7 Ways Gen AI Supercharges B2B Sales Teams
Artificial intelligence entering the workplace is a foregone conclusion. Now, the focus is on how it transforms entire B2B growth cycles.
Forward-thinking leaders are deploying Generative AI across their sales ecosystems, not just to automate tasks, but to rethink how deals are discovered, nurtured, and closed. Here are seven high-impact use cases to consider:
1) Realize the next-best opportunity
B2B sellers often struggle with manual customer outreach, account research, mapping relationships, data integration, or insufficient training to make the most out of their sales tools.
With artificial intelligence, they can prioritize lists of customer-based recommendations and help target the right opportunities through internal and external data integration. The idea is to uncover the next-best chance for your business based on awareness and outreach automation.
2) Identify and take the right next step
Knowing the opportunities based on engagement and intent data is one thing, but knowing what actions require immediate engagement is another.
Gen AI allows B2B sellers to understand their next actions. For instance, Gen AI could analyze a prospect's recent interaction with a product demo and recommend sending a personalized follow-up email with a case study tailored to their industry or trigger an alert for the sales rep to schedule a call while the prospect’s interest is high.
3) Get instant meeting support
Prepping for client meetings takes hours, as you dig through notes, past deals, service tickets, and other complex correspondences. Gen AI auto-generates pre-call briefs, like highlighting a retailer’s inventory challenges and suggesting up-sell hooks for your analytics tool.
Meeting assistance doesn’t require a long time to deploy. Although many Gen AI-based tools out there are industry-agnostic, leaders and business development executives can pull valuable information from different sources which are easy to customize with existing solutions. This particular use case attracts the most excitement in industries with long sales cycles, continuous meetings, and massive deal valuations.
4) Respond to RFPs faster
Similar to meeting responses, manually replying to RFPs can be equally time-consuming. Gen AI can enhance the accuracy and efficiency of RPF responses, reduce response times, and manage internal tracking.
Such use cases are helpful in industries like life sciences, which require frequent handling of complex, regulated, and data-centric proposal requests, typically done through manual efforts.
5) Price smarter
Business leaders often rely on the commercial instincts of the sales team and data from analytics to determine their pricing model. With Gen AI, companies can adopt advanced pricing models commonly used in highly dynamic industries like online retail. This opens up significant opportunities for early adopters while putting slower-moving companies at risk of falling behind.
Key applications include AI-led price setting through customer micro-segmentation, which enables more accurate assessments of willingness to pay. Generative AI also supports negotiation by comprehending customer interactions and public data to provide sellers with insights, personalized arguments, and negotiation power scores.
6) Act as a real-time research assistant
Top-performing B2B sellers spend considerable time researching customers and products by gathering insights from websites, reports, market research, emails, and internal data. This process can be burdensome, especially during live calls, when quickly locating, digesting, and synthesizing information is critical for prompt replies.
Generative AI aids these instant interactions by operating as a smart research assistant, offering real-time fact-finding support. With on-demand insights, B2B sellers become sharper and more insightful in customer interactions, significantly enhancing the overall customer experience.
7) Coach your sales team
Given the lengthy and complex nature of many B2B sales processes, seeing managers struggling to accurately benchmark seller performance is not uncommon. Generative AI addresses this by analyzing performance data across all customer interactions, offering leaders a comprehensive overview of each seller’s effectiveness.
Additionally, AI-driven insights allow for targeted coaching tailored to specific needs. By providing personalized performance feedback directly to sellers, it supports their development and encourages them to keep pursuing continuous growth.
Sales Reinvented: The B2B Analytics Firm’s Story
Meet XYZ, a mid-sized B2B analytics firm selling data platforms to enterprise retailers. Like many growing companies, their sales process was solid but painfully manual until they brought Gen AI into the mix.
What Sales Looked Like Before Gen AI (And How It’s Done Now)
What’s Next for You?
Which of these use cases are you using or considering to deploy Gen AI in B2B sales? All seven use cases we discussed have the potential to become “Agentic” or autonomous, allowing business leaders to leverage the next wave of innovation.
Related read: Agentic AI vs. Generative AI
How to deploy these use cases in your sales cycles is a separate discussion in itself. In short, leaders should consider the basics before opting for Gen AI solutions for their sales teams.