A research recommendation is a clear, evidence-based proposal for what an organization should do next based on research findings. In market research, it translates data, insights and interpretation into business decisions, often forming the core of an actionable research recommendation report.
Its value depends not on the volume of analysis, but on the strength of the link between evidence, decision context, feasibility and expected business impact.
What is a research recommendation?
A research recommendation is a practical conclusion derived from research evidence that indicates a preferred course of action, decision or change. It is not merely a summary of findings. It is the step that connects what has been learned from respondents, customers, users, stakeholders or market data with what should be done by a company, brand, product team or institution.
In market research, research recommendations are typically based on quantitative studies, qualitative studies or mixed-methods projects. In quantitative research, they may be derived from survey results, segmentation, tracking data, driver analysis, concept testing, pricing research or customer satisfaction measurement. In qualitative research, they may emerge from interviews, focus groups, ethnography, diary studies, usability sessions or expert interviews. In mixed-methods research, recommendations often combine the scale and comparability of quantitative data with the explanatory depth of qualitative insight.
A research recommendation should be specific enough to guide action, but cautious enough to reflect the limits of the evidence. It should distinguish between what the data clearly supports, what is a reasonable interpretation and what remains uncertain. This distinction is essential in B2B and B2C market research, where decisions may concern brand positioning, product development, customer experience, communication strategy, channel management or market entry.
A well-formulated research recommendation usually includes four elements:
- Evidence – the finding, pattern or insight on which the recommendation is based.
- Interpretation – the explanation of why the finding matters for the business question.
- Action – the proposed decision, change, test or next step.
- Condition – the relevant limitation, assumption, target group or implementation context.
For this reason, a research recommendation is different from an observation. An observation may state that younger customers perceive a product as expensive. A recommendation indicates what should be done with this knowledge, for example whether to adjust communication, test a value-based message, review packaging architecture or examine price sensitivity in a follow-up study.
Application of research recommendation in practice
A research recommendation is used whenever research is intended to support decisions rather than only describe a market, audience or behavior. It is most useful at the point where decision-makers need to choose between alternatives, reduce uncertainty or prioritize actions.
In practice, research recommendations are used by marketing managers, product managers, customer experience teams, sales teams, innovation teams, brand managers, analysts and senior management. They are also used by research agencies and internal insights departments to make research outputs understandable and usable for non-research stakeholders.
Typical applications include:
- Brand and communication research – recommending which message, benefit or positioning route should be developed further based on audience response.
- Concept and product testing – indicating which product concepts merit refinement, rejection, additional testing or launch preparation.
- Customer experience research – identifying which touchpoints should be improved first because they are most strongly connected with dissatisfaction, churn risk or unmet expectations.
- Segmentation studies – recommending which segments should be prioritized for targeting, product adaptation or communication planning.
- Pricing and value research – suggesting whether pricing should be tested further, repositioned or supported by clearer value communication.
- B2B market research – recommending how to adapt sales arguments, onboarding materials, service models or account management processes to different decision-maker groups.
An actionable research recommendation report is especially important when research findings must be translated into decisions across teams. Such a report does not only present charts, transcripts or analytical outputs. It organizes evidence around business questions and makes clear which actions are supported by the data. In projects conducted by Hume’s Institute, this logic is particularly relevant when quantitative results and qualitative explanations need to be integrated into one decision-oriented narrative.
The practical value of a research recommendation also depends on timing. A recommendation delivered after a decision window has closed may have limited business usefulness, even if it is methodologically sound. Therefore, research recommendations should be aligned with the decision calendar, stakeholder responsibilities and the level of risk associated with the decision.
Research recommendation and related methods
A research recommendation belongs to the final interpretive layer of the research process. It is connected with research objectives, hypotheses, findings, insights, conclusions and implications, but it is not identical with any of them.
The distinction can be described as follows:
- Research objective defines what the study is intended to learn.
- Finding describes what the data shows.
- Insight explains why the finding matters and what underlying mechanism may be present.
- Conclusion synthesizes the meaning of several findings.
- Implication indicates what the conclusion may mean for the organization.
- Research recommendation proposes what should be done next.
Research recommendations are closely linked with data triangulation, because stronger recommendations often result from combining several sources of evidence. For example, survey data may show that a feature is important, while interviews may explain why users value it and usability testing may reveal how the feature should be presented. A recommendation based on these combined sources is usually more robust than one derived from a single metric or isolated quote.
A research recommendation also differs from a business strategy recommendation. In market research, the recommendation should remain anchored in empirical evidence and the defined research scope. It may inform strategy, but it should not overreach beyond what the study can reasonably support. For example, a study of customer preferences can recommend which communication claims to test or emphasize, but it should not independently define a full market expansion strategy unless the research design covered the necessary market, financial and operational dimensions.
Related tools include executive summaries, insight statements, decision matrices, prioritization frameworks, personas, journey maps, dashboards and research debriefs. These tools can support a research recommendation by making evidence easier to interpret and act upon. However, they do not replace the need for a clear recommendation that states the proposed action and the evidence behind it.
How to write actionable recommendations in a research report?
The question of how to write actionable recommendations in a research report is central to the usefulness of market research. An actionable recommendation should be concrete, evidence-based, decision-oriented and realistic for the organization that will use it.
A strong research recommendation should meet several practical criteria:
- Start from the decision – relate the recommendation to the business question that initiated the research.
- Use direct evidence – refer to the relevant finding, pattern, segment difference, respondent need or behavioral signal.
- Specify the action – avoid vague wording such as “improve the offer” unless the specific improvement is described.
- Define the target – indicate whether the recommendation applies to all customers, a segment, a channel, a product line or a decision stage.
- State the rationale – explain why the action follows from the evidence.
- Clarify uncertainty – show where further testing, validation or monitoring is needed.
- Prioritize – distinguish high-impact recommendations from secondary or exploratory actions.
In an actionable research recommendation report, wording should be precise. Instead of writing “Customers are not satisfied with the onboarding process,” a more useful recommendation would be: “Redesign the onboarding email sequence for new users, because qualitative interviews indicate confusion after registration and survey responses show weaker evaluations of first-use guidance than of later service stages.”
Good recommendations should also avoid presenting personal opinion as evidence. They should make visible the chain of reasoning from data to action. This is particularly important in mixed-methods research, where qualitative evidence explains meanings and motivations, while quantitative evidence helps assess prevalence, scale or differences between groups.
A research recommendation is therefore the decision-facing output of research. It is strongest when it is based on a transparent method, connected to a specific business question and written in a form that enables managers, marketers, analysts and researchers to act without losing sight of the evidence.