AI for Sales Teams

Let’s first talk about the status quo. So, you want to sell a product or service. Let’s say you sell fire insurance. You will track your fire insurance sales in a CRM like SalesForce, Odoo, SugarCRM, etc… Maybe even using excel or Google Sheets. To make a living, you want to fill a pipeline of leads that looks like a funnel. The more you talk to people, the fewer are qualified leads. In doing this, you find that leads can be acquired from lists (e.g. lists by NAICS codes) or by credit authorities like Dun & Bradstreet.

A sales funnel

At this point you have your lead generation set up, which fills your funnel with potential clients, and you spend lots of time writing emails to info@something.com addresses, and getting your cold calls rejected by secretaries and decision makers alike. You get your wins where you can, and this is the status quo you have to live with.

What if there was a better way to find and qualify leads, using AI to help you out? When you are selling your fire insurance, you start to come up with some productivity metrics like minutes per qualified lead, or qualified leads per hour. Sales per month is a higher-level number that you keep in mind.

You keep what you kill. This just means you make more money if you sell more product, and also it’s a direct quote from this delightful Vin Deisel movie.

Now, back on track. You’re selling fire insurance and you begin to find that many of the leads on your call sheet and email list have no reason to talk with you. There is no ice breaker. You try and get creative but it tends to come through that you are “calling on behalf of [insurance company X], to sell [product Y].” You can cast this effort as introducing a feature “Let me tell you more about all the benefits” or an add-on product “You have insurance? Great! More is even better…” But, you now want to spend less time qualifying leads and therefore, hopefully, improving our sales. You want automation.

Introducing GenRush

Where does AI fit in? Well, imagine that we have an AI that recognizes events. For example, an AI bot that browses the internet looking for hints (i.e. leads) that a company may want to buy your fire insurance. For example, a list of leads that have recently changed address may need fire insurance, and your icebreaker can now be relevant to the client e.g., “Hello Mrs Johnson. I see you have moved/expanded recently to a new location in [neighborhood name], and wanted to make sure you considered purchasing fire insurance protection for your new location.

GenRush Demo Animation

This lead generation approach is not about you approaching clients cold. Before the AI got involved, you were making your way down a static list. With this new AI tool, your day is now about the leads coming to you, and your response to their relevant events.

Now, it would be nice if you could still experience these events as a list, like you are used to in your CRM. You also want to save multiple criteria (saved searches, like companies that recently moved address) and get email notifications that give you lists of relevant people to contact, and a reason to contact them.

As you may have gathered, I’m going to introduce you to a select few features of our tool, GenRush, which does the lead generation introduced above. There are many AI features in GenRush that are still in stealth mode, and so this is my way of showing some leg without putting out on our first date. GenRush is still in alpha testing.

Let’s compare GenRush to finding clients on Google. Consider the features that each platform has to offer. In GenRush, the user can sort by the date of a company’s registration, recent activity, keywords, and location. Google has much more limited search parameters like keywords and specific dates. Another feature in GenRush lacking in the other platforms is the ability to export search results.

Say you want to search for “technology” “tech” in some specific neighborhood, making sure to exclude results related to “food” or “skydiving”. GenRush accepts this sort of search, including idea search (semantic word embedding) rather that simply employing text keyword search.

Conclusion

In conclusion, GenRush is a promising new lead generation platform for helping sales staff. We are bootstrapping this new venture, and early results are very promising. By efficiently targeting relevant leads, this system could be a game changer. We are still in alpha and steaming ahead with R&D. If you want to participate in the beta version of GenRush, then email me or fill in the form on GenRush.com

Happy coding!

-Daniel
daniel@lemay.ai ← Say hi.
Lemay.ai
1(855)LEMAY-AI

Other articles you may enjoy:

Daniel Shapiro, PhD

Written by

Passionate About Machine Learning R&D and Value Creation. ✍ daniel@lemay.ai ⬱ https://lemay.ai

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