Research software is growing. What should insights teams expect from their investment?

Esomar's latest industry report highlights the continued growth of research technology. For insights teams, that raises important questions about how software performs in practice and the value it delivers over time.

Research software continues to account for a growing share of the global insights industry, according to Esomar's newly released Global Market Research 2026 report. The industry reached an estimated $164.5 billion in turnover in 2025, with research software accounting for 42% of the total.

The report examines the industry's performance and the changing role of technology, including the influence of AI. Its findings reflect a market in which software is an increasingly significant part of how research is delivered and used.

At Infotools, we're particularly interested in what this means for the organizations investing in research technology. As software capabilities expand, insights teams have more options for managing data, conducting analysis and delivering findings to stakeholders. They also face more complicated decisions about which platforms will meet their needs over the long term.

The real test comes after implementation

Research software can make a strong impression during a demonstration. A platform processes a dataset, generates a visualization or answers a question using AI, often in seconds.

The experience of using that software within an established research program can be quite different.

Consider a multinational brand tracking study that has been running for several years. The questionnaire has changed, markets have been added and the organization has introduced new reporting requirements. Different stakeholders need access to different views of the data, while researchers must maintain consistency in how results are calculated and compared.

A technology investment needs to accommodate all of this. It also needs to remain useful as the research program changes.

These requirements can be difficult to assess during the purchasing process, particularly when attention is focused on the newest features. Understanding how a platform handles complex datasets, ongoing changes and existing workflows deserves just as much consideration.

AI is changing expectations of research software

The rapid introduction of AI capabilities has added another layer to technology evaluations.

Natural language interfaces can make research data more approachable. A stakeholder who might previously have requested a new report can potentially ask a question directly, explore a particular audience or investigate a change in results.

This creates opportunities for insights teams to support more people across their organizations. It also makes the underlying analytical capabilities of the software particularly important.

Research data carries requirements that aren't always apparent to someone asking a question. Weighting, significance testing, sample sizes, filters and questionnaire changes all affect how results should be interpreted.

For example, a stakeholder might ask an AI tool why brand consideration declined in a particular market. Answering that question responsibly may require looking at several waves of tracking data, examining specific audience segments and determining whether an apparent change is statistically meaningful.

Researchers need to understand how the software arrives at its answers and be able to investigate the underlying results.

At Infotools, this has informed our approach to AI capabilities within Harmoni. ChatHarmoni provides another way to interact with research data, supported by the analytical functionality of the broader platform. We see considerable potential in making research easier to explore while preserving the methods and controls researchers depend on.

The people using the software have different needs

Technology decisions also need to account for the different people involved in research. An experienced analyst may need detailed control over data preparation, statistical analysis and reporting. An insights manager may be focused on identifying changes across markets or tracking performance against business objectives. A marketing stakeholder may simply want to understand how a particular customer group is responding to a campaign. These users have different levels of technical knowledge and different expectations of the software.

Providing broader access to research can be valuable, but organizations need to consider how that access will be managed. Which questions can stakeholders investigate independently? When is specialist analysis required? How will teams maintain consistent definitions and calculations across reports?

The answers will vary by organization and research program. Software should give insights teams the flexibility to establish an approach that works for their business.

Looking beyond the feature list

Esomar's latest report provides a useful indication of the industry's continued investment in technology. The growth of research software also makes the process of evaluating that technology increasingly consequential.

For insights teams, several considerations deserve attention: how well a platform handles real research complexity, how easily it fits into existing processes, what controls it provides over analysis and how it supports different users.

There are also practical questions about implementation, training, ongoing support and the work required to accommodate changes in research programs.

These factors can have a substantial effect on the return organizations receive from their software investments, particularly when platforms are expected to support research over many years.

As the range of available technology continues to expand, insights teams have good reason to examine these questions closely. The strongest software investments will be those that continue to serve researchers and their stakeholders long after the initial implementation.

Source: Esomar, Global Market Research 2026.