The Monday-morning brief is a classic ritual. A founder or leader spends the weekend obsessing over the latest growth hacks — LinkedIn carousels, AI visibility, paid-media funnels — and arrives at the office with a singular demand: "We need a campaign. How fast can we go?"
The intent is sound; growth has stalled. But the request is not backed by the business or the marketing strategy. When you strip away the tactical noise to ask the hard questions — why is revenue flat? where is the customer journey failing? — you're often met with a shrug. We've learned to mistake motion for diagnosis. But a campaign built on guesswork costs way more than one built on evidence; it also fails more expensively.
Understanding isn't the delay before the work begins. It's the work that stops the wrong solution moving faster.
Why Decision-Led Growth
Marketing teams are working across distributed discovery, AI-mediated recommendations, platform volatility, fragmented attribution, tightening privacy laws, and growing pressure to prove commercial value. None of that makes the job simpler — it just creates more possible actions, not necessarily better ones.
Marketing Decision-Led Growth is XL's working method for cutting through that ambiguity. It runs on four connected disciplines — Understand, Decide, Design for execution and Learn. They aren't a rigid sequence forced onto every engagement. How deep each one runs, and which tools are leveraged, is determined by the nature of the problem.
Understand: establish the real directive
Understanding starts with commercial clarity. What is the business actually trying to change? What's the baseline, the target, the timeframe, the gap? Which driver is expected to move the number, and which parts of that can marketing genuinely influence?
| Diagnostic area | Questions |
|---|---|
| Commercial performance | Is the problem revenue, profit, margin, market share, pipeline, win rate, retention, frequency or customer value? |
| Market and demand | Has category demand shifted? Is the market growing while the brand loses share? Has a substitute appeared? |
| Acquisition | Does the business need greater reach, mental availability, access, consideration or qualified demand? |
| Retention and leakage | Are customers being gained and lost at similar rates? Is onboarding, service or delivery breaking the promise? |
| Positioning | Can customers explain what the business does, for whom, and why it matters — or is the language cleverer than it is useful? |
| Conversion and sales | Does interest turn into a meaningful conversation, opportunity and purchase? Does context survive the handover? |
| Experience | Can customers complete the intended journey, and get help when the standard path fails? |
| Public evidence | What do reviews, forums, search results, AI answers and third-party sources lead buyers to believe? |
| Organisational conditions | Is there enough authority, capability, budget, data and time available to act on the finding? |
These areas influence each other, so the diagnostic stays proportionate rather than exhaustive. Its job is to cut through enough ambiguity to find the likely point of constraint — not to produce a report for its own sake.
When to diagnose first, and when not to
Diagnose first when
- The current campaign or channel mix is underperforming and nobody agrees on why.
- Customers, sales and leadership each describe the offer differently.
- The last three initiatives moved activity metrics but not the commercial number.
- A significant budget decision is about to be made on an assumption nobody has tested.
Move straight to execution when
- The problem and its cause are already well evidenced — a completed customer study, a clear conversion drop-off, a documented positioning gap.
- The fix is operational, not strategic, and further analysis would only confirm what's already known.
- Timing is genuinely fixed — a launch date, a market window — and the team is acting on the best available evidence, not a guess.
Revenue needs an equation, not just a number
"Increase revenue by 20%" doesn't tell marketing what to do. Growth could come from more customers, better conversion, more frequent purchases, larger transactions, better retention, a new market, a different product mix or a pricing decision. Each needs different approaches and different interventions.
The commercial objective is set in Understand, prioritised in Decide, built for in Design and Execute, and tested in Learn.
Decide: identify the decision that actually matters
The decision stage is where the team names which constraint needs to be unravelled, which commercial driver the work should move, and how much evidence is enough to proceed. It also makes the trade-offs visible: what changes, what stays, what stops.
Decision-led doesn't mean waiting for perfect information — some uncertainty only resolves through action. The discipline is knowing what's established, what's assumed, what risk is acceptable, and what the next move is meant to teach you.
Design for execution: build the conditions for progress
Design turns the decision into positioning, systems, experiences, communications or coordinated activity. Human-centred design contributes useful practices here, and much of the thinking behind Decision-Led Growth draws on it.
Empathy starts back in Understand — through interviews, observation, reviews, support cases, search behaviour, lost-customer conversations and customer data. It's evidence about lived experience, not a team imagining how it would feel to be the customer.
Design for the intended, exception and recovery paths
Most organisations design only the happy path. Real customers hit duplicated payments, locked accounts, delayed deliveries, unusual circumstances, and systems that can't recognise their problem. Unfortunately, with AI as the main customer care response, customers can be sent from pillar to post and in circles by bots that may not understand the problem outside their training. This affects the brand, the positioning, the experience and even the impact of the campaign intent. A complete design answers three questions:
- Intended path: What should happen when the experience works as intended?
- Exception path: How will the system recognise that this situation falls outside the standard process?
- Recovery path: How will contextual support reach an accountable person who can actually resolve it?
The system should reduce customer effort. It should never carelessly decrease customers instead.
At a former employer, I experienced how quickly an organisation can come under reputational pressure when claims linked to a former employee start circulating publicly. Handling it required facts, judgement, escalation, coordinated ownership, and an understanding of what different stakeholders needed to hear. It taught me that a system isn't tested by how well it runs on the happy path. It's tested by whether the organisation can recognise a breakdown, respond humanely, and rebuild trust when the standard process no longer applies.
Learn: improve the next decision
Learning looks at market response, commercial achievement, customer experience, delivery performance and new insights. It's the difference between busyness and changed fortune.
Learning rarely lands as one dramatic result. It might start as a clearer objection, less friction, or a single percentage point of improvement. Long-term partnerships create value when those signals carry into the next decision, rather than getting filed away after the campaign is closed and the report is sent.
Be patient enough to understand, and decisive enough to act. Move at the speed of evidence — not the speed of anxiety.
The Monday-morning brief, one level down
Go back to that founder. Investigation shows the offer is described in language customers can't follow — the business understood it, and assumed everyone else would too. More reach would only expose more people to the same confusion. The first intervention isn't more content. It's making the business easier to understand.
If people can't explain your value in their own words, more visibility just distributes the confusion further.
This is the diagnosis the Monday-morning brief was missing. Not a bigger campaign — a clearer answer to what's actually not working. And that means we still run a campaign, only this time it fulfils the founder's requirements and may even exceed them because it is now designed to solve the right problem.
When XL doesn't recommend a full diagnostic
If the problem is already well evidenced — a completed study, a documented drop-off, a positioning gap the team can point to — we don't manufacture a discovery phase to justify the engagement. We name the decision, agree on the evidence bar, and get on with the work. Diagnosis earns its time when the cause is genuinely unclear. It's a waste of a client's time and budget when it isn't.
How the design-thinking practices map to Decision-Led Growth
| Design-thinking practice | Where it strengthens Decision-Led Growth |
|---|---|
| Empathise | Customer target, experience, insight and problem discovery — feeds Understand |
| Define | Scoping the core challenge and commercial priority — feeds Understand and Decide |
| Ideate | Developing creative solutions and strategic options — feeds Design |
| Prototype | Building tangible touchpoints and system concepts — feeds Execute |
| Test | Evaluating market response and refining performance — feeds Learn |
The XL perspective
Great marketing helps people move forward, which helps your business grow. Decision-Led Growth keeps asking one question: what needs to change for people and the business to move forward?
The aim isn't to make marketing slower or more academic. It's to stop activity substituting for clarity, and to design the conditions in which execution can create real progress — not just movement.
