Artificial intelligence (AI) isn’t a futuristic concept anymore—it’s here, and it’s already changing how we approach and realize results regarding conversion rate optimization. That’s right, CRO best practices and hacks are out, and machine learning and AI-led optimization are in.
And doesn’t that make sense? After all, CRO was born out of the need to provide better experiences to consumers: helping them find what they came for with ease. And, AI was born out of the desire to streamline complex tasks for simplified experiences.
Today, our growth goals haven’t changed. But with AI’s ability to understand visitors, users, and customers at an unprecedented level and deliver results – how you approach conversion optimization is changed. In fact, it’s drastically improved.
We’re enthusiastic about AI, but knowing the foundations of conversion can help make the transition from manual CRO tactics to AI smoother for everyone on your team.
What is conversion rate optimization?
Conversion rate optimization (CRO) is about enhancing your digital touchpoints – your website, landing pages, and applications – to get prospects and customers to complete a goal. Often, the goal, or macro-conversion, is making a sale. However, micro-conversions are also important during optimization strategy, for example, increasing:
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Newsletter subscriptions
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Add-to-carts
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Shopping cart completion rate
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Email opt-ins
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Social shares
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Leads generated
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Asset downloads
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Recommended content engagement
Prioritizing CRO, and making meaningful changes across your digital products, means deeply understanding who your customers are, and what they want, and then creating experiences that fit them best.
Why is conversion rate optimization important in digital marketing?
Today, 66% of customers expect companies to understand their needs, and customers who feel brands understand their needs are willing to pay up to 10% more in purchases, agnostic of industry.
That’s why conversion optimization strategies must be part of a holistic effort to improve customer experience. More than just gains in revenue, when customers are satisfied with the interactions they have with your brand, you can:
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Increase retention
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Improve engagement
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Increase marketing ROI
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Lower acquisition costs
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Reduce churn
But CRO isn’t just about making ad hoc changes and hoping you’ve made the right decision for your customers.
To succeed with CRO strategies, brands must understand every touchpoint across unique customer journeys and pinpoint what drives the conversions or creates friction points at a product level across various channels and segments of users. You need a deep understanding of:
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How individuals interact with your digital products
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Why certain website changes lead to better conversions
And then, make data-driven changes that improve user experience, and solve your prospects and existing customers’ pain points.
Challenges marketers face with manual conversion rate optimization strategies
Even the most minor changes in design, layout, or wording can influence customer buying decisions and, in turn, improve conversions. For example, are navigation buttons and CTAs clear, or are your users needing clarification? Do you have a plan to fix these UX problems once you unearth them?
The challenge for the most straightforward UX problem is that there are so many small changes you can experiment with to rectify the solution– how do you know which is best?
It would be considerably easier if all visitors had similar preferences and followed a straightforward buying journey. But, the reality is that every journey has multiple touchpoints requiring optimization as visitors bounce between desktop and mobile channels as well as competitor sites, social media, and review sites.
According to G2, the average B2B customer journey involves 31 touches across 3.1 channels over 192 days spanning channels like:
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Your site
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Paid advertising like Google, LinkedIn, or Instagram
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Marketing and sales emails
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Online webinars
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Landing pages
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Field marketing events
The best application of conversion rate optimization involves many variables and, thus, many possible experiences. By changing a relatively small number of elements on a web page, for example, the number of possible customer experiences quickly grows into millions. And this is just for a single web page. When you are optimizing across an entire funnel and different devices, the problem gets even more complex. And, without tapping technology, like AI, which is exceptional at solving analysis-based queries, the task can become even more challenging.
Overcoming common challenges and complexities of conversion rate optimization with AI
With all these factors influencing conversions, optimization teams must be equipped with the right technologies to help them succeed. The only way to keep pace with evolving customer expectations is to have the ability to optimize for conversions across all channels at scale. We find this most manageable with human-in-the-loop AI capabilities:
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Experiment at scale
Build complex experiments from text descriptions and immediately push your ideas into A/B tests for faster results with fewer resources. -
Automate segmentation
Leverage AI to evaluate all potential segmentation opportunities, identify new segments, and test audiences for improved conversion rates. -
Optimize customer journeys
With AI accelerating learnings and increasing testing velocity, you can more easily personalize experiences based on the predicted lift.
Get Started with Evolv AI
A massive advantage gained by using Evolv AI is that conversion optimization teams don’t have to prioritize and constrain the number of ideas to test. All ideas can be added at the onset of the experiment, knowing that AI uses natural selection to identify which ones work best. As part of the optimization process, low-performing ideas get automatically discarded or paused, making it easy to identify discarded ideas before additional resources are wasted on them. Additionally, with Evolv AI, you can:
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Test more ideas faster and with less traffic.
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Leverage text-to-design capabilities to make iterations on the fly without design and development bottlenecks.
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Continuously learn from data and automate the micro-decision process.
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Discover and deliver personalization via targeting and auto-segmentation capabilities across multiple touchpoints.
AI-driven conversion optimization aims to quickly identify and prioritize the best-performing experiences for further improvement, resulting in increased revenue and profitability for businesses and happy customers.
