Predictive Marketing Analytics with B2B Intent Data

Translate B2B Buying Signals into Actionable Intelligence

Translate B2B Buying Signals with Predictive Marketing and B2B Intent Data

B2B buying signals can be particularly challenging for marketers to identify — and even more challenging to translate those signals into some sort of actionable information.  Whether we know it or not, companies in various stages of the B2B buyer journey send constant signals to vendors. The key for businesses is to identify and interpret those signals that are being created and sent out across global networks within the business to business community.  

Not every signal is a B2B buying signal and some buying signals are stronger than others. Knowing what those B2B buying signals are, understanding how to effectively interpret them and put actions in place to take advantage of them, is the primary goal of predictive marketing which makes for more knowledgeable – and successful – marketing and sales teams.

Most seasoned marketers understand that their relationship with the sales department hinges upon their ability to deliver qualified prospects. It’s true that marketers dream of converting every anonymous website visitor or reader of an eBook or presentation deck. But in reality, only about 15% of a target audience is ‘in market’ and ready to buy at any given time. So how do companies identify which prospects are actually ‘in market’ and which ones are not? This is the holy grail that often appears to be just out of reach, but it doesn’t have to be.

Emerging technologies, advances in data science and the growth of AI-driven collection platforms are influencing traditional predictive analytics solutions, forging a path towards predictive marketing solutions powered by B2B intent data. Businesses have an opportunity to leverage predictive marketing to more easily identify and more effectively interpret the buying signals coming from prospects — buying signals that pinpoint those 15%. Once marketers know exactly where to focus their resources, they become significantly more efficient at driving qualified demand into their sales funnels and converting the right buyers at just the right time.

Identify web visitors actively sending b2b buying signals

Identifying and Interpreting Buying Signals

Prospective buyers emit various signals as they progress through the B2B buyer journey. The starting point of the buyer journey begins with research. In most cases, this research begins with a website visit. Website visits can be a powerful intent signal, but website visitors remain anonymous about 98% of the time.

The research phase of the buyer journey means these prospective buyers are actively and increasingly visiting websites and consuming various forms of B2B content online. Website visits, whitepapers, webinars, e-books, social networks and other online information resources empower prospective buyers to thoroughly educate themselves while keeping sales people at bay until they are ready to have a conversation. In fact, according to Forrester, 60% of buyers prefer not to interact with a sales rep as the primary source of information and 68% prefer to conduct research on their own by consuming available content via the Internet.

On the surface, it seems as though prospective buyers have gained the upper hand in being able to successfully evade direct contact with a sales person. Until now. Predictive marketing using B2B intent data has created a way for marketers to gain insight into all this research and content consumption that is going on under the radar.

Whether it’s a website visit, an ad clicked, a whitepaper downloaded or something else, each of these online activities create a consumption event signaling where a prospect is in the B2B buyer journey, as well as their likely intent. For businesses, having the ability to capture, organize, and translate the billions of daily consumption events into B2B intent signals that can be matched to anonymous website visitor identification is fueling the growth of predictive marketing with B2B intent data.

Predictive marketing, as the name suggests, predicts which strategies or actions will have the highest probability of success based on spikes in content consumption trends that can be identified through B2B intent data. Intent data is information collected about a web user’s content consumption or behavior that provides insight into their interests and objectives.

B2B intent data, when matched to anonymous website visitor tracking data, allows businesses to accurately identify and effectively interpret B2B buying signals and determine where their time and resources are best spent to drive more qualified demand through the funnel. This is predictive marketing at its best. What better way to reliably and consistently drive revenue than to know who is visiting your website and what they’ve been researching across the web?

B2B buying signals + anonymous website visitor identification is key to predictive marketing analytics

Turning Interpretation into Action

Once companies are able to identify their most likely prospective buyers from the anonymous website visitor traffic, they can see which B2B buying signals are attached to various businesses coming to their website as well as the strength of those signals. This makes it easy for marketing teams to identify and focus their efforts on the prospects who are far enough along in the B2B buyer journey and who are interested enough to pass those along to their sales teams for follow up.

For example, sales teams can be proactive by reaching out to prospective buyers with the necessary introductions and provide any additional information to help make the business buying decision easier. Another option would be to tailor content and talking points around key business topics that prospective buyers are researching, and deploy account-based marketing campaigns to deliver exactly the kind of information their top prospects are searching for. Either way, predictive marketing with B2B intent data makes it easy to identify and translate the B2B buyer signals, which can strengthen one company’s position over another as a more valuable and capable resource that properly anticipates needs.

Results Speak for Themselves

Companies that have implemented predictive marketing solutions are demonstrating an improved ROI as a direct result of their ability to consistently identify and interpret these B2B buying signals. For example, some B2B companies have exhibited a 33% reduction in the sales cycle by properly identifying and interpreting buying signals, demonstrating an ability to meet the right buyer at the right time with the right solution. Companies have also been able to demonstrate significant improvements in B2B marketing campaigns and experience an increase in email open rates by 60% while also doubling their email reply rates. With more buyers initiating the sales cycle by doing their own research, some companies that capture and effectively use B2B intent data have experienced a 40% increase in paid social engagement while others have been able to narrow their target accounts by 72%, resulting in more effective campaigns.

The bottom line for marketers and sales teams is results. Initiatives that lead to reductions in sales cycles, increases in email open rates and refinements in target accounts will lead to more effective marketing campaigns and increased profits. Successfully identifying the anonymous website visitors and interpreting the B2B buying signals through predictive marketing solutions powered with B2B intent data will ultimately drive those results.

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Predictive Marketing Analytics with B2B Intent Data

by | May 14, 2019 | Blog