Does Your Data Reveal or Conceal Business Intel?

Bob Dumouchel
google ads data

Data is the center of our universe and we are always seeking actionable business intelligence from it. Data does not always reveal its mysteries and secrets easily, often concealing its intel, using its own sleight of hand. Nobody in business designs data to conceal business intelligence but it happens. Let’s look at a story that demonstrates unintended data concealment.

Several years ago, a high-end luxury brand came to us to be part of the team for a digital campaign launch. Our role was as the programmatic placement and data experts, specifically for the Google Display Network. The creative team created great content for placements, and we placed them in the Google Display Network using a variety of tactics including keyword, named placements, audiences, remarketing, and others. After checking everything multiple times, a launch date and time was set.

On launch day, we activated everything and within a few hours the impression levels were building, and we started to watch the data closely. Over the next few hours, the team went from concerned to happy. Within a few days impression levels were in the millions and the click through rates and orders were solid. The client was pleased and there were lots of high-fives and nice to read emails. To be honest there was some basking in the glory of a job well done. My gut instinct was on edge because we were well above plan, but everything was coming up roses, so I went with it. I remember thinking to myself that it seemed too good to be true, but sometimes you do get lucky in marketing. 

You knew there was going to be a but and here it is. Over the next couple of weeks, the results faded, and smiles turned to frowns. The impressions and clicks held but the results went from great to barely making its numbers. This sent our team scurrying back into the data to see what was happening. As we peeled back the traffic, we quickly found data that concealed the reality from our eyes in the early days. Under the display traffic, was a layer of referral traffic that turned out to be the source of many of the orders. Referral traffic is almost always low volume and good quality. 

As we researched this, we found that six months before the launch date, a PR firm had pitched a story to a large industry publication. This PR firm no longer worked for the client, but the article was already in the pipeline and the publication went to press with it on the launch date. This was purely an excellent accident. The traffic it generated was low volume but super high quality. The traffic barely moved the needle in the inbound traffic, but it was rich with orders. What everyone saw was a jump in inbound traffic from the campaign with a spike in orders.   

The lesson learned from this is never stop drilling into the data just because what you see makes you happy. Human nature is to take the win, bow, and take the glory. We looked at the start and finish and we stopped because it was the answer we wanted. The golden rule here is to continue to follow the data until you get to the end of the final results. 

Marketing data is notoriously complex, and everyone wants a clean simple path from start to finish.  Unfortunately, that rarely happens with sales paths that involve 5 to 20 touches along the path to the close. This is why we have to watch data at both a micro as well as macro level within the sales paths.