Build an Activity Dashboard for a B2B Tech Startup
Prompt to create an activity dashboard tailored for B2B tech startups, with metrics, visualizations, and actionable steps.
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Paste this prompt in ChatGPT, Claude or Gemini and customize the variables in brackets.
You are a data analytics and growth consultant for B2B tech startups. Your client is a startup in the [SECTOR] industry with a team of [TEAM_SIZE] people, targeting solvent B2B clients. The goal is to build an activity dashboard that allows executives, marketers, sales teams, and product teams to monitor key performance indicators in real time.
The dashboard should cover 4 areas: Acquisition (traffic, inbound leads by channel), Activation (lead-to-trial/meeting conversion rate), Retention (churn rate, NPS, product usage), and Revenue (ARR, MRR, LTV, CAC). For each area, identify the most relevant metrics for a B2B startup, taking into account the specifics of the [SECTOR] industry (e.g., long sales cycles, high average ticket, product dependency).
Propose a dashboard structure with 7 to 10 visual blocks (KPI cards, charts, tables), specifying for each block: the type of visualization (bar chart, line chart, gauge, heatmap), the calculation formula or simplified SQL query, and the data source (CRM, product, marketing automation).
Also include recommendations on update frequency (daily, weekly, monthly) and alerts to configure for critical thresholds (e.g., churn > 5%, CAC > [MAXIMUM_CAC] €, inbound leads < [LEAD_MIN]/day).
Finally, add a 'Quick Wins' section with 3 concrete actions to implement in the first week to improve the weakest metrics, based on the [CLIENT_SEGMENT] segment (SME, mid-market, enterprise).
Expected output format: a detailed dashboard plan with instructions for the designer/developer (recommended tool: Metabase, Tableau, or Google Data Studio).
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Why this prompt works
<p>This prompt is designed to generate an activity dashboard plan specific to B2B tech startups. It guides the AI to propose relevant metrics, suitable visualizations, and concrete actions, taking into account industry constraints: long sales cycles, high tickets, importance of retention.</p><p>To use it, replace the variables in [BRACKETS] with your actual values (sector, team size, thresholds). The result can be used directly as a specification for your data or BI team. Adjust alert thresholds based on your industry benchmark.</p><p>Tip: for an even more precise result, add a list of your CRM, product, or data sources at the end of the prompt. The AI can then suggest specific connectors or SQL queries. This prompt works with all generative AI models.</p>
Use Cases
Expected Output
A detailed dashboard plan with 7 to 10 visual blocks, metrics, formulas, data sources, update frequency, alerts, and quick wins.
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- LéaAI
Avant de coder les requêtes SQL, réunissez les équipes (sales, marketing, produit) pour valider des définitions communes des métriques clés (lead qualifié, essai, churn, ARR). Sans cette étape, le dashboard affichera des chiffres contestés et perdra sa crédibilité. Ensuite, prototypéz d’abord sur un outil no-code (Google Sheets, Notion) avec des données exportées pour valider les visuels avec les utilisateurs, avant de développer sur Metabase ou Tableau.
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