Artificial intelligence has been transforming business for years, but that transformation accelerated when ChatGPT opened the door to its easy-to-use generative AI in December 2022. Since then, companies have been integrating AI into everything from internal communications to customer-facing messaging to productivity tools.
Well-managed AI tools can work in marketing, finance, manufacturing, and even B2B sales. But you may not want your critical connection to your business accounts to be replaced by a B2B sales AI. So what role can B2B sales AI play beyond administrative tasks?
First, let’s peel back the layers of how your sales and revenue departments operate to uncover the manual, analytical, and technical skill aspects where AI can handle tasks on its own or act as a handy assistant (copilot) for your team. Here are some early possibilities of what AI can do:
Create detailed customer profiles and account strategy plans
Personalized outreach at scale
Train sales reps through interactive role-play simulations and provide instant, detailed feedback
Track all new sales, renewals, cross-sells, and up-sells opportunities to ensure nothing slips through
Give directors and managers the information they need through training profiles, predictive models, and detailed reports, all created and readable by artificial intelligence.
But technology is evolving quickly, so let’s think about the broader vision next.
What can AI platforms do for B2B sales? Robust AI tools are still in the early stages of development. Since ChatGPT was widely adopted in early 2023, its business tools have expanded to offer a wide range of AI-powered support features, analytics options, easy-to-use productivity options, and more. See where AI in B2B sales can usefully fit into your sales team’s workflow. Marketing
One of the most important use cases for artificial intelligence in today’s B2B environment is marketing. People can’t handle customer-based marketing and increasingly personalized approaches alone. That’s why companies are adding AI-powered ad creation tools, marketing campaign platforms, and robust marketing analytics integrations to their tech stack. As enterprise-level companies refine their messaging to directly appeal to key decision makers in the target organization at the right time and with the right reach, other companies must do the same or be left behind.
Specific tasks that AI can optimize include:
Automating the lead scoring process
Timing interactions to shorten the sales cycle
Understanding the context of an interaction to determine a prospect’s intent, goals, and concerns to better translate intent metrics. Unraveling B2B sales relationships, especially when multiple stakeholders are involved, allows salespeople to deliver the right message to the right stakeholders.
Background work of account management
Salespeople must assume the role of account manager and salesperson to provide a broader, more customer-focused service. This is one of the most effective approaches to overcoming distrust. This is true in any sales environment, but it is even more important in B2B sales, with its lengthy sourcing process and long-term relationships.
Managing all the customer touchpoints, interactions, org chart details, and SWOT analyses that AMs traditionally do can overwhelm busy salespeople with manual processes. AI-based AM tools work quietly in the background, informing salespeople of the best time to start a conversation, what needs their attention, and what their priorities are for the day, week, or quarter.
Monitoring
No company can ignore the importance of data in today’s sales environment, and business leaders who operate in the dark are doomed to fail. Sales managers need to stay on top of their team’s progress on big deals, accounts that could be lost, and deals that will spill over into the next quarter. To make strategic decisions, VPs and sales managers need a more holistic, guided view.
Again, the data companies can and need to collect quickly makes it impossible to manually manage all of these monitoring and analysis tasks. AI and machine learning tools for B2B sales can analyze raw data and surface the key trends and insights leaders at every level of an organization need to act effectively.
Related: Is AI for Sales Pitch Training the Next Breakthrough? Predicting Quarterly and Annual Goals
Everyone in the sales organization has quarterly goals they need to hit. Entry-level sales reps and business development reps have sales call quotas. Regional sales managers have sales goals for new customers and retention. Executives need to ensure the company is on track to pay its bills, reassure stakeholders, and plan growth initiatives for the coming year.
While traditional tools and even five-year-old smart spreadsheets can uncover underlying trends and estimate the likelihood that executives will hit their targets, B2B AI can provide much more accurate forecasts. Finally, trend lines based on performance in the first half of a quarter won’t fully reflect the second half, especially in a fourth quarter with a lot of travel and delays. Smart salespeople may have made adjustments in their heads because of their experience. Still, only AI can provide accurate forecasts that take into account human factors, past years’ performance, competitor performance, and hundreds or thousands of other factors. For companies that need to get the most tangible return possible from their tech stack investments, this is one of the most significant and immediate benefits of AI in B2B sales. According to a McKinsey data analysis written by Forbes Technology Council member Selva Pandian, “Research and insights show that what McKinsey defines as data-driven decisions can lead to a 2% to 5% increase in revenue. Agility to scale revenue and reprioritize accounts can yield a 5% to 10% lift simply by reprioritizing sales according to data, without changing sales processes or training efforts.”
Sales Training
AI in B2B sales will have the biggest impact on B2B sales training. Any sales training leader knows the training process is tough: repetitive training procedures, countless small variations in prospect responses, and a lot of time spent trying to turn salespeople from expense sources into revenue streams. After all, salespeople don’t make money on training, and the company benefits less from experienced salespeople training salespeople, answering questions, and keeping deals from falling through the cracks.
Let’s take a closer look at how AI in B2B sales revolutionizes B2B sales training in these key aspects:
Interactive Sales Role Plays
Interactive sales training is one of the most valuable learning techniques. Salespeople can model common scenarios, practice messaging, and develop techniques for dealing with confused, frustrated, or ambivalent prospects. Role-playing scenarios allow each sales rep to focus on their individual skills without worrying about practicing on customers.
However, traditional sales role-playing training has several drawbacks. First, most sales reps don’t like it. They don’t like performing in front of an audience. They may feel shy or judged by their trainer and feel they don’t get any benefit from the scenario. It’s artificial. Because of the one-on-one nature of role-playing exercises, providing regular sessions and feedback may not be an option for busy training or management teams.
AI training software can handle this task with AI sales simulators. A robust AI sales coaching platform can:
Generate an endless set of realistic scenarios that revolve around a seller’s everyday interactions while focusing on specific skills and concepts.
Role-play the role of a “prospect” or “customer” so sellers can practice without a live audience.
Evaluate reps on exercises like mock sales calls, cold calls, and upsell scenarios.
Generate meaningful responses for each part of the interaction, driving the realism and goals of the scenario.
Provide real-time coaching and feedback to deepen learning.
Allow sellers to practice again and again.
Handle prompts.
AI can read increasingly detailed cues, providing deep insights and informing B2B sellers of the best tactical move in every interaction. It does this by:
Analyzing voice sentiment in audio, video, and text messages to help sellers deliver the right response.
Recognize which phrases and negotiation points were most successful in similar interactions with similar prospects
Distinguish between true intent-to-buy signals and time-wasting signals
Having AI tools built into your CRM or available as open tabs on your workstation can help your salespeople work more efficiently, reducing mistakes, delays, and lost deals. This also speeds up training by helping new and inexperienced salespeople quickly learn your company’s unique sales process and typical customer base. Even less experienced salespeople can move from training sequences to cold leads to hot leads quickly and with confidence.
Personalized learning paths for every salesperson
Every salesperson has different learning needs that can be difficult for sales managers and training teams to accommodate. As your company grows, you may bring on new inside salespeople, field salespeople who have been with the company for years, and new hires who are experienced salespeople but new to the industry. Each employee needs training, but the training needed can vary widely between basic skills, industry-specific topics, and entirely new messaging for a newly launched product line. Additionally, each employee has different natural talents and preferred learning styles.
This is where AI comes into play, allowing you to develop individualized learning paths for each employee. The process begins with a series of assessments aimed at objectively determining each participant’s current skill level and knowledge base. Based on these insights, Training AI can identify which modules make the most sense and generate scenarios that address gaps and deficiencies as efficiently as possible. This allows trainees to start their training without waiting for a trainer to arrive or waiting for a seminar or course. Modules, training exercises and next steps are always available, even during downtime.
Sales managers and trainers can see everyone’s progress at a glance, enter new goals and evaluate how each individual is developing new skills.
Automated feedback and standardized evaluations A successful sales process requires continuous improvement. Even the most effective tactics and workflows need to adapt to changing buyer behavior with frequent, incremental changes. AI employs growth-oriented design principles: making and testing small changes without compromising core processes to make them even more efficient. She can read signals from small, largely unnoticed buyer and seller actions and provide feedback to fill gaps and improve interactions. This means that salespeople are constantly improving their performance, whether they are entering the market as new sales experts or experts adapting technology to modern B2B buyers.
This flow of information is not only continuous, but also objective and data-driven. Toxic workplaces, high turnover, and simple human subjectivity are dangers in any training situation or performance evaluation. But when AI continuously analyzes workflow and performance, trainers and trainees (and managers and salespeople) can see where they’ve made progress and where they can still improve. Even better, this information is available for review at the end of each quarter or week, even after the interaction is over and the employee is ready to reflect.
