Test optimisation is a central component of successful projects today. With targeted experiments, decisions can be made based on data and continuously improved. Test optimisation is becoming increasingly important, especially in the area of digital offerings. Many clients come to us with the question of how they can make their offerings more effective. This often involves increasing interactions, improving user experiences or increasing conversion rates. With the right support and a structured approach, test optimisation is a sustainable success.
What is test optimisation?
Test optimisation means testing different variants of an offer against each other. Individual elements are changed and the effects on user behaviour are measured. The aim is to find out which variant performs better. This means that decisions are no longer based on intuition alone, but on concrete data. Test optimisation helps to make targeted improvements and to learn continuously.
Examples from practice
For example, an online shop tests the colour of a call-to-action button. Variant A shows a green button, variant B a red one. The click rate is measured to see which colour encourages more users to click. Another example is the subject line of a newsletter. Here it is tested whether a personalised approach or a neutral formulation achieves more opens. The position of a form on landing pages can also be tested in order to increase the number of contacts.
Test optimisation in the process
A structured process is crucial for successful test optimisation. Firstly, the goal is defined. What is to be improved? Then a hypothesis is formulated. Why could a change lead to better results? The variants are then created and tested. The results are analysed and the best variant is adopted. This cycle can be repeated again and again in order to optimise continuously.
Practical tips for test optimisation
Prioritise your test ideas. Not every change has the same impact. Use frameworks such as ICE to assess the potential impact, confidence and simplicity. Document all test ideas and hypotheses centrally. This way, all team members can participate and priorities become transparent. Test only one variable at a time to get clear results. If you want to test several elements, use multivariate tests.
Test optimisation and iROI coaching
iROI-Coaching supports test optimisation projects. Many clients come to us with the challenge of improving their offerings based on data. Together, we define goals, formulate hypotheses and carry out tests. The results are analysed and translated into concrete measures. This results in a continuous learning process that leads to sustainable improvements.
Examples from the accompaniment
A client from the e-commerce sector wanted to increase the conversion rate of its product page. A hypothesis was jointly developed: The product description is too long and off-putting. A shorter, more concise version was tested. The results showed a significant increase in the conversion rate. Another customer from the B2B sector tested different formulations for their contact enquiry. The variant with a personalised approach generated more enquiries. A third customer from the education sector tested the position of a registration button on their landing page. The variant with the button at the top of the page led to more registrations.
BEST PRACTICE with one customer (name hidden due to NDA contract) and then the example with at least 50 words.
My analysis
Test optimisation is a powerful tool for making data-based decisions and continuously improving them. With a structured process and the right support, sustainable improvements can be achieved. Test optimisation helps to make targeted improvements and to learn continuously. Many clients report positive experiences and measurable results. Test optimisation is a central component of successful projects.
Further links from the text above:
6 A/B testing tips for more success when experimenting
How A/B tests work: Step-by-step process for ...
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