Attention heatmap design decision workbench

Reduce review cycles and make attention evidence usable in one owned workspace. For marketing and product design teams reviewing landing pages, ads and email layouts, convert uploaded screenshots, heatmap images, campaign goals and platform exports into reviewed attention findings, design variants and stakeholder reports. The benefit is a testable hypothesis, measured through accepted design decisions per review hour and corrections after campaign launch; do not assume that AI output alone produces business value.

Confirm the buyer's problem and scope, collect uploaded screenshots, heatmap images, campaign goals and platform exports, then follow this sequence: 1. Generate attention heatmaps from uploaded screenshots. 2. Mark areas of interest such as buttons or headlines. 3. Compare design iterations on predicted attention. Resolve uncertain cases with qualified reviewers, approve reviewed attention findings, design variants and stakeholder reports, and measure accepted design decisions per review hour and corrections after campaign launch against a documented baseline.

How the AI works

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Attention predictions are directional estimates, not measured user behavior; final design and campaign decisions remain with the marketing owner. A model suggestion is never a verified fact, professional decision or authorization to act.

Safeguards

Preserve brand guidelines, source attribution, asset permissions and usage rights. Marketing owners approve substantive design and campaign changes and publication scope. One fixed set of page types and one email platform; final design and campaign decisions remain with the marketing owner. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.

What to build first

Pilot scope: One fixed set of page types and one email platform; final design and campaign decisions remain with the marketing owner. Implement one approved input format, a bounded representative case set and the first two task modules: generate attention heatmaps from uploaded screenshots; mark areas of interest such as buttons or headlines. Support the third module with operator review: compare design iterations on predicted attention. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.

What it can connect to

Client-owned screenshots, heatmap images, campaign goals and permitted platform exports. Cloud asset storage, design-file import/export and email marketing destinations. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.

The screens in detail

Primary screens: Asset and goal intake, Editable analysis workspace, Client proof and delivery. Use a thumbnail gallery for projects, a large central canvas for heatmap overlays and variant comparison, and a right-hand panel for goals, marked areas and comments. Let users compare design iterations side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant asset. Make the task-specific outcome reviewed attention findings, design variants and stakeholder reports visible beside its evidence, review state and value baseline.