Data problems are probably lurking somewhere inside of your marketing stack. Don’t freak out, just yet. Most analytics packages and marketing software services that deal with data have some gaps or inaccuracies.
Today’s guest is Dan McGaw, CEO and founder of McGaw.io, a marketing technology and marketing analytics consulting company. Dan talks about how to make better marketing decisions—identify and fix deeper issues to avoid data disasters. He explains everything you need to know to keep your data clean and metrics moving.
Some of the highlights of the show include:
Why is data cleanliness important? Analytics + Bad Data = Bad Decisions Directional: Data is not meant to be perfect, the goal is to grow and take action Data Spectrums: Everybody has unreliable data—how bad is it? Marketing Stacks: Different problems stem from data issues Taxonomy: Common problem is not having consistent or connecting names Be Intentional: Set up and configure marketing tech, or set yourself up for failure Audit: You know there’s a problem, but you don’t know what it is, where to begin Solution: Plan and be more proactive by understanding how data flows in Best Practices: Urchin tracking parameters (UTM) are culprits of bad data How to Build Cool Sh*t: Take it slow, take your time, don’t try to rush projects
Dan McGaw on LinkedIn Mcgaw.io McGaw.io Downloads and Resources How to Build Cool Sh*t by Dan McGaw UTM.io KissMetrics Pluralsight - Code School BrowserStack Segment Tag Inspector Ben Sailer on LinkedIn CoSchedule
Quotes from Dan McGaw:
“If you have analytics and your analytics have bad data that means your analytics are wrong, which means that you’re naturally going to be making bad decisions.”
“Companies that are typically growing the fastest, are the ones who are less focused on definitive and more focused on how do we get directional data that’s going to tell us which way is growth and let’s start moving and let’s make action.”
“If you take the quality time to do taxonomy right, you see really, really good outcomes. Trying to make sure that taxonomy works across the stack I think is where you get the best outcomes, as well.”
“The best way to audit is really to build good rigor around your analytics, understand how that data flows in, and use the auditing tools to be able to do that.”