In short — the case in one block
Over an 8-week engagement, I audited and re-architected the commercial model of an established player with 25+ years in professional education (client not disclosed under NDA). I didn't just hand over a strategy — I built data instruments that recalculated the real economics of the business, exposed hidden losses, designed the architecture of an AI agent for retention and upsell, and delivered a 2026 forecast model: ~€43,000/year in payroll savings, a projected 8–12% revenue lift, and +72% in customer lifetime value (LTV).
This is what I do as an AI revenue architect: I cross classic commercial consulting with artificial intelligence — both as a diagnostic instrument and as a product that earns.
What kind of company was this?
An established player in professional education for finance and legal specialists (tax, law, accounting), with 25+ years of history, a strong brand, ~€3M in annual revenue, and several thousand active clients. Stable on paper. Stagnating underneath: the client base shrank every year and new acquisition had slowed.
The cause was a "change of eras." The sales model was built on mandatory qualification requirements — clients bought for the formal credential. But the market had shifted toward demand for real skills and career growth. The old engine still turned, but it was losing traction.
What did the diagnosis reveal? I calculated, I didn't guess
This is where the AI part begins. Instead of intuition, I pulled a year of raw sales data and reconciled two pictures the company had never compared:
- accounting by payments — real cash inflow (Cash Flow);
- accounting by delivery — real margin and cost-to-serve.
The recalculation instruments exposed what ordinary reports hid:
Off-site events consumed about a third of all redeemed subscription units
~160,000 units were redeemed in total. The off-site format is the highest-cost one — heavy offline logistics (venue rental, travel, accommodation) — with low margin, yet cost the client the same units as a near-100%-margin webinar. Clients were getting expensive events out of a "common pot" of cheap prepaid units, generating a hidden loss.
About 60% of clients bought only once
The funnel behaved like a sieve: most arrived for a one-off service and never came back.
10% of clients drove ~80% of revenue
A classic Pareto concentration — yet the sales incentive system ignored it entirely.
What did I do? Classic consulting, amplified by AI
No 200-page strategy. I built and handed over nine practical tools. The core ones:
Split sales into Hunters and Farmers
Separate KPIs and ownership for acquisition vs. base development.
Pruned the product matrix with a "white list"
A product stays only if it sells more than 10×/year with margin above 35%. The survivors were grouped by margin into clusters: Foundation (core vertical, 52→55%), Efficiency (professional development, 62%), Future (AI & digital, 67%), with loss-making off-site events moved into a separate paid "Status" cluster.
Moved to a subscription SaaS model (MRR)
Annual contracts with unlimited online content (near-zero cost-to-serve per extra client), off-site events charged separately. For B2B, an "add an employee for +30–50%" mechanic that locks in the company.
Designed the architecture of an AI agent — a career coach in Telegram
The concept, dialogue scenarios, and monetization mechanic (I owned the architecture, not the development). By design, the agent diagnoses a specialist's skills, builds a personal development roadmap, rewrites their CV for a target role, preps them for interviews — and natively embeds links to the company's courses into the plan. It's an automated "Farmer": the agent surfaces the need, the salesperson just sends the invoice.
Mapped the customer journey across 6 stages
With CRM triggers that alert a manager the moment a client shows churn risk.
How the AI agent becomes a revenue engine
I designed a growth mechanic, not a "bot." By design, the agent is free for a month with any core purchase, then €12/month — but only Club members (€48/month) can keep it. A cheap wow-product pulls clients into a high-margin subscription.
By the model's math: 500 base clients on the agent at €12/month = +€6,000 MRR per month at near-zero cost, on top of Club revenue (€48/month per member) and annual online-content subscriptions (from €1,400/year per client).
What were the results?
~€43,000/year saved
A schedule audit exposed "hidden duplicates": the same material was taught several times to different small groups, and the company paid the lecturer for every repeat. I merged the duplicate groups into shared cohorts (several small groups into a single lecture) and moved part of the offline sessions online — one stream or recording instead of several live repeats. That cut the lecturer payroll by €3,500+/month (~€43,000/year).
A full 2026 transformation roadmap
- revenue growth of 8–12%, driven by focus on high-margin products;
- LTV up 72% — average revenue per client rising from €380 to €655 — via farmer-led upsells, CRM tracking, and the subscription model.
Why does this beat classic consulting?
Ordinary transformation swaps one static strategy for another. I change the engine, not the paperwork: AI instruments first calculate the real economics and find where the business leaks money, classic consulting then rebuilds sales and product, and the AI agent stays inside the company as an asset that retains and upsells without human effort. "We've always done it this way" intuition is replaced by a digitized, manageable architecture — while the company keeps running.
The market context this runs on: AI search has already moved the client's decision point — what AI search did to the sales funnel in 2025 →
Does your business look stable but feel stuck?
That's usually inertia — not a ceiling. I help mature B2B companies find where their commercial engine is leaking and rebuild it into a measurable, scalable system — using data and AI.
