Marketing is undergoing a rapid transformation with the help of AI. More than 80% of marketers integrate AI into their overall tech stack today in everything from programmatic advertising to chatbots to copywriting.¹ In turn, the introduction of AI into marketing workflows enables marketers to automate manual tasks, allowing them to focus on more strategic and impactful projects, ultimately accelerating growth and the pace at which they can work.

According to the Marketing AI Institute, many early adopters are using AI to power personalization in marketing communications that are massively more effective, more customized, and even more human.²

Marketers have an opportunity to be the change agent and drive digital transformation within their organizations by investing in and learning more about how AI can shape their strategy. With the right tools and use cases, marketers are using AI to accelerate growth, personalize and optimize customer experiences across channels, create content at scale, reduce customer acquisition cost (CAC), and drive more revenue.

Today, 48% of marketing leaders cite AI as making the most significant difference in how customers interact with their companies and brands.³ According to a recent study by Redpoint Global, nearly half of all consumers say they would interact with AI more frequently if it would make their customer experience with a brand more seamless, consistent, and convenient.⁴

With numbers like these, it’s clear that not only are marketing leaders acknowledging the significant impact that AI is having on consumer interactions with brands, but also that AI is critical when it comes to marketing team productivity rates as a whole.

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Just as programmatic technology revolutionized digital advertising, the same is now true for conversion rate optimization (CRO). CRO is the process of increasing the percentage of website visitors who take a desired action or complete a conversion goal. Due to the sheer size of online audiences, even small improvements in conversion rates can produce significant positive impacts on business performance. In addition to improved ROI on existing program spend, better conversion rates equate to reduced CAC, enhanced customer lifetime value (CLTV) and unlock huge opportunities to make more data-driven decisions for businesses to scale even faster.

Currently, despite valiant efforts, marketers still spend billions of dollars annually on digital ads that are wasted on low converting websites. Disjointed ad-to-landing page experiences and static pages created for one general audience are just a few of the reasons that brands see poor conversion rates on their websites and dismal ROI on their ad spend.

Using AI, marketers can improve the end user experience by delivering uniquely personalized experiences, at scale, to every website visitor in a frictionless way. Leveraging powerful machine-learning technology, AI optimized websites can continuously “learn” and improve over time without human interaction. This delivers the best possible combination of page attributes to maximize conversions, customer acquisition, and revenue.

AI optimization programs focus on driving more conversions that increase revenue for their companies. An important part of achieving that objective involves personalizing the website experience on a one-to-one level.

Marketers can tailor their websites to deliver the optimal user experience (UX) in an effort to convert both anonymous and known visitors into customers. By pairing human creativity and expertise with AI, marketing teams can increase their testing velocity, learning faster than with a standard experimentation approach.

AI optimized websites are driving marketing efficiencies in several key areas: 

Time savings and velocity: AI enables marketers to test hundreds of website combinations without needing to build separate landing pages or outsource web development. AI decides which versions to show unique visitors at any given time, and adapts over time to improve performance.

Personalization at scale:  AI empowers marketers to deliver one-to-one experiences. Insight into which messages, experiences, and creative resonate for different audiences are then used to inform a lifecycle strategy across the entire buyer and customer journey, accelerating the buying cycle. 

Risk minimization: With AI, the best performing page variations are shown more often. When macroeconomic conditions or buyer behaviors change, AI adapts to show a better performing variation, increasing the likelihood of conversion even in sub-optimal conditions.

Predictive analytics and forecasting: AI can analyze historical data to help predict future trends and patterns, streamlining decision making around resource allocation and strategy, and tightening the feedback loops between brands and buyers.

“Digital channels, including our website, are a top source of high-quality leads and pipeline for our sales teams. The rapid testing process is delivering significant improvements in conversion rates across our site.”

-Suku Krishnaraj, CMO, Sumo Logic

As the marketing ecosystem shifts to using more tools with AI capabilities, it’s increasingly important that questions around ethics and responsible best practices are incorporated into the evaluation stage of these tools. Ensuring that teams are aligned with how the tools will be used for specific roles and what mechanisms are in place to mitigate risk and prevent against poor quality content production are just a few of the considerations to take into account. When evaluating AI tools to augment an existing marketing tech stack, teams should ask the following:

1. How does the AI and machine learning model work?
2. What datasets does the tool require in order to work and to get true value out of the technology?
3. How will the tool integrate with my existing marketing tech stack?
4. Are there other marketing tools that this tool makes redundant?
5. What real-world use cases will we be tackling by implementing this tool?
6. What kind of guard rails are in place to protect against poor quality AI-generated content?
7. Will my team need ongoing training to use the tool?
8. How often does monitoring and auditing of the AI tool occur?

Analyzing responses to these questions, teams should feel confident that the prospective tools they’re evaluating integrate with existing systems and datasets, provide comprehensive training resources, have clear product roadmaps, and align with their core business goals.

The impact of AI on business is only beginning to be realized, and marketers who understand the importance of incorporating AI into their tech stacks stand to keep themselves and their organizations ahead of the curve. Embracing AI means keeping pace and staying ahead of the constantly changing digital landscape and will allow marketers to deliver website experiences that meet the unique needs of all visitors, known and anonymous.

To learn more about creating a highly personalized website experience for your customers and prospects, get in touch with our team.