How to Leverage AI and Hyper-Personalization to Transform Mass Marketing to Precision Marketing

By David Brutman and Peter Isaacson On Nov 14, 2019

While over 80% of marketers have used AI in some way, only 15% are using it effectively. Personalization, powered by AI, is critical to B2B Marketing – it enables deeper engagement, stronger relationships, and better ROI. AI in a vacuum, however, is not effective – it must be aligned to a Business problem or Marketing challenge.
There are two keys to activating AI. First, make data actionable – by creating hyper-personalized experiences across the entire customer journey of Marketing and Sales touchpoints. Second, define the dimensions – of customer data points and pieces of context – that really matter to your organization. Focus only on the ones that are meaningful to your business goals.
We are still early in the AI journey, but marketers can and should take advantage of the opportunity to leverage AI for Personalization and ABM now.

In today’s age of Big Data and rapid technological growth, Artificial Intelligence (AI) is revolutionizing how business-to-business (B2B) marketers engage with their target accounts. But while some organizations are seizing the opportunity, many still have a long way to go. For example, a recent Forrester report shows that 88% of marketers have used AI. Less than half, however, say technology is helping them meet their objectives, and only 15% of enterprises are effectively using AI to enhance the customer experience.

In addition, according to a survey by Demandbase, Salesforce Pardot and Demand Metric, while there is strong interest in AI – with 84% of Sales and Marketing professionals currently planning, evaluating, implementing or using AI – 40% of respondents are not aware of or fully taking advantage of existing AI capabilities in their vendor-supplied technologies.

When it comes to B2B Marketing, engaging with customers requires Hyper-Personalization: customers expect meaningful experiences at every touchpoint and on every channel, throughout the entire customer journey. Generic landing pages or email templates aren’t going to cut it anymore. AI, coupled with high-quality data, is the key to making such Hyper-Personalization happen, but leveraging the technology takes more than just implementing a platform.

Most companies are interested, and some even are investing millions in the technology, yet they’ve experienced challenges activating AI with clear programs that generate real business value. Oftentimes, the reason for this is that it can be challenging to view AI-enabled technology from the perspective of how it can support overarching business goals.

The Promise of AI in B2B Marketing

AI has the potential to drastically transform B2B Marketing. AI can help enterprises ingest and analyze the huge amounts of data they’re gathering, gain insights from it, and ultimately, take action on it. AI can automate processes, predict customer behavior, and inform and enable better decision making. Ultimately, in the case of hyper-personalization, when combined with good data, AI provides marketers with deeper and richer context around their customers’ intent and interests so they can better engage with them – leading to better relationships and stronger ROI.

Still, AI is just a means to an end. AI or predictive technologies in a vacuum don’t yield business results. In order for AI to be impactful, it needs to be aligned to a Business problem or Marketing challenge. When AI-enabled technology is not connected to strategic goals, marketers may eventually find that they’re not investing in the right tools or solutions for their business needs, are not leveraging their data effectively, and are not able to effectively activate AI to personalize the customer experience – ultimately leading to lost revenue.

When you connect those technologies to an actual Business or Marketing challenge, however, you move from Mass Marketing to Precision Marketing – from rote automation to surgical, intelligent outreach, and that’s when you see real gain in your Marketing ROI.

This is the promise of AI in Marketing, and where the MarTech industry is headed. The question is: how, exactly, do you set your AI program up for success?

You Have the Data, Now What? Putting AI Into Action

The key to activating AI is making data actionable by creating hyper-personalized experiences across the entire customer journey of Marketing and Sales touchpoints. There are several business opportunities that AI can support, for example:

Creating new relationships (pipeline creation)
Optimizing up-sell opportunities
Mitigating competitive threats

Creating Pipeline

Understanding the prospective customer is an important place to start. When you understand your customers you can create a richer context with which to engage them more effectively. Take intent data, for example – which can be gathered through many kinds of technologies. Intent is a signal marketers are constantly challenged by – without talking to the customer – but can be extremely valuable in understanding what they’re interested in, what stage of their buying journey they’re in, and who else is involved in that process, along with anything else they can learn to inform the Marketing process.

The way to transform this intent data and insights into business results is to take a step back and think about the goal – which is to paint a clear picture of your customer(s). With intent data, marketers can dramatically improve the effectiveness of their outreach because they’re now Marketing to the right people, at the right time, with more accuracy and relevancy. It’s effective and creates trust. Instead of trying to guess who to market to or what to say, connecting siloed data about customers provides context to start intelligence and meaningful conversations. However, it’s important to always keep the business goals and results in mind – in other words, work toward the goal of creating a strong pipeline by winning the trust of your customers and guiding them through their journey with AI-enabled hyper-personalization.

For example, if one of your business goals is to grow your financial services practice, you can connect data about the specific industry, prospects, and buyers within a particular account you’re looking to win, and be amongst the first to reach out to them with personalized content. By using intent data powered by AI to build a relationship and convert your target accounts, and do it at scale, you can effectively grow the practice – that’s a true business result.

Optimizing Upsells

Hyper-personalization doesn’t end once a lead becomes a customer. In the same way, you would leverage intent data to understand prospects, you can leverage data about your current customers, their industries and specific pain points to better understand their needs and anticipate potential upsells. It’s critical for there to be a strong connection between Sales and Marketing to ensure that the hyper-personalized messaging continues after marketing hands the lead off to sales.

The key, though, is taking data and making it actionable by creating personalized experiences for customers, and/or by enabling sales to act on the insights. Again, make sure to map back to business goals, such as growing certain verticals or accounts.

Mitigating Competitive Threats

Intent data can also be used to mitigate competitive threats with your customers. Leveraging cookies, intent-data vendors can identify trends with website behavior over time to warn of a customer’s intent to potentially engage a competitor. This kind of data can enable you to identify a competitive situation early on so you can proactively take action before it’s too late.

Richer Context Means Better Marketing: Getting Hyper-Personalized

Another important factor in implementing AI activation is defining the “dimensions” that matter to your organization. Creating a personalization taxonomy will allow you to focus on only the parameters that matter to your business goals.

Both Account-Based Marketing (ABM) and Hyper-Personalization are approaches that focus on certain dimensions that enable marketers to be more targeted. When dimensions are defined and narrowed down to meet business goals, it allows marketers to be more effective in their approach. ABM is focused on knowing the account so as to be more targeted, and hyper-personalization is focused on knowing the specific individual in the company or account. It’s not just about who the customer is, however, it’s about very rich context, such as the use cases or problems they’re trying to solve, what other products they might be interested in, which country or regulations they operate under, their persona, their stage in the buying cycle, their pain points and other data.

The richer the context, the better marketers can engage them. Personalization taxonomy and hyper-personalization are ways to expand into different dimensions – choosing to select the handful of dimensions that are most critical to them.

Companies are very sophisticated organisms with different moving parts, elements, people and dimensions that define their interests. Understanding and predicting their behavior could incorporate an almost endless stream of data and requires an equally sophisticated, methodical approach to analyzing and understanding it. This is why AI and hyper-personalization are so important, as they allow marketers to gather, analyze, and act upon said data for effective engagement programs.

The AI Journey

Achieving the true potential of AI and hyper-personalization is a long-term vision, but we are on the right path.

On the road to realizing the promise of AI in marketing, the first step is understanding customers better – understanding their intent, what they’re interested in, and where they are in the buying process. Truly knowing customers is critical to creating that richer context in order to engage them more effectively. This is where we are as an industry now – and companies are already realizing business results.

The ultimate step in the journey is moving to complete autonomous engagement: there will no longer be a need for individual marketing campaigns. With the right data and Machine Learning tools, coupled with the right business and marketing goals, AI platforms should be able to predict customer behavior and execute accordingly. “Always on” AI will be capable of making decisions on what needs to happen next in the journey, constantly responding to customer needs. This will free people to do what they’re naturally superior at – building and nourishing the high-value person-to-person relationships that result from this AI scaled approach.

AI holds a lot of promise and is certainly yielding impressive benefits for those who have already adopted, but we are still fairly early in the journey and there is much exploration yet to be done. Marketers should take advantage of the opportunity to leverage AI for personalization and ABM now, however – and in order to ensure ROI and the success of the technology, implement AI programs toward specific business goals.