Online Experimentation Trends for 2018: Part 1

It’s that time of the year again…a time for reflections and setting goals for yourself personally and professionally. While we’re still struggling with our goals to workout daily and eat better, we did take a look back at lessons learned from 2017, and what we’re anticipating for the world of testing in 2018.

Part 1: 2017 Findings

1. The rise of mobile conversions

In December of 2016, we predicted that consumers would become much more comfortable shopping on mobile devices in 2017, and that rates of purchase on mobile will increase.

For our clients, this prediction certainly rang true:

  • Mobile traffic either has surpassed desktop or is trending to overtake it within 2018.
  • Tablet traffic is declining. This means a growing majority of web experiences are happening on a small screen.
  • Although desktop conversion rates are still higher now, mobile conversion rates are trending more positively and closing the gap for 80% of our clients.

2018 will be a year that brands need to ensure that they are thinking mobile-first and testing their customer’s mobile experience.

2. The growth of personalization

Though “personalization” remains one of the biggest buzzwords in our industry, our findings from 2017 are that many companies are still confused about what exactly personalization means, how it differs from segmentation and how to go about implementing a personalization program (HINT: our Personalization Jumpstart one-pager clears it up).

Over the past year we worked with many organizations to run proof of concept (PoC) programs for personalization, and one key finding is that you can’t expect a successful personalization program if you don’t have a mature optimization program in place.

As Brooks Bell Director of Analytics Brian Shampnois put it, “All experiences need to be optimized, but not all experiences need to be personalized.”

Think of it this way: if someone is shopping for a car, they need to decide if they are buying a sedan, truck, or van before they pick out their paint color and interior package.

In short, you need to understand what people are responding to and when, and how to reach them, before you can determine where personalization makes sense.

3. The maturing of experimentation teams

As early arrivers to the experimentation scene, we’ve watched programs grow from one person flying the experimentation flag to centers of excellence that are perpetuating a culture of experimentation.

Much of the growth we witnessed in 2017 was due to the availability of tools in the marketplace to help automate and manage experimentation programs. Tools like Optimizely, Adobe Target and more have provided structure and scalability to programs; however, the most successful programs start with a clear and measurable strategy.

Stay tuned for what we predict for the evolution of experimentation teams in 2018.

4. The importance of clean data

Imagine trying to wipe down your counter-tops after cooking before you clear away and wash the pots and pans. You have to straighten up before you clean up in order to be efficient and not cut corners.

The same principle applies to data. While this sounds simple, it’s a huge issue we see most of our clients facing.  When systems aren’t built to integrate with other technology, you may realize that data is not actually available for real time targeting and personalization efforts.

Data auditing was a big focus of 2017, and will continue to be important in 2018.

Tomorrow we will reveal our predictions for 2018 and conclude with some of our best and worst performing strategies in Part 2!

The Brooks Bell Team