Required Datapoints
- Survey Audience: Must match ICP criteria.
- Recall Responses: Number who remembered your brand.
- Survey Type: Aided vs. unaided.
- Survey Period: When recall was measured.
Brand Recall Score in ICP Surveys measures the percentage of ideal customer profile (ICP) respondents who remember your brand, either unaided or aided. It helps assess brand strength and category awareness among target buyers.
Brand Recall Score (in ICP Surveys) measures how easily your brand comes to mind for your ideal buyers, capturing the strength of your mental availability and category positioning within your most strategic audience.
The relevance and interpretation of this metric shift depending on the model or product:
A high unaided recall signals strong positioning and category association. A low score — especially among ICPs — flags message dilution or poor competitive visibility.
Segment by persona, region, or deal size to refine who your brand is sticking with — and who still needs convincing.
Brand Recall Score in ICP Surveys informs:
These are the main factors that directly impact the metric. Understanding these lets you know what levers you can pull to improve the outcome
Actionable ideas to optimize this KPI, from fast, low-effort wins to strategic initiatives that drive measurable impact.
Activities commonly tied to improving or operationalizing this KPI.
| Activity | Description |
|---|---|
| Positioning Validation | Positioning Validation is a critical process that involves systematically evaluating how a product or solution is presented in the marketplace. It gives teams a clear plan for where to focus, how to sequence work, and what to measure. Relevant KPIs include Brand Recall Score in ICP Surveys. |
| Brand Testing | Brand Testing is a systematic process that enables organizations to understand how their brand is perceived by target audiences, stakeholders, and the broader market. It improves performance by removing friction, testing changes, and scaling what works. Relevant KPIs include Brand Awareness Lift and Brand Recall Score in ICP Surveys. |
| Persona Targeting | Persona Targeting is a structured process for identifying and documenting ideal customer profiles and key buyer personas within target markets. It gives teams a clear plan for where to focus, how to sequence work, and what to measure. Relevant KPIs include Brand Recall Score in ICP Surveys and Engagement Rate from Buying Personas. |
| Survey Research | Survey Research involves the systematic design, distribution, and analysis of structured questionnaires to collect both quantitative and qualitative feedback from targeted audiences. It helps teams translate strategy into repeatable execution. Relevant KPIs include Brand Recall Score in ICP Surveys. |
ICP Survey (CIOs at companies >500 employees):
This KPI is associated with the following stages in the AAARRR (Pirate Metrics) funnel:
This KPI is classified as a lagging Indicator. It reflects the results of past actions or behaviors and is used to validate performance or assess the impact of previous strategies.
This role is directly accountable for the KPI and is expected to drive progress and decisions around it.
These roles contribute directly to performance and typically partner on execution, reporting, or optimization.
These roles should stay informed on changes in the KPI because it influences adjacent planning, coordination, or outcomes.
These leading indicators influence this KPI and act as early signals that forecast future changes in this KPI.
These lagging indicators confirm, quantify, or amplify this KPI and help explain the broader business impact on this KPI after the fact.
How this KPI is structured in Cube.js, including its key measures, dimensions, and calculation logic for consistent reporting.
cube('IcpSurveyResponses', { sql: `SELECT * FROM icp_survey_responses`,
measures: { recallResponses: { sql: `recall_responses`, type: 'sum', title: 'Recall Responses', description: 'Number of respondents who remembered the brand.' }, totalResponses: { sql: `id`, type: 'count', title: 'Total Responses', description: 'Total number of survey responses.' }, brandRecallScore: { sql: `100.0 * ${recallResponses} / NULLIF(${totalResponses}, 0)`, type: 'number', title: 'Brand Recall Score', description: 'Percentage of ICP respondents who remember the brand.' } },
dimensions: { id: { sql: `id`, type: 'number', primaryKey: true, title: 'ID', description: 'Unique identifier for each survey response.' }, surveyAudience: { sql: `survey_audience`, type: 'string', title: 'Survey Audience', description: 'Audience of the survey, must match ICP criteria.' }, surveyType: { sql: `survey_type`, type: 'string', title: 'Survey Type', description: 'Type of survey: aided or unaided.' }, surveyPeriod: { sql: `survey_period`, type: 'time', title: 'Survey Period', description: 'Time period when recall was measured.' } }});Note: This is a reference implementation and should be used as a starting point. You’ll need to adapt it to match your own data model and schema