Optimizely is perhaps the most advanced of the A/B testing software tools out there and one that we suggest to clients all of the time for the conversion rate optimisation power and experimentation possibilities it offers.
But if you have a team of developers working on your split tests, it can take some management to know what’s going on everywhere at once. So we’ve rounded up our best Optimizely split testing features for 2019:
Optimizely launched a free new feature, called Optimizely Rollouts, which allows your team to work faster and smarter together through Feature Flags.
Feature Flags in action, the core part of Optimizely Rollout
One of the key benefits is to simplify messy rollbacks and hotfixes. Instead, you could use feature flags to roll out to a small percentage of users to reduce risk and fail safer. If you detect errors, performance spikes, or user backlash, just roll back – all without redeploying code, thereby making your CRO program that much more resilient.
You can also test new features in production before a broad rollout to help you innovate faster by validating new features with a percentage of your users or key segments before rolling out to everyone. What’s more, you can free up engineering time by allowing business users to grant access to features to early access or beta customers as there is no coding required.
Of course, all of this can be managed through a simple, intuitive front end interface (which also integrates with Jira) providing full visibility to all stakeholders.
Optimizely Rollout has a simple, intuitive interface for all stakeholders to clearly see what is happening at any time
Source: AWA, August 2019
Adaptive Audiences aims to give marketers an entirely new way to personalise user experiences
It does this by giving you the control of rules-based targeting, yet with the reach and scale of automated personalisation. The idea is to use machine learning to match people with dynamic audience segments – not rigid rules – based on real-time user behaviour. Meaning you can target people based on their interests to give you better relevancy.
This could be a really nice balance. Currently, there are two types of personalisation tech around: rules-based targeting and automated 1:1 personalisation – and both approaches have their positives and negatives.
Rules-based targeting defines personas such as “people who have browsed a holiday in Spain more than 3 times in 7 days”, which can be very powerful. But it is also very labour intensive as you need analysts to constantly monitor behaviours and keep up with changing consumers. With automated 1:1 personalisation you’d create dozens of different user experiences upfront and let an algorithm decide when to feature each one. Good in theory, but that’s why our Spain traveller above would now get followed around the web for 3 months being shown pictures of paella. And, as a consumer, that can rapidly get tiresome.
Adaptive Audiences works on interest-based targeting
So, when we saw that Adaptive Audiences gives you a blended approach that combines machine learning with human insights we got a bit excited. At its core, automation is there to turn long-winded processes into quick and easy ones. But when it comes to our visitors experience, we want to stay in control to ensure conversions are being maximised. At least a little bit anyway and Adaptive Audiences seems to offer the right blend.
One of the key benefits though is in the speed of set up. Most personalisation workflows require that you spend weeks or months assembling, integrating and maintaining audience data and complex rules engines. That’s why so many automation programmes never get much out of first gear. However, Optimizely Personalization works with the data sources you’re already using today. So you can now combine their automated machine learning with your own 1st or 3rd party data to extend your reach.
It works with all of your existing data sources to make setup much quicker
Of course, this is Optimizely, so everything is a test with all their normal reporting and analysis to help you gain further insights to continually improve your personalisation.
Source: AWA, July 2019
Speed matters on the web. And, as mobile traffic continues to grow year over year, it matters even more on the mobile web. Users expect the same experience on mobile devices as they do on desktops. In 2019, it’s clear that the mobile web is in need of performance and user experience improvements.
Luckily, Optimizely seem to be on a one-company mission to solve these issues. Last year, they became the first experimentation company to provide out-of-the-box support for dynamic websites. This month, they have announced another first – they are the first experimentation company to extend support to AMP.
Optimizely in action
If you’re unfamiliar with AMP, it’s an open-source project spearheaded by Google to make the web incredibly fast. You’ve probably experienced this technology before on your own devices – when you click on a link, you don’t have to wait for the article to load because it’s been preloaded natively.
But, of course, many of the biggest winning tests require much more than that. With this latest update, you will now be able to run sophisticated A/B tests created in the Optimizely interface on any AMP pages.
That’s a big boost as it will help encourage big brands and ecommerce stores to embrace AMP without sacrificing their testing program – both of which can only help make the mobile web a much better experience for all of us users.
Source: AWA, May 2019
If you want to learn more about conversion rate optimisation, read our Advanced Guide to CRO. This guide shares nearly a decade’s worth of experience of increasing online sales and revenue for multichannel businesses to empower you with the skills and knowledge to transform your business.
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