Set up the measurement tool. Clean and process the data. Turn it into information. Analyze it. Extract insights.
That’s hard work. But to have value, there’s still another step—the work must also be well communicated. You want data to form a straight line from KPIs to influencing business decisions.
When it comes to Google BigQuery, there are plenty of articles and online courses out there. Most are “tech to tech” explanations—which are great. But they can be intimidating for those beginning their marketing-to-tech journey.
If you’ve ever tried to build an attribution model that wasn’t position-based (i.e. last click, first click, linear, etc.), you might have felt overwhelmed. But customer paths are non-linear and pretty complicated—sooo many things influence conversions.
Most businesses have a lot of data about customer behavior: the devices they use to purchase, ads, competitors’ pricing, keywords, etc. But they can’t make sense of it all.
“Getting great results” and “creating great reports” are very different skill sets. If you’re like most marketers, you’d rather sharpen your subject-matter expertise than spend time in PowerPoint.
The result is that reporting becomes an afterthought rather than an opportunity—a “necessary evil” with imperfect solutions:
- Manual reporting is too time-consuming, but it’s been the only way to report on the right platforms with the right analysis.
- Automated dashboard reports save time but bring limited functionality and don’t help clients understand the story behind the scorecards.
It’s not unusual in our line of work to see the exact same landing page convert at 11% one month, and 55% the next – without making any changes. How so?