“The money is in the list” is an old direct marketing adage going way back to the development of the envelope. Despite all the digital changes in in sales and marketing, if you’re running a business and trying to use outbound to grow it, the money is still in the list.
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I recently had a conversation with a business owner about how to improve their CRM data. It’s a conversation I’ve had many times over the years.
It’s not that this business needs more data in its CRM or is missing an important prospect list. The CRM in question has plenty of contacts and accounts–think nearly a hundred thousand contacts. It’s that with this huge list of potential customers, the business is not actually easily able to sell. There is too much data and not enough useful information.
If you find yourself with a CRM that is full of data but not easy for you to use to make actual sales and nurture relationships, consider some of the following ways to organize it. Think of this like Marie Kondo for your CRM.
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We may be entering a “new, new era” of selling—an era that takes us back to good old-fashioned relationship selling.
Up to this point many of the tools available to sales teams have encouraged volume-based sales techniques, like mass emailing and cold calling. But as more and more salespeople use these tools, buyers have become inundated with low value communication. Inevitably connection rates and conversion rates have dropped quickly.
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Data has been called the “new oil” because of its value to today’s computer systems. When it comes to AI, data is critical. AI needs huge amounts of data for training.
Essentially ChatGPT is now giving us access to a portion of the knowledge out there on the Internet (which is a lot—at least 1,200 petabytes.)
For many of us our focus over the last several months has been how to develop the best prompts to get the best responses from ChatGPT. Prompts have been getting longer and more complex, some of them essentially turning into a form of computer programming language. “Experts” are designing prompts that squeeze just a little bit more out of ChatGPT each time by “talking to it” in a way that makes it work more effectively (or just harder.)
Here’s my forecast though: Prompt engineering will not be enough to give any business a lasting competitive edge.
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“Her” is a 2013 film about a lonely writer named Theodore Twombly, portrayed by Joaquin Phoenix, who develops a romantic relationship with an AI on his phone named Samantha, (voiced by Scarlett Johansson). The film predates the “coming out” of ChatGPT by a decade but surfaces some of the behavior that apparently is already happening on certain online dating sites.
In our more mundane, but still relationship-centric, world of sales, how far will buyers go with replacing relationships with humans with relationships with AI? My guess, for the foreseeable future, is not that far—at least when it comes to large purchases.
I believe AI will play the role of sales assistant not sales lead when it comes to important buying decisions.
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In the near future, savvy salespeople are going to greatly enhance their sales by leveraging AI. One of the mechanisms for this improvement will be leveraging the “social graph” more effectively.
It’s always been true that a referral beats any other lead, with referrals converting to customers 50% of the time, according to Joanne Black. AI will help us use our “social graph” to find referrals without spending too much time on research. Up to this point, this kind of research has generally been too time-consuming for the average salesperson.
The best tool today for this research is LinkedIn. LinkedIn can show us who knows who. Unfortunately, this connection data is not reliable, with the system showing people knowing many more people than they actually do in “real life”. In my research, I find that less than half the connections someone has on Linkedin are people they really know.
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