A/B testing or split testing is the practice of showing two different versions of a page to users to determine which one performs better. Learn about A/B testing tips and best practices that companies have used to improve conversions on their websites and mobile apps.
This post originally appeared on the BBC Data Science Blog. When speaking of optimization, most of us will think about increasing conversions and revenue in e-commerce, otherwise known as CRO (conversion rate optimization). More and more though, media and services brands are using experimentation as a means for increasing customer engagement and fostering loyalty; focusing […]
Why retailers need to focus on the online user experience Ecommerce is the fastest growing retail market in Europe and with growth expected to reach £215.38 billion in 2017, it is becoming pivotal for online brands to keep their customers engaged throughout the entire shopping experience. Optimizely recently conducted a survey of over 3,500 consumers […]
At Opticon 2016, customer experience leaders convened in San Francisco to discuss what it means to be brave and experiment everywhere. Catch the highlights from the day and sign up to tune into the keynote live stream.
When growing your business, you need more than a couple of quick hacks to bring customers in the door: you need a proven strategy for customer acquisition that is dependable, scalable, and profitable in the long run.
But how do you find the right customer acquisition opportunities without burning through budget or over-investing in the wrong channels?
In an increasingly challenging and fast-moving retail environment, organizations are looking for every opportunity to reduce cost and risk while improving the end-to-end customer experience.
Given the disruption created by online pure players, how can traditional retailers maximize the value of the multi-channel model of customer engagement and also gain new levels of agility and innovation, from introducing new products through to marketing?
Hypotheses are the statements that clarify our thinking leading up to a test. They make a clear prediction about how changes in customer experiences will impact a given goal. They provide a rationale for why customers might react positively or negatively to that change.
But even with standard hypothesis best practices, there are opportunities to elevate your testing, align your hypothesis with challenges that are core to your business, and increase the odds of producing a positive result. It starts with identifying problems.
Lead nurturing sounds simple, right? Set up an email drip campaign that gives new prospects more detail about what products you offer and what problems you solve. Done. And as you get more complex, scale it up.
But like any machine, lead nurturing has to be constantly tuned and tested. A/B testing is an ideal tool for this. So how do you best take advantage of A/B testing to build great lead nurturing?
We want to make sure 2016 is the your best year yet; that you make decisions grounded in data and customer understanding, and that your ambitious goals are within reach.
That’s why we’ve put together a toolkit of resources to help start or grow an A/B testing program. Whether you’re on test number one or 1,000, these tools can help make sure you run more winning experiments this year than ever before.
Mobile app optimization helps the Trunk Club team ensure that their app is efficient at converting browsers to customers, but it also helped them with an important discovery—finding the right customers to focus on, which means stylists can focus their attention on customers that are most likely to purchase clothing from their trunks.
Blick, the leading online and print tabloid in Switzerland, has boldly ventured into unchartered territory for most in the media industry: editorial A/B testing. By experimenting with headlines and teaser images, Blick’s editorial team is able to better understand what readers are most interested in, in real time.