Most businesses sit on tons of data – dashboards in Google Analytics 4 (GA4), export sheets from advertising platforms, CRM outputs, and social-media metrics. And yet, many still ask: “Is our marketing actually working?” or “Why is our marketing not working?”.
There’s nothing wrong with having the data. The problem is not a lack of information but a lack of insights and action. Data should lead to decisions. If it doesn’t, you’re simply accumulating noise.
This guide is written for those who want more than reports, they want results. We’ll walk through:
- How to pick the right metrics
- How to dig into what they’re telling you
- How to convert insights into action
- How to prioritise for commercial impact
- How to build a repeatable optimisation loop
Step 1: Identify What Actually Matters
In many organisations, the measurement function is under-resourced and unfocused. A recent survey found that 54% of UK business leaders view marketing as a cost-centre, not a revenue driver, and 48% of marketers say their biggest barrier is demonstrating long-term impact.
In short, if your metrics don’t link to commercial outcomes, you’ll keep fighting an uphill battle with the board.
What to track
Instead of chasing every number and data point you can find, focus on a small set of metrics that map directly to business performance. For example:
- Cost per Acquisition (CPA) – what you pay to gain a customer
- Conversion Rate – of those who engage, how many complete a meaningful action
- Revenue per Lead (RPL) – the average income generated from each enquiry
- Customer Lifetime Value (CLV) – your long-term return per customer
- Lead Quality – the likelihood that a lead will turn into a high-value customer
These metrics allow you to ask: If CPA rises, what do we do? If conversion falls, what changes do we make? A number without a “so what?” is just noise.
A UK study of 53 SMEs found that although these firms generated large volumes of data, they found it difficult to embed it into decision-making because they lacked a clear measurement framework aligned with their business models.
The lesson: volume of data is meaningless unless it maps to outcomes.
What you should do
Pick 3 to 5 metrics that reflect your commercial goal (e.g., “Grow revenue by 25% this year”) and make sure each metric has an owner. For each, ask: “If this metric changes by X%, what will we do differently?”
Make this part of your reporting framework.
Step 2: Diagnose What’s Working (and What Isn’t)
The analysis mindset
Collecting data is easy. Understanding what it means is harder. When a key metric changes, don’t just accept the shift – drill into why. Without analysis, you’ll base changes on assumptions, not insight.
Key questions to ask
- Is the change happening in a single channel (e.g., paid search) or across all channels?
- Is it restricted to a device type (mobile vs desktop)?
- Did anything change recently (landing page, ad creative, targeting, offer)?
- Is this external (seasonality, market trend, competitor action)?
- Could data integrity/tracking changes be at fault?
Kellogg’s’ UK operations used an integrated dashboard across multiple retail media platforms. Working with their agency, they discovered that by applying a unified cross-retailer dashboard and limiting wasted spend via experimentation, they achieved:
Since launching campaigns on Nectar360 two months ago, ROI has already improved by 25%
+85% revenue increase on ASDA and ROI grew by 19.25% quarter on quarter
They didn’t just track results. They asked why things changed, and changed what they did accordingly.
What you should do
Build a “drop-off map” for your key metrics. Example: your conversion rate dropped 15% this month. Instead of panicking, map: traffic – engaged visits – inquiries – sales. Locate the weak link and generate a hypothesis (“Mobile load time up by 2s on average”). Then test.
Step 3: Turn Insights into Actions
Once you understand what changed and why, the next step is action. Here’s where many organisations stumble: they analyse, they report – but they don’t act. Or they act, but based on guessing.
Here are actionable examples:
| Metric Flagged | Action to Take |
| CPA rising | Stop non-performing keywords, test new creative, refine audience targeting |
| Conversion rate down on mobile | Simplify mobile layout, reduce form fields, improve page speed |
| Revenue per lead low | Introduce qualification step, cross-sell higher-value products, refine lead follow-up |
| High bounce rate from email traffic | Match subject line to landing page, strengthen CTA, refine offer relevance |
BIC UK used enhanced first-party data and more refined look-alike audiences.
The result? They saw 3× higher purchase intent rate and a strong lift in ROAS.
They didn’t buy more media. They used data to shift which media, moved audiences, and measured the outcome.
What you should do
Create a “metric-to-move” table for your top 3 metrics. For each metric: define a specific action you’ll test within the next month, assign an owner, set a finish date. Review results and iterate.
Step 4: Prioritise for ROI
Why prioritisation is essential
There’s always more that can be improved. But resources (time, budget, people) are finite. Without prioritisation you’ll chase low-impact fixes and get frustrated.
The Impact vs Effort grid
Evaluate proposed changes along two dimensions: impact (commercial upside) and effort (time/cost).
- High impact / low effort – start here
- High impact / high effort – plan and schedule
- Low impact / high effort – deprioritise
A UK B2B firm ran a thought leadership campaign and achieved a 782% ROI by focusing heavily on three high-impact areas (content, events, PR) and ignoring dozens of lower-level experiments.
They didn’t try everything. They selected what mattered and then executed.
What you should do
List 5 improvements you could make in the next quarter. Score them (impact 1-5, effort 1-5). Immediately pick the one where effort is ≤3 and impact ≥4. Allocate resources and deadlines.
Step 5: Build an Optimisation Loop
Why a one-off won’t cut it
Marketing performance doesn’t improve through single changes alone. The most successful teams run monthly loops of review, test, learn, refine.
The monthly optimisation framework
- Review metrics: what’s changed from last month?
- Identify 1-3 hypotheses: e.g., “Our mobile conversion dropped after the new checkout update.”
- Run a test: e.g., revert checkout change for 2 weeks.
- Measure outcomes: How did conversion and CPA change?
- Decide: Keep change if positive; rollback or refine if not.
- Document learnings and update dashboards/hypotheses for next cycle.
A UK retailer integrated data across SEO, ads, and website optimisation. Within six months they achieved:
+220% in overall traffic
Leads up from 7 to 34 per month
ROI on ads of 4.2:1
They didn’t rely on a “big bang” change. They improved incrementally, consistently.
What you should do
Block out one 90-minute session each month. Bring the metric table and list of hypotheses. Decide who will run which test, and track results. Make sure you record not just what you did but why.
Data doesn’t grow businesses. Decisions do.
If your dashboards look impressive, but you’re still asking “Do we know what to do next?” then you’re still in the dark. The difference between reporting and improvement lies in one question: “What decision will I make because of this number?”
When you start answering that question regularly, you’ll stop focusing on dashboards and start putting your marketing investment to work.
Ready to move from data to decisions? Book a consultation and let’s build the roadmap to turn your marketing data into real ROI.