1.6% to 3.1%Conversion in 8 Weeks,on the Same Traffic.
A £1.9M DTC ecommerce brand was converting at 1.6% and about to spend its way out of the problem. We audited where visitors were actually dropping — a value proposition that never landed, product pages missing the information buyers needed, and a shipping cost that only appeared at checkout — then tested and shipped the fixes in order of what each was worth.
Free, no obligation — we reply within 48 hours.
Client DTC ecommerce · £1.9M annual revenue · steady paid and organic traffic
About to Buy More Traffic for a Funnel That Leaked
The brand is a DTC ecommerce business generating £1.9M in annual revenue, with consistent traffic arriving through both paid and organic channels. It converted at 1.6% — well below its category benchmark — and that shortfall had been read as a traffic problem.
The plan was to increase ad spend. That would have bought more visitors for a funnel already losing most of the ones it had, so the team paused to look at what was happening on-site first.
Three Points Where the Funnel Was Losing Buyers
Session recordings, heatmaps and funnel analysis were read together rather than one at a time. Three problems accounted for most of the loss, and none of them was traffic quality.
The value proposition never landed
First-time visitors could not tell within seconds what separated the brand from its competitors, so landing pages bounced heavily despite the traffic arriving being relevant.
Product pages hid the deciding information
Sizing, materials, shipping timelines and the return policy — everything a hesitant buyer needs before committing — sat below the fold or was missing entirely, so people left to go looking rather than adding to cart.
Shipping cost arrived as a surprise
Recordings showed a consistent abandonment spike at the exact moment shipping cost first appeared in checkout, with nothing earlier in the journey setting the expectation.
Three Phases of Testing Over Eight Weeks
Research before hypotheses, hypotheses before tests, and winners rolled out the moment they proved out rather than held back until the programme ended.
- Weeks 1–2
Research and hypothesis building
We analysed session recordings, heatmaps and funnel drop-off across the homepage, product pages and checkout to establish exactly where and why visitors were leaving, then built a prioritised list of test hypotheses ranked by expected impact against implementation effort.
ranked by impact - Weeks 3–5
Landing page and product page testing
We A/B tested a clearer above-the-fold value proposition and rebuilt the product page layout to surface sizing, materials and shipping information earlier, with social proof moved up next to the add-to-cart button. Winning variants went sitewide as results came in.
winners shipped early - Weeks 6–8
Checkout and trust optimization
We moved shipping cost messaging earlier in the funnel so it stopped being a surprise, cut fields out of the checkout form, and placed trust signals — guarantees, reviews, secure checkout badges — at the specific steps where drop-off had been highest.
friction removed at source
Eight Weeks, Same Traffic, Measured Against the Baseline
| Metric | Before | After (8 weeks) |
|---|---|---|
| Site-wide conversion rate | 1.6% | 3.1% |
| Cart-to-checkout completion | 52% | 74% |
| Average order value | £68 | £71 |
| Monthly revenue at the same traffic level | £29,800 | £57,900 |
Conversion rate nearly doubled with no increase in traffic or ad spend, so the entire revenue gain came from converting visitors the brand was already paying to acquire.
The Cheapest Growth Was Already on the Site
The biggest lever was not more traffic — it was removing friction the brand did not know existed. Session recordings and funnel data pointed straight at specific, fixable problems: an unclear value proposition, missing product information, and a checkout surprise. Fixing those in priority order produced faster and cheaper revenue growth than scaling ad spend would have, and unlike more spend, the gain keeps applying to every visitor who arrives afterwards.
Where Is Your Funnel Leaking?
Most sites lose the majority of their buyers at two or three specific, findable points. A free call is enough to tell you where yours are and what fixing them would be worth against what more ad spend would cost.