In the very small business, the freelancer knows each customer. By name, by volume, by preferences.
And in the huge business, expensive software, data analysts and relentless margin seeking pushes organizations to increase their yield.
But most businesses (and non-profits and groups) are somewhere in between.
We donβt think of our customer list as a spreadsheet, but it is.
Perhaps you know names, addresses, emails and purchase historyβbut itβs likely that the customers you pay attention to are the noisy ones, or the ones that left in a huff. Weβre distracted, though, because theyβre not the majority, or the profitable ones, or the ones that really matter in the long run.
Tools like numerous.ai were inevitable, but seeing it work is still something of a miracle.
Hereβs a list of email addresses. Guess the first name of each customer.
Hereβs a list of recent purchases. Do an analysis of which customers are the most loyal.
Here are our donors. Find out which ones respond to this sort of project.
Hereβs a list of zip codes. Please build a table or graph to show us where are customers are clustered.
Here is our membership list along with recent attendees at our meetings. Who has dropped off in attendance and how should we contact them to see whatβs up?
At a big company like Amazon, this is all used against the customers, creating dark patterns designed to extract more ad money while denigrating the user experience (but not enough to get people to leave).
At a small organization, though, it can be a breakthrough. It uses the smaller size of the organization to your advantage, because the insights can actually be put to use by a human. Used to make things better for the people who count on you.
This is worth the effort. And if youβre not doing it, you can hire a freelancer to do it for you. And if youβre looking for a new gig, this is the sort of project you can build a business around.