Living Strategy Workspace

For

Marketing directors at mid-sized consumer brands

Solves

Static marketing plans become obsolete quickly and teams execute from memory

Delivers

Updated strategy document, weekly tactical moves, campaign briefs and copy

Built in

about 2 weeks of creation time, MVP in 2 days

Investment

$5,500 for the MVP, $17,000 for the full product

Run it

Inside your business, or as part of your offer to clients

For marketing directors at mid-sized consumer brands, turn market data and competitor insights into an updated strategic playbook and campaign briefs.

1. Connect data sources and build baseline strategy.
2. Monitor market signals and competitor moves.
3. Update strategic playbook automatically.
4. Flag changes and suggest tactical moves.
5. Draft campaign briefs and copy.
6. Measure results against the current strategy

What goes in, what comes out

The workflow

1. In
   Start with

   Website, CRM, social accounts, competitor URLs, last three campaign briefs

2. 1

   Connect data sources

3. 2

   Build baseline strategy

4. 3

   Monitor market signals

5. 4

   Update strategic playbook

6. 5

   Flag changes and suggest tactical moves

7. 6

   Draft campaign briefs

8. 7

   Measure results against the current strategy

9. Out
   Finish with

   Updated strategy document, weekly tactical moves, campaign briefs and copy

AI does the heavy lifting, people stay in charge

Use language models to read competitor websites, customer reviews and sales transcripts. Detect signals like price changes or new trends. Update the strategic playbook automatically and draft briefs aligned with the current strategy. A human reviewer checks the generated strategy updates for brand voice and relevance before deployment

What your team sees

Key screens: Strategy dashboard, market signal feed, campaign brief generator. Use a central dashboard to display the current strategy, a feed to show detected market shifts, and a brief generator to draft campaign content. The first view is the strategy dashboard, followed by the market signal feed and campaign brief generator

Accounts and administration

User accounts, data source permissions, strategy version history, approval workflows, audit trail of changes

Integrations and data access

CRM systems, social media APIs, competitor website scrapers

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

   2 days

   One buyer segment, one recurring use case. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   3 days

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

4. 4

   Full product

   6 days

   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 marketing directors at mid-sized consumer brands use it to solve "static marketing plans become obsolete quickly and teams execute from memory"?
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. Establish a baseline of current strategy effectiveness and compare it against the AI generated weekly suggestions to prove value
4. Measure, then decide. Track percentage of strategy updates adopted by the team and reduction in time spent on market research. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. Ship a simple dashboard that ingests website data, a handful of competitor sites and last three campaign briefs. It generates a one-page strategy document and a weekly email with three suggested tactical moves. The first buyer is a marketing director at a mid-sized consumer brand

After the MVP. Automated continuous monitoring, full campaign drafting, sentiment analysis, and integration with ad platforms

What the build depends on. Large language models, web scraping infrastructure, data storage

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

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.

Your brand, or this one

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

Selling it to your own clients: the go-to-market playbook

Pricing to test

$299 per month per brand for the paid tier

Message to test

Stop writing static marketing plans. An AI agent reads your market, updates your strategy, and drafts the next campaign

Where to find buyers

LinkedIn, marketing industry publications, SaaS directories

Lead magnet

A free demonstration of a one-page strategy document generated from their own website

The first 30 days

1. Week 1: Build dashboard and ingest website data.
2. Week 2: Add competitor site monitoring and baseline strategy generation.
3. Week 3: Implement weekly email alerts and tactical move suggestions.
4. Week 4: Launch to first customer and gather feedback on strategy quality

Paid pilot

Establish a baseline of current strategy effectiveness and compare it against the AI generated weekly suggestions to prove value

Success metrics

Percentage of strategy updates adopted by the team, reduction in time spent on market research

Retention and expansion

Monthly subscription based on the number of brands and data sources connected

Why clients would pick it

Data accumulation and model fine-tuning over time make the strategy updates more accurate and specific to the client's brand voice

Alternatives and positioning

Manual spreadsheets, static marketing plans, general AI writing tools without market context

Main delivery costs

Compute costs for data ingestion and model inference

Brand voice guardrails, notification filtering to avoid spam, human approval loops for major strategy shifts