For years my job was taking care of actors. I was Head of Customer Care and Community at Backstage, the trade magazine actors have trusted since long before I got there. My job was to look after my fellow performers. I in-housed our remote print fulfillment and built a 17-person care team, and none of that would have worked without automation.
But the reason I fell for automation is smaller and dumber than that.
To cancel your subscription, you had to reach a person. On the phone. That person was me, or someone on my team. Every single time.
“To cancel, you had to talk to a human. For a long time, that human was me.”
We grew from 30,000 to 60,000 paying subscribers. At the time we were one of the 300 most trafficked websites in the world. And somewhere in the middle of all those calls I learned something about myself that I did not expect: I liked bringing new people in a lot more than I liked keeping them.
The free year
Not long before, I had volunteered at an event Backstage produced. I did it to get a free subscription. That is the honest reason.
So I had a thought. What if I could hand a free year to actors who were just starting out? The people I had been volunteering alongside. The ones with nothing yet.
I took it to our CTO and started reading. That is when I found The Bastards Book of Ruby, and a tool inside it called Nokogiri. Nokogiri reads a web page and hands you back only the parts you asked for. Plain HTML and XML in, clean rows out.
Here is the part that still gets me. Those actors had posted their showcases in public, on purpose, hoping somebody would notice and give them a hand. That is exactly what I was offering. So the data I needed was already sitting there, put there by people asking for the thing I wanted to give them.
Tens of thousands of rows. Every row a real person I had been serving for years, now matched to what they had shared in the open.
Of the hundreds of actors who took the free year, 90% became paying customers.
That was it for me. I was done with retention as a career. I wanted acquisition.
The morning list
Argyle Executive Forum found me and hired me. Their sales development reps had a routine. Every morning they went looking for which logos our competitors had just won. Then they called the field marketer at those companies and asked if they wanted to run a side event, next to the big one they had already booked at a Gartner or a Conference Board.
It was a good play. Watching it happen was painful.
Open a competitor's site. Scroll. Squint at a wall of logos. Work out which ones are new. Go find the right human at that company. Do it again tomorrow. Hours of it, every week, by hand.
So I asked the same question I had asked at Backstage. Surely there is a way to automate this.
There was. I worked out how to read our competitors' public pages, ran a reverse image search on the logos every morning, and dropped the results into a sheet. The sheet checked each company against Salesforce and found the right decision maker. Then it handed our rep a call list, before they had finished their coffee.
In the age of Clay this sounds like child's play. It was not child's play then. It gave our sellers back hours a week, and it helped us buy CFO.com and take the business global.
What it taught me
Two jobs, two builds, one lesson. Both times the win came from getting better data to the people doing the selling, faster than they could have gotten it themselves.
Your data pipeline predicts your revenue pipeline. If the first one is slow, manual, or thin, the second one will be too. You can hire around that for a while. You cannot outrun it.
Which brings me to now.
The AI answer engines are the largest extraction operation anyone has ever built. They read everybody's pages, including yours, and then they answer the question themselves. Sometimes they name you. Usually they do not. The work I did by hand with Nokogiri, on a few thousand actor pages, is now happening to the whole web at once.
So I went and built the meter. It asks the engines real buying questions and records who gets named. Same instinct as the morning list at Argyle, pointed at a bigger pipe. You can run it yourself, or read how the answer layer works.
Web scraping changed my life because it taught me that the data comes first. Everything a marketing team is measured on sits downstream of it.