Conversion rate optimization (CRO) is a surefire way for marketers to deliver better results from their marketing efforts and improve campaign efficiency, which is why most sophisticated marketers make CRO a part of their core strategy.
But the discipline may be headed for a shakeup.
As at other companies with a culture of experimentation, most of our conversion optimization efforts at CallRail stem from A/B-testing. Although there is a lot to be said for techniques such as heatmaps, session recordings, and usability studies, A/B tests are the be-all and end-all for driving results.
Accordingly, it makes sense that much of the budget for conversion optimization goes toward A/B-testing platforms, such as Optimizely, Adobe Target, and Convert. In fact, major players in the market are anticipating that their share of clients’ budget will grow. Optimizely is charging into 2018 with an aggressive upmarket strategy, enforcing a $50K contract minimum, although it values its main Web product at just $30K per year.
However, the practice of A/B-testing is already under attack, and new technology applications are pointing toward a market shakeup and a refocusing of the optimization discipline.
In the same way that cost-per-click (CPC) campaigns are relying more and more on algorithms to drive traffic to variations of ads, companies are now offering SaaS systems that will direct website traffic to variations of a webpage to optimize that traffic for specific conversions. These machine-learning algorithms are automating the process of website content iteration, obviating the need for step-by-step A/B experimentation altogether.
Vendors, including FunnelEnvy and Intellimize, offer systems that rely on behavioral cues from users, supplementary data such as reverse IP lookup, and CRM-enabled user identification. That means how users interact with websites and what we know about them on an individual basis will determine what versions of a webpage they will see. Moreover, the algorithms can be set to optimize for either on-page metrics or down-funnel results, such as revenue.
The result? Automation of day-to-day test tracking for program managers, increased efficiency in conversion rates, and better content personalization.
What to Do If…
‘I’m new to conversion optimization’
If you are already in an early-stage experimentation program, or you’re headed toward one, start with Google Optimize. It’s a free platform that will give you the tools for creating and running A/B tests using a standard WYSIWYG (what you see is what you get) editor, as well as allowing you to run more-complex experiments (with the help of a developer) and split-URL tests.
Although you will be limited both by the number of experiments you can run simultaneously and by the number of metrics you can track in each experiment, Optimize has everything you need to start out and get some wins.
‘We are an SMB’
For a small-to-midsize business with an optimization program in place, you will likely want to stick with an A/B-testing platform, such as Convert. This robust and comprehensive tool will deliver the functionality of an enterprise-grade tool without the enterprise-grade price. (Although the algorithmically driven systems on the market may be a fit for your organization, and they will accelerate your optimization program, their $50-60K annual price tag would likely be a prohibitive barrier.)
‘We use an enterprise-grade tool’
Tools like FunnelEnvy and Intellimize are already competitively priced against other enterprise-grade solutions, such as Optimizely and Adobe Target. Moreover, the Intellimize product also comes with a full development-support service agreement that makes the offering even more attractive. For certain industries or business models, early adopters will see a competitive advantage by employing the new technologies. If your optimization program is already showing a six-figure return, the time to consider an algorithmically driven solution is now.
What About Optimization Managers?
While the market navigates its way through this technology development, marketing professionals in the conversion optimization field, as well as marketers more broadly, face significant implications.
Conversion optimizers that harness these new systems will shift their time and focus away from rudimentary data analysis and experiment tracking, toward the psychological tools of marketing, such as persuasion theory and consumer insight. Holistic understanding of consumer motivations and decision journeys will become the hallmark of this new breed of optimizers.
Soon it will be time to think of websites not as collections of pages that leapfrog from iterative test to test, but as collections of volumes with interchangeable content blocks and variances in deliverability based on unique users and everything that we can collectively know about them.
Moreover, individual content blocks will be uniquely created and variated by AI systems, in the same way that UK-based Phrasee constructs email headlines with an astonishing probability of success.
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The actual execution of theory will certainly reveal new issues and dictate future trends in the development of the optimization discipline, but marketers should begin to prepare now for a change in the landscape.
Current practices, such as A/B-testing, will likely evolve, automating and streamlining the data-analysis side of the optimizer’s workload. Forward-thinking practitioners should therefore invest now in further developing their skillsets around consumer insight and user experience.
But it is worth mentioning, in closing, that analytics tools, like CallRail, that close the gap on understanding the consumer’s entire journey, online and offline, will be just as critical tomorrow as they are today.