“It’s tough to make predictions, especially about the future.” – Yogi Berra
Digital marketing moves at a fast pace. One year something works, and the next year it is obsolete.
Similarly, conversion optimization moves quickly. Sure, there are some core skills that seem foundational and everlasting, but year to year there are also some new skills that crop up.
What are the skills someone should invest in learning if they want to be a top 1% optimization expert in 5 years? What should they learn today?
What are the industry and technology trends that are fueling the need for these skills?
I talked to a handful of experts as well as polled different forums to get people’s thoughts. We also had internal discussions as to the trends we’ve seen here at CXL, both from the skills people request at CXL Institute and the experiences we’ve had with clients.
Table of contents
Optimization Beyond the Landing Page
Everyone has railed against these practices (including us, many times), but it still seems that much of the industry is focused on short term metrics and surface level changes. Just read this (terribly lacking) Wikipedia page for CRO.
The future seems to belong to those moving far past myopic CRO practices and into the strategic and universal realms.
Those working in data-centric tech organizations probably don’t find this idea out-of-the-norm. With agile development cycles and uncertain monetization models, they live and die by data and experimentation.
But this type of universal optimization is reaching more and more organizations as they see the value in controlled experiments at scale.
As Ronny Kohavi, Distinguished Engineer, General Manager, Analysis and Experimentation at Microsoft, put it:
Stephen Pavlovich, CEO of Conversion.com, echoed this as well:
With the overlapping areas of marketing or product with optimization, it helps to be skillful at one of the former areas. Similarly, it helps to have a unified view of conversion optimization to help you approach every avenue of optimization – from product to communications and call centers to landing pages and more.
Matt Gershoff, CEO of Conductrics, advises those in the space to learn about reinforcement learning as a framework for optimization and targeting. Here’s a good article to read if you’re looking to brush up on such a framework.
Conversion Optimization as a Mainstream Discipline
It looks like conversion optimization as a skill will also be embedded in many other traditional disciplines.
For example, a web designer. As Maarja Käsk said in a Facebook group discussion, “everything a CRO-minded designer does & knows how to do will be common knowledge for all UX/UI designers. So there would be no point in including “CRO” in the name of the position.”
Similarly, growth marketers, digital analysts, email marketing specialists, and customer acquisition specialists all do some form of conversion optimization. As we learned in our 2016 State of the Industry report, those who do conversion optimization go by a variety of titles.
While this doesn’t mean that centralized conversion optimization teams will go away (that would likely be a bad idea), it does mean that anyone involved in a marketing function should have a good understanding of the CRO process and the skills that make up the discipline.
This trend will likely be expedited by both the increasing salience of conversion optimization by “thought leaders” and the ease of access to testing tools.
The democratization of testing also accompanies and increased integration of data across tool sets. According to Krista Seiden, Analytics Advocate at Google, analytics and optimization are moving closer together, making so the data speak together more fluently and accurately:
He worries that the increased salience and adoption will inevitably lead to more low-information users. That, in turn, may lower the perceived value of experimentation as people become disillusioned by poor results and ROI.
It’s up to leaders in the industry, then, to educate and evangelize those new to the space on the correct ways to do things.
Michele Kiss, Senior Partner at Analytics Demystified, also mentioned the tradeoff between the convenience of cheap, easy-to-use tools, and the skills required to use them intelligently. Though, she mentioned that these tools are not entirely new:
Matt Gershoff also talked about the lack of depth and the technical debt incurred by this type of narrow-focused optimization:
Deeper Data Skills
We know that knowledge of statistics is important for A/B testing, and that many people get the simple things wrong. We also know intuitively that it’s important to be able to dig around in Google Analytics to get insights.
But that’s just the tip of the iceberg.
Ronny Kohavi puts it this way:
If you’re active in the analytics community, you may have noticed a trend in 2016 towards things like R and Python, and it seems that this combination of technical abilities with traditional analyst tasks is becoming increasingly valuable.
The ability to use data is, of course, not limited to conversion optimization. Emarketer made a similar prediction that the future would belong to those with advanced data skills (check out the “in 3 years” bars below):
The ability to connect large disparate sets of data and pull actionable value is central to website optimization as well as other marketing channels.
Regarding increased data analysis skills, Michele Kiss had this to say:
Ryan Urban, founder and CEO of Bounce X, puts the emphasis on repeat traffic and behavioral marketing, saying that if you can connect anonymous visitor behavior to leading indicators of purchase intent, you can unlock value you didn’t even know was there:
Of course, the technology to do this is becoming increasingly sophisticated, but it doesn’t hurt to really grok Data Management Platforms (more ad-focused) and Customer Data Platforms (more conversion/personalization/retention focused) as well as marketing automation systems.
AI and automatic optimization
It’s a lot of noise, but what does it really mean for digital marketers on a personal level?
AI is still largely misunderstood by the population at large, and that includes marketers. If one wanted to prepare for the future in which we are the slaves of our robotic overlords, one should start with a simple understanding of what AI actually is.
A lot of the skills necessary for AI and predictive targeting will revolve around the management problem. Matt Gershoff explains this in the context of a real and very much current law in Europe:
But human creativity and strategic input still applies. You still need to pull your own insights.
Paul Rouke argues that this doesn’t mean the diminishing importance of human intelligence. In fact, it means it’s more important than ever to use creativity and empathy in your work:
While AI-based algorithms can test hundreds of combinations or serve the best variations to the most relevant traffic segments, it’s still up to humans to create those variations.
Peep Laja, founder of CXL, had this to say about the proliferation of AI in optimization:
More Human Intelligence Needed, Too
This gap between the functionality of artificial intelligence and the necessity of human creativity and insight opens up the increased need for applied behavioral psychology.
As Jairo Moreno said in a Facebook group discussion, “As time progresses and the web is maturing, the layers of the conversion pyramid become commodities from the bottom up.
With functionality nearly solved, when good usability is almost standardized at a reasonable level, it will be all about persuasion.”
That leaves psychology, neuromarketing, etc., as an important point of differentiation and actionability. With your deeper data skills (or those of your data scientists), you can tell where campaigns are lacking and correlations between customer segments and purchase intent. You can cluster behavioral data at an increased level of granularity to predict actions.
But that data doesn’t become truly actionable until you can connect human psychology triggers to those data points.
There’s no shortage of people proclaiming 2017 as the year of the chatbot.
So where there used to be a form or a human support rep, you may soon be seeing a conversational interface in the form of AI and chatbots.
As Craig Sullivan put it in a Facebook group discussion, “I’ve been predicting for years that lead generation, contact, and various other types of forms would disappear, to be replaced by conversations. Chatbots, voice AI – all of these can do the job of converting people far better than shitty web forms.”
He also shared an article that outlines an open source chatbot. Check it out here.
A bit part of the future of commerce, user experience, and optimization could lie not just in the technical understanding of chatbots, but in understanding the nuances and qualitative things that make them effective.
Virtual and Augmented Reality
Virtual reality is another area in which we’re already seeing huge changes. Lowes and Myer have both bought into delivering a virtual experience, and augmented reality lets you see an IKEA couch in your own home.
As Benoît Quimper said in a Facebook group discussion, “Forget the website as we know it – it has 10 years on the countdown and augmented reality is a likely disruptor. Therefore, product demos, “trying before buying,” live support, etc., may all become part of a performance strategy.”
One massive constraint of ecommerce, and one reason brick and mortar has stayed so strong, is that you can’t actual experience the items you’re shopping for. You can’t pick up and hold a pair of jeans, seeing how they would look on you, etc.
We’ve tried to bridge that gap in many ways, like offering 3D rotating images or videos, and investing in ROPO attribution so customer can choose to buy and research wherever they feel comfortable.
Today’s CRO experts are already, on average, more technically savvy and comfortable with data than traditional marketers or more generalist digital marketers. That trend will only continue and deepen in the future.
Learn advanced data analysis skills and more traditional data science crafts – Python, SQL, R, and other big data skills. Get comfortable with AI and predictive targeting tools, and learn to play with conversational UI elements like chatbots.
Look to experimentation and optimization as a driving force in product development and other business areas, not just landing pages and UI changes. Full-stack optimization will become more and more mainstream, especially as testing tools build out features to promote this universal optimization.
Finally, as Peep commented in the article, as our robot overlords take over the more rudimentary data tasks, the ones that rise to importance are remarkably human: writing copy, persuasion, UX design, drawing insights, etc.