Our website uses cookies to help us to understand how you use our website and to provide you with advertising based on your use of our website. By continuing to use our website you consent to our use of such cookies. More information including how you can disable these cookies can be found in our Privacy Policy.

UX Analytics

Customers are curious, demanding and impatient. Negative experiences with a brand's website cause individuals to question future engagement. Read our 4-step process for what to do about it.

Categorisation

We start by creating segments so that we can see where the traffic is focused

Benchmarks

Benchmarks, KPI's and Targets underpin our approach

Prioritisation

We can now prioritise tests and changes against established metrics

Measurement

Tools such as A/B and Multivariate tests are used to measure effectiveness

20%

 

Increase in e-commerce revenue after 12 months of running the programme

x3

 

Increase in conversion rate at point of purchase

£10m

 

Incremental revenue over same period

Categorisation

The first step aggregates the large pool of data available into buckets. BY creating these segments we can reveal the relationship between the data points clearly.  Common categories are:

  1. Product
  2. Site Sections
  3. Audiences
  4. User Behaviour
  5. Marketing Channels
  6. Device Type

This identifies areas of opportunity and tells us where to focus our efforts.

Benchmarks

Once we understand the relationship between categories and conversion we can then set benchmarks and targets.  Benchmark examples include:

  1. Business Objectives
  2. Conversion Funnel Behaviour
  3. Bounce Rate
  4. Content Interaction

Prioritisation

With the first two stages defined prioritisation no longer needs to be guess work.  Once design commences it is best practise for the designer and analyst to work collaboratively and challenge each other's ideas:

  1. What problem is this solving
  2. What hypotheses are you trying to prove
  3. What does the design look like

Measurement

We recommend the use of A/B testing or multivariate tools to allow us to conclude with more certainty what the uplift is due to.  We use a combination of technologies throughout the process that include Adobe & Google Analytics to review this data, Clicktale & Google Optimize to inform it and typically Google Data to visualise it.

Start your UX Analytics conversation

With Jarmany on your team you are closer than ever to improving your performance with UX Analytics.

Start your conversation by calling us on +44 (0)203 051 4960 or email hello@jarmany.com.