DATA-DRIVEN SOLUTIONS
Better results through A/B Testing
In modern society, companies in almost all sectors have to respond to changes ever faster. This makes making fast, smart decisions more important than ever. Using all available and relevant information is therefore hugely important. Companies that use this 'data' optimally have a big advantage over their competitors who do not.
Yet many entrepreneurs think that data solutions are complicated, expensive or only for large companies. That doesn't have to be the case at all.
Simple data-driven methods like A/B testing show that data-driven decisions are attainable, regardless of the size of the business. In this article, I explain what A/B testing is, how it works, and how it can help companies from small to large across many industries achieve better results.
WHAT IS A/B-TESTING
A/B testing is a simple data-driven method where you compare two versions of something - for example, a website page, an email or a menu - to see which performs better. By measuring and comparing this performance, you can discover which version works best to achieve your goals.
Here are a few example situations to clarify how A/B testing works:
- You test two email topics to see which version gets opened the most
- You compare two versions of your website to see which one generates the most sales
- You test two different pricing packages to find out which generates the most sales
- You compare two versions of a menu to see which one generates the most sales and profits
What all these examples have in common is that data plays a central role. By measuring and analysing results, you can make better choices. A/B testing takes the guesswork out of decision making, and gives you confidence in the effectiveness of your choices.
Although some companies opt for very complex methods, A/B testing is a flexible method that can be used by both small and large businesses. I outline below an example of how even small businesses without large investments can benefit from A/B testing
A/B-TESTING BUSINESS SCENARIO
Imagine this: a local restaurant-café wants to increase their profits by serving the highest-margin dishes more often. They suspect that adjusting their menu might influence guests' choices.
The restaurant-café runs an A/B test with two versions of their menu:
Version A: The current menu with simple categories such as starters, main courses and desserts
Version B: A revamped menu with a special category called 'House Specialties', highlighting the dishes with the highest profit margins. These dishes will be given distinctive names and presented visually more appealingly
The test is conducted over a four-week period. Guests are randomly distributed among the tables, and each table has one of two versions of the menus during the weeks. By linking the bills and the POS system to the table number, the results of the A/B test can be easily measured.
After the test, it appears that Version B performed significantly better than Version A:
- Sales of dishes from the 'House Specialties' category increased by 28%
- Average revenue per guest increased by 6%
- Average profit per guest increased by 9% due to higher profit margins from 'House Specialties'
Through these insights, the restaurant found an effective way to increase their profits. This experiment shows how small, data-driven adjustments can have a big impact on business results.
conclusion
This example shows how small, data-driven experiments like A/B testing can have a big impact. It is a simple but powerful tool that can be accessed by any business, regardless of size or industry.
Wondering how A/B testing or other data-driven solutions can help your business? Contact me for a free consultation! Together, we will discover what opportunities exist for your business and how data can take your business to the next level.
