“Data? You’re giving me data?”
(or ‘What we’re doing here,’ part 1)
My first full time job, for $30K USD (in the Year of Our Lord 2008), was professional services. Account work at a digital and direct marketing agency.
It was also the hardest job I’ve ever had, pre-or-post business school.
Adjusting to 40 hour office life was a real bear. I had to learn Outlook filing, copiers, how to sit still for more than 30m at a time. (This isn’t why it was hard).
At first, the toughest part was dealing with the customer data that drove these campaigns.
We’d get an excel file on an FTP, download it, check the contents with several sorts, rename it, place it in a shared network location, fill out and initial a checklist, copy and file it, and then run a physical copy two floors up.
I had to do this for 8 “SMB clients” (aka local-based nonprofits in different DMA metros across the country), and for 12–16 marketing campaigns for each annually, with their own nested date driven by a workback schedule driven by mailing schedule. Clients would be late with the data and we’d have to call them. Or our artwork, billing, or analytics duties would spike on a day when dozens of checklists were due, each with its own idiosyncratic error conditions.
Or the data would be wrong, in an identifiable way. *This was the scary stuff.*
- It might have an artificial ceiling on customer trans range, meaning it was an excel full of the lowest value customers to target. (gross rev, avg cart, etc would suffer as a result).
- It might be drastically smaller than previous files or way, way larger (indicating that the query used had changed and at the very least we had a mystery on our hands).
- It could be from the wrong date range, or if pre-segmented have wildly different segment counts.
- Or the text fields for customer flags might have values like “Do not ever ever mail” in them — but everything else would be in order. If you didn’t check for that every so often, you would miss it.
If something went wrong with one of these and made it past the checklist — you would hear about it in 3 months or so when the mail pieces hit and the client ID’d an issue. The first point of failure was the checklist, and your signature on it.
These were great client organizations, often with sophisticated databases. But as an account coordinator, the data QC process of 2008 was a dud. We all hated it (there were about 15–20 of us across different accounts). I was particularly bad at first. With a hard time focusing, busy account leads, and no formal training program — I missed a couple issues that my boss caught. Then one made it through once she trusted me — and I had to write an apology email that got run up the flagpole to an EVP.
I ended up distilling both types of data checklist processes (cultivation/acquisition) into an SOP document. I didn’t know what to call this at the time — just that it was my ass if more issues slipped through. And that I needed to put all the oral history I had been trained on down on one sheet of paper. So I could look at one doc and know everything I had to do.
Things changed after that. I stopped missing things, and a few account leads came around, asking for my training doc. That was cool, I guess? It was more of a necessity than a leadership moment, because I was on thin ice, #PeteArmy. I would absolutely tell someone to take that step today — but at the time…the checklist was the most robotic, boring work we did as account coordinators. And was not a glamorous thing to focus on.
Glamorous or not, formalizing that data QC process, improving on it, figuring out ways to automate it or train others — was the start of something big for me. Becoming known for that skill internally stopped the bleeding, put me on good footing, and helped us improve relationships with the clients. And when a new account director came looking for people willing to make an internal move — it positioned me well (and several others).
Right before I got selected for that team — another colleague and I were discussing why this director would want to bring us on board. “Well, I’ve been working on creative strategy and some analytics profiles. You, you’ve got…data or something.”
“You’re…you’re giving me data?” I said, channeling Chandler from Friends. “That’s what I get to be good at?”
That phrase has stuck with me. Customer demand (esp since 2008) is driven by data, not Don Draper speeches. And that data is captured, analyzed, and julienned using some technology that’s evolving faster than anything biological ever did.
Marketing technology is a $100 billion dollar industry. Every day you receive hundreds of emails and see thousands of ads. Every move you make online is tracked or deduced using incredibly powerful algorithms, often faster than regulation can emerge to protect consumers.
Salesforce, Microsoft Dynamics CRM, various SQL databases, marketing automation platforms and email service providers used as CRMs. I even had a client who kept customer data in an MS Word tab template, shared on a desktop. Your purchases, online behaviors, and large tranches of third party data about you are sitting in electronic form on all of your favorite brands’ cloud servers. And even those cloud servers are scaled and powered by leadgen and upsell campaigns — the large brands’ data sitting on a server somewhere as a nice juicy target for an AWS sales team. The marketing technology industry sits downstream of a slightly larger data industry, eating its fill and then some.
I used to work directly with customer data — and don’t currently. To stay sharp I’ve been training a bit on Salesforce’s excellent Trailhead curriculum. And I’ve continued to follow the martech industry. As the tools by which bits and bytes get converted to targeted campaigns and then to customer demand — these things hold the key to the top line of business growth across the entire economy. Anything that’s not foot traffic driven.
So to scratch that itch — I’ll be writing about it here, among other things.
Stay tuned for next post, where I wax eloquent about journalism and digital publishing (my other quixotic obsession).
Peter out —
