How You Can Use AI to Create Customer Value Based on Insight into Customer's Business
It is the two letter word that dominates almost every conversation, these days. Almost to the point of boredom and fatigue.
But when it comes to how you can actually put AI to use in sales and selling, there's not much help available.
A ebook on AI-Powered Sales - An overview of how artificial intelligence is changing the game for current and future sales organizations published by Mercuri International Research lists some practical ideas on leveraging AI to raise the bar on sales and selling.
Here are adapted excerpts from the book that discuss how AI can actually be used to prepared before every client meeting and create value for Customers by gaining insights into their businesses:
Salespeople need to have insights into Customers' business even before meeting them
- Understanding the customer's industry, business and long-term ambitions is a critical factor for any salesperson who wants to be perceived as creating value.
- No Customer or decision-maker has the desire or commitment to spend time in unnecessary meetings that don't give them anything. Thus, salespeople need to find out as much as possible about the Customer that is relevant.
- This may involve understanding the Customer's current situation, challenges and needs, financial health or goals and growth plans to help them improve their business.

AI Tools like ChatGPT can act as a sounding board for you
AI tools like ChatGPT or Perplexity can act as a sounding board and advisor to answer questions you have about a particular company, its market or products.
There are also several more niche AI tools like Baron that work as enhancements enabling you to use standard AI tools like ChatGPT in all regular applications like Excel, Word etc. to generate data about customers' businesses.
Going beyond names and details of the tools involved, what's more important for a salesperson is that this means an increased opportunity to adapt your selling style based on the Customer profile.
A Use Case Example – Conversation with a Soya Farmer with Large Holdings
Let's say you work as a salesperson in a company that sells all kinds of agricultural products to farmers. You realize that if you could access information on weather conditions, crop yields, plant physiology and soil conditions, you could help your customers make better decisions and optimize their operations using your products. So, you want this information to help you do a better job and create value for your customer.
Now it's time to think about where you can find this information and how you can use AI to analyze it. You don't need to think about the technology behind AI, but you do need to know what tools are available and which companies or organizations could provide this information.
In this case, you discover that there is a company that collects data on weather conditions and climate change specifically designed for farmers. This is done using meteorological satellites, radar and weather stations. You also discover that the local government also collects data on soil topography, moisture, plant cover and pests. Finally, you find out that a tractor maker provides tractors equipped with sensors that collect real-time data on all its machines. These are routes, positioning, fuel consumption, machine status but also data on weather, soil and plants. These three sources thus collect millions of different data points from various sources that can be of great value to a farmer.
What if you could now access this data and use a AI prompt to analyze and identify patterns and trends that can help your customer make better decisions? Such an analysis would be at a level that a human being is nowhere near capable of.
Now imagine that you are going to contact a potential Customer who could benefit from this information. He is a large farmer with extensive land holdings. The classic way would be to call and say:
"Hi, my name is X and I'm from this company, let's make an appointment so you can tell me about your farm!"
Equipped with AI, the salesperson can now tell the Customer:
"Hi, I have done some research about your farming activity which could be potentially useful to you. May I share it with you? Last season, your soybean harvest may have been reduced by 20%. I understand that the rain ruined a lot. But it is not only that. According to data, soil conditions have changed, resulting in several new pests becoming established. That's why planting was delayed by most farmers this year. We now also see that the harvest planned for October could be delayed until at least November. This means that return on activity may be lower by 4%. However, there is a solution for this.
To reach the desired yield, a special plant protection product may have to added that is adapted to your crops. Given the soil conditions, a different fertilizer may have to be added than the one being used now. This work should start now in August.
"By the way, with the increase in output prices, your interest costs can go down by 1 percentage point if funding is arranged now. That could fetch savings of around 50000 annually".
"I will be happy to share details more about this when we meet. Would Thursday be convenient for you?"
Such extensive pre-meeting research is made possible by AI tools that are currently available for all and is poised to revolutionise selling.
There is no such thing as luck. There is only adequate or inadequate preparation to cope with a statistical universe
– ARobert A. Heinlein