AI app for marketing · no coding needed
Marketing attribution reporting
Transparent model differences and missing data beside performance claims.
Made for: Small marketing agencies reporting across channels
What it does for you
The problem
Clients misinterpret inconsistent attribution numbers.
What it gives you
Reviewed marketing performance report
What you give it
Authorized campaign exportsattribution definitions
How it works, step by step
- Reconcile source totals
- Distinguish attribution models
- Flag tracking gaps
- Compare consistent periods
- Explain uncertainty
- Produce client reports
What you see on screen
- Channel overview
- metric definitions
- narrative report
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for Marketing attribution reporting with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Marketing attribution reporting with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links1 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare22 KB
- prompt-vps.mdThe same build on your own server (Docker)22 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria12 KB
- demo/index.htmlThe working demo on sample data197 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
For small marketing agencies reporting across channels, turn authorized campaign exports and attribution definitions into reviewed marketing performance report. Address the recurring problem: clients misinterpret inconsistent attribution numbers. The pilot measures reconciled totals and client comprehension against the buyer's current method, before the larger build.
Agree definitions, import authorized data, validate coverage and identifiers, compute transparent measures, group relevant evidence, review findings, assign investigations or improvements, and repeat on a comparable period. Start with authorized campaign exports and attribution definitions and finish with reviewed marketing performance report.
How the AI works
Classify text, summarize evidence and propose explanations to investigate. Compute financial or operational measures with deterministic code. Separate observed patterns from causal claims and preserve examples that contradict the summary.
Safeguards
Verify product claims and permissions. Distinguish observed campaign results from causal explanations and keep customer data collection authorized. Validate source access and reviewer availability during the pilot. Maintain customer-level access, data deletion controls and a record of final approvals.
What to build first
Begin with small marketing agencies reporting across channels and one recurring use case. Build the first two modules: reconcile source totals; distinguish attribution models. Provide operator assistance for the third module: flag tracking gaps. Deliver reviewed marketing performance report through a manual review queue. Perform other necessary full-scope functions manually during the pilot. Include all applicable access, accuracy and professional-review controls from the start.
What it can connect to
Approved brand material, campaign exports and authorized customer research. Read-only business data exports, reporting databases and task trackers. Reconcile source totals before scheduling recurring data refreshes. These are candidate integration categories, not verified supported connectors.
The screens in detail
Open with a compact overview and filters for the relevant period or segment. Let users drill from each theme or metric into underlying records. Keep source definitions and missing-data notes near the result. Use an action panel to assign investigations and record what was learned. In this product, the first view is channel overview, followed by metric definitions and narrative report.
