Interpret B2B Buyer Signals with Artificial Intelligence

September 14, 2017 Brett Eckrich

We’ve previously talked about how artificial intelligence (AI) has the potential to drive personalization in a B2B marketing situation. So, how do we put that AI into action and create a two-sided, thoughtful conversation that adds value for the buyer? We need a strategy for the implementation of these conversations and the proper technology to enable successful interactions. 

When the website itself takes the place of the face-to-face conversation, it becomes vitally important that the content presented be of quality. But not all content is interesting to or appropriate for everyone—it’s situational on the web just as it is in real life. 

As marketers, we must be able to provide the right content within those conversations, to all of our prospects and customers, based on our understanding of their situation as augmented by their digital interactions with us. Harte Hanks CMO Frank Grillo explains how this is content’s highest calling: 

 

Prepare for Conversations

In a conversation, we need to understand the verbal and non-verbal cues presented (hence the old adage: it’s not always about what you say, but also how you say it). Walking into a room with a blindfold on would rob you of an important information gathering mechanism. From a digital perspective, ignoring your website’s role as a bi-directional communication limits your ability to create obvious signals of intent.

Strategically, the goal of a website’s content is to encourage customers to engage. This engagement, via continued browsing of pages, downloading of content, form submissions, or responding to a chat, for example, all leave behind the digital breadcrumbs for us to follow along in the conversations. 

As in our daily lives, there are different conversations for different situations, and conversations that take twists and turns. To determine what content is best within a conversation, we need to consider the current situation, as well as where it sits in a buyer’s journey. 

Consider that a browser along the buyer’s journey is looking to learn, so we want to be there to assist and provide valuable content to facilitate their learning—we don’t want to be that pushy or insensitive salesperson that drives them away. This may require that we monitor their visits before deciding that they’re ready to open a dialogue. A shopper is evaluating their options, so it's likely expected that we would begin to engage this person with more focused content about the solution to the problem they are trying to solve.

It's important that we as marketers then plan to have content prepared to engage with a variety of personas at each of these stages so that we can participate in the conversations buyers want to have with us.

Invest in the Technology

Once you have a plan in place, the next step is organizing your underlying technology around that digital strategy.

This is where AI comes into play. Based on an individual's behavior, it can interpret each buyer's signals and decipher what content to serve up that offers value at that moment in the digital conversation, ensuring we engage each person contextually. But, it must be trained.

The reason website personalization misses the mark for many organizations is because they have the capabilities to create and track the right data (Google Analytics is the most popular, but while it can track a granular level of interaction detail, it doesn’t actually deliver personalization as a delivery engine). But having tools that let marketers track user actions beyond simple page views, or ascribing attributes to specific pages, allows for a much richer view of the visitor engagement. This ensures the tracking systems are set up to capture intent data and not simply page visits or click actions.

At Harte Hanks, we’re working through the process of integrating our AI-driven personalization into our messaging technologies so that we can help our clients to do the same. Our most important underlying technology is our website, because that’s where we’re driving our digital conversations. So, preparing our technology involves tagging each page with metadata and organizing it. This enables the AI engine to collect those metadata tags as customers browse and utilize them to interpret intent based on past learnings. Based upon their behaviors, we are able to provide relevant content in response.

Personalizing with this approach requires two tools beyond the website: 

  • A real-time personalization engine
  • An end-to-end data analytics platform 

We’ve chosen Evergage as our real-time personalization tool and Signal Hub as our end-to-end data analytics platform. Here’s how we’ve set up these platforms—integrated with our website—to help us begin to personalize our conversations: 

  1. Enable digital breadcrumbs within the real-time personalization tool (Evergage). We’ve ascribed attributes to every webpage, case study, blog post and more to create signals of intent. Evergage has a tracking cookie that allows us to capture behaviors (from clicks, hovers and scrolls to amount of time spent per page and where they go next) at a granular level. From here we can try to intuit their situation, the problem they are trying to solve and where they are in the buying process.
  2. Interpret the breadcrumbs. It can then assign additional meaning to those actions for later use in the AI engine portion of the tool, as well as within Signal Hub. The data is fed into our end-to-end data analytics platform (Signal Hub) where the two platforms (Evergage and Signal Hub), use AI to examine each visitor’s site behavior. The technology then determines—based on these behaviors—what content is likely best to come next in our conversation with this person. Note: Signal Hub also analyzes a wealth of information outside of website interactions and uses that intelligence to continuously augment Evergage’s knowledge of the visitor.  
  3. Execute the personalized conversation with Evergage. Once the tools have used the interaction data and past learnings to determine next-best content in the digital conversation, Evergage serves up this content on the website the next time it sees the visitor arrive.

AI-Driven Personalization In Action

Here’s an example of the personalization of an interaction for a website visitor: 

  1. An individual is in Times Square in New York and notices our billboard ad that has a vanity URL to our Five Pillars of Best-in-Class Marketing webpage.
  2. Evergage drops a cookie and assigns our anonymous visitor a unique ID. Our website then redirects that vanity URL to our Five Pillars page with a string of parameters included that indicate they got to the page from the vanity URL that is associated with the billboard. Evergage takes note of all of this.
  3. The prospect continues to interact with a variety of our web pages, specifically looking at consulting services. 
  4. Evergage is tracking each time the prospect visits these pages and shares its deduction with Signal Hub: this individual has an affinity for consulting services.
  5. Signal Hub, at the end of the day, would check back with Evergage to see if there is further information available. If so, Evergage would forward that new information back to SignalHub to determine there is added affinity.
  6. Signal Hub decides that Evergage should populate a lightbox the next time the prospect visits the site, asking if the prospect would like to hear from a consultant.
  7. The anonymous prospect once again visits the consulting page and the lightbox appears. The prospect decides to let us know they are ready to hear from us by sharing their first, last and company name, as well as their email address.
  8. Now the contact is no longer anonymous. We have additional insights and the constituent ID: we can put a face to a name so to speak. As we move forward we can be more personable because they have given us information that moved the relationship (and thus the permissiveness) to the next level.

In this instance, our anonymous browser has turned into a shopper by taking an important turn in the conversation with us. By tracking the visitor’s behavior, we were able to make an informed decision about what might be most engaging. And in doing so we created a deeper connection as demonstrated by their action to provide us with their name and contact information.

Plan, Build, Learn, Expand

None of this will happen overnight. It’s a process we’re still building, and will continue to build upon as we finesse our strategy around website tagging and the implementation of the right tools that allow us to provide a personal buyer's journey. The capability to be intelligently personal exists today; and it is within reach of most marketers if they chose to make the commitment to provide their prospects and customers the most relevant, individualized conversations and experiences in the moments that they need them.

Stay tuned for a more in-depth look at the workings of both Signal Hub and Evergage for creating more contextual, human interactions with our prospects and clients.

About the Author

Biography

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