it’s your first sales job, and you have limited experience selling (correction: you popped up a lemonade stand when you were 6-years-old). You’re a business development representative at a startup company with no clients and very minimal training. And on top of it, you’re selling software to banks and credit unions. You’ve got great talking points, a convincing ROI, and a call list.
It will take a while to get clients, and it will take a while to get used to selling in a new role. For me, it took a while to get comfortable using artificial intelligence terminology to explain why we were better than our competitors. However, with the help of my company’s executive team, I learned to talk the talk without earning a PhD in machine learning.
Without patience and teachings, I would never have gained the trust and respect of most of my prospects in the initial 30 seconds of a cold call. This is why I’m advocating for technical leaders building artificial intelligence solutions and other technical solutions to teach all salespeople about the different approaches technologists take to solving problems.
Here are my three reasons:
In a world where time is our biggest asset, and buyers are guarding it more closely, sales organizations are becoming true teams with business development representatives, enterprise sales executives, and sales engineers. While teamwork is great, it sometimes means there are a lot of people talking.
Some sales take longer, I get that. Our sales cycle was 9-12 months, but this isn’t usually because the provider can’t implement or get it to you faster. It’s usually the buyer’s internal decision making battles. A good salesperson guides the conversation to a decision, and the less they have to rely on the next meeting or availability of calendars, the better they can help the buyer make a decision.
So let’s describe the perfect scenario: it’s been four months, you finally get on the decision-makers calendar, and you have a champion! At the last minute the CIO shows up.
And the CIO asks about what makes you different than the current models they use?
The usual response is, “Let me follow up with you after talking to our CTO.”
After using this enough times, I decided I needed to really learn and ask questions. I learned the differences between a decision tree and a neural net, and tokenization vs. encryption. But it didn’t stop there. I learned how to weave it into a compelling story.
And that’s exactly what engineers could learn from salespeople when answering technical questions. A good salesperson will weave it into a compelling story, and then ask follow up questions such as, “How have you compared different vendors with different models, previously?” or “How would you suggest we ensure the solution fits your needs right now?”
The technical understanding allows you to shape your story for the most technical and the least technical person in a meeting. It allows you to show credibility and gain trust from everyone in the room. As always, there are exceptions, and you may need help. I called for help several times.
Getting a PhD in machine learning is the last thing people think about, but take it upon yourself to learn about it in any way possible even if you are in sales. I’d suggest other salespeople put in the time to learn about how engineers do what they do, as well. Why? Because it’s pretty clear: when salespeople and engineers work together, organizations do, too.