With inbound marketing growing at a rapid pace, personalization has become critically important to B2B marketers. Presenting visitors with relevant content can turn a marketer’s website into a lead machine and ultimately further marketing’s transformation into a profit center.
However, there are significant limitations with the data and tactics that B2B marketers have had at their disposal historically. The good news is, that’s changing fast.
Until recently, marketers have been able to do two things in an effort to personalize and convert inbound users. First, they can detect a “known user.” This is a user that’s been to their site before or that they’ve already captured in marketing automation. Unfortunately, this is a rare occurrence — 5% or less. Even when they are known, the behavioral data that a marketer may have on that user could be very much out of date, as the intent of users changes rapidly.
Secondly, marketers use domain-level data to determine what company a site visitor is from, and then tailor content to their particular industry or vertical. Marketers make assumptions about the types of solutions they want to sell to specific verticals, and then personalize accordingly. There are huge limitations with this strategy as well. Marketers can only resolve the domain of around 20% of their site visitors, and of that only 5% can resolve to real target companies (many are ISPs, .edu domains and other non-target users).
This means that, at best, we’ve only had a data-driven conversion strategy 10% of the time, and only a small fraction of that can be expected to actually match personalized content with the true needs of the user.
Intent And Job Function Data To The Rescue
Marketers can now leverage new tools and strategies that allow them to understand a visitor’s top area of intent. The moment a visitor arrives to a site, marketers can tell what topic is most likely to engage them. Just as significant, marketers can also understand the job function of the user — for example, a marketing professional vs. an IT Person.
This is incredibly powerful information both for marketers who sell multiple products and for marketers who sell products to multiple departments within a larger organization. Most importantly, it scales. Tracking the anonymous behavior (intent) of a user and in turn the job function of that user has taken the roof off personalization, often delivering overlap rates of close to 50%.
For a practical example, consider a marketer like IBM. They sell solutions into HR, IT, Marketing, and other departments and they have hundreds of products. With intent and job function data, they can know that a totally anonymous user is a marketer whose top area of interest is analytics. This is a massive leap forward from hoping to resolve the company the user works for and then guessing at what content to show that company.
This not only means better results for the marketer, but also means a better user experience for the site visitor. Further, from an analytics perspective, understanding the intent topics and job functions of site visitors drives data content creation strategies. For example, if a marketer finds out that 30% of their site visitors have intent on Security, they may be inspired to create more content around that topic area. Or if they find out that a large percentage of their site visitors are in a finance job function, they may create more content targeted at finance.
These new data points allow us to bridge the gap from the demand of the business buyer and the supply of the marketer’s content and solutions, and ultimately drive a positive customer experience.
Michael Burton is SVP Data Sales and Co-founder of Bombora, an aggregated source of behavioral intent data for B2B marketers.
