Conversion Rate Optimisation & Personalisation
We run the experiments that establish why a journey is not converting, and build the personalisation that acts on the answer. Both start from your customers’ behaviour rather than from a design opinion.
Tell us what is not converting, what you have already tried, and which testing tool you are running. We will tell you where we would start.
The Client’s Situation
The journey is not converting and nobody can say why
The conversion target is being missed and the reasons are a matter of opinion. There are ideas about the landing page, several of them perfectly reasonable, and no agreed way to establish which is right. Analytics shows where people leave. It rarely explains why, and a decision still has to be taken this quarter.
Often the tooling is already in place. A testing platform was bought, a handful of experiments ran, and then the programme stalled, because running one properly needs hypothesis design, build, quality assurance, statistical judgement and somebody to own the roadmap. Very few marketing teams have all of that spare.
The personalisation ambition sits in the same position. Everybody agrees customers should see content relevant to them. What is missing is the behavioural data, the segmentation and the triggers that would make it happen, which makes it a data problem some time before it becomes a content one.
What changes when the programme is actually running
Talk to usDesign arguments get settled by evidence
Competing ideas about a page or a journey become an experiment with a result, so the decision stops depending on who is most senior in the room.
The tool you already bought starts earning
Hypothesis design, build, quality assurance and analysis are the parts most stalled programmes are missing, and they are what turns a licence into a steady rate of experiments.
Tests that reach a conclusion
Experiments sized and run long enough to be statistically confident, so a result can be acted on rather than argued over for another month.
Personalisation based on behaviour rather than assumption
Segments and triggers built from what customers actually do, with propensity and cancellation modelling where the data supports it.
A capability your team can keep
Upskilling is built into the programme where you want it, so the practice stays in-house rather than depending on us indefinitely.
What the work covers
1
Experimentation
Strategy, ideation and hypothesis design, then build, quality assurance and implementation across A/B, multivariate and recommendation experiments.
2
Analysis and reporting
Experiment analysis and statistical interpretation, reported with a clear recommendation for the next step rather than only an account of what happened.
3
Personalisation and marketing automation
Data-driven triggers, segmentation and automated journeys, including advanced modelling such as propensity to buy and cancellation risk where the behavioural data supports it.
4
Marketing technology implementation and integration
Implementing the optimisation and personalisation stack and connecting it to the rest of your marketing technology, so a segment built in one place can be acted on in another.
5
Programme governance and upskilling
Ways of working, prioritisation, roadmap governance, and training in-house teams to run the programme themselves.
Turn your data into a competitive advantage.
Whether you’re trying to prove marketing performance, modernise enterprise reporting, or build a stronger data strategy, we’ll help you create analytics that deliver measurable business value.
Audit first, because the data has to be trustworthy before anything else matters
We audit what you already have
A technical audit of the current optimisation setup, validation of the tracking and measurement behind it, and an honest assessment of how mature the programme is. If the measurement is wrong, every experiment built on it is wrong too.
We agree what we are optimising for
Your business and product objectives, and a review of how any current activity aligns with them. This is where a programme that has been running on inherited assumptions usually gets redirected.
We build a prioritised roadmap
A roadmap for optimisation and personalisation maturity, with experiments prioritised against business ambition rather than against ease of implementation. The cheapest test to build is rarely the one worth running.
We run the cycle
Analyse, implement, learn, repeat, improve. Experiments are built, launched, measured and interpreted, and what we learn from one shapes what we run next rather than being filed as a result.
We hand the practice over where you want it
A structured upskilling programme for your in-house team, and agreed ways of working so the cycle continues whether or not we are running it.
Every recommendation here comes out of behavioural data rather than a design opinion, which is why the first thing we do is establish whether that data can be relied on.
CX & Marketing
Why organisations bring us in
Start with what the data will actually support
Whether the programme has stalled, never started, or is running without anyone able to say what it has proved, the first piece of work is the same. We look at the tool, the tracking behind it, the traffic you have to work with and what the business is trying to achieve, then tell you what a realistic programme looks like from there.
What do our clients say?
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Questions we are asked
Do you have examples of increasing conversions for your clients?
Yes, across call centre deflection, marketing automation, retargeting and journey optimisation, in sectors including financial services, travel and gaming. The results are published as case studies rather than listed here, because a figure means very little without the context of what was tested, over what period and against what baseline.
Can you build and run experiments on our behalf?
Yes. We can take the whole cycle — ideation, hypothesis design, build, quality assurance, launch, analysis and the recommendation that follows — or any part of it alongside your own team. A common arrangement is that we run the programme while training your people to take more of it over.
Do you work with our existing testing tool?
Usually. We work across Adobe Target, Optimizely, AB Tasty, VWO and Dynamic Yield, and the first question is whether the tool is implemented correctly rather than whether it is the right tool. A surprising proportion of stalled programmes turn out to have a measurement problem rather than a platform problem.
How many experiments should we be running each month?
Fewer than most people expect, and the constraint is almost never a shortage of ideas. It is traffic: a page needs enough visitors for a difference to be detectable, and running more experiments than your volume supports produces results nobody should act on. We would rather agree a realistic rate from your actual traffic during the audit than quote a number that sounds ambitious.
How long does a test need to run before we can trust the result?
Long enough to reach statistical confidence, which depends on your traffic, your current conversion rate and the size of the difference you are trying to detect. Small improvements on low-traffic pages take considerably longer than people expect, and stopping early because a variant looks ahead is the most common way a programme produces results that do not survive contact with reality. We size each experiment before it launches, so the answer is known in advance.
Can you audit our current setup?
Yes, and it is usually where we start. The audit covers the technical implementation of the optimisation tool, the tracking and measurement behind it, how mature the programme is, and whether what is currently being tested aligns with what the business is trying to achieve.
Can you train our team to run this themselves?
Yes, and we would rather you asked. Upskilling is a defined part of the programme where you want it, covering the tool, the statistical judgement and the ways of working that keep a cycle going. A capability that stays with you is worth more than a dependency on us.
Start with what the data will actually support
Whether the programme has stalled, never started, or is running without anyone able to say what it has proved, the first piece of work is the same. We look at the tool, the tracking behind it, the traffic you have to work with and what the business is trying to achieve, then tell you what a realistic programme looks like from there.
London Office
51 Lime Street
c/o HCR Law LLP
London EC3M 7DQ
United Kingdom
Zagreb Office
Centar 2000
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10000 Zagreb
Croatia
Tell us which testing tool you use, what is not converting, and whether you have a programme running today. A consultant who runs these programmes will come back to you.
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