Factworks GmbH

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Factworks is an award-winning international market research and analytics consultancy with a global presence spanning Berlin, Silicon Valley, and Bangalore. Our extensive industry expertise in technology and financial services, coupled with over 20 years of consulting experience, positions us as trusted partners to our clients, enabling them to make informed marketing and management decisions.
 
 
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Factworks is a leading international market research and analytics company with offices in Silicon Valley, Berlin, and Bangalore. 

Brand Image Tracking

Market Segmentation

Price & Pricing Research

As we look ahead to 2025, the market research landscape is buzzing with change. New technologies, especially AI, shifting consumer behaviors, and the increasing complexity of products are reshaping how we gather and apply insights. For researchers, this presents both a challenge and an exciting opportunity to adapt, evolve, and drive even more impactful results.
In this article, we&rsquo;ll dive into four key trends that are set to define the future of market research. Let&rsquo;s take a closer look at how you can stay ahead of the curve and ensure your research continues to deliver value in this fast-changing environment.
<h2 class="p1">1. Synthetic Data Is on Course to Revolutionize the Research Landscape</h2>
Synthetic data is the buzzword in market research right now, with the 2024 conference circuit and industry publications teeming with provocative statements like &ldquo;Are Surveys Dead?&rdquo; and &ldquo;Synthetic data is as good as real!&rdquo; Many believe 2025 will see synthetic respondents and responses take off. The excitement around this development is understandable given it offers potential solutions to many challenges impacting data quality in market research, such as data privacy concerns, the uptick in fraud, data scarcity, and survey fatigue.
By training AI on high-quality datasets, respondent behavior can be simulated, potentially providing a level of consistency often missing from traditional panels. In well-documented categories, synthetic respondents are already proving to be nearly as accurate as real ones. The <a href="https://www.greenbook.org/grit/grit-business-and-innovation-edition" target="_blank" rel="noopener">GRIT report</a> shows that research teams using synthetic data report high satisfaction, with 87% expressing positive feedback about its results.
We believe synthetic respondents likely already outperform poorly engaged respondents and will improve rapidly, particularly where comprehensive training data exists. Imagine the convenience of using expert synthetic respondents trained specifically to act as cardiologists or CFOs, making it that much easier and cheaper to gather insights from these hard-to-reach audiences.
You could also explore hypothetical scenarios and gather insights on sensitive topics &ldquo;real experts&rdquo; might be hesitant to discuss at great length. As the technology improves, we foresee synthetic data becoming an increasingly valuable resource for faster and perhaps even more reliable insights.
However, while these advancements are exciting, limitations remain. Synthetic data can replicate known patterns based on existing information but struggles in less-explored categories or predicting future preferences. As Axel Bichler, Founder of Factworks, points out:
<blockquote>
&ldquo;Synthetic data shines in areas with established trends and extensive datasets&mdash;for instance, analyzing US car brand perceptions of style, comfort, and price. But for novel product features or niche markets, synthetic data is still catching up. It&rsquo;s a promising tool, but we need to be cautious about relying on it just yet. It&rsquo;s still up to us researchers to critically evaluate and validate results.&rdquo;
</blockquote>
Moving forward, for now it&rsquo;s essential that <a href="https://www.greenbook.org/insights/data-science/is-now-the-time-for-synthetic-sample" target="_blank" rel="noopener">synthetic data</a> is viewed as a complement to, not a replacement for, traditional research methods. By combining synthetic and real respondent data, researchers can leverage the strengths of both approaches&mdash;using synthetic data to address challenges like survey fatigue and fraud, while still grounding insights in real-world behaviors and attitudes.
Incorporating synthetic data into your research approach should be done thoughtfully and critically. As the use of synthetic data becomes more prevalent, it will be crucial to engage with synthetic data providers to understand their data sources, the diversity of their training datasets, and how frequently they update their models. This ensures that synthetic insights remain aligned with current market realities and reflect the complexities of evolving consumer behaviors.
<h2 class="p1">2. Demonstrating ROI Is Becoming an Imperative for Researchers</h2>
Over the last year, we&rsquo;ve seen that demonstrating the return on investment (ROI) of market research is becoming an essential skill for research teams, and it will likely continue to be as important in 2025.&nbsp; As companies rely more on data to guide decisions, stakeholders&mdash;from heads of product and marketing to the C-suite&mdash;are more invested in research. Yet, these stakeholders are often not researchers themselves, and tighter budgets mean internal teams must justify their work's value and sometimes secure funding from other departments.
To gain support, researchers need to craft arguments that demonstrate ROI before the research project even begins. For example, this could mean showing how a price optimization study could reveal that increasing the product price by 5% could potentially generate an additional $10 million in annual revenue.
<blockquote>
&ldquo;Market research has always been about uncovering truths that drive better decisions, but in today&rsquo;s environment, it&rsquo;s equally about proving its worth in measurable terms," says Nadja B&ouml;hme, CEO of Factworks. "This means not only delivering insights but also connecting those insights to tangible business outcomes&mdash;whether that&rsquo;s increasing revenue, reducing costs, or improving customer retention. To ensure research projects get the backing they deserve, research teams must become experts in stakeholder alignment as well, fostering clear communication, trust, and shared objectives from the very beginning.&rdquo;
</blockquote>
Engaging stakeholders early through methods like stakeholder interviews aligns research goals with business priorities and builds enthusiasm. Providing progress updates, interim findings, and workshops keeps stakeholders engaged, ensuring insights are embraced and acted upon.
Another way to strengthen these efforts is by involving research suppliers and vendors from the outset. Their experience and ability to provide practical examples of similar studies and outcomes can significantly bolster the case for <a href="https://www.greenbook.org/insights/research-methodologies/reimagining-insight-communities-3-strategies-to-maximize-engagement-and-research-roi" target="_blank" rel="noopener">ROI</a> and increase the likelihood of securing the necessary support to move forward.
Ultimately, demonstrating ROI goes beyond making a strong case for funding&mdash;it&rsquo;s also about elevating the role of market research within the organization. By focusing on stakeholder alignment, financial impact, and collaboration, research teams can drive measurable value and solidify their position as strategic business partners.
<h2 class="p1">3. Research Must Be Tied to Tangible Business Outcomes</h2>
Alongside proving ROI, we find that it&rsquo;s becoming ever more common for stakeholders to ask for a clearer connection between research insights and measurable business outcomes as part of the research design. This shift reflects a growing demand for more actionable insights that go beyond consumer preferences or hypothetical scenarios.
Clients more than ever want to know how the research translates into real-world outcomes that drive business growth and impact their bottom line whether it&rsquo;s tweaking product features and design, changing prices, or launching a new marketing campaign.
Anchal Chhabra, Co-CEO of Factworks, shares:
<blockquote>
"Increasingly across segmentation studies we conduct, research buyers want more than just statistically sound segments&mdash;they want clear answers to critical questions: 'Whom should we target, and why? How valuable is each segment? What is the opportunity cost of prioritizing one segment over the other? How many customers can we win, and how much revenue will they generate?'&rdquo;
</blockquote>
To meet these demands, research teams must plan from the beginning to connect their studies to business outcomes. By establishing these connections early, studies can be designed to deliver business-relevant insights. Additionally, integrating analytics, customer data, and market performance metrics into traditional research provides a more accurate view of how different strategic actions will play out.
For instance, in segmentation studies, connecting segments to a client's media targeting can make the research highly actionable. Recently we had a client utilize the link between their Data Management Platform and one of our panel providers, enabling us to directly flag segments within their DMP. This allowed the client to target those segments with greater precision in future marketing campaigns.
<h2 class="p1">4. Rising Product Complexity Demands Custom Research Design</h2>
The digital product landscape is more intricate than ever. Take for instance the rise of SaaS products and the growing subscription economy. Typically these already feature tiered pricing structures&mdash;some even employ hybrid models that blend usage-based fees with monthly subscriptions. Streaming services are now introducing ad-supported plans, and dynamic pricing, once limited to e-hailing services and concert tickets, may soon expand beyond these categories.
Willingness to pay can vary significantly across <a href="https://www.greenbook.org/insights/researc-technology-restech/the-evolution-of-b2c-consumer-segmentation-in-the-digital-age" target="_blank" rel="noopener">consumer segments</a>, driving businesses to experiment with diverse pricing strategies to optimize revenue. All this increasing complexity shows us that standardized, cookie-cutter approaches to product and pricing research simply don&rsquo;t cut it anymore (if they ever did).
Understanding preferences now requires tailored approaches. Fortunately, methods like conjoint analysis, the gold standard of product and pricing research, have the flexibility needed to adapt. Conjoint research can be customized to handle these complex demands, allowing you to simulate customer preferences across a wide array of features, bundles, and pricing strategies. Our experience in the fintech sector, where digital products often combine subscription fees, usage-based charges, and other variable pricing models, underscores the need for adaptability.
To aid respondents with making realistic decisions concerning these complex products, Alex Wendland, Conjoint Expert at Factworks suggests:
<blockquote>
&ldquo;You should try to mimic real-world decision-making environments as much as possible. For instance, if you&rsquo;re testing a new product, you can use dynamic, visually interactive elements in your survey that mirror real user experiences and how they would actually compare options online. In addition, you can use visually rich stimuli for new, conceptual products that immerse respondents in future scenarios.&rdquo;
</blockquote>
In addition to the complexity of the products themselves, increasingly nuanced research questions are being asked. This shift has led to an increased demand for mixed-methods research, with a renewed emphasis on qualitative insights. Beyond price sensitivity, research stakeholders want to understand the broader impact of their product features such as how ad-supported tiers might influence brand perception or how different feature sets affect overall user experience. Ultimately, the rising complexity of digital products means the research designs of the future will need to be more responsive, immersive, and tailored.
<h2 class="p1">Conclusion</h2>
In 2025, market research will be marked by an increasing demand for ROI-driven, actionable insights that directly inform business outcomes. Synthetic data will have a significant impact on data collection, while customized research designs will be essential to understanding the growing complexity of modern products and pricing strategies.
By embracing these trends, researchers can position themselves as vital contributors to their organizations' success, ensuring that research continues to drive strategic decision-making and business growth. The ability to navigate these trends and harness new technologies will set strong research teams apart, ensuring that their work is both relevant and indispensable in a rapidly evolving market landscape.

Explore 2025 market research trends: synthetic data, ROI focus, and custom research designs to tackle product complexity and thrive in a changing landscape.

4 Trends Shaping Market Research in 2025

Have you ever felt like you're shouting your message into a crowded room, hoping it resonates with someone... anyone? Consider this: not all customers are the same. This broad brush approach to marketing might have worked in simpler times, but today's consumers crave personalization. This is but one of many reasons why strategic segmentation studies have become so popular in recent years.
At its core, <a href="https://www.greenbook.org/market-research-firms/segmentation" target="_blank" rel="noopener">market segmentation</a> is the practice of dividing your target audience into distinct targetable groups. By segmenting based on attitudes, needs, and behavior, you gain a deeper understanding of your customer base. And with this better understanding, comes a multitude of business benefits.
Studies back the power of segmentation. According to<a href="https://www.mckinsey.com/capabilities/quantumblack/our-insights/capturing-value-from-your-customer-data?roistat_visit=6704328%23/"> McKinsey &amp; Co.</a>, companies leveraging customer behavioral insights outperform peers in sales growth (by a staggering 85%) and gross margin (over 25%).
<a href="https://www.bain.com/insights/find-your-sweet-spot/">Bain &amp; Company</a> adds to this by reporting that 81% of executives view segmentation as crucial for profit growth. However, the same survey exposes a critical gap &ndash; less than 25% believe their companies are using it effectively. A clear disconnect exists between recognizing the value and achieving successful implementation.
It&rsquo;s true: A robust successful segmentation resulting in stable segments that are homogeneous within and distinct from one another is certainly not a walk in the park. As method experts in the field, we conduct several strategic segmentations in a year and with this experience, we can pinpoint what makes the practice truly successful. In this article, we detail our 5 factors that make for a successful segmentation and the pitfalls to avoid.
<h2 class="p2">1. Understanding the Objectives of the Segmentation is Key</h2>
Just like with consumers, a one-size-fits-all approach simply doesn&rsquo;t work with segmentation. Before we can dive in, we have to know the exact purpose of the segmentation. Are you informing product teams about what features should be developed? Should the segmentation provide insight into brand positioning to aid direct marketing? Or should it help with growth and targeting specific customer segments?
In addition, we have to think about the segmentation units. Do we want to do a people-based segmentation, an occasion-based segmentation, or perhaps combine them into a demand landscape? One can clearly see how these questions can take the segmentation down several different directions, so the answers to them must be followed to guide the research and survey design.
<h2 class="p2">2. Continuous stakeholder engagement is crucial</h2>
A segmentation study serves multiple stakeholders within an organization, each with distinct expectations and goals for the research. To ensure the study fulfills its intended purpose and is actionable, continuous engagement with stakeholders is essential.
That&rsquo;s why we prioritize integrating them into the research team from the onset. The first step is setting up interviews with key stakeholders right at the beginning of the project and developing clear hypotheses so that these insights can be incorporated into the research design.
By doing so, you enable stakeholders to articulate their specific research needs, thereby ensuring that the study aligns with their objectives. Moreover, every decision throughout the research process can then be guided by the intended use and the needs of end users of the segmentation.
The best practice would be to have various touch-points including workshops with stakeholders throughout the process.
We know the report is not the end of the road. The immersion phase with external stakeholders is equally important, but more on that in the fifth point.
<h2 class="p2">3. As with Everything: Less is More, Especially When it Comes to Input Vectors</h2>
One might say that the more variables you include in your segmentation the better, as it presumably sets up your segments to be more nuanced and really stick out from one another, but the discerning researcher would advise otherwise.
The reason is that the more input vectors you include, the less the differences between them will be, making it more difficult for product and marketing teams to create effective interventions. Rather, the input vectors that should be prioritized are precisely the ones that will have the most meaningful impact on those teams.
This highlights the importance of synthesizing existing knowledge from stakeholders and developing clear hypotheses from them prior to conducting the research. By doing so, you ensure that the most valuable input vectors are identified and used, reinforcing the idea that less is more.
<h2 class="p2">4. Use Segmentation-Friendly Survey Question Formats</h2>
Do not incorporate rating scales in your segmentation surveys. We repeat, don&rsquo;t. One of the reasons is that many studies including those by&nbsp;<a href="https://psycnet.apa.org/record/2006-09757-006">Harzing (2006)</a>, <a href="https://ro.uow.edu.au/commpapers/251/">Dolnicar and Gr&uuml;n (2007)</a>, and <a href="https://academic.oup.com/poq/article/79/S1/325/2460990">Yu &amp; Yang (2015</a>), have shown that there are inherent cultural differences in the way people use rating scales. To quote from Harzing&rsquo;s study:
<blockquote>
&ldquo;Country-level characteristics such as power distance, collectivism, uncertainty avoidance and extraversion all have a positive influence on response styles such as acquiescence (likelihood to agree with something) and (positive) extreme response styles. [...] Respondents from Spanish-speaking countries show higher extreme responses and acquiescence while Japanese and Chinese respondents tend to be far less extreme in their response styles.&rdquo;
</blockquote>
Instead, ask respondents to rank their preferences or to complete a tradeoff exercise, like MaxDiff or SemDiff. In addition, we also recommend not using multi-select questions on their own, instead asking respondents to pick up to X items or combine multi-selects with pick-up-to-X-items questions.
When writing the survey questions keep the overall goal in mind. You want variables that are as differentiating on meaning inputs as possible, while minimizing the influence of response style and cultural bias.
Also, remember to keep it simple. You want to include simple questions that are easy to follow up on at a later stage.
<h2 class="p2">5. Make the Segment Results Accessible and Understandable</h2>
In our experience, one of the main reasons why executives may believe that their companies are not using segmentations effectively is because the insights are not readily available across the organization in actionable ways. Experienced researchers are aware of this and will spend a great deal of effort ensuring that stakeholders of segmentation research have access to insights in ways that let them see beyond the numbers and statistics.
Traditional methods of immersing an organization in segmentation results include persona development, town hall meetings, team workshops, posters distilling segment insights, or other printed or digital material like short videos, but what if you can take that one step further?
Recently, we&rsquo;ve been experimenting with training custom GPTs with segmentation insights to aid in this regard and presented this research at several conferences. Imagine, being able to interact with a persona chatbot that can step into the shoes of your segments and provide all your answers to your burning segment questions instead of turning to detailed reports.
Though we found that custom personas <a href="https://www.greenbook.org/insights/the-prompt-ai/chatbot-and-virtual-assistants-research-partners-that-work-247-and-never-get-tired" target="_blank" rel="noopener">chatbots</a> are not quite able to reproduce answers with 100% accuracy, even when trained on segmentation data, watch this space. These limitations may soon be of the past as the technology rapidly develops.
Segmentation market research studies may be challenging to pull off successfully, but the potential benefits it poses for businesses are immense. In our experience, these five tips have proved well in ensuring success for us and our clients.

Master market segmentation with 5 key factors for success. Avoid common pitfalls and unlock the full potential of strategic insights for confident decision-making.

Five Tips For Market Segmentation Success

Factworks is a leading international market research and analytics company with
offices in Silicon Valley, Berlin, and Bangalore. Redwood City, California, United States of America.

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