The future of marketing automation, personalization, and other B2C marketing strategies is top of mind for many marketers today. Consumers are inundated with abandoned cart e-mails, product recommendations, personalized pricing based on their segments, and more. With so many diverse strategies, the “marketing technology stack” is also getting more complex and harder to manage. More and more marketing professionals are asking how personalization is set to change, and how it will affect their day-to-day work. Today, we’re sharing a few insights that help shed light on the future of marketing automation, personalization, and customer analytics.

From personalization to “individualization”

According to Forrester, the need for “individualization” of content is becoming more prevalent over time. Personalization remains focused on business rules and models based on a limited amount of data – most companies “personalize” by building segments and catering unique content to those segments. Individualization – or as some would call it, Personalization 2.0 – moves away from this segment-based approach to one where every individual is offered a completely unique experience.

This level of granularity is ultimately achieved through analytics platforms that track the entire customer journey: observing how people browse, what content they read, and ultimately what they buy, to build a unique understanding of each specific individual and algorithmically select products that fit each person’s context.

More tech in the marketing stack

The challenge with individualization is increasing complexity in the technology stack. Catering to an individual across dozens of different platforms means that companies need to have the customer’s profile in a centralized location, and to offer the same deals, offers, and content to serve across these channels. This presents a major integration issue, requiring what Stephanie Miller calls an “architecture to allow disparate systems to speak to each other seamlessly.” The obvious path is a gradual consolidation of such technologies.

To some extent, today’s marketing clouds all present a unified vision for marketing stacks (where each marketing cloud provides the entire end-to-end experience around optimization, content management, customer experience management, and more). However, given that many clouds are growing their feature sets through acquisitions, there is much more to be done before these systems are truly integrated. One example of this is Salesforce’s marketing cloud, where customers first need to choose a product that fits their (somewhat siloed) needs, rather than offering an integrated platform.

salesforce
Salesforce offers a variety of products, but many companies struggle with building an integrated view of their customers.

Moving to predictive marketing automation

As companies aim for more “1 to 1” experiences with each customer, traditional marketing automation will begin to fall apart – not because of the technology requirements, but user interfaces. If you’re a user of marketing automation software today, you’re probably familiar with setting cadences and communication sequences, and might even model them in Visio or another advanced flow chart tool.

As you divide your customer base into more segments, this becomes untenable. One common challenge that arises as marketers move from “one size fits all” to “personalization” is the increased workload around segmented outreach. Before, many marketers were familiar with sending one e-mail to everyone, but with “personalization” they need to send one for every segment. This increases their workload exponentially and is particularly challenging for small marketing teams.

While it’s true that some marketing solutions offer the ability to insert content and create template e-mails “auto-catered” to each individual, there aren’t many of them. Furthermore, no tools monitor the actual customer decision journey and optimize for it. As industry expert David Raab notes from a recent speech by Phil Fernandez, “customers follow many more paths than any manageable chart could contain.” There need to be tools and platforms that generate optimal customer journey paths and help cater content, recommendations, and offers to each unique path.

To do this, of course, software needs to be “predictive-first” – to understand the customer journey and be built from the ground up to support individualized journeys through predictive models.

AI as a helping agent for marketing professionals

The above paradigm of “predictive-first marketing automation” will intrinsically change the way marketers perform their tasks and reach out to their customers. The Economist predicts that artificial intelligence (or machine learning, or predictive modelling, or…) will be another tool in the shed for marketers – rather than manually analyzing customer journeys, paths, and data, predictive-first marketing automation tools will help guide marketers determine which content needs to be created for the biggest and most relevant opportunities.

There is still a long way to go before the “AI-Driven Marketer” becomes a formal job title, but given the challenges marketers face today and the solutions being proposed, this future is inevitable. Tomorrow’s marketer needs to be comfortable with predictive models and working in gray areas where content, product messaging, and more are cultivated by the marketer, but ultimately promoted by a machine.