Interview with Fred Pike, managing director at Northwoods


We continue our Expert Opinion column, and today we present to your attention an interview with Fred Pike, an experienced presenter, and blogger on Google Analytics, Google Analytics 4, and Google Tag Manager topics. Fred is a Managing Director at Northwoods, a digital agency and software-dev shop. At the same time, he’s been teaching technical courses for years in MeasureSchool, SDEC, etc., along with creating three online video courses for CXL Institute.

Fred Pike, managing director at Northwoods

As always, here are the main topics for navigation:

Could you say a few words about yourself and your previous experience?

I am a Managing Director at Northwoods, a digital agency and software-dev shop in Milwaukee, Wisconsin.

I also lead Northwoods’ Google Analytics/Google Tag Manager Practice Area. In some ways, I have Peep Laja from CXL to blame for that. Years ago, I took his CRO course.  I learned immediately that my understanding of Google Analytics — which I believed to be sophisticated — was in fact terrible.

That led me to a life-changing Google Analytics class from Jeff Sauer at Data Driven U. Jeff’s class, in turn, led me to Julian Juenemann Google Tag Manager class at Measure School, another life-changer. 

All of the above — plus the courses, blogs, contributions, and friendships of Simo AhavaJulius Fedorivicius, and Brian Clifton — led to years of working with clients on Google Analytics and Google Tag Manager implementations, work that I love.

Skills and problems

What hard and soft skills are most important for analysts today?

First, curiosity. The desire to find out why certain things happen. What caused them? Can you measure — even approximately — causes and effects? Act on that curiosity. Dive into the data and get answers.

Second, humility. Get comfortable with the idea that you don’t know all the answers. Learn from others. Watch what they’re doing.

The best courses I’ve taken make me feel as if I’m sitting next to masters of the craft as they share knowledge, both in explicit lessons and by letting me peek over their shoulders while they do their things.

Third, communication. Whether I’m explaining things to a client or designing a class, I strive to clearly communicate my questions, findings, assumptions, and conclusions. What I know doesn’t matter much if I can’t convey that knowledge to other relevant parties. Good communication can take time. I re-read my emails before I send them. When I record a course, I expect to spend about one hour working on each minute of final-cut content. Want to get your message across? Revise. Then revise some more.

What’s the biggest mistake an analyst can make? Can you share some of your analytical mistakes?

I spend a great deal of time — all of it necessary — making sure that my implementations of GA and GTM are correct and collecting the cleanest possible data.

Most of my mistakes have to do with not checking my work carefully enough. I once set up an IP filter on a client’s account and added an extra pipe (|) at the end of my RegEx filter — which blocked ALL traffic to the GA property. This was for a large international client. Luckily (but embarrassingly), after three days of no traffic in GA, the client asked me what was going on. Of course, we had a raw view set up, so we still had a decent sense of what had happened. But still — that oversight haunts me.

Another instance: Testing changes in GTM, getting it all set, and then forgetting to publish the container.

I keep thinking of that saying — if you don’t have time to do it right, when will you have time to fix it? So I consciously try to take my time, make sure it’s right, and test the change after it’s live.

Do you think miscommunication between analysts and marketing teams is common? Do you have any recommendations on how to overcome it?

I’ve read about this more than I’ve encountered it. It might just be rare in the SMB market we primarily serve, but even among our larger clients, analysts and marketing teams generally communicate well. The marketers we work with tend to be fairly technical. They usually understand analysts.

Analytical challenges

According to Gartner among the main pains that marketers face are poor data quality, finding relevant insights, and creating ad hoc reports. What do you think about these pains?

Amen to two of them. Poor data quality makes me spend so much time up-front sweating the details on data collection (see question 3).

Relevant insights are hard to get — that’s why I hate dashboards without some level of analysis.

A recent example: One of the music festivals we work with has a schedule of events, with a search bar exclusive to that schedule, quite apart from the overall website search box. We captured the search terms people entered into that schedule search box and found an amazing array of variant and alternate spellings searchers entered for one of the festival headliners. The name is a bit counter-intuitive, in terms of spelling. So — what to do? Damn well better have a fuzzy-logic/variant-spelling search engine in the schedule, to return useful results to ticket buyers.

I’m not so sure that ad hoc reports are too difficult. That depends on the type of marketer. True digital marketers have the curiosity (see question 1) and enough understanding of analytics and reporting tools to handle ad hoc reports. This training is not hard to find or difficult to complete. In a month or two, you can develop decent skills. And jeez, if nothing else, they should be using OWOX! :-)

What difficulties do you see when it comes to implementing analytics and how would you assess the overall development of the market?

Again (see question 3), make sure the initial implementation gives you good, clean data.

For GA3 (Universal Analytics), creating a great set of GA events (category/action/label) that are clear, well-laid-out, and that capture the key user interactions on the site can be a formidable, but necessary, task. The events in GA3 are the heart and soul of a great implementation; without them, you have a pretty generic set of data.

For GA4, the challenge lies in figuring out how to capture those same key user interactions, but in the GA4 event/parameter model. This means using the Enhanced-measurement or Recommended events, and existing parameters as much as possible. (This was the topic of my presentation at MeasureSummit, on Oct. 1, 2021.)

The now and then of the analytics

What do you think is the future of marketing analytics? What trends do you see coming and what’s in demand?

The field is immature and rapidly changing, and the rate of change will not slow down in the foreseeable future. Analysts with deep knowledge in one or two areas, but who remain open and adaptable, will be in high demand. If you tend to resist change, find another line of work.

What problems do you see on the market today?

I suspect that in most cases we barely scratch the surface of what our tools can do. If we’re not even doing a good job with data collection now, why worry about a cookie-less future? 

A while back, I gave a masterclass on Chrome extensions to students of Data Driven U. I talked about FAST — Fred’s Awesome Sniff Test. I don’t even have to go into the GA property to get a good whiff. In under five minutes, I can determine the sophistication level of a GA set-up by answering a few questions:

  • Are they using custom dimensions? (99%+ of websites don’t.)

  • If it’s an ecommerce site, do they track add-to-cart and remove-from-cart correctly? (About an 80% fail rate on remove-from-cart.)

  • Are they double-counting pageviews? (10-15% of sites do.)

  • Are they tracking outbound links and downloaded files? (Fail for 60-70% of all GA3 sites.)

  • What type of user interactions are they tracking, if any? (50-60% don’t track any.)

How can analysts help the business grow nowadays despite the crisis?

Make sure the data is collected properly! :-)

Google Analytics 4 is our new future. What do you think about it? Have you already tested Google Analytics 4? How does Google Analytics 4 affect analysts’ reality?

I’m doing quite a bit with GA4. We’ve set up dual tagging on most of the client accounts we touch (we’re running GA3 and GA4). I’m currently involved with a large project for a university, as we move all 30+ properties to GA4.

I like a lot about GA4, notably the enhanced measurements that are on by default and the cleaner e-commerce data structure. But it’s still missing some things. It’s important to set up GA4, but I still hesitate to recommend it as your one-and-only analytics.

How to prepare for a cookieless future?

Data is incomplete now; it’s going to be incomplete in the future, and it’s always been incomplete. We figure stuff out and make do.

Mikko Piippo, a digital analyst in Finland, gave me perhaps the best perspective on data collection and analysis. It really helped me stop catastrophizing.

Mikko studied Medieval history. At a SuperWeek breakfast, he explained that even without minute-by-minute data of that period, we still know a lot about Medieval times, and our knowledge keeps expanding. I think that will be true in our field as well!

Tag the one person in the industry whose answers to these questions you would love to read.

Let’s go with Mikko Piippo!

Oh jeez — I see you already interviewed him. How about Ahmad Kanani?

Summing up

If you want to become an excellent specialist in analytics, remember these things: stay curious (never stop finding out why certain things happen), get comfortable with the idea that you don’t know all the answers, and take your time to test, double-check and make sure you did everything right.

We really appreciate Fred’s honest responses about and sharing his experience. We hope this interview was useful and you’ve enjoyed reading it.

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