No more guesswork. Modelling marketing outcomes for Investors and CMOs

Marketing budgets and targets rarely line up neatly. Ambitions are high, but the true cost of acquiring customers — and the pace at which they arrive — is often obscured by optimism or by a lack of grounded modelling.

That’s why we’ve built the Marketing Outcomes & Budget Planner GPT: a simulator that turns marketing spend assumptions into transparent projections of customers, cost of acquisition (CAC), and ROI. The model isn't designed to make promises. Instead, it gives investors and CMOs a reality-check framework — so budgets, targets, and strategies can be tuned until they balance.

What the GPT Does

At its core, the GPT models the full funnel for every major marketing channel:

• Email marketing — considers platform costs, database size, open rates, click-throughs, nurture curves, and eventual customer conversion.
  
• Paid Search and Paid Social — CPC-driven, grounded in realistic B2B benchmarks, with editable assumptions.
  
• Organic Search and Content — starts with a baseline of site traffic, then compounds slowly with content investment.
  
• Direct and Referral traffic — adjusted for quality (Google “dark traffic” included), with modest conversion rates.
  
• Organic Social — free by default, but scaled realistically by content and community management spend.
  
• PR and Content Placement — not its own funnel, but adds uplift to Referral and Organic channels.
  
• Events and Webinars — expensive but credible: modelled as cost per event, leads generated, and lead-to-customer conversion.
  
• Advertising / ATL — CPM-driven brand awareness campaigns (e.g., YouTube, LinkedIn), with very low click-through rates and modest downstream conversion.
  

Each channel has its own B2B-calibrated defaults and, crucially, its own growth curve. Some — like Paid Search — show results quickly. Others — like Email nurture and Content/SEO — take months to build momentum.

Scenarios You Can Model

The GPT makes answering “what if?” questions practical and fast:

• Target-driven planning: “What budget and mix do we need to acquire 50 new customers over 12 months?”
  
• Channel allocation: “How does moving £20k from paid search to paid social affect total customers and CAC?”
  
• Sensitivity analysis: “What if paid search CPC rises 25% and conversion rates halve?”
  
• Investment payoff: “If we double content spend, how many extra organic and organic social customers might we win?”
  
• Event impact: “What if we run four webinars instead of two?”
  
• Scenario bounds: conservative, realistic, and optimistic outcomes side-by-side.

Example: 50 Customers for £50k?

Here’s a practical case. Imagine a company aiming for 50 new paying customers in 12 months, each with a lifetime value of £5,000 — a total value of £250,000. The marketing budget for the year is stated as ~£50k.

B2B-calibrated assumptions

With only a few additional inputs, the model generates a first-pass plan with a £55k blended budget (40% Search, 20% Email, 20% Content, 10% Events, 10% Social) This, however, delivers only ~20 customers — well short of the target.

• Spend: ~£55k
  
• Customers: ~20
  
• Blended CAC: ~£2,800
  

Options and their impact

The model then gives three simple, credible levers that can be combined to close the gap; each includes quick maths to help the user pick a direction:

Scale Paid Search to capacity (first)

• Double search spend from £22k → £44k (same CPC & rates). This will add ~7–9 customers, pushing total to ≈27–29.
  
• Risk: diminishing returns; monitor CPC creep.
  

Add a focused Retargeting + Email nurture layer

• Carve £5–10k into retargeting (social/search display) to recycle site visitors; assume modest CTR but much higher visit→signup (~2–3%).
  
• Paired with Email (and perhaps a webinar CTA), this can lift Email’s effective yield even with slow curves. Expect +3–5 customers.
  

Run more Events/Webinars with tighter targeting

• At £5k/event → 10 leads → 3 customers, adding 5 more events (~£25k) yields ~10–12 adjusted.
  
• Costly, but reliable for B2B; good when high-quality MQLs are essential.
  

What this shows

• The gap between ambition and reality is visible at once.
  
• To close it, the model points to levers: scale paid search, run more events, or layer retargeting and nurture into Email.
  
• Investors see whether growth targets are credible. CMOs see where to re-allocate spend.

Why It Matters for Investors and CMOs

• For investors (VCs, angels, PE): The GPT is an essential due diligence check. You can stress-test whether customer targets in a pitch are achievable with the proposed budget, or whether CAC is realistic compared to LTV.
  
• For CMOs and marketing leaders: It’s a scenario-planning partner. You can model the trade-offs between brand spend and lead generation, and explain to boards or CEOs why an extra £20k in content or events might (or might not) be justified.
  

The Bottom Line

Marketing Outcomes GPT doesn’t replace strategy, creativity, or execution. What it does is shine a bright light on the economics.

That clarity sparks the right conversations:

• Are our targets realistic?
  
• Where should we spend the next £10k?
  
• What’s the risk if our best channel underperforms?
  

For anyone considering an investment — in a business or in a marketing plan — those are the conversations worth having.

Photo by Carlos Muza on Unsplash