Screenshot of the Evidence-backed campaign optimization workspace interactive demo
Screenshot of the interactive demo, on sample data

Evidence-backed campaign optimization workspace

Reduce tool sprawl and manual transfer work while keeping campaign decisions traceable.

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For
Digital marketing teams and agencies running paid search and YouTube campaigns
Solves
Keyword research, audience targeting and competitor analysis live in separate rented tools, so campaign decisions are split across subscriptions and evidence is hard to trace.
Delivers
Reviewer-approved audience and keyword sets linked to campaign evidence
Built in
about 5 weeks of creation time, MVP in 5 days
Investment
$11,000 for the MVP, $37,500 for the full product
Run it
Inside your business, or as part of your offer to clients
01

What it does

Reduce tool sprawl and manual transfer work while keeping campaign decisions traceable.

  1. Ingest authorized campaign and audience data.
  2. Build high-performing ad audiences from business and audience inputs.
  3. Expand keyword topics and related terms.
  4. Sync approved audiences and keywords to Google Ads.
  5. Summarize competitor YouTube ad strategies, statistics, metadata and targeting.
  6. Optimize target audiences for Google and YouTube ads.
  7. Test content against current ranking standards.
  8. Give on-page guidance on keyword usage, HTML structure, meta components, heading tags and image optimization.
  9. Generate draft content with an AI editor.
  10. Run spelling, grammar and originality checks on drafts.
  11. Surface niche-specific competitive observations.
  12. Compare the reviewed result with the recorded baseline and value assumptions.
  13. Capture corrections and named-owner approval before consequential use.
  14. Export a versioned reviewer-approved audience and keyword set with source references and unresolved questions.

Everything these tools do, in one app

What goes in, what comes out

What the customer puts in
  • Authorized campaign data
  • Audience inputs
  • Competitor observations

AI drafts, people review. Evidence-backed analysis and reporting workspace.

What the customer gets
  • Reviewer-approved audience
  • Keyword sets linked to campaign evidence
02

How it works

The workflow

  1. In
    Start with

    Authorized campaign data, audience inputs and competitor observations

  2. 1

    Confirm the buyer's problem and scope

  3. 2

    Collect authorized campaign data

  4. 3

    Audience inputs and competitor observations

  5. 4

    Then follow this sequence: 1

  6. Out
    Finish with

    Reviewer-approved audience and keyword sets linked to campaign evidence

AI does the heavy lifting, people stay in charge

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One authorized ad account and one supported export format; final campaign targeting, budget and content decisions remain with the marketing owner. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Campaign brief and data sources, Editable optimization preview, Client proof and delivery. Use a thumbnail gallery for campaigns, a large central analysis canvas, and a right-hand panel for sources, constraints and comments. Let users compare keyword and audience versions 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 reviewer-approved audience and keyword sets linked to campaign evidence visible beside its evidence, review state and value baseline.

Accounts and administration

Project ownership, asset versions, client comments, approval states, usage allowances, revision limits, download history and a rights record for supplied material. Add organization access boundaries, named reviewers, usage caps, data retention controls, export logs and explicit approval for external actions.

Integrations and data access

Authorized ad accounts, analytics exports and permitted competitor sources. Cloud storage, spreadsheet import/export and ad platform 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.

03

How we build it

We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.

  1. 1

    Scoping call

    Day 1

    Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.

  2. 2

    MVP

    5 days

    One buyer segment, one recurring use case; first modules: ingest authorized campaign and audience data; build high-performing ad audiences from business and audience inputs. Manual review in the loop. Built by our AI software factory.

  3. 3

    Paid pilot

    6 days

    Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

  4. 4

    Full product

    2 weeks

    Self-serve onboarding, billing, monitoring and the wider integration set.

  5. 5

    Run and improve

    Monthly

    We host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.

Why we start with an MVP

An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.

  1. Pick the riskiest assumption. Here: will digital marketing teams and agencies running paid search and YouTube campaigns use it to solve "keyword research, audience targeting and competitor analysis live in separate rented tools, so campaign decisions are split across subscriptions and evidence is hard to trace"?
  2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
  3. Run a paid pilot. Agree quality and outcome thresholds before the pilot using this measure: Accepted audience and keyword sets per analyst hour and corrections after campaign launch.
  4. Measure, then decide. Track accepted audience and keyword sets per analyst hour and corrections after campaign launch; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. Pilot scope: One authorized ad account and one supported export format; final campaign targeting, budget and content decisions remain with the marketing owner. Implement one approved input format, a bounded representative case set and the first two task modules: ingest authorized campaign and audience data; build high-performing ad audiences from business and audience inputs. Support the remaining modules with operator review. 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.

After the MVP. Once paid pilots prove usefulness, automate repeatable reviewed steps and add one verified source integration. Expand supported inputs and case volume only after new evaluation cases pass. Build reusable customer configurations and recurring value reports around reviewer-approved audience and keyword sets linked to campaign evidence. Retain the explicit scope boundary: One authorized ad account and one supported export format; final campaign targeting, budget and content decisions remain with the marketing owner.

What the build depends on. Data upload and preview, asynchronous processing jobs, editable version history, reviewer access and tested export formats. High-fidelity campaign work requires specialist marketing QA. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One authorized ad account and one supported export format; final campaign targeting, budget and content decisions remain with the marketing owner.

04

Investment

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

  1. Phase 1

    MVP

    One buyer segment, one recurring use case; first modules: ingest authorized campaign and audience data; build high-performing ad audiences from business and audience inputs. Manual review in the loop.

    $11,000 · about 5 days of creation time

  2. Phase 2

    Paid pilot

    Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

    $11,000 · about 6 days of creation time

  3. Phase 3

    Full product

    Self-serve onboarding, billing, monitoring and the wider integration set.

    $15,500 · about 2 weeks of creation time

Indicative total, MVP to full product$37,500about 5 weeks of creation time · start with the MVP from $11,000

Running costs per month

A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.

StageHosting and infrastructureAI usageTotal per month
MVP and paid pilotabout 3 customers$30–$60$80–$160$110–$220
Full productabout 50 customers$110–$210$880–$1,750$990–$1,960
05

Run it or resell it

Internally

For your own team

Digital marketing teams and agencies running paid search and YouTube campaigns run it inside the business: authorized campaign data, audience inputs and competitor observations in, reviewer-approved audience and keyword sets linked to campaign evidence out, reviewed by your people.

For your clients

As part of your offer

Agencies, consultancies and software companies can offer it to their own clients under their brand. We build and maintain it; you sell and deliver it.

Your brand, or this one

Run it under your own brand, or start from this concept style.

  • primary#2c2791
  • accent#c9bf54
  • surface#e5e4f1
  • ink#22201e
Headings
Fraunces
Text
Inter
Voice
Energetic, specific, results-minded
Selling it to your own clients: the go-to-market playbook

Pricing to test

Test a USD 300-1,500 fixed pilot for one defined campaign package. Offer a monthly production allowance after repeat demand. Quote complex multi-account or specialist integrations separately. These are test prices, not market benchmarks. Package the initial sale as one bounded reviewer-approved audience and keyword set. Recurring fees must specify volume, review depth and integration support. For exchanges, test a disclosed coordination or successful-service fee rather than holding customer funds. Reprice only after measuring real delivery labor; platform-build cost is separate from a commercial pilot fee.

Message to test

Reduce tool sprawl and manual transfer work while keeping campaign decisions traceable. Demonstrate a concrete reviewer-approved audience and keyword set using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Digital marketing teams and agencies professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample reviewer-approved audience and keyword set from a small authorized input set, with a transparent calculation of accepted audience and keyword sets per analyst hour and corrections after campaign launch and no promised savings.

The first 30 days

  1. Week 1: interview five digital marketing teams and agencies running paid search and YouTube campaigns and inspect a recent example of keyword research, audience targeting and competitor analysis living in separate rented tools.
  2. Week 2: prepare a consented or synthetic demonstration of the task modules.
  3. Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
  4. Week 4: measure accepted audience and keyword sets per analyst hour and corrections after campaign launch, reviewer effort and repeat-purchase interest. This is a demand-validation plan, not a thirty-day full-product delivery promise.

Paid pilot

Agree quality and outcome thresholds before the pilot using this measure: Accepted audience and keyword sets per analyst hour and corrections after campaign launch. Continue only if the buyer accepts the actual output, the intended job outcome improves without unacceptable errors, and measured delivery cost fits willingness to pay. Revise or stop if access is unavailable, qualified review cannot be provided, or apparent savings disappear after corrections and support. Use held-out cases when comparing model quality; use a properly reviewed comparison design before making causal claims. Record missing cases and negative results alongside successful outputs.

Success metrics

Accepted audience and keyword sets per analyst hour and corrections after campaign launch; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs reviewer-approved audience and keyword sets linked to campaign evidence. Retain permissioned settings and reviewed examples, report realized value honestly, and sell increased volume or adjacent approved workflows only after contribution margin and quality remain acceptable.

Why clients would pick it

A reusable library of approved campaign configurations, audience rules and review examples, together with reliable delivery for a narrow marketing niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for digital marketing teams and agencies running paid search and YouTube campaigns. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

KeywordSearch, Keyword Search and KeywordSpy, plus freelancers and manual spreadsheet work. Compare this product with the buyer's present method on accepted audience and keyword sets per analyst hour and corrections after campaign launch. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Model calls, data processing, storage, reviewer hours, client revision rounds and licensed source data. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of reviewer-approved audience and keyword sets linked to campaign evidence. Track cost per accepted output, including correction work, unsuccessful cases and support.

06

Safeguards

Preserve brand voice, source attribution, data permissions and usage rights. Marketing owners approve substantive targeting, budget and content changes. One authorized ad account and one supported export format; final campaign targeting, budget and content 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.

Get this solution built

Built for you by our AI software factory, MVP in about 5 days. Tell us about your business and how you want to run it: inside your company, or as part of what you offer your clients. We reply within one working day.

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