The goal of personalization is to develop long-lasting relationships between customers and brands through authenticity, relatability, and contextual relevance. Through one-to-few and one-to-one personalizations, brands can create moments that excite and engage their customers, giving them a sense of personal attention that mirrors the personal shopping assistant, so effective in bringing customers back to the same store again and again.
A/B testing is the application of a framework to compare two versions of a website to see which is performing better. Personalization refers to the techniques employed to make online experiences more relevant to customers.
A/B testing provides a tool for measuring the effect your personalization efforts have on key site metrics such as conversion rate (CR) and average order value (AOV), by comparing one version of your website with the banner, product badge, or a control version of the same website without the banner or product badge, for example.
By looking at the behavior of customers that saw the personalization and comparing it to the behavior of those customers that didn’t, we have the foundation to make statements about which performed better. With this data to hand, merchandisers have the confidence to roll-out personalizations to a greater proportion of your customers or even sitewide.
Many of the leading brands that have adopted personalization as part of their strategy for doing online business, begin their personalization journey by thinking big but starting small.
With a clear vision and well-defined short and longer-term objectives, adopters of personalization rely on A/B testing to quickly iterate through the range of personalization solutions to find out what works best for their customers and at what point in the customer journey. Being data-driven is key. Data gives online businesses the tools to understand their customers and identify trends and patterns.
The best way, therefore, to discover what tactics to use on your website is to:
Your decisions around which segments to target, for example, might be based on a hypothesis that you wish to test, a promotional campaign with particular appeal to a group of users, or data surfaced by Visitor Pulse, for example. You may even choose to target users based on the results of a previously run experience that highlights the need for an advertising campaign for example.
Before launching an experience, make sure you have a clear idea of what you are trying to achieve. Goals are a great way to do this and provide the basis for an A/B test
Just because a tactic works for a brand operating in the ecommerce space, doesn’t mean the same tactic will work equally as well for a brand operating in a different space. Equally, a tactic that works for a brand might not work for a brand operating in the same space.
The answer therefore to the dilemma of what tactics to choose is to find out what works for YOUR business. The combination of your website, products, and certainly your customers and their behavior will be unique, so relying on what works elsewhere might not be the most prudent course of action. Experiment, rely on a robust A/B testing methodology to demonstrate what works and what doesn’t and make data-driven decisions to drive personalization for your business.