Here's how you can incorporate artificial intelligence into sales engineering.

In my experience, AI can add a lot of value in solution selling some usages : automating routine tasks, taking meeting notes, crawling public information about your customer and also targeted solutions campaigns based on CRM data. AI is an enables and should be used to enhance the experience.

Grasping the fundamentals of AI is crucial for effectively integrating it into sales engineering. AI's algorithms empower machines to handle tasks that usually demand human intelligence, such as data analysis, problem-solving, and language comprehension. In sales engineering, leveraging AI helps analyze customer data and predict buying patterns, which can enhance our strategic decision-making. By automating routine tasks, AI enables us to devote more time to creative, high-level work that adds value to our clients and business. Understanding these basics paves the way for smarter sales engineering strategies.

AI enhances sales engineering by streamlining processes, personalizing customer interactions, and providing data-driven insights. It analyzes customer data for tailored pitches, predicts sales trends for better lead prioritization, and automates proposal generation. AI-powered chatbots handle routine inquiries, allowing sales engineers to focus on complex tasks. It suggests product recommendations for upselling and cross-selling, offers personalized training, and improves CRM systems for efficient relationship management. Overall, AI enables smarter work, quicker responses, and improved sales outcomes.

The platform I sell leverages AI to make data analysis easier, and one of my biggest things I help customers/prospects understand is how to use AI effectively for data analysis, which means how to create the right prompts. While AI is great, it still needs the user to guide it, and this also applies to data analysis. The user need to provide detail on what kind of analysis to perform to the AI, so the AI will know what to focus on. Working with customers/prospects, I have helped them leverage AI-powered data analysis for understanding what influences sales, affects Return on Ad Spend, what causes people to open emails, similarities of customers that might be a churn risk, etc. in a way they can feel confident in the results.

As a leader of a Sales Engineering team, I enjoy using Clari to investigate the current Q and next Q pipeline. I can find trends that I use to guide my team's focus. For example: if there are a lot of opportunities I can use the AI to find the ones that are most promising to focus our time on and help the team prioritize. Or if there are too few opportunities I can use the AI to identify which ones we could potentially pull forward. Great and quick responses to demo request for these opps should be the priority.

AI can be a game-changer in sales engineering tasks. From streamlining RFP responses by providing relevant information quickly to automating demo engineering processes and even assisting in design templatization, AI has the potential to enhance efficiency, accuracy, and effectiveness in various aspects of sales engineering. By leveraging AI tools and technologies, sales teams can focus more on building relationships with clients and delivering tailored solutions.