Conversion Optimisation

Conversion optimisation is the practice of increasing the percentage of people who take the action you want—click, book, buy—without slashing prices or margins. Yes, I could raise your “conversion rate” overnight by dropping every product to €0, but that would destroy profit. Real conversion optimisation is a balancing act: deliver more revenue from the same spend while protecting—or improving—profit per sale. The craft involves spotting friction, testing improvements, and keeping anything that lifts performance and keeps unit economics healthy.

A B2B growth engine is only as strong as its weakest conversion step. If ads win clicks but landing pages leak leads, or discovery calls qualify prospects yet quotes go unanswered, new traffic just pours through holes. By optimising conversions at every stage you:

1. Unlock revenue without extra media spend Lifting a landing-page rate from 2 % to 3 % gives 50 % more leads from the same budget.
2. Improve customer acquisition costs Higher downstream conversion means lower cost per closed deal—vital when paid channels get pricier.
3. Create a culture of evidence-based decisions Rather than arguing preferences (“make the button green”), you run tests and let data decide.

Common bottlenecks and matching metrics

Each stage has its own “mini-conversion” that can stall growth if ignored. Fix the weakest link, then move to the next.

Start with insight, not guess-work

Interview users

Speak to five to ten recent prospects or customers. Ask what nearly stopped them buying, which proof points mattered, and what they expected to happen next. Patterns in language and objections translate directly into testable hypotheses for ad copy, landing-page proof, or proposal decks.

Session recordings

Use a tool from the user behaviour stack to watch how visitors navigate forms, scroll heat-maps, or rage-click buttons. Seeing hesitation or back-tracking pinpoints friction you cannot spot in aggregate data.

5-second tests

Show your page or email to someone for five seconds, then ask what they remember and what action they would take. If they cannot tell you the value or next step, your message is unclear—rewrite headline, hero, or call-to-action and retest.

Google Analytics & dashboards

Before running A/B tests, verify that pages, events, and revenue attribution flow correctly in your analytics and dashboarding setup. Mis-tagged goals lead to false “wins” or “losses” that waste optimisation cycles.

Once qualitative clues highlight friction points, quantify them with data. High-traffic pages move to A/B or multivariate testing; low-traffic assets rely more on qualitative tweaks and longer-running tests.

When you have data, experiment methodically

A/B testing

A/B (split) testing compares two versions—A (control) and B (variation)—served at random to visitors. If B produces a statistically significant lift in your metric, you keep it. Examples:

• Change an ad headline to emphasise pain, not product.
• Shorten a booking form from eight fields to four.
• Swap a generic case study for an industry-specific one on the landing page.
  

Tips: ensure you have enough traffic, run tests for a full buying cycle, and track profit as well as conversion so a higher rate does not erode margin.

Multivariate testing

Multivariate testing changes several elements at once—headline, image, CTA—creating multiple combinations. It shows which mix performs best and which element drives the lift.

Best for: high-traffic pages (e.g. product home pages) where many visitors allow quick, reliable results.

Watch-outs: complexity rises fast; stick to a limited set of variables and analyse interaction effects.

Practical optimisation ideas across the funnel

Build a repeatable programme

1. Log every hypothesis in a testing backlog—impact, confidence, effort.
2. Prioritise weekly; pull the top ideas into a sprint.
3. Run one change at a time per step to isolate effect (multivariate is the exception).
4. Declare a winner or loser; document the outcome so future hires learn what already failed.
5. Rinse and repeat: once a metric is healthy, move to the next bottleneck.
   

Keep profit front and centre

A change that lifts conversion but drops average deal size might hurt overall revenue. Always pair your conversion metric with a value metric such as pipeline value per visitor or profit per sale to avoid false victories.

By treating conversion optimisation as structured, data-led experimentation—from ad click to proposal sign-off—you turn every stage of your B2B funnel into a revenue lever. The payoff is compound growth: more deals, same spend, healthier profit.