The most efficient growth lever in D2C is converting more of the traffic you already have. We run systematic CRO programs — hypothesis-driven A/B tests, checkout optimisation, and AI personalisation — that compound CVR improvements month over month.
Realistic CVR improvement depends on your starting baseline and how much optimisation has already been done. Brands we take over from no prior CRO program typically see 20–45% CVR improvement within 6 months of systematic testing. Brands with existing CRO programs see 8–18% improvement as the low-hanging fruit is already captured. The compounding effect is significant — a 25% CVR improvement on $5M revenue means $1.25M additional revenue from the same traffic, with zero increase in ad spend.
We typically run 3–6 tests simultaneously, ensuring each test has enough traffic to reach statistical significance within 2–4 weeks. Test velocity matters — the teams that run more tests compound learning faster. We prioritise tests by expected impact versus implementation effort, starting with high-traffic pages and high-abandonment funnel steps where even a small win produces significant revenue impact.
Our CRO toolkit covers: VWO or Optimizely for A/B and multivariate testing, Hotjar or Microsoft Clarity for heatmaps and session recordings, Google Analytics 4 for funnel analysis and segment performance, Shopify Analytics for checkout funnel specifics, and custom data pipelines for attribution modelling. Tool selection is adapted to each client's existing stack — we integrate with what you already have rather than forcing platform migrations.
We use an ICE scoring framework — Impact, Confidence, Ease — assessed against your analytics data. Impact is estimated by the traffic volume on the page and the magnitude of the opportunity based on competitive benchmarks and heatmap data. Confidence is based on the strength of the supporting evidence. Ease is based on implementation complexity. The result is a prioritised CRO roadmap that ensures your first 90 days produce measurable revenue impact, not just test infrastructure.
A/B testing requires sufficient traffic to reach statistical significance — typically 1,000+ conversions per variant per test. For brands below this threshold, we shift the CRO approach toward qualitative methods: user interviews, usability testing with recruited participants, and expert heuristic reviews. These produce high-confidence recommendations that can be implemented without waiting for statistical significance. As traffic grows, we transition to quantitative A/B testing on validated hypotheses.
Our CRO team has run 1,000+ A/B tests across D2C brands in beauty, health, food, and lifestyle. Let's start with a conversion audit of your current funnel.