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 is enhancing the user experience but is also driving 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 when people of all generations are surfing through the internet looking for some sort of services they need their online experience tailored/ aligned to their needs and preference. While an increase in personalization guarantees growth in customer engagement and experience, but that’s not all the customers toward the conversion.

Sure personalization makes the users feel like an individual even if the product or service is marketed the same for targeting the right audience 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 Rate Optimization (CRO) is the relatively recent discipline to drive more conversion. A/B is one of the best CRO’s 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 provides guidance to your personalization practices. You can create scenarios and have ideas what your customer’s interest are but with the help of data you can prove your ideas right or wrong. Even Netflix before any product change implements a robust A/B testing process before becoming the default user experience.

Stakeholders can have different opinions and ideas about what wants or A/B testing lets the data do the talking. Let’s take an example of an e-commerce website where A/B testing can help to find the single best performing page to show all users. For better success, a mix of testing mentality while you do personalization goes a long way. You can test potential personalization using by setting up an audience for each segment and then A/B testing within that audience.

Let’s understand this example better- Company X runs an e-commerce website which sells sweaters with and without logos. . But since you have different colors in the same product you want to see the impact of different color on the sale of the same product. So you run an A/B testing where a third of your users the green sweaters, a third red, and a third rated drastically improve for the red colored sweater. Blue also did your green was the worst performing. 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 to a say 65% of your users preferred red sweaters, 30% blue, and just 5% red. 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 and color which people chose according to their taste? 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 tailored 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 logo image on the sweater to the path of conversion for the users which want specific sweater color with the logo 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.

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.

There are many strategies that are helping the companies change the user experience and customer approaches such as personalization, customer journey and Artificial Intelligence (AI) but 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 also formulate ways to improve and apply those 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 to check out and beyond. A/B testing can be your first solid step towards truly personalizing your customer experience from recommendation, offers campaigns by revealing audience response to different experiences.

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