Every engagement starts the same way. You do not need to know what is wrong - that is our job. The process is designed to move from diagnosis to outcome with clarity at every step.
We meet your team. We assess your stack, your data, your key events, and the baseline visitation behaviour. This is a full present-state analytics assessment - no assumptions, no shortcuts. The output is a diagnosis and a clear proposal for what comes next.
Conversations with your product, engineering, marketing, and sales teams to understand goals, constraints, and what has been tried before.
A comprehensive review of your existing tracking, data quality, and event architecture. What are you measuring? What are you missing? How trustworthy is the data?
Establishing the current state of visitation behaviour - where people come from, what they do, where they drop off, and what the existing conversion rates look like.
Identifying the highest-impact opportunities for optimisation based on the data, the business model, and the volume of visitation at each stage of the funnel.
A diagnostic report and proposal: what we found, what we recommend, and a clear scope for the Engineering phase. You decide whether to proceed.
We work with your teams to implement the analytics and tracking technology required to conduct experimentation. Server-side tracking, event architecture, platform integrations - bespoke to your stack. We do not change anything yet. We layer on the technology, observe, and identify the pages and flows to work on.
Implementing server-side event collection to capture the data that client-side tracking misses. This is the visibility layer - the foundation everything else depends on.
Designing and deploying a structured event taxonomy that captures the actions of value, micro-conversions, and behavioural signals specific to your business.
Connecting PostHog, GA4, Google Ads, Meta Ads, and any other tools in your stack. Ensuring data flows cleanly and attribution is accurate.
Once the technology is live, we observe. New data flows in, patterns emerge, and the experiment targets become clear. Nothing changes on the site yet - we are building the evidence base.
A fully instrumented analytics stack, a baseline data set, and an experiment roadmap - the prioritised list of experiments to run in the next phase, ranked by expected impact.
We design and run experiments in collaboration with your team - from macro strategic changes to micro interface adjustments. Every experiment has a defined hypothesis and a measurable outcome. This is where the optimisation happens.
Every experiment starts with a clear hypothesis: if we change X, we expect Y to happen, and we will measure it by Z. No experiments run without defined success criteria.
A/B tests, multivariate tests, and self-learning experiments - the right tool for the right question. Convert manages the build, the deployment, and the statistical analysis.
Every experiment produces learning, whether it wins or loses. Convert documents findings, shares insights with your team, and feeds results into the next round of experiments.
Winning experiments are implemented permanently. Convert works with your engineering team to ship validated changes - or ships them directly when embedded.
Measurable uplift. Validated changes shipped to production. A growing body of evidence about what works for your specific audience, product, and market.
Tell us what you are seeing - or not seeing. The exploration phase is designed to meet you where you are, not where you think you should be.
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