I’ve been excited about AI for a long time. Before Superpanel I was working on AI models to compare the language in insurance contracts, and my co-founder was leading machine learning teams building best-in-class ML models over the last 7 years.
We’ve been exploring AI in PreSales since mid-2022 and as AI capabilities advance I think PreSales is a great place to be. The role of PreSales will evolve but I think it will also become more important.
Here are a few ways I think AI will impact PreSales over the coming months and years:
AI will automatically capture and organize discovery information and detect whether adequate discovery has been done before doing a demo, POC, or looping in an SE. AI bots may even run solo on initial calls and perform discovery before a human joins a deal. You’ll still need to review the discovery documentation, make necessary edits, and flag unanswered questions, but the quality and consistency of discovery will be significantly higher across every sales opportunity.
AI will read notes, listen to calls, read your calendar, and automatically update whatever CRM fields are necessary for you - but give you the option to review and edit if needed.
You’ll be able to ask an AI assistant to show you how much time you’ve spent on each deal, how much time you spent on small deals vs large deals, a breakdown of types of work done, and a breakdown of time spent with each AE. You’ll know where your time has the highest ROI and which AEs are wasting your time. SE leaders will use this data to drive SE coaching, headcount planning, as well as AE coaching so that each AE is not wasting SE time.
Discovery data and natural language descriptions will be used to create demo environments, demo recordings, or slide presentations. SEs will need to become proficient editors and AI collaborators to ensure the accuracy of these materials.
Rather than searching through Google Drive, Highspot, Seismic, etc., AI will read your calendar, understand upcoming projects, accounts, and opportunities you’re working on and surface relevant competitive intelligence, product updates, industry use case materials, technical learning, etc. to ensure continuous learning just in time.
If you want to research a company, dive into their investor reports, financial filings, or earnings calls, you’ll have an AI assistant to do that for you and summarize findings. If you want to know about any recent news, announcements, or job changes at a company, your AI assistant can do that for you. If you have calendar conflicts and need to reschedule meetings, an AI assistant will flag the conflict and handle rescheduling.
With all the conversations that SEs have with prospects and customers, insights around customer needs and marketing messaging will be auto-summarized for you to review, edit, and share with other teams. Product managers will be able to make better product decisions based on learnings from PreSales teams, and marketers will know if their messaging is resonating and be able to mine conversation data for better messaging ideas.
With AI-enabled discovery documentation, you’ll have instant recall of why every customer made a purchase or didn’t make a purchase. The discovery data will be connected to product usage and churn data to understand what discovery learnings are indicative of a good customer or bad customer. This will help every department improve. Marketing and sales can create more targeted messaging and product/design/engineering teams can make better product decisions.
What do you think about these predictions and about the future of AI in PreSales?
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