AI, an impeccable force has transformed the landscape of several industries over the years. Painting a futuristic picture and creating distinguished experiences for the customers, with AI, we can surely say that the Future is Here!
AI and ML together have started to impact customer experience functions more than ever before. B2B selling has always been considered unique and varies widely in terms of consumer sales. What role AI could potentially play in B2B sales despite the presence of impeccable Sales technologies, has been a bewildering question for B2B business leaders today.
Gartner predicts that up to 30% of B2B companies will employ some kind of AI technology to augment at least one of their prime sales processes.
Multiple pointers highlight the probable impact of AI in B2B sales.
Let us consider a few prominent use cases of how AI could be deployed:
1. Prospect Research and Business Intelligence
Various statistics reveal that sales teams spend less than 50% of their time in the core activity i.e., selling. Whereas, a good amount of time is invested in trying to gather information on the prospect’s business and key contacts.
Keying the data into one of the essential sales technology tools like CRM is also important. Modern AI algorithms assist users to automatically update leads with more precise information and in quick time.
It also allows companies to check on the key searches undergone by prospects and the time spent on specific web pages. This intelligence goes a long way to understand unstated needs in the early stages of the buyer journey
2. Lead Scoring and Qualification
AI-centered tools scan voluminous prospect leads data and correlates with the profiles of existing customers to pick the best that have a high probable likeliness to buy.
This scale is impossible to replicate manually and saves valuable time during the lead scoring and qualification stage.
3. Email Follow-up
Sales executives end up spending a lot of time writing to leads that don’t respond. Surveys and real-time experiences have shown that B2B prospects need multiple touches before they respond.
There are AI-powered tools that mimic human behavior and that communicates with those unresponsive leads and respond to the leads on multiple queries nearly human-like. Such leads after an automated basic check of qualification are handed over to sales executives.
The sales team gets into productive engagement with qualified prospects and doesn’t lose focus by chasing seemingly good leads that would never buy.
4. Account-based Sales
Business buying involves multiple stakeholders and is collective in nature. B2B sales managers try to align the value proposition with apt communications for different functional departments within the buyer organization.
Many AI-supported platforms in account-based marketing/sales domains enable operating with multiple functions focused on their key result areas through multiple social tools.
5. Conversation Intelligence (CI)
Several factors contribute to the success of a sales professional and a key one is the way they converse with the customers.
Organizations have been recording sales calls for years now but the best out of these recorded tapes are placed in the darkest ends of a drawer/cupboard that have never been heard.
AI-powered CI software tools process these conversations from recorded calls to identify and present data on ways of introduction, Talk: Listen ratio, objection handling, commonly used keywords, success stories, asking for closures among others. This presents ample data for sales coaches to pick up the key traits of successful sales executives and to provide personalized coaching to the fringe sales players to substantially improve their sales performance.
With the potential they possess and the results they deliver, AI and ML technology will evolve further and contribute more to the B2B selling ecosystem.