Who needs Message Prioritization?

Message Prioritization is for teams that have several possible messages and need to decide which ones should lead their communication strategy.

It is useful for brand strategists, campaign planners, brief writers, product marketers, and growth teams who are working with multiple value propositions, benefit claims, positioning statements, or campaign territories. When several messages appear relevant, Message Prioritization helps identify which ones the selected audience responds to most strongly.

Use Message Prioritization when you need to answer questions such as: Which message should lead the campaign? Which claim should appear in the hero position? Which value proposition is most credible? Which supporting messages strengthen the overall narrative? Does the message hierarchy remain the same across different audience groups?

Message Prioritization is designed for comparative decisions. It is not intended to judge a single message in isolation. Its purpose is to evaluate a set of messages together and help you understand which message should lead, which messages can support it, and which messages are less effective for the selected audience.

What is Message Prioritization?

Message Prioritization is a quantitative research study within consumr.ai’s Concept Testing module. It evaluates how a defined audience responds to a set of written messages before those messages are developed into final creative or placed into market.

Message Prioritization is one of three Concept Testing study types on consumr.ai. Creative Testing evaluates ads, packaging, landing pages, and other creative executions. Product Testing evaluates product concepts and feature directions. Message Prioritization evaluates written claims, value propositions, positioning statements, and communication territories.

Message Prioritization is different from testing a finished advertisement. At this stage, the input is the message itself. The study helps determine which idea deserves to lead the communication strategy before final creative decisions are made. A message can be a value proposition, a product benefit, a positioning statement, a campaign territory, a proof point, or a customer facing claim. The closer the message is to the way it may eventually appear in market, the more useful the response will be.

What does Message Prioritization evaluate?

Message Prioritization accepts between 2 and 5 written messages in a single study. These messages are evaluated against the same selected audience and under the same study conditions. Each message is scored across three dimensions:

Clarity

Clarity shows how easily the audience understands the message. A message may contain an important benefit but still perform poorly if the language is difficult to interpret or if the promise is unclear. Use the Clarity score to identify whether the message is simple enough to carry into communication without unnecessary explanation.

Resonance

Resonance shows how strongly the message connects with the audience. It indicates whether the message feels relevant, meaningful, or personally important to the Respondents in the selected cohort. Use the Resonance score to understand which message has the strongest potential to attract attention and create audience relevance.

Believability

Believability shows whether the audience finds the claim credible. A message may be interesting or emotionally relevant but still perform weakly if the audience does not trust the promise being made. Use the Believability score to identify which messages feel credible enough to support the communication strategy.

These dimensions should be read together. A clear message that does not resonate may be easy to understand but not meaningful enough to lead. A resonant message that is not believable may create interest but weaken confidence. A believable message that is not clear may need rewriting before it can be used effectively.

What does a Message Prioritization study produce?

Message Prioritization returns a comparative view of the messages included in the study. The result is designed to help teams move from a list of possible claims to a usable message hierarchy.

Message Hierarchy

Message Hierarchy is the central output of the study. It ranks the tested messages based on how the selected audience responded to them. Use the highest ranked message as a lead candidate for the campaign brief, product page, launch narrative, or communication architecture. Review the remaining messages to identify which ones can support the lead message and which ones may not be strong enough to carry into execution.

A ranking should always be read in context. A message that ranks first has performed better than the other messages included in that study. It does not automatically mean that no stronger message could exist outside the set tested.

Clarity Scores

Clarity Scores show how easily each message is understood by the selected audience. Use these scores to identify messages that may need simpler wording before they are used in market. If a message has strong strategic value but performs weakly on clarity, the issue may be expression rather than the underlying idea.

Resonance Scores

Resonance Scores show how strongly each message connects with the selected audience. Use these scores to identify which messages are more likely to feel relevant and motivating to the audience. A message with strong resonance may be a useful lead candidate, especially when it also performs well on believability.

Believability Scores

Believability Scores show whether the audience finds each message credible.

Use these scores to identify claims that may require stronger proof, more precise language, or a different role in the message hierarchy. A message that is believable but less resonant may work as supporting evidence rather than as the lead communication idea.

Message Architecture

Message Architecture helps show how the messages relate to one another. It can identify which messages are performing similar roles, which messages stand apart, and how a broader narrative may be structured from the results.

Use Message Architecture when the objective is not simply to select one winning message, but to build a layered communication structure. For example, one message may lead because it has the strongest resonance, while another may support it because it provides credibility or functional proof.

Demographic Breakdown

Demographic Breakdown shows how responses to each message vary by Age Range, Gender, Income Bracket, or Lifecycle Stage.

Use this view when a message performs strongly overall but you need to know whether the result is broad or driven by a specific audience group. A message that leads among one high value audience slice may require a targeted execution rather than a universal lead role.

Filters

The filters at the top of the results page allow you to review how the hierarchy changes within selected demographic groups without rerunning the study.

Use the filters to understand whether the lead message remains strong across the audience or whether different groups respond to different messages.

Full Dataset

The Full Dataset option allows you to download the underlying counts from the results page.

Use this when you need to analyze the results outside consumr.ai, include the data in a report, or share the detailed output with another team.

See Trace

Each surveyed question on the results dashboard includes the See Trace feature. See Trace helps you inspect the intelligence layer supporting the response shown in the results.

When you click See Trace, the Question Trace side panel opens. This panel helps you understand the consumer variables and supporting context associated with the response pattern.

The trace view includes three layers:

Citations show the audience variables or context connected to the result. These may relate to audience traits, familiarity with the topic, or relevant behavioral and conversational signals.

Confidence Scores indicate how strongly each cited signal contributes to the response interpretation presented in the trace view.

Drill Down allows you to explore the supporting sentiment and decision context in greater detail.

Use See Trace when you need to audit the basis of a result or better understand the signals connected to a message score. It is intended to make the output easier to inspect and interpret, not to replace additional qualitative research where deeper reasoning is required.

What a Message Prioritization study will not tell you

Message Prioritization evaluates written messages without visual treatment, layout, channel context, or final creative execution.

A message that performs strongly in this study may perform differently once it appears inside a finished advertisement, landing page, video, email, or social post. Visual design, placement, format, offer framing, and media environment can all influence how the final communication performs.

If the communication depends heavily on an image, video, layout, or full advertising treatment, use Creative Testing to evaluate the message within that complete creative context.

Message Prioritization also does not fully explain why one message performs better than another. It shows the hierarchy, the scores, the demographic patterns, and the supporting trace information available in the dashboard. When the team needs deeper reasoning behind a result, use a qualitative study against the same or a related AI Twin.

Why Message Prioritization matters

Many briefs contain more messages than a campaign can realistically lead with. A product may have several benefits. A brand may have several possible promises. A strategy team may have multiple positioning lines that all appear credible internally.

Without testing, these messages are often ranked through stakeholder opinion. The message that becomes the headline may be the one preferred by the most senior person in the room, the one that sounds most polished, or the one that has been used before. None of these reasons confirm that it is the message the audience responds to most strongly.

Message Prioritization gives teams a structured way to make that decision. Instead of choosing a lead claim only through internal discussion, teams can see how the selected audience responds across clarity, resonance, and believability.

This allows the brief to become more precise. A team can identify the strongest lead candidate, understand which messages should support it, see where credibility is stronger or weaker, and check whether the hierarchy changes across audience groups.

How Message Prioritization Respondents work

Message Prioritization on consumr.ai is answered by Respondents generated from the selected AI Twin or Segment.

For a clear understanding, these Respondents can be understood as smaller respondent units derived from the selected audience foundation and designed to answer structured quantitative questions. The selected AI Twin or Segment determines whose response to the message set is being evaluated.

The study does not rely on recruited survey panelists. The Respondents are generated from the selected audience foundation and aligned to the demographic filters configured during setup.

For a complete explanation of how Respondents are created and weighted across quantitative research studies, see the Respondent Creation Guide or the Concept Testing guide.

Message Prioritization inputs on consumr.ai

Message Prioritization has a focused setup because the study evaluates written messages rather than complete creative assets or product concepts.

Messages

Enter between 2 and 5 messages in a single study. Each message should be written in customer facing language and should represent a distinct claim, value proposition, positioning line, or communication idea.

Keep the messages comparable. If one message is polished and concise while another is written as an internal note, the quality of the wording may affect the result independently of the strength of the underlying idea.

Text only input

Message Prioritization evaluates the written message itself. There is no image upload field in this study.

Use this study when you need to understand the relative strength of messages before creative execution. If the visual expression is essential to how the message is meant to land, use Creative Testing instead.

Recommend

The Recommend option appears in the setup screen and can suggest messages based on the selected Segment and portfolio category.

Use Recommend when you need a starting point, when you want to compare your drafted messages against platform suggestions, or when the message set is still being developed.

[Image Placeholder 2: Message Prioritization setup screen]

Add the screenshot of the Message Prioritization setup screen showing the written message input area and the Recommend option.

When to use Message Prioritization

• Use Message Prioritization when you need to rank value propositions before preparing a campaign or communication brief.

• Use it when you need to identify which product benefit should lead a launch narrative.

• Use it when you need to compare positioning statements or communication territories for the same audience.

• Use it when you need to decide which headline idea should lead and which messages should act as supporting proof.

• Use it when you need to understand whether the same message hierarchy holds across audience groups.

• Use it before developing final creative when the main decision is about what the communication should say.

When not to use Message Prioritization

• Do not use Message Prioritization to evaluate finished ads, packaging designs, landing pages, images, or videos. Use Creative Testing when the full creative execution matters.

• Do not use it to evaluate product concepts, product features, new SKUs, or product directions. Use Product Testing for those decisions.

• Do not use it to measure brand awareness, consideration, preference, loyalty, or brand health over time. Use Brand Track for those questions.

• Do not use it when the primary need is to understand the deeper reasoning behind a message response. Use qualitative research when you need to explore the why.

How consumr.ai’s Message Prioritization differs

Traditional message testing and its limits

Traditional message testing is often conducted through recruited survey panels. Some studies use comparative methods such as MaxDiff, while others use structured message scoring or ranking methods.

These approaches can be useful, but they often require panel recruitment, survey fieldwork, analysis, and reporting. This can make it difficult to test message hierarchies at the speed at which individual briefs and campaigns are developed.

Internal decision making creates another limitation. Teams may select a lead message through stakeholder agreement without a structured audience read. This may be fast, but it can result in communication priorities shaped more by internal preference than audience response.

consumr.ai’s approach

Message Prioritization on consumr.ai evaluates written messages through Respondents generated from the selected AI Twin or Segment.

The test can be run when the brief is being developed, allowing the team to compare messages before they are committed to final creative. The output includes the hierarchy, scorecard results, demographic patterns, Message Architecture, filters, Full Dataset access, and See Trace capability.

Because the same audience foundation can be used across other consumr.ai studies, Message Prioritization can be part of a connected research process. A team can prioritize messages, test the resulting creative, run Brand Track over time, study media behavior, or conduct qualitative research to understand the reasoning behind a result.

Limitations

Text is tested without final creative context

Message Prioritization evaluates written claims without images, layout, channel placement, motion, sound, or final advertising execution. A message that performs well in text may behave differently once it appears in a complete creative asset.

Use Creative Testing when the decision depends on the message and visual treatment working together.

Wording quality influences performance

The study evaluates messages as written. Two messages expressing similar ideas can perform differently if one is clearer, shorter, or more credible in its wording.

Keep the polish level consistent across the messages being compared. If a strategically important message performs weakly on clarity, consider refining its wording before deciding whether to remove it from the communication strategy.

Rankings are relative to the messages tested

The hierarchy identifies which messages performed best within the set included in the study. A message ranking first does not automatically mean it is the strongest possible message for the audience.

If all messages perform weakly or appear closely grouped, the team may need to improve the message set rather than simply select the highest ranked option.

Message Prioritization measures response, not full reasoning

The results show how messages perform and how the hierarchy changes across audience groups. See Trace can help users inspect the supporting intelligence layer connected to a result. However, the study does not replace deeper qualitative exploration when the team needs to understand why a particular message works or fails.

Use qualitative research when the reasoning behind the result is required for the next decision.

Message range

A Message Prioritization study accepts between 2 and 5 written messages in a single run. If you need to evaluate more than five messages, conduct more than one study or reduce the initial list before launching the test.

Audience definition shapes the result

The hierarchy describes the audience selected for the study. A message that performs strongly with one group may perform differently with another.

Select the Segment or AI Twin carefully and configure the distribution filters around the audience the message is intended to reach.

The practical role of Message Prioritization

Message Prioritization helps teams decide what to say before they decide how to say it.

It gives brand, product, and growth teams a structured way to rank possible claims, identify a lead message, understand which supporting messages strengthen the narrative, and inspect how message performance differs across audience groups.

Used before final creative development, Message Prioritization helps make communication briefs clearer and more audience grounded. It does not replace strategic judgment. It gives that judgment stronger evidence before the message enters market.

How to Run a Message Prioritization Stuy

A step by step guide to running Message Prioritization on consumr.ai

Overview

Message Prioritization helps you compare written value propositions, claims, positioning statements, or communication messages before they are developed into final creative or used in market.

The study evaluates between 2 and 5 messages in a single run. Each message is scored on clarity, resonance, and believability. The results help you identify which message should lead, which messages can support the communication strategy, and how the hierarchy changes across audience groups.

Message Prioritization sits inside Concept Testing under Quantitative Research.

Step 0: Go to Message Prioritization

Sign in to consumr.ai. From the dashboard, open Calendar, click New Event, and select New Research Study.

Choose Quant as the research type and then select Concept Testing. On the Concept Testing landing page, you will see three study options: Creative Testing, Product Testing, and Message Prioritization. This guide covers Message Prioritization.

Step 1: Start a Message Prioritization study

Select Message Prioritization from the Concept Testing landing page. Message Prioritization tests written value propositions and claims by evaluating them on clarity, resonance, and believability. The study accepts a minimum of 2 messages and a maximum of 5 messages in one run.

The results include Message Hierarchy, Resonance Scores, and Message Architecture. The runtime shown on the platform card is approximately 30 minutes. When you have more than five messages to evaluate, reduce the message set before launching or divide the messages into separate studies.

Click Start Study under Message Prioritization.

Step 2: Set up your cohort

The Setup screen is where you define the audience whose response to the messages will be measured.Select the Segment or AI Twin that best represents the audience the messages are intended to reach. The required fields are Select Segment or Twin, Age Range, Genders, and Income Range. States is optional and can be left blank when geographic filtering is not required for the study.

Message Prioritization is answered by Respondents generated from the selected AI Twin or Segment. For a clear understanding, Respondents can be understood as smaller respondent units derived from the selected audience foundation for structured quantitative studies.

The selected AI Twin or Segment matters because the same set of messages can produce a different hierarchy when evaluated against a different audience. In this walkthrough, the study uses the AI Twin Samantha Lee, representing current and lapsed buyers of A Shoe Brand.

Match these settings to the audience the message is designed for. A distribution that is too broad can cause the scores to reflect people outside the intended audience. A distribution that is too narrow may reduce the strength of the Respondent cohort.

In this demonstration, the study was created for A Shoe Brand. The audience was anchored to the Samantha Lee AI Twin. The selected distribution included five age ranges, beginning with 18 to 24 and 25 to 34, both Female and Male genders, and five income bands, including $40K to $60K and $60K to $75K. No States were selected, so the study retained a broader geographic footprint within the selected audience definition.

Click Check Distribution.

Step 3: Review the distribution

The Distribution screen allows you to review the Respondent cohort before the study runs. Use this step to confirm that the selected audience reflects the people the messages are intended to reach. If the distribution does not look right, return to the previous screen and adjust the filters before entering the messages.

Population Demographics

Population Demographics shows male and female counts across the selected age brackets. Use this view to check whether the age and gender composition of the Respondent cohort matches the audience definition required for your message decision.

Income Distribution

Income Distribution shows how the selected audience is divided across the available income tiers. Use this view to check whether the income composition of the Respondent cohort matches the intended audience for the messages.

If the distribution is correct, click Add Value Propositions.

Step 4: Add your value propositions or messages

The Message Prioritization Setup screen is where you enter the messages you want to compare. A Message Prioritization study accepts between 2 and 5 messages in one run. Each message should be written in customer facing language and should represent a distinct communication direction.

Messages can include value propositions, benefit claims, positioning statements, headline ideas, or communication territories. To produce a useful hierarchy, follow three practical rules.

1. Make the messages meaningfully different from one another. Do not enter several rewritten versions of the same idea unless the purpose of the study is specifically to compare wording. A stronger message set tests different communication directions, such as performance, daily versatility, and style or wearability.

2. Keep the writing quality comparable across the messages. A polished message can outperform an unfinished one because it is easier to understand, even when the underlying idea is not stronger.

3. Keep the messages concise and direct. A message that includes too many clauses or ideas may score lower on clarity because the Respondents have more to process.

To add another message, click Add Message below the existing message blocks. To remove a message, click Remove on the right side of the relevant block. In the A Shoe Brand walkthrough, three messages were entered, each representing a different communication direction.

Message 1: Performance

Built for runners who chase splits, not steps. Responsive cushioning technology absorbs impact at race pace and holds its shape across consecutive long runs, helping mile 18 feel closer to mile 8.

Message 2: Daily Versatility

The only pair you need from sunrise intervals to the standing hours of a clinic shift. Lightweight, supportive, and built to move through the run, work, and life routine without requiring a shoe change halfway through the day.

Message 3: Style and Wearability

A serious running shoe that does not look like one. A considered silhouette, restrained colorways, and a finish that reads as athletic without looking limited to the gym, so it works on a long run and at the coffee shop afterwards.

If you need message ideas as a starting point, click Recommend in the top right of the setup screen. Recommend suggests value propositions based on the selected Segment and category. Use these suggestions as a starting point or as a check against the communication directions you have already drafted. Once the messages are ready, click Create Questions.

Step 5: Review the survey questions

The Questions screen loads survey questions based on the messages entered in the study.

For the three message example shown in this walkthrough, the platform loads questions that evaluate the messages across clarity, resonance, and believability, together with comparison questions that help build the message hierarchy.

Review the question set before running the study. In Message Prioritization, questions can be edited, removed, or added when the brief requires adjustment. If a saved question set exists from a previous study, it can be selected from the dropdown at the top of the screen. The purpose of this step is not simply to count the questions shown on screen. It is to confirm that the study is measuring the dimensions needed for the decision you are making.

At the bottom of the screen, you will see two execution options. Conduct Meeting Once runs the study once against the selected Respondent cohort.

Start Meeting and Schedule creates a recurring study using the same setup. Use this option when you want to monitor whether the message hierarchy changes over time. Repeated runs are most comparable when the message set, selected audience, and distribution filters remain consistent across waves. Changing the messages or audience definition changes the basis of comparison.

Before you launch

Before selecting an execution option, confirm the following:

• The selected AI Twin or Segment represents the audience the messages are intended to reach.

• The audience distribution is appropriate for the decision.

• The message set contains between 2 and 5 distinct communication directions.

• The messages are written at a comparable level of polish.

• The questions cover the message dimensions needed for the study.

For a single brief stage decision, click Conduct Meeting Once.

Step 6: Review the Survey Results Analysis

Once the study is complete, the platform takes you to the Survey Results Analysis page.

In this walkthrough, the study is titled Shoe Brand Message Evaluation, with Concept Testing shown as the parent module.

The results page shows the statistical analysis of survey responses with confidence intervals. The population counts shown in the charts are confidence banded estimates based on the Respondent cohort and the represented audience universe.

Each results card is linked to a survey question and shows how the selected audience responded. Review the results across the scorecard dimensions rather than choosing a message from one score alone.

For example, a message may perform strongly on clarity because it is easy to understand, but another message may perform more strongly on resonance because it feels more meaningful to the audience. A lead message should be selected after reviewing clarity, resonance, and believability together.

In the walkthrough example, the Daily Versatility message performs more strongly on clarity than the Performance message. This suggests that the run, work, and life framing is easier for the audience to understand immediately. However, clarity alone should not determine the final hierarchy. Review the resonance and believability results before deciding which message should lead.

Three filters are available above the results cards: Age Range, Genders, and Income Range. Use these filters to understand whether a result remains consistent within a narrower part of the selected audience. Click Clear Filters to reset the view. The Full Dataset button in the upper right allows you to download the complete results for further analysis or external sharing.

Each result card includes controls that allow you to arrange response options, download individual response data, and access See Trace for a closer inspection of the response context.

Step 7: Open the Demographic Breakdown

Use the Demographic Breakdown to understand whether a message performs consistently across the selected audience or whether its score is being driven by a particular group.

Click the grid icon at the top right of a results card. The Demographic Breakdown drawer opens from the right side of the screen.

The drawer repeats the question being analyzed and allows you to select a breakdown axis. The available views are Age Range, Gender, Income Bracket, and Lifecycle Stage. Age Range is selected by default when the drawer first opens.

The heatmap shows the relationship between the selected demographic group and the response options for the question. Stronger concentrations appear with deeper color shading, making it easier to see which audience groups are driving the response.

In the walkthrough example, the age breakdown helps show whether the Performance message is understood consistently across age groups. A message may look strong in the overall result but show weaker clarity within a particular audience slice. This can affect whether the message should be used broadly or adapted for a more specific group.

Use the radio buttons to switch between Age Range, Gender, Income Bracket, and Lifecycle Stage. Close the drawer using the X in the top right when you have completed the review.

Step 8: Use See Trace

Every surveyed question on the results dashboard includes the See Trace feature. Use See Trace when you need to inspect the intelligence layer and supporting context associated with a response pattern. Click See Trace on a question result to open the Question Trace side panel. The panel includes the following information:

Overall Score

The Overall Score appears at the top of the trace block. It gives a summary indicator for the trace information shown for the selected result.

Citations

Citations identify the audience variables or supporting context associated with the response pattern. These may relate to audience traits, familiarity with the topic, or relevant consumer signals connected to the interpretation.

Relevance Scores

Each citation card includes a Relevance Score. This indicates how strongly the cited signal is associated with the response interpretation shown in the trace panel.

The Relevance Score should not be read as a statistical weight in the final survey result. It is intended to help users inspect the relationship between the cited context and the interpretation displayed in the trace view.

Drill Down

Click Drill Down on a citation card to explore the supporting consumer signal or sentiment context in greater detail.

How to read the complete Message Prioritization flow

• Every Message Prioritization study on consumr.ai follows the same core process.

• Start by selecting Message Prioritization under Concept Testing.

• Define the audience by choosing the relevant Segment or AI Twin and applying the appropriate distribution filters.

• Review the distribution before launching the study.

• Enter between 2 and 5 distinct messages written in customer facing language.

• Review or adjust the generated survey questions.

• Run the study once or schedule it for repeated measurement.

• Review the message hierarchy and the clarity, resonance, and believability results.

• Use filters and Demographic Breakdown to see whether the hierarchy changes across audience groups.

• Use See Trace when you need to inspect the supporting context associated with a response result.

The text input is what distinguishes Message Prioritization from the other Concept Testing study types. Creative Testing evaluates completed or near completed creative assets. Product Testing evaluates product ideas and feature directions. Message Prioritization evaluates what the communication should say before the final creative expression is developed.

Final note

Use Message Prioritization when you need to choose which message should lead a communication strategy and which messages should support it.

A useful study begins with the right audience and a set of distinct, comparable messages. Once the results are available, review the full hierarchy across clarity, resonance, and believability rather than selecting a winner from one score alone. Use Demographic Breakdown to understand audience differences, and use See Trace where a result requires closer inspection.