What maturity level are you at?

There are many ways you could attempt to measure conversion optimisation and experimentation maturity.
At Conversion.com our model focuses on strategic maturity and measures this against three key factors:

Experimentation goals

What are the goals of your optimisation programme?

Experimentation strategy

Where does your strategy for optimisation come from?

Data and technology strategy

How do you find the answer when a question is asked?

Take our short maturity assessment to see how you weigh up in each of these areas. It will take about 2 minutes to complete.

Check your maturity level

Answer the 10 questions below as best as you can to find out your maturity level. All questions are required.

 

1. What is the goal of your current experimentation activity?

2. Who in your organisation is invested in the idea of experimentation?

3. How are your priorities for experimentation determined?

4. What does your overall experimentation strategy look like?

5. What timeframes do you operate in when planning your experimentation strategy?

6. Who is involved in the generation of hypotheses for experimentation?

7. For an individual experiment, how much data generally supports the hypothesis?

8. How connected is one experiment to the next?

9. How do you measure the results of your experiments?

10. What is your approach to user research?

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Your overall maturity level

Your overall experimentation maturity level

Getting started

Developing

Intermediate

Advanced

Expert

Experimentation
goals

Getting started

Developing

Intermediate

Advanced

Expert

This factor can be characterised by the question - what are the goals of your optimisation programme?

At this level you're probably still trying to get experimentation off the ground so your goal might just be to run your first experiment or get your first positive result.

Developing your maturity in this area involves shifting the scope of your goals and developing alignment of the goals of experimentation with the overall goals of your business. Moving from goals being about short-term results and impact on KPIs, towards being about answering business questions and informing business decisions and strategy.

This factor can be characterised by the question - what are the goals of your optimisation programme?

At this level your main goal for experimentation might be to show impact and a positive return on investment to secure further investment and to grow your programme. Another key goal might be to build momentum - reducing the time it takes to launch an experiment to allow you to move faster.

Developing your maturity in this area involves shifting the scope of your goals and developing alignment of the goals of experimentation with the overall goals of your business. Moving from goals being about short-term results and impact on KPIs, towards being about answering business questions and informing business decisions and strategy.

This factor can be characterised by the question - what are the goals of your optimisation programme?

At this level you likely have a key business metric that you're trying to impact through experimentation and so your goals are aligned to that. You also want to spread experimentation through the business to broaden its reach.

Developing your maturity in this area involves shifting the scope of your goals and developing alignment of the goals of experimentation with the overall goals of your business. Moving from goals being about short-term results and impact on KPIs, towards being about answering business questions and informing business decisions and strategy.

This factor can be characterised by the question - what are the goals of your optimisation programme?

At this level your goal for experimentation is more than to just deliver an uplift in key metrics. Your focus shifts to begin to solve key business problems using experimentation.

Developing your maturity in this area involves shifting the scope of your goals and developing alignment of the goals of experimentation with the overall goals of your business. Moving from goals being about short-term results and impact on KPIs, towards being about answering business questions and informing business decisions and strategy.

This factor can be characterised by the question - what are the goals of your optimisation programme?

At this level experimentation is inseparable from the strategy of the business and so the goals of experimentation are to deliver the goals of the overall business.

Developing your maturity further is about pushing the boundaries of what you can experiment with. Can experimentation be used in offline situations as well as online? Can product be experimented with? Can pricing, discounting and commercial strategy be dictated by the results of experiments in the so called real world?

Experimentation
strategy

Getting started

Developing

Intermediate

Advanced

Expert

This factor can be characterised by the question - where does your strategy for experimentation come from?

At this level you are likely just starting to explore experimentation, you may not have thought too much yet about an overall strategy. You're probably generating your hypotheses largely on gut-feeling or around fixing known problems.

Developing your maturity in this area relies on having a clear goal for experimentation, so if you haven't already then you should spend some time defining what you want to achieve. With a clear goal in mind you can then set out a plan for how to achieve it. At this level that might be recognising where you need to focus your experiments to have the greatest impact, and starting to look at ways to prioritise experiments and how you allocate resources to them.

This factor can be characterised by the question - where does your strategy for experimentation come from?

At this level, experimentation strategy tends to be largely tactical in nature, with ideas generated on an ad-hoc basis and experiment prioritisation based on most urgent priority or a simple impact/ease model.

Developing your maturity in this area requires taking steps away from gut-feel and towards data and insight as the driver of your experimentation strategy. User research will start to expose the key conversion levers impacting a user's likelihood of converting and focusing experimentation on addressing those levers to understand what moves the needle and what doesn't is the next strategic step.

This factor can be characterised by the question - where does your strategy for experimentation come from?

At this level you probably have a solid roadmap of experiments and a strong handle on where you need to focus experimentation to deliver the most impact. Each experiment is treated as an individual exercise and when an experiment is concluded you move on to the next experiment in the list.

Developing your maturity in this area means starting to group experiments into more strategic themes or projects. Optimisation strategy becomes more thematic. Experiments are considered now as one tool for exploring a specific theme or conversion lever. At higher levels, experimentation strategy is organised as a series of projects, each made up of a combination of targeted user research pieces and experiments. These projects align to business strategy, and experimentation starts to play a more leading role in overall business strategy.

This factor can be characterised by the question - where does your strategy for experimentation come from?

At this level you likely have a solid grasp of your experimentation strategy in both the short-term and over the longer-term. Experimentation is organised around themes or key focus areas in alignment with team or department goals or targets.

Developing your maturity even further in this area means starting to explore the wider potential role experimentation can play. Expert optimisation teams view testing not as a tool for increasing conversion rates but as a tool for answering questions. Starting with the big picture, they identify the business questions that need to be answered. They then break these problems down to define the tests and research that they need to complete to validate their hypotheses and answer that question.

This factor can be characterised by the question - where does your strategy for experimentation come from?

At this level your strategy for experimentation is significantly advanced. Experimentation is closely aligned with business strategy and is delivering impactful insights into key business problems.

At the highest levels, experimentation strategy is indistinguishable from business strategy, with experiments used as a tool for answering complex business questions. If you're already at this level then developing maturity even further means looking for how experimentation can have an even wider impact and how a culture of experimentation can be fostered throughout your organisation to accelerate this process.

Data & technology
strategy

Getting started

Developing

Intermediate

Advanced

Expert

This factor can be characterised by the question - how do you detect and measure the things that matter?

If your goal is just to get some experiments live, ensuring those experiments have a solid grounding in data can end up as more of an afterthought. Ensuring the data the experiments produce when they do run is reliable and actionable is the other piece of the puzzle.

Developing your maturity in this area is about realising that the quality of data and insight that supports an experiment directly impacts the quality of that experiment. The specific tools you use to carry out user research aren't important. Your focus should be on ensuring that you trust and can make actionable the data they generate. When it comes to experiment tracking and analysis you want to make sure you're being strategic and planning your primary and secondary KPIs in advance.

This factor can be characterised by the question - how do you detect and measure the things that matter?

You're likely already using analytics data to identify where you should be running experiments for the most impact but a common problem at this level is knowing where to experiment but not having data to tell you what to change and why.

To develop your maturity here look for how you can gather more qualitative data on user-behaviour and start to use it to inform your experimentation. Surveys, usability-testing and customer interviews can be great sources of data straight from the horse's mouth and will very quickly tell you why your users aren't taking the action you want them to. If you can start to connect these tools to your experiments to see how behaviour in the variations differs then you'll have significantly more actionable data than before.

This factor can be characterised by the question - how do you detect and measure the things that matter?

You're using both quantitative and basic qualitative data to support your experimentation hypotheses. You're tracking the impact of your experiments through the whole funnel and on secondary metrics that might be impacted by your changes.

The next step for developing your maturity here is to explore how you can greater connect your data tools to deliver greater quality of insight that one advanced but isolated tool couldn't. Start with your experimentation tool, and connect it to any other tools you have such as surveys, session recording and heatmaps. In particular, connect it to your back-end reporting systems so that the impact of experiments can be measured against the KPIs that really matter, and that people look at on a daily basis.

This factor can be characterised by the question - how do you detect and measure the things that matter?

You've an advanced analytics setup, potentially with experiments integrated directly with back-end financial reporting to understand the true impact of each experiment. You're using a combination of quantitative and qualitative data to support your hypotheses.

Maturity here is being confident in your data so that you can challenge it, ask probing questions of experiment impact, and be able to confidently produce the answers. Advanced optimisation teams will put emphasis on making experiment data a valuable source of insight for the business that's available and actionable.

This factor can be characterised by the question - how do you detect and measure the things that matter?

Developing your maturity further here, assuming your tools and technology are already connected and reliable, focuses on the availability of that data and how actionable it is. Can anyone in the business quickly and easily get the data they need to support their hypothesis, estimate their experiment's impact or analyse the findings of their experiment? Breaking down the walls between data silos and getting more value from the data you collect should be an ambition for any organisation trying to take experimentation to higher levels.

Looking to develop your experimentation maturity further? There's a lot more to it than we could fit on one page. Get a free experimentation consultation by requesting a call back below and we'll be in touch as soon as possible.

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