Anush Kumar Anush Kumar
Anush Kumar is the Director Consulting Sales at Sigmoid. A seasoned veteran and consulting sales leader, Anush loves to write about technology and innovation.
Anush Kumar
Anush Kumar is the Director Consulting Sales at Sigmoid.
A/B testing + Personalization = Better Customer Experience

Personalization is the new powerful trend that not only enhances the user experience but also drives the e-commerce and retail industry. Be it increase in customer engagement, improvement in conversion rates, increase in sales or growth of revenue, personalization does it all.

Today people of all generations use internet for different services and applications. One necessity which is common between all age groups is online experience tailored to their needs and preferences. While an increase in personalization guarantees growth in customer engagement and experience, but that doesn’t assure customer conversion. 

Sure personalization makes the users feel like an individual even if the product or service is marketed the same for targeted audience, it is also necessary for personalization to work better. Personalization has to work in tandem with other optimizing strategies and techniques for online stores and e-commerce sites to do Conversion Rate Optimization (CRO). It is the relatively recent discipline to drive more conversion. A/B testing is one of the best CRO’s technique which aligned with personalization can provide higher conversion rates and better performance.

A/B testing allows you to use your data to make informed decisions and guides your personalization practices. You can create scenarios and have ideas about what your customer’s interest are but with the help of data you can prove your ideas are right or wrong. Even Netflix, before any product change, implements a robust A/B testing process before becoming the default user experience.

Different stakeholders involved in a project can have different opinions and ideas about what they want or which approach is right. A/B testing lets the data do the talking and provide concrete results. For example, an e-commerce website can use A/B testing to find the single best performing page or products to show all its users. For better success, a mix of testing mentality while you do personalization goes a long way. Personalization can be tested easily by setting up an audience for each segment and then doing A/B testing within that audience.

Let’s take this example- You run an eCommerce website which sells sweaters with and without logo. But since you have different colors in the same product you want to see the impact of different color on the sale of the product. So you run an A/B testing where a third of your users select the green sweaters, more than one- third select red, and remaining selected blue. A/B testing resulted in drastically improve rating for the red colored sweater. Blue and green was performance was not at par with red. In traditional A/B testing, these results might lead you to display the winning red sweater image to all users, as this has the best chance of leading people(say 65%) of your users preferred red sweaters, blue(say 30%), and blue (5%). So even though you’ve optimized for the majority, there’s still 35 % of visitors that are not instantly attracted by your logo image and in danger of bouncing straight off your site.

What if you knew each color user preferred and identify those sweaters with a logo? This can be achieved with the help of personalization.

Personalization uses learning techniques and data to identify what is most likely to appeal to each user and at the same time ensuring the content on the site is individual and customized just for the user.

If you notice A/B testing has served an important purpose in the above example. It has indicated the significance of the colour of the sweater to the path of conversion for the users which want specific sweater color while using personalization to make the content specific (here preferred sweater color with the logo or preferred sweater color without logo) to each visitor. This audience segmentation can help to ramp up the persuasion up to another level. A/B testing can provide proof of concept and help direct your optimization strategy before you decide where to focus time and resources on delivering personalized experiences.

Companies are implementing many strategies to change the user experience and customer approaches such as personalization, customer journey and marketing attribution. In midst of all these strategies,  A/B testing and optimization should not be ignored. A/B testing not only allows you to use your data to find areas ripe for opportunity but also formulate ways to improvement. A/B testing can help you to leverage your hypotheses to learn from your results and to gain actionable insights from your data. It helps you to optimize user experience from start to finish- from the landing page to product information, check out and beyond. A/B testing can be your first solid step towards truly personalizing your customer experience and win their loyalty.

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