Five AI Solutions Transforming B2B Marketingartelligence
AI solutions such as automated emails and predictive analytics can act as a force multiplier for B2B marketing teams.
Megan Wharton is an excellent sales assistant. She’s been at her job only a few months, but she’s easily the best person at qualifying promising leads on her team. Megan has a remarkable knack for chatting with potential customers over email, and knows exactly what to write to get prospects talking with a salesperson. While her counterparts disqualify leads after a few attempts, she keeps pushing. To top it off, she’s never taken a sick day in her career and is an employee any team would be lucky to have.
There’s a catch — Megan’s not a real person. She’s an artificial intelligence program designed to help B2B marketers qualify leads. As Megan illustrates, even though a lot of chatter around AI may be “hype,” in marketing, it’s becoming a practical tool in the near-term. Eighty percent of B2B marketing executives believe AI will revolutionize their field in the next five years, and a recent survey of marketers identified AI as the technology they are most likely to implement by 2020.
Marketing departments are always constrained. There’s never enough time, manpower, or money. To push back against such constraints, companies are beginning to rely on AI solutions like Megan to enhance their B2B marketing capabilities. AI marketing products can act as a force multiplier. Imagine being able to fill your headquarters with thousands of brilliant marketers, expertly analyzing massive amounts of data and providing actionable insights that increase the productivity and efficiency of your existing marketing team. That is what AI can deliver to B2B marketers.
Despite AI’s potential, marketers acknowledge they aren’t ready for this technology. Marketing executives identified AI as the trending technology they were least prepared to handle. Moreover, only 13% of marketers stated they felt very confident in their knowledge of AI.
While many companies are still investigating AI solutions, several top organizations have already taken the plunge. A recent Salesforce report found high-performing companies are more than twice as likely to use AI as underperforming companies. Soon AI integration will become a necessity for running modern marketing operations. In addition to AI chatbots, there are many AI applications marketers can wield. Here are five actionable ways marketing teams can begin using AI to improve business outcomes.
Lead Scoring and Predictive Analytics
Lead scoring generates some of the biggest excitement around marketing and AI. This interest is likely due to substantial lead-handling obstacles in the existing system. A company might get 10,000 leads in a month, but which of those leads will result in actual sales? Marketing teams can analyze their existing customers and prospect base using AI, identify prospects most likely leading to sales, and then prioritize efforts. AI services also help companies uncover look-alikes, or companies with the same characteristics as existing B2B customers.
Organizations are also incorporating predictive analytics into lead scoring. These AI tools look at signals, or details such as customers’ IT environment, recently purchased services, or where they are in the buying process, to help determine a given prospect’s intent — whether they are in the consideration phase or ready to make a purchase. Companies can use such predictive analytics to target their marketing at prospects, based on where they are in the buyer’s journey.
Various AI platforms allow marketing teams to track prospects across multiple touch points, and then use predictive analytics to assess how likely they are to buy. Those interactions take place in a variety of settings. A prospect can visit a booth at a trade show, visit a company website, watch a webinar, or read a marketing email. AI platforms also follow a prospect’s behavior to monitor the buyer’s life cycle on third-party sites and across different devices, such as a work computer, mobile phone, or tablet.
Like the numerous prospect touch points, purchasing decisions are also a multifaceted aspect of buyer behavior, because they usually have multiple stakeholders. A Gartner study found the average number of people involved in B2B purchase decisions is 6.8. To account for various stakeholders, AI lead-scoring services track the behavior of numerous employees and give marketing teams a comprehensive view of an organization’s place in its buying journey.
Automated Email Conversations
AI clearly can affect spotting the best leads and predict imminent sales, but another key area for marketing teams is effectively responding to customer emails. Conversica, a Bay Area startup with clients like Microsoft and Oracle, is one of the leaders in providing automated email solutions like the Megan Wharton persona. Conversica’s software reaches out to all inbound leads via email and engages them in a two-way conversation, by sending emails that read as though they were written by a real person. According to Conversica, 35% on average of all leads reply to its humanlike automated sales assistant.
Such authenticity is important. As AI becomes more mainstream, companies using the technology will be at major risk if they can’t secure trust and engagement from their customers. Conversica’s software uses AI to analyze customer responses and determine the intent of the lead. According to Conversica, one customer found that the software could understand a prospective buyer’s email responses and respond appropriately to 99% of them. Conversica keeps the conversation going, using an approach the company calls “pleasantly persistent” — relentless follow-up via email or text. Once the lead signals an intent to buy, the marketing group passes the prospect to the sales team.
While working with Conversica, Epson saw its customer response rate increase 240%, and the number of qualified leads rose by 75%. Those numbers are particularly meaningful considering Epson receives as many as 60,000 leads per year.
AI products have also become increasingly adept at analyzing unstructured data like images, video, and audio. Chorus is a startup offering an AI software solution for audio analysis of recorded sales calls with prospects. Its AI software transcribes and analyzes call content, and provides insights on how to better serve customers and increase workforce productivity. Marketing teams using such AI tools can reshape their messaging based on insights from real customer conversations. If prospects begin mentioning a new competitor, the marketing group can create sales collateral to help the sales team fend off this new threat. Marketing teams can also shift paid media strategies to address new competition.
Other AI companies, such as Affectiva, are working on solutions to measure tone and sentiment in a person’s voice. It’s easy to imagine how this technology could be applied in this case — marketers will know precisely when prospects are enthusiastic or disinterested on sales calls.
Personalizing With Data
Until recently, the amount of personal data marketers knew about prospects was relatively limited. Marketers could only segment potential clients into broad categories involving organization, location, and industry. Today, AI products allow for deeper personalization through massive data gathering. Marketing teams can then deliver messaging that addresses the particular needs of their individual customers.
AI can also analyze entire industries to gain personal insights. The process includes inspecting the website and the online employee presence of every company in a given market, such as auto manufacturers. By gathering a tremendous amount of customer information and internal data, AI products give marketers deep insights into each company in the space. This approach works on a scale that was once inconceivable. Rather than trying to market to a health care company, with the help of AI-assisted data gathering, companies can fine-tune their targeting — for instance, a biotech company in Seattle with 5,000 employees that recently announced a major acquisition and will need help merging its IT infrastructure.
Once insights about individual customers are in hand, companies can also deploy a deep level of personalization in their marketing approach. AI products can evaluate all relevant content created by a marketing team, such as web pages, blog posts, and emails, and indicate the ideal material to display to a customer at each point in their journey. When prospects click on a link in a marketing email in this scenario, they are shown a dynamic landing page specifically designed to appeal to them.
AI can even help with content creation, just maybe not in the way marketers hope it can (at least, not yet). Many marketing leaders may wish for AI programs that can write compelling content for customers such as blogs or newsletters. Unfortunately, these types of solutions are not yet ready for prime time. Current AI solutions, such as Conversica’s automated emails, still lack the creativity to construct the engaging narrative that blogs and newsletters require. Despite this, AI can still assist marketing teams to create content, by automating basic tasks and reducing overall workload for teams. Companies can use AI products to improve their marketing emails by creating subject lines and calls-to-action that generate the most customer clicks.
There are a few situations where AI programs can create acceptable narrative content. Those conditions require copious amounts of data for the AI solution to use. For example, by ingesting the play-by-play data from a football game, an AI program can generate a relatively simple recap of the contest. So if marketers have a tremendous amount of information and data, they may be able to use AI to evaluate the information and develop relevant content for something like a short blog post on the company website.
Implementing one or several of these AI marketing solutions will ensure marketing teams are set up for AI success and help companies reach business goals. Predictive analytics and automated email messaging can advance your AI strategy, and when combined with customer insights, data personalization, and AI content creation, your company and marketing team can scale an AI strategy to support your broader business initiatives.
SOURCE: MIT Sloan Management Review