By Crispin Beale, CEO, Insight 250
(Photos courtesy of Pixabay)
As the spring season appears, growth and renewal emerge across the landscape. The same can be said of the insight industry and market research in general, with innovations and opportunities appearing to provide greater value and enhanced utility. Given these changes, I reached out to a variety of experts from across the globe, asking:
Enterprises are in a season of 'insight renewal,' yet many still rely on obsolete winter-grade market research tools and tactics and need upgrades. To maximize insights for growth, what are three research dimensions teams should 'clean out' and three research innovations that they should cultivate to drive success?
Urpi Torrado, CEO, Datum, Peru
“Many organizations still rely on outdated research habits. Three dimensions to clean out: siloed insights that never connect across teams; dashboards overflowing with data but lacking interpretation; and the tendency to look at numbers without context, separating quantitative from qualitative understanding.
To move forward, teams should cultivate three innovations: continuous insight ecosystems that capture signals in real time; AI-assisted analysis that augments, rather than replaces, human judgment; and sustained investment in technology alongside the training of research teams. The future of insights depends not just on better tools, but on better integration, context, and human capability.”
Justine Clements, Consumer Insights Manager, Samsung Australia
“I’ve had enough years in research to learn that growth comes from knowing what to let go of. Clear out the legacy trackers that measure what we’ve always measured, not what matters, get rid of long slide decks that mistake volume for rigour and the immediate instinct to treat AI as a way to cut costs and people. Instead, I’d cultivate conversational AI, research that meets consumers in the moment, and I’d be looking for synthetic data to extend research to places fieldwork can’t reach and I’d embrace analysis that is augmented by AI tools that allow us to scale but also the opportunity to apply human thinking where it matters. Research functions that thrive in the next decade will be the ones brave enough to clean house now.”
Pavi Gupta, BOD Member, Market Research Institute International &
Global Brand Ambassador, Insights Lighthouse, USA
“Spring cleaning is a reminder of sunnier days ahead. While the winter gear has served its purpose, deep cleaning helps us get ready to spring into the future.
This is a great analogy in the business environment as well.
As we look forward to the Spring of 2026, it’s time to reflect and ask a few questions of yourself. Are your ongoing research studies (tracking et al) truly working for you? What could you do to improve outcomes? Are there any new approaches that you could start considering that could be even more effective?
More specifically, as AI becomes too big to ignore, think about how LLMs can play a greater role in any of the day-to-day business decision-making. Right from understanding fertile areas and territories to innovate in, audiences to target, communication to drive engagement, and efforts to drive conversion at the point of sale. As another example, as agents and agentic commerce become more omnipresent in driving conversion, ask yourself what you are doing to understand and appreciate how to navigate this fast-evolving space.
So, the 3 things I have for you are more in terms of mindsets and behaviors - continue to fuel your curiosity, look to build greater connection across data sources, and experiment with new approaches.”
Mark Langsfeld, CEO, mTab & Co-chair Insight 250, USA
“Cleaning out the obsolete data silos that hinder insight access and deeper understanding of consumers, products, markets and competitors should be a spring cleaning priority for every enterprise. Cultivating an integration of these data sources with an agentic-based decision intelligence solution will unlock efficiency, speed, efficacy and success for teams across the organization. Companies that are leading the charge across industries like automotive, entertainment, food & beverage and consumer packaged goods, to name a few, are seeing tremendous growth and flourishing success across their Marketing, Product, Sales and Innovation teams.”
Kristin Luck, Chair, Women in Research, Founder, Growgetter, Scalehouse, USA
Clean Out:
1. Static, single-point research. Annual trackers and one-and-done studies are the flip phones of the insights world. They tell you where you were, not where you're going. By the time that deck hits the boardroom, it's already a history lesson.
2. Data dumps dressed up as insight. If your team spends more time cleaning and contextualizing data than actually acting on it, you don't have an insights function - you have a very expensive spreadsheet habit.
3. Siloed research programs. When brand, product, and CX are running separate studies that never speak to each other, you end up with three different customers - none of them real. Fragmented research produces a fragmented strategy. Full stop.
Cultivate:
1. Always-on intelligence. Move from episodic research to continuous feedback loops. Spot shifts before they become crises - or missed earnings calls.
2. AI-augmented synthesis. Not "AI instead of researchers." AI with researchers - accelerating analysis, surfacing patterns, and letting lean teams punch well above their weight.
3. Decision-linked research design. Start with the decision you need to make, then design backwards. Revolutionary concept, I know (and ironically something I learned in 2006 at LRW).
The teams winning on insights right now aren't spending more — they're spending smarter.”
Danny Russell, Chief Customer Officer, IDX, UK
“Three outdated research dimensions that are “winter-grade” and doing you no favours:
1. Long-form Tracking Surveys over 10 minutes long
2. Any research study that mentions anything about Generational Cohorts
3. Publishing anything that won’t illicit a behaviour change within the business
Instead, teams should cultivate three innovations to usher in a new insight “spring” of growth:
1. AI-assisted analysis that uncovers deeper patterns across existing datasets and research findings (you already have your customer’s Top 10 Pain Points)
2. Calculate the RORI (Return on Research Investment) for the last ten most expensive projects undertaken (cull the type of work that is adding the least)
3. Undertake an analysis of Stakeholder Decision Making, so you understand how decisions are actually made in your organisation (so you can influence more).”
Sharmila Das, Chairwoman, Purple Audacity, India
“Across boardrooms today, everyone speaks about insight renewal. Yet much of our industry is still working with tools designed for a slower marketplace. India makes this gap very visible. Consumers are changing faster than the systems meant to understand them. We are collecting more data than ever before, but clarity is not increasing at the same pace.
“Three things need clearing out. First, the belief that bigger datasets automatically produce better insight. Second, rigid silos between qualitative, quantitative and analytics when consumers live integrated lives. Third, research that arrives after the business instinct has already made the decision.
“What we must cultivate instead is equally clear: AI that accelerates pattern recognition but does not replace human judgement; continuous listening through communities and lived consumer contexts; and above all, researchers who can translate culture into decisions.
“The future will not belong to those who collect the most data, but to those who understand people most deeply.”
Priscilla McKinney, CEO, Little Bird Marketing, USA
“True insight renewal begins with an honest reflection about what is limiting your team. Three things teams should look for and toss include siloed research practices that keep findings trapped within individual teams rather than informing the broader organization; vendor relationships built on data delivery alone, where partners simply execute briefs rather than contribute strategic thinking; and retrospective-only measurement that tells us what happened but not what to do next.
It's no longer possible to gain or maintain a competitive advantage unless teams invest in cross-functional insight communities that embed researchers as genuine collaborators across marketing, product, and commercial teams. These are the real blockers to impact from insights. They should also demand more from their partners, expecting co-creation and rigor in the consultation. This is the start of powerful collaborations that produce big wins. Finally, integrating real-time and predictive intelligence tools allows organizations to move from seasonal snapshots to continuous, forward-looking understanding. Think windshield, not rearview mirror.
Tools alone won't get you to the podium. You need to reimagine how insights flow across every team and partnership.”
Melanie Courtright, Chief Strategy Officer, Sago, USA
“The defining goal for enterprises this year is decision velocity, the ability to move from insight to action with confidence and speed. To increase decision velocity, organizations need to be clear about three things: what to start doing, what to keep doing, and what to stop doing.
● “We need to start designing insight systems around iterative decision-making. That means clarifying the decision cycles upfront; integrating tools, AI, and process transformation to accelerate synthesis and pattern recognition; and ensuring humans remain accountable for judgment, context, and consequence.
● “We need to keep investing in trust and quality. That includes the quality of the inputs, the clarity of the outputs, and the transparency of how conclusions are reached. Speed only helps when people believe in what they are acting on.
● And we need to stop confusing more information with better decisions. Overcollection, unnecessary complexity, and insights without accountability slow organizations down. Decision velocity improves when insights are focused, trusted, and ready to use.
Our strategic priorities must align with decision velocity rooted in confidence.”
Wim Hamaekers, Co-Founder, One Inch Whale, Belgium
“Companies are indeed entering a season of 'insight renewal,' yet many still operate with research habits built for a very different environment.
● “First, organisations should clean out insights that are detached from strategy. Too often, research ends as reporting rather than shaping decisions.
In a world of increasing complexity, insights must sit at the core of strategic thinking and help organisations remain genuinely customer-centric.
● “Second, teams should move away from adopting new tech, AI or methods for their own sake. The industry sometimes treats tools as the innovation itself. Even briefings increasingly request “an AI method.” Technology should remain a means to an end: better understanding and better decisions.
● “Third, we should clean out shallow research. Whether it is superficial quant, purely declarative questioning, or light qualitative work that never reaches real depth, too much research today generates data without true understanding.
At the same time, companies should cultivate three capabilities.
● Strategic and critical thinking around data. As AI and data volumes grow, the real differentiator is the ability to interpret insights, think critically and translate them into business implications.
● Depth over speed and quantity. Faster tools are valuable, but depth of understanding should remain the priority. Smaller, high-quality samples and contextualised research often create more value than large but shallow datasets.
● Finally, organisations should invest in true brand–agency partnerships. As more insight tools move in-house, there is a growing temptation to treat research as a DIY function. Yet the real value often emerges when internal knowledge and external expertise are combined. Brands should work with agencies not merely as suppliers, but as strategic partners who challenge assumptions, bring an outside-in perspective, and help organisations see what they cannot from within.”
Chris Wilhelmi, Global Head of Data & Media, Monks, USA
Clean out:
1. Third-party data dependency. For years, teams layered purchased audience segments onto media plans as a proxy for precision. Between accelerating signal loss and the rise of AI-driven platform optimization - where algorithms learn in real time from native behavioral signals - these overlays aren't just outdated, they're often counterproductive.
2. Last-touch tunnel vision. Too many teams still anchor measurement to last-click attribution and surface-level delivery metrics. If your framework can't account for the interplay between touchpoints and tie back to business outcomes, you're optimizing toward a mirage.
3. Conflated data supply chains. When audience data, measurement, and media inventory all sit under one roof, objectivity becomes difficult to guarantee - regardless of intent. Teams should pressure-test whether their insights are independent or downstream of a commercial interest.
Cultivate:
1. Intelligence over activation data. Audience segments still have a critical role in guiding media planning and content strategy - the waste is in paying premium prices to activate against them when platforms already optimize natively. The real opportunity is an intelligence layer that marries top-down segmentation insight with bottom-up platform signals, letting each do what it does best.
2. Layered - then unified - measurement. No single methodology answers every question. Start by building from outcome-based KPIs, through cookieless cross-platform attribution, up to MMM and incrementality testing. But the layers are the foundation, not the finish line - the future is a holistic system that connects these inputs and delivers real-time, continuous-learning optimization rather than periodic backward-looking reports.
3. The convergence of media, creative, and data. The era of treating these as separate workstreams is over. In a privacy-first, algorithm-driven landscape, creative is targeting, data is strategy, and media is the research instrument. The teams driving growth are the ones organizing around outcomes, not channel silos.”
Laura Ruvalcaba, CEO, BRAIN & Esomar Representative, Mexico
“Spring is a good reminder that insight work also needs renewal. Today, the challenge is not the lack of information, but the excess of it. Teams are surrounded by dashboards, reports and data streams, yet real understanding often gets lost in the noise.
Three things I believe we need to clean out:
First, the obsession with collecting more data instead of extracting meaning.
Second, rigid research frameworks that assume we already know what the right questions are.
Third, the habit of rushing to conclusions, leaving little space for reflection.
And three things we should cultivate this season:
First, curiosity and openness: being willing to discover differences from what we expect.
Second, patience to interpret insights, not just generate them.
Third, combining AI-powered analysis with human judgment, where technology accelerates discovery, but people provide context and meaning.”
Oualid Benchama, Global Sr. Director, Shopper Digital & Innovation Insights,
The Coca-Cola Company USA
“The insight renewal challenge isn't a data problem — it's a stack problem. Tech-powered products can simulate market conditions, cultivate more robust predictive & prescriptive models & deploy sentiment & behavioral signal intelligence - in real time. Time to rethink the static methodologies (Quant & Qual), the disconnected data sources/lakes and lagged/delayed data flows. Replace them with research loops that enable better screening capabilities and faster quality-first flows that connect research to decision-making. Build the research engine your growth actually needs.”
Isabelle Fabry-Frémaux, Founder & Managing Director, ActFuture; ESOMAR Associate & WIRe France Representative, France
“Spring cleaning for insights teams: Many companies talk about 'insight renewal.” But renewal requires cleaning out the attic first. Too many research teams still operate with tools and habits built for yesterday’s questions.
Three things it may be time to throw out. First, “PowerPoint archaeology.” Reports that carefully document the past but rarely shape the future.
Second, methodology silos. The old qual-versus-quant mindset belongs to another era. Today’s insights emerge from ecosystems where behavioral data, AI pattern recognition, and human conversations intersect.
Third, research that arrives too late. If insights only appear once decisions are almost made, their power is already limited.
And three innovations worth cultivating.
First, AI as a curiosity engine – not to replace researchers, but to help them explore faster and ask smarter questions.
Second, living insights – dynamic knowledge systems that evolve with the business rather than static reports.
Third, co-creation with real people – involving consumers earlier to shape ideas, not just validate them.
Because the future of insights is not about producing more data.
It’s about creating understanding early enough to change what happens next.
Christian Dössel, Head of Innovation at Bonsai, Germany
“Everyone talks about insight renewal. But too often it just means running the same old research faster.
Real renewal starts by clearing out what no longer works.
● First, opinion mining is the belief that asking people what they think will reliably predict what they’ll do. It rarely does.
● Second, research is approval theater, where studies are commissioned not to learn, but to confirm decisions already made.
● Third, blind faith in AI outputs, assuming that faster pattern recognition automatically equals deeper insight.
What should grow instead?
● Start with behavioral evidence, not just attitudes. Observe decisions in real contexts.
● Build immersive testing environments where people actually choose (on shelves, in feeds, in moments of friction, …).
● And combine AI with human curiosity: algorithms surface patterns, but insight still requires judgment.
If insight renewal means anything, it means one thing: stop asking people what they might do; and start watching what they actually do.”
Mark Ursell, EVP, Largo, UK
Clean Out:
“Data tables, manual analysis and report production. So long as the data or project construction is designed well initially, fieldwork is conducted to high standards and data is checked using AI quality checks, there should be no need for manual analysis, producing data tables, or manually creating reports. AI can handle all this legwork, speeding up the time from insight to decision-maker.
Innovations to cultivate:
AI Simulated Twins (created from real people using a questionnaire) to speed up advertising development. Twins can significantly improve ideas before the final stage of testing with real humans. Secondly, AI tools to analyse and write reports to quickly improve successful decision-making. Thirdly, create online customer panels to ensure the customer drives decision-making.”
Arundati Dandapani, CEO and Founder, Generation1.ca, Canada
“Enterprises may be in a season of insight renewal, but too many are still dressed in winter-grade legacy gear: slow research design, fragmented dashboards, consumer/citizen blindness, and unguided AI. Growth now requires an insights strategy anchored in a clear, well-communicated AI governance playbook and a living map of the ecosystem: partners, platforms and the data flows shaping decisions. To maximize insight, teams must eliminate three blockers: siloed thinking that obscures context, resistance to technology that slows learning, and short-termism that trades signal for speed. In their place, they must embrace three innovations: governance-informed workflows that make trust repeatable, ecosystem intelligence that links data to value chains, and a builder mindset of cross-functional teams who prototype with machines, market test, and ship learnings often. In this collaborative age, builders win. They turn governance into velocity, ecosystems into advantage and research into a compounding engine for stronger partnerships and powerful data-driven outcomes.”
Dr. Roland Abold, Managing Director, infratest dimap, Germany
Enterprises and public organizations must retire siloed data, static trackers, and poor visualization. In market and public opinion research, progress comes from cultivating integrated analytics, adaptive AI‑supported methods, and real‑time visualization & insight systems. These innovations strengthen validity, accelerate learning, and provide clearer guidance in volatile environments.”
Mariela Mociulsky, CEO Trendsity, Argentina
“Organizations are entering a period of insight renewal. The challenge is no longer to generate more data, but to generate deeper cultural understanding and stronger anticipatory capability. This requires moving beyond some of the inertia of traditional research models and adopting new ways to observe, experiment and learn.
Three research dimensions to clean out
Episodic, reactive research. Moving from one-off studies that produce “snapshots” toward continuous learning systems about consumers and culture.
Overreliance on declarative data. Not limiting research to what people say, but integrating observation of real behaviors, contexts and decision-making.
Representativeness as the sole criterion of truth. Many signals of change emerge in niches and subcultures; early detection requires cultural exploration, not only large samples.
Three innovations to cultivate
Human-AI hybrid insight systems capable of reading culture and detecting emerging patterns.
Research is continuous experimentation, testing ideas in real-world contexts.
Synthetic consumers and simulation to explore scenarios and accelerate innovation before market launch.
Herbert Höckel, CEO, moweb research, Germany
“From my very subjective perspective, enterprises should treat today’s 'insight renewal' as a question of better decision-making, not more data. Three research dimensions to clean out are: siloed, backward-looking research, where customer, market, and sales insights remain disconnected; static, infrequent methods, such as annual surveys that cannot keep pace with volatile markets; and reporting overload, where dashboards multiply but actionable guidance does not.
In their place, companies should cultivate three innovations. First, continuous, connected insight systems that link customer feedback, market signals, and operational data. Second, predictive and scenario-based research that helps firms navigate uncertainty in regulation, geopolitics, and supply chains. Third, AI-enhanced but human-centered methods, combining faster pattern recognition with qualitative depth and real-world quantitative context.
In German terms, the goal is called "Entscheidungsfähigkeit"; research that is precise, practical and directly useful for steering sustainable growth.”
So, as you can clearly see, there are many insightful ways research and insight teams can clean out obsolete aspects and cultivate innovation in their methods. Keeping pace is always a challenge, but it allows us to push the boundaries to elevate our impact. It will be exciting to see where these advancements take us as we move ahead. Have a wonderful spring season.
ABOUT THE AUTHOR
Crispin Beale - Chief Executive, Insight250, Senior Strategic Advisor, mTab; Worldwide CEO, IDX
Crispin is a marketing, data, and customer experience expert. Crispin spent over a decade on the Executive Management Board of Chime Communications as CEO of leading brands such as Opinion Leader, Brand Democracy, Facts International, and Watermelon. Before this, Crispin held senior marketing and insight roles at BT, Royal Mail Group, and Dixons. Crispin originally qualified as a chartered accountant and moved into management consultancy with Coopers & Lybrand (PwC). Crispin has been a Fellow, Board Director (and Chairman) of the MRS for nearly 20 years and UK ESOMAR Representative for over 10 years. Crispin is currently a Senior Strategic Advisor at mTab as well as worldwide CEO at IDX.