According to Gartner’s CMO spend survey in which B2B marketers were asked about the top areas for budget increase in 2016, converting leads to sales came in second only to innovation. Gartner also predicts that by 2018, companies that “consumerize” their B2B digital commerce sites, aka take their lead from popular consumer sites like Amazon, will see revenues increase by as much as 25 percent. This is because B2B buyers are bringing their B2C shopping behaviors to the workplace.
Since buyer behavior is evolving, B2C marketing is influencing how B2B marketers do business. Data-driven segmentation, personalization and predictive analytics are becoming more important in B2B as these marketers take a cue from B2C.
Predictive analytics is playing an even larger role in B2B nowadays. Marketers looking to take advantage of this powerful approach start by identifying intent. Intent data allows B2B marketers to track site visitors to understand a buyer’s online process. Predictive lead scoring techniques include the use of data models from traditional data sources and third-party sources to determine the how likely a person is to buy based on intent.
B2B marketers are then using this data to create a lead score for inbound prospects so that they can hit them at the right phase in the customer journey. Not only are B2B marketers using traditional firmographic data such as company size, revenue and industry classification to create these lead scores, they are also able to incorporate individual behavioral characteristics and attributes of the people themselves — a practice common in B2C marketing.
Account based marketing (ABM) techniques are at the center of the innovation since ABM allows B2B marketers to increase revenues among already loyal customers – an easier prospect than converting new leads. So it should come as no surprise that B2B marketers are more likely than B2C marketers to invest in centers of excellence for analytics, according to Gartner. For B2B marketers it makes sense to invest in technology that gives them a deep understanding of who the decision makers are across target organizations.
B2B marketers may be able to use IP targeting to track company-level information but they must go beyond this to identify the individual players who have different needs in tools and services, and different powers in the decision making process. Once intent has been identified, personalization is core to making ABM successful. Personalization relies on reaching different people within one organization, whom often have different needs.
This is where B2B marketers can take note from B2C and adopt retargeting and cross-channel personalization to help better reach prospects on an individual level based on their individual online behavior. This approach is more likely to increase engagement and conversion, than simply going blindly after leads. ABM relies on companies identifying not just the right accounts, but also the people inside those accounts, and then sending personalized messaging that meets the individual’s specific interests.
Predictive analytics bundles intent data with sophisticated statistical modeling to help companies prioritize their outreach to potential prospects. Marketers are merging all of their relevant CRM and marketing automation data, with their vendor’s predictive analytics tools, to construct custom statistical models based on the identified accounts. In doing so, B2B marketers can identify buyer personas within their audience to better personalize messaging.
B2B buyers are also consumer buyers when they go home after work. B2B marketers can use this to their advantage by employing B2C techniques to connect with buyers in new, innovative ways.