Marketing today is not absolute. It's experimental, iterative, and ever-changing. And with that comes many challenges that we have to overcome and adapt to as agency leaders. One of those challenges is offering data analytics services to our clients. Many of us got into the industry, hoping to avoid doing math. And yet, here we are again, going over another way tech and mathematics are imperative in our industry. While it might be exhausting or frustrating, a subject matter expert is joining us to help make it a little less confusing for everyone.

This week, I'm interviewing Jim Sterne, a data analytics expert who knows so much about the industry. Jim started the Data Analytics Association and wrote 12 books on the topic.

In this episode, he'll share the importance of offering data analytics expertise to better serve clients, how to hire either in-house or third-party data analysts, and tons of resources on where to look for advice and find other experts to help get you started.

Those who adapt survive. Don't wait on this one, and don't try to be a hero. The more we can help our clients reach their goals, the better off we are as an industry. Get help, look to the experts, and start offering your clients data analytics services as soon as possible.

A big thank you to our podcast's presenting sponsor, White Label IQ. They're an amazing resource for agencies who want to outsource their design, dev, or PPC work at wholesale prices. Check out their special offer (10 free hours!) for podcast listeners here.

What You Will Learn in This Episode:

Why data analytics is more about the questions you ask rather than the answers you get
The biggest hurdles agencies face when presenting data to clients
Should you go third-party or stay in-house?
What to look for when hiring a third-party data analytics expert
How to make data useful to the client
Data reports vs. data alerts, which is better?
How to become a data storyteller
Helping clients embrace experimental results over having absolute certainty
The best resources for wannabe data analysts or those just starting out

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