Automation, interoperable ecosystems and synthetic data are shaping the future of ResTech
Editor’s note: Patrick Comer is CEO of Cint and founder of Restecher.
ResTech has undergone a rapid transformation over the past decade. What began as a niche layer within the broader marketing and insights landscape is now evolving into a foundational infrastructure for how businesses operate in a data-driven world. Today, brands and agencies rely on ResTech not only to understand their consumers, but to do so at the pace of real-time decision-making.
As industries across marketing, media, product development and beyond shift toward faster, more iterative workflows, the need for scalable, automated insights is rising. ResTech’s growth is directly tied to this demand. The stakes have changed: it's no longer enough to deliver high-quality data, we must now do it continuously, flexibly and with minimal friction.
This evolution isn't about creating the next shiny tool. It's about building infrastructure: platforms and systems that enable decision-making to happen as insights are generated. In the same way that cloud computing revolutionized software delivery, ResTech could redefine how research is embedded across an organization. That opportunity hinges on three key shifts: automation, interoperability and the emergence of synthetic data.
The rise of automation in research workflows
In nearly every industry, automation is now table stakes. From media buying to customer service, the pressure to reduce manual processes and increase output efficiency has reshaped entire functions. Research is no different. Yet, until recently, automation in research workflows has often been limited to surface-level efficiencies – automated survey delivery or templated reporting.
We are now seeing a deeper wave of automation. Platforms are beginning to offer fully automated project lifecycles, from sample sourcing to quota management to real-time dashboards, without requiring a human to manually intervene at each step. This enables a shift from reactive research to proactive, always-on intelligence. The benefits extend beyond speed. Automation reduces the room for human error, drives consistency in data collection and makes insights more repeatable and scalable. As the volume and velocity of decisions increase, this scalability becomes essential. The organizations that thrive will be those that can build research into their everyday operations, and automation is what makes that possible.
We should also consider how automation impacts talent. Rather than replacing researchers, it allows them to focus on higher-order thinking. Analysts and strategists can move beyond managing logistics to interpreting findings, identifying trends and advising internal stakeholders. In a sense, automation is elevating the role of insights professionals, not diminishing it. And automation isn't limited to execution. Increasingly, platforms are using machine learning models to recommend methodologies, suggest sample sizes or flag anomalies in data quality. These applications of AI are still developing, but they hint at a future where research becomes more predictive, intuitive and accessible across organizations.
What’s more, we’re seeing a rise in self-service tools that enable marketers, product managers and analysts to launch their own research projects without routing every request through a centralized insights team. This democratization of access is a direct result of automated workflows, and it’s redefining the scope and pace of research inside organizations.
Interoperability as the new competitive advantage
Another shift reshaping ResTech is the move toward interoperability. In today’s enterprise environment, no platform exists in a vacuum. Marketing teams work across CRM systems, media planning tools, customer data platforms and product analytics suites. ResTech must fit into this ecosystem, not operate as an island. This means APIs aren’t just nice-to-haves. They are the backbone of modern research platforms, allowing insights to be used in real time – not weeks later.
Interoperability also helps unify fragmented data systems. When platforms can "talk" to each other, researchers can stitch together behavioral, attitudinal and performance data into a single narrative. But there's work to be done. Many legacy systems still resist integration, and a lack of data standardization slows progress. Moving forward, platforms that embrace open architecture and prioritize ecosystem compatibility will gain an edge. This shift toward interoperability mirrors what we've seen in other enterprise software categories. From cloud storage to communication tools, the winners have been those prioritizing openness and extensibility. ResTech is now at that same juncture. Building solutions that can flexibly plug into the broader stack will be essential not just for functionality, but for survival.
Additionally, interoperability creates new opportunities for innovation across adjacent functions. As insights tools integrate more seamlessly with media activation platforms or product testing environments, researchers can move from being reactive observers to proactive contributors in shaping business outcomes.
The role of synthetic data in a privacy-conscious, real-time world
As the demand for rapid, real-time insights grows, so does the complexity of data privacy and compliance. At the same time, traditional sampling methods are being tested by shrinking response rates and rising costs. Recent studies indicate that average survey response rates have dropped to between 5% and 30%, while the global market research industry has seen spending exceed $90 billion, with a significant shift toward digital data collection methods. In response, synthetic data is emerging as a powerful tool. Synthetic data refers to computer-generated data sets that simulate real-world behavior without exposing actual consumer identities. This creates potential use cases to help fill gaps in traditional samples, model potential future behavior and reduce bias in hard-to-reach populations.
While a recent study (registration required) conducted by Cint surveying research and insights professionals showed only 12% of respondents have used synthetic data, there is much discussion across the industry around appetite for adoption. In markets where direct surveying is restricted or impractical, synthetic data can provide directional signals and when targeting niche audiences it can augment small sample sizes. But while the upside is clear, so are the trade-offs. Synthetic data must be transparently modeled, validated and interpreted with care. It can’t replace real human feedback; it can enhance it.
Looking forward, we may see hybrid models become more common – blending synthetic and traditional methodologies to achieve both scale and depth. The more ResTech enables this type of flexible design, the more valuable it becomes in navigating a fragmented consumer landscape. And as research teams look to scale globally, especially across regions like Southeast Asia or Latin America, synthetic models may offer a cost-effective way to localize insight gathering without full-scale operational overhead.
Investors seek scalable platforms
It’s not just the operational side of ResTech that’s changing, capital is moving, too. Investors are increasingly seeking scalable platforms that enable decision-making, not just data delivery. In a tighter economic climate, point solutions that solve one narrow pain point are struggling to win interest. What’s attracting capital now are systems that offer breadth, depth and long-term utility. This is a natural evolution. As the industry matures, the bar rises. Investors want to see not just growth but infrastructure-level thinking: How does this platform integrate into the broader business stack? Can it serve multiple functions? Does it offer operating leverage to its users?
What we’re seeing is a redefinition of what success looks like in ResTech. It's equally about innovation as it is about durability. Healthy growth means building platforms that teams rely on every day to understand, predict and adapt.
And as market conditions evolve, the ability to show measurable business impact, not just engagement metrics, will become central to ResTech’s value proposition. Platforms that can connect insight to action will be the ones that earn lasting investment. Increasingly, that includes demonstrating value not just at a project level, but through platform-wide ROI and workflow efficiency.
While the insights industry has historically been a lagger in technology investments, this is no longer going to be an option for companies that want to stay in the game. This will shape the next wave of merger and acquisition activity in two ways: larger platforms looking to absorb niche capabilities to offer more unified solutions to clients, and companies needing an influx of capital support building new technologies in-house. Entering this era of technological advancement in the ResTech industry brings with it a wealth of opportunity for business leaders and investors alike.
ResTech as the operating system of modern insights
Looking ahead, the companies that win in ResTech will be those that act less like tools and more like operating systems. The future isn’t about point solutions that solve for individual questions; it’s about connected environments that make insights accessible across the business. In this environment, research isn’t something that happens at the end of a planning cycle, it’s embedded from the start. Teams use real-time data to test ideas, validate decisions and optimize outcomes on the fly. ResTech becomes the layer that powers this new way of working. And that makes it one of the most important spaces in the modern enterprise stack. As AI, automation and privacy reshape how companies operate, ResTech can become the connective tissue between data and decision. But to do that, it must keep evolving – more interoperable, intelligent and integrated.
This also requires a cultural shift. Embedding research at every level of an organization demands trust in the data, alignment between teams and tools that make insights usable, not just accessible. ResTech will play a critical role in making that possible. Ultimately, the promise of ResTech is not simply faster research, it’s smarter decision-making at scale. It’s about giving organizations the confidence to act in uncertain environments because they’re equipped with a deeper, more connected understanding of the world around them. Data may be the world’s most valuable resource. But without the infrastructure to turn that data into action, it remains untapped.