“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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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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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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This is the third in a series of interviews I am conducting with subject matter experts and practitioners in the sales profession. I am examining where we are today with AI in sales and where we are going.
This interview is with Amelia Taylor. Amelia is the lead evangelist for Regie.ai. Regie helps sales, marketing, and success teams write engaging content faster using AI.
Here’s a summary of our conversation and below this summary is the full transcript of our interview.
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This is the first in a series of interviews with sales management subject matter experts, examining the current and future states of AI in sales.
This first interview is with Oliver Churchill, the founder and CEO of Acuity Sales Decision Science. Acuity enables B2B sales teams “to improve sales productivity in implementing prospecting and customer growth strategies using flexible process technology and Artificial Intelligence (AI).”
Oliver knows the space and has been a sales management practitioner for 20+ years. I was curious to hear what he thinks.
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