Conversion Rate Optimisation (CRO) is a technique designed to increase the number of prospects converting to customers in an online shopping experience.
Online, conversion rates tend to be a lot lower than in retail. So to make the most of your traffic, you will need to analyse your website data in order to find out whether your site is effective in aiding these conversions or not.
Google analytics, adobe analytics and others can be used to flag poorly engaging areas on your website. Typically these will be steps in the online purchase process. Once you have gathered adequate data, use this to guide a hypothesis for an A/B or a multi-variant test.
Test whether changes to your content, creative or CTA’s make an impact on your conversion statistics.
You need to fully understand your user’s behaviour in order to work through what will drive them through the conversion process. Questions like: at what point should you inform and at what point should you hit hard on the sell? Remember not all prospects will be at the same point in the conversion funnel, so cater for this in your testing.
Ensure behind all tests there is structure, this enables you to observe, build, measure and learn quickly what is actually happening. Approach your testing with a strong hypothesis, otherwise you could find yourself testing random variations which turn out to be insignificant. Define success in order to identify what behaviours you want to create (these will tell you what metrics to measure). Link CRO successes back to your overall business goals.
Fortune favours the brave in conversion rate optimisation
Take a proactive approach when implementing tests. Once you have informed data hypotheses don’t hold back, it is a fail fast, learn quick environment. It is best to be ambitious as this is where you will make your biggest learnings which can then be adopted across multiple pages on your site.
CRO applied in the right way will help you achieve your overall business objectives and improve low performing KPIs.
What does conversion rate optimisation best practice look like?
It is always best practice to start with analysing web traffic. Your goal is to identify high abandonment points in a customer’s shopping journey. Key data points you will need to consider:
- Conversion rates and micro conversion rates
- Average time on page
- Bounce rates
- Exit rates
- Click through rates on calls to actions
Once you have amassed your data insights it is important to look at areas onsite where you can shape your traffic and move shoppers further down the conversion funnel.
You might like to look at the following:
- Are your CTA’s visible and engaging?
- Is the website optimised to help prospects navigate the site, leading them to hit the different stages of the shopping journey
- Prioritise tests based on what you think will make the biggest impact – create a plan identifying audiences and prioritise based on importance
- Launch tests live onsite making sure changes are controlled so results can be monitored
- Could your site be changed to improve UX?
After gathering the data above you should be in a position to create a testing plan.
Testing is key to optimisation
Tests are easily built with the drag and drop tool these days. There is no need to code these things anymore. Results are generally captured in reports identifying the winning and losing variant.
Statistical significance is used to measure your tests, reducing the likelihood that the results are down to chance. If you reach 95% statistical significance you can be confident that your results are not as a result of chance.
How conversion rate optimisation differs from live stream shopping optimisation
Conversion rate optimisation on a website is about changing self service infrastructure. You have thousands, even millions going through an online shopping experience. as a result, you are building a large scale self service tool to cater to everyone. You are finding barriers to purchase and you are trying to break down those barriers.
Livestream shopping creates an environment where can adapt to shoppers needs instantly. A human is far more adaptive to customers needs in a live stream environment. You can watch reactions and use emotional intelligence to respond to customer needs.