Return appoints new CRO manager: Q&A with Abbie Senior

After 2 years’ experience within iProspect, part of the Dentsu Aegis network within the CRO and web analytics department I moved in house to focus more closely on understanding user behaviour. I moved to Kaplan, a global training provider to work within the UX department to help with the reconstruction of Kaplan’s previous ecommerce websites.

Return worked on Kaplan’s digital marketing which is where I started to build relationships ultimately leading to my current position as a CRO manager.

2) What attracted you to Return as a company and the role?

It was the ambition of the business that attracted me to the company, they have big plans and being a part of that growth both personally and for the business is what ultimately drove my choice and attracted me to the company.

Return are in the process of bolstering their senior leadership team to bring in more experience within other departments, this gives me the opportunity to work alongside other senior roles in developing and positioning CRO within the agency.

By joining Return I am shaping a new department developing new processes and building a team around my experience within the CRO and UX industry.

3) What are you looking forward to achieving within your role at Return?

Ultimately, I am looking to expand both the UX and analytics departments within Return. I am look forward to achieving growth within the CRO channel, ideally to pitch to those clients that return previously did not have the expertise to do so. I feel my presence can open the door to new opportunities which will allow Return to gain recognition within the industry.

What is conversion rate optimisation (CRO)?

Conversion rate optimisation (CRO) is a process of increasing the percentage of website visitors to take an action on your site that you want them to take. This can mean increasing the number of visitors that fill out an enquiry form, make a purchase or download an app.

CRO takes the current website traffic and aims to make most of it, ensuring that as many visitors as possible reach your website’s unique objectives (KPIs).

The process of conversion optimisation is about taking opinions out of design and using data to develop decisions that aid growth and improve performance. Primarily, a combination of web analytics and user testing are used to formalise hypotheses that are then A/B tested. It is about understanding why your visitors are not converting, and then fixing it.

The A/B testing process is a method using the data to fix the conversion problems and should include the following steps:

1. Data Analysis - Analytics and quantitative insights

A thorough investigation of your web analytics data should be conducted in order to identify conversions barriers that impact site visitors. This will be used in conjunction with heat mapping, scroll mapping and other tools to understand exactly what it is visitors are doing on the site.

2. Data Analysis - Qualitative insights

Once an understanding for which parts of the customer journey are working well or not are established, the motives behind understanding why is needed in order to try and address any problems. This can be in the form of customer surveys, moderated research and lab studies.

3. Hypothesis development

By identifying the problem areas and reason behind why they are potentially causing issues, tests can be developed to combat these areas. A hypothesis is usually a statement that states that by changing x, it will affect y.

4. Test development

By taking all of the insight and learnings from the previous steps, we can start to design a test strategy based on the hypothesis. How are we going to change the design to improve the performance? What can we introduce, move around or take away?

5. Live AB tests

When the test is live, it is measured against the baseline data gathered from steps 1 and 2. The data resulting from the test will inform the next steps and actions. It is important to consider the macro and micro conversions when running the test. How will changing a micro conversion aid other metrics on the site?

6. Post Test Analysis

Post analysis of the test is crucial as it is important to understand how the test impacted the site, and necessary for a successful strategy in improving performance. It is great that the test increased the number of visitors to the main KPI, but what if sales of a particular product fell, or call centre calls increased to an unmanageable amount?

If the test was successful and statistical significance was found, then this can be implemented into the live site or it can be re-tested to ensure it is as optimised as possible.

If the test was unsuccessful, this is not a failure. The next step in the process is key to gaining insight and understanding the potential reasons why it might have failed. If a test was unsuccessful, the learnings from it are still important, so do not be discouraged.