The Top 3 Innovations in AI-Driven B2B Sales

June 18, 2019, Gil Allouche

Alongside cloud computing, artificial intelligence (AI) has been one of the two major innovations and change agents in B2B sales. AI especially has changed the way in which marketing integrates with data administration, trademarks and other aspects of selling.

Gartner Research produced a study that said 85% of customer activity will have no need of human interaction. Machines will have the ability to communicate with prospects like human B2B sales reps and assemble that data across any channel it needs to pass through. AI is undoubtedly the future of sales and marketing, and marketers are always looking for the next innovation to keep a leg up on competition.

With this in mind, let’s look at three of the top recent innovations in AI-driven B2B sales technology.

AI Driven CRM

The days of dropping a lead based on simple human forgetfulness or data misinterpretation are almost over. With the exactness of AI-enabled CRM, future prospects who do not convert will come by the decision honestly, not because of a careless mistake from the sales rep or by pivotal data falling through the cracks. The AI/CRM crossover is expected to grow into a $46 billion industry by 2020, according to IDC.

In traditional sales, the individual salesperson was the catalyst in determining the success or failure of the interaction. In the future, a salesperson will become more of an administrator to a CRM system that uses predictive marketing, probability analysis and machine learning elements to continuously optimize every touch point in the customer journey. Although the current generation of AI does not possess the creative outlook of a human salesperson, it is fast developing something almost as good – an endless well of data from which to create a reliable simulation of that creativity.

AI-driven CRM also automates the accumulation of that data. Automated data input virtually eliminates human data-entry error and scraping tools can update accounts as companies change structure in real time. The result is increased functionality that Salesforce predicts will account for $68 billion in cost savings and $195 billion revenue increases by 2021.

Conversational Computing

The machine learning technology that AI empowers creates less of a need for coders and programmers in sales intel. Through illustrations and predetermined rules, even companies like Google can constantly reinvent their smart products like Assistant, Maps, Search and many others. Assistant is one of the best examples – through its conversational experience, Assistant can give each user an individualized version of Google. Each user has a personal speech recognition and language processing application that can assist with scheduling business meetings, personal outings, gadget controls and other management functions.

 

Conversational computing also allows a company to scale its information grabs without scaling its manpower. One machine script can interact with an unlimited number of prospects across the entire customer journey. Not only can a company assemble information more readily, but it can begin to successfully predict how to interact with new prospects on the horizon. Through a humanized conversation, a company can also discriminate between visitors and high value prospects, driving revenue through increased efficiency.

Predictive Analytics and the Empowered Customer

Savvy executives know that understanding Pareto’s Rule has the ability to do much more than identify top prospects. AI empowers predictive analytics as well as conversational computing, and its “traditional” [read: obvious] value to business has been to send personalized messages to prospects that have been identified as likely to buy.

The information comes from an AI-driven collection methodology, so it’s definitely precise. However, the collection is far from the only reason this data is relevant. The two-way conversation that it potentially starts is just as important for a business to consider.

Ideally, prospects who receive personalized communications are more likely to respond. This does not mean they are automatically driven to purchase. However, most companies do not have the manpower to hold a conversation until conversion with every prospect that comes down the pike. AI-driven predictive analysis is for more than just demand generation. It is for continued prospect engagement, retention and nurturing all the way to the buying decision.

The innovations mentioned here are just a few of the many reasons that AI will become a more important aspect of B2B marketing in the future. Incorporating these functions into your funnel should be a priority now, not later. Although AI is still considered a luxury in name, more companies than ever are finding out that AI is a vital component of any modern B2B marketing arsenal.

Want to learn more about applying AI and machine learning within your demand generation process? Contact us today!

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