Your sales team is about to get bigger.
Sales automation isn’t anything new. About a third of sales can be automated, according to McKinsey, and a remarkable 86% of sales and marketing leaders say their sales teams already use AI in some form to enhance one or more business processes.
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But the rapid adoption of ChatGPT and other large language models (LLMs) – with their ability to engage website visitors, generate leads, handle customer objections and develop proposals – is destined to become the real game changer.
The under-tapped potential of ChatGPT for enterprise sales
Most know the basics of large language models by now: you can have conversations, create content, and brainstorm on everything from simple social media posts to complex reports and white papers. Other chat-powered AI tools, like Midjourney or Dall-E, can turn text into digital images.
While some have used ChatGPT to support various aspects of the sales process, LLMs’ value as a de-facto business development representative (BDR) has been underplayed. This means not just providing market insights or audience analytics, but interacting with customers directly and independently mapping creative solutions to their problems in real time. LLMs can listen and engage with customers and prospects as individuals, not as a set of demographic or other pre-loaded criteria.
“One of AI’s largest benefits to my team is in creating a starting point to organizing how you think about something – be it for starting outreach to prospects, understanding potential objections, understanding the impacts of legislation on a market or laying out a potential dialogue with a customer,” said Rikki Schmidle, Informa Tech’s Vice President of Sales for EMEA.
We’re in the early stages of generative AI, but there are plenty of ways you can take it for a test drive today. Here are seven examples of how enterprise sales reps can leverage large language models in the buyer journey:
Website sales engagement
Large language models can integrate into your site as a supercharged virtual assistant. In the form of a chatbot, a LLM can both understand and respond to inquiries, provide product information and make personalized recommendations. Microsoft uses AI chatbots in this way, and in fact has used AI-powered sales tools for years to improve lead generation and accelerate the sales cycle.
Lead generation and qualification
Identifying and qualifying leads for the correct sales action is a time-consuming and often monotonous task. But LLMs can collect and synthesize essential customer information quickly, assess needs and determine level of interest, as well as filter out any unqualified or low-value leads. Salesforce uses this approach with its Einstein application.
- Keep in mind: There is a caveat, however: The data you plug into free-use LLMs like ChatGPT is used to train the LLM, which means it could eventually be shared with other users. “We’re still learning about the impacts of sharing data through large language models,” Schmidle said, “and as a research and data firm, we have to be particularly careful about what we share and put into these models.”
Objection handling
Addressing customer objections is crucial for sales success. ChatGPT and other LLMs have this covered too, as they can be trained to answer frequently asked questions about pricing and features, explain product benefits, provide troubleshooting tips, and offer self-service options to customers. Those actions reduce the workload of customer support teams and have the potential to improve customer satisfaction.
Customer proposal and RFP assistance
LLM integrations can assist sales teams by providing real-time access to product or service information, case studies and pricing options. They analyze RFP requirements and help sales teams provide responses that meet customer needs, streamlining the proposal development process and increasing the likelihood of winning deals. Microsoft Viva, for example, boosts sales by using Azure OpenAI and ChatGPT to create proposals or reply to inquiries.
- Keep in mind: While enticing, Schmidle cites the need for diligence here, too. If generative AI provides incorrect information that leads sales reps to present misguided assumptions – or generates cardboard, impersonal copy, as ChatGPT is known to do before humans edit it – the potential customer could be turned off quickly. “Both of those would have a negative impact on relationships and trust,” Schmidle said.
Follow-up messages
LLMs can be trained to create personalized messages for leads and customers based on their behavior and engagement with a company’s website or social media channels. This includes automated emails, text messages or chat messages that ask about the customer’s experience and offer support. This personalized approach, when combined with longform thought leadership based on market intelligence and analysis, is a great way to drive digital demand generation.
Appointment scheduling
LLMs can be integrated to schedule appointments for sales representatives by asking qualifying questions and recommending a convenient time. They can also be trained to send calendar invites and reminders.
Sales training
According to Statista, 57% of B2B marketers as of October 2022 used chatbots to understand their audience better. With ChatGPT, reps can simulate sales conversations and improve their communication skills with real-time feedback and coaching.
Experiment, but don’t forget who brings the value
If you haven’t yet experimented with ChatGPT, start with small-scale implementations and test the model with real-world use cases or problems you’re looking to solve (but don’t share any proprietary data). Collect feedback from customers – many of whom will expect you to already be testing AI technology in your work – and identify areas of improvement, looking to unlock personalization opportunities where possible. LLMs like ChatGPT learn the more they’re used, but it’s an opportunity for you to learn, too.
And that’s probably the most important aspect of AI – you.
While LLMs can do a lot, they can’t replicate the nuances of a human touch. You’re still the best brand representative for your customers, especially when guiding them through complex or sensitive issues. Striking the right balance between AI automation and human engagement is the ultimate key to success in the age of AI.
“There is a fear that generative AI could make research and data firms less critical, but I see it doing the opposite,” Schmidle said. “ChatGPT might be a good starting point for understanding a topic at a high level, but in order to validate the analysis – you must cite a data source that is reliable and unbiased. This is where our data and research becomes incredibly important.”
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