customer-journey-ai

AI-Driven Customer Journeys

Many of the AI solutions available to marketers focus on a specific problem, such as email send times or conversion ratio optimization of a landing page. However, what happens when we zoom out, combine them, and take a more complete approach?

AI will profoundly change how marketing campaigns are executed.

With new machine-learning tools, you can create campaigns that listen and adapt automatically to audiences to improve performance. Tools can hyper-personalize the messaging using dynamic content, adapt email send times, and more.

Some tools go beyond specific marketing campaigns and use machine learning to personalize and optimize the entire customer journey, in effect adjusting them for each individual person.

AI will profoundly change how marketing campaigns are executed.

For automated campaign optimization, it’s important that the system can automatically find and exploit the best messages through multivariate experimentation, searching for the best message option to drive click-throughs without prompting the user to unsubscribe.

Tools can test anything about an electronic message including subject lines, copy or body text, design elements, graphics, and more. Campaign optimization tools perform experiments that automatically shift from lower performing towards higher performing messages.

They can adapt the email send times as well to optimize the open rate.

Motiva is a company that fits this niche. Their tool creates marketing that listens and adapts automatically to audiences. This helps marketing teams save time and enhances the response performance of campaigns. David Gutelius, CEO and co-founder of Motiva, explains:

“At a high level, leveraging customer data in a deeper way creates the opportunity to uncover meaningful populations that exhibit shared content preferences. This opens up new ways to understand customers, both individually and in larger segments, as well as tailor personalized messaging experiences.”

In essence, this involves learning what relationships exist, if any, between customer attribute and behavior data and their responses to the available message options in an ongoing campaign. Gutelius continues:

“By learning models that predict the likelihood of message engagement based on customer attribute and behavior data, we are automatically learning definitions of the underlying populations that are most likely interested in the associated message content. Coupled with an evolving model of message content similarity, the game changes. The possibility of continuous learning across campaigns without human intervention is within reach.”

With tools like this, we can go from executing one campaign targeting a million leads, to automatically running a million campaigns in parallel, each targeting one lead with a hyper-personalized message.

BloomReach is another tool vendor in this space. They try to improve the digital experiences by optimizing the customer journey. Artificial intelligence technology is used to eliminate the guesswork from digital experience design.

Data harvesting, machine learning, and intelligent analysis are used to create a personalized user journey for every individual visitor using the content available. The system also helps suggest what content is missing that would be valued by visitors, and helps companies produce only the content that provides value.

I had a conversation with Tjeerd Brenninkmeijer, EVP of EMEA at BloomReach. His take on AI in digital marketing is that smart algorithms will help marketers make better decisions instead of simply replacing them.

He says the combination of human creativity and the machine’s ability to process big amounts of data within a short period will be most impactful on the business. According to him, it’s not likely that AI is going to take over people’s jobs on a large scale.

Instead, it will make people more productive and help them drive better business outcomes.  I’ve heard the same conclusions from other industry experts as well, and I agree. 

A company called Pointillist offers another customer journey optimization product that can visualize the actual paths your customers take graphically as they engage with your company across touchpoints over time.

Their tool links customer behavior and metrics like revenue, profitability, churn, or customer lifetime value, and can help segment customers so you can determine an optimal engagement strategy for every individual visitor.

Additionally, marketing automation system vendor Act-on now supports adaptive customer journeys, that can predict and deliver the best message, at the right time, through the ideal channel, with machine learning.

As we’ve seen, relationships can be improved at scale if the customer journey of each lead is personalized. We can expect most marketing automation system vendors to include AI-powered customer journey personalization in the next few years.

This will be an important area for AI in marketing going forward, and those who do not adopt these strategies risk being left behind.