitting, or do they spread them across multiple occasions?
In each scenario, recall-based data risks overstatement or understatement, while real-time data grounds innovation and messaging in truth.
Why the say-do gap matters more today
Several forces make bridging this gap especially urgent:
- The high cost of failure. With failure rates of up to 85%, every improvement in predictive accuracy delivers real ROI.
- Inflation and tariffs. As costs rise, consumer behaviors shift. Understanding how often products are used and how often they are finished helps brands predict price sensitivity.
- Compressed timelines. Products are launched and tested faster than ever. Real-time feedback enables brands to pivot mid-launch rather than after failure.
- Behavioral science emphasis. In a world awash with opinions, what consumers actually do is the strongest predictor of what they will do in the future.
Complementing, not replacing, traditional research
Importantly, real-time approaches don’t replace established methods; they complement them. Each provides a piece of the puzzle: purchase data reveals what consumers bought; survey data captures their beliefs and feelings; and real-time usage data shows how products are actually used.
The integration of these streams creates a closed-loop intelligence system, where researchers can connect intentions, purchases and behaviors to outcomes. This triangulation reduces blind spots and gives brands confidence in their decisions.
From insight to action across the organization
Real-time usage insights ripple across an organization:
- Research and development validate how products perform under real-life conditions, beyond lab tests
- Insights teams uncover unmet needs and discover new usage occasions
- Innovation teams identify adoption barriers early, feeding stronger ideas into the pipeline
- Marketing designs campaigns based on lived consumer experience rather than aspirational claims
By turning behavior into evidence, organizations move from assumptions to truth.
Looking ahead: The future of in-the-moment research
As technology advances, the ability to capture and analyze real-world behavior will only expand. Sensors, mobile prompts and AI-powered analytics are lowering barriers to scale, while consumer comfort with digital engagement continues to rise.
The question for the research industry is no longer whether to embrace real-time, in-context methods, but how to integrate them effectively with other research approaches. Forward-looking organizations are already adopting hybrid models that combine surveys, qualitative immersions and real-time triggers. Those who lag risk being left with a distorted picture of consumer reality.
Ultimately, the path forward reflects a simple truth: you can’t fix what you can’t see. In an era when growth demands precision, behavior speaks louder than surveys. Bridging the say-do gap isn’t just about better data; it’s about aligning business decisions with the way people actually live, use and experience products.