The World of Analytics Redux: Grading My ‘21 Predictions

by Jim Cain

Hi All, and thanks for coming to check out some Napkyn content as you kick off your new year.  If you keep an eye on us, you’ll know it’s been a pretty exciting last few months. I’m an employee for the first time in 13 years, which is a bit of a trip.  Frankly i’m really excited about this shift, as I can spend all my time doing the innovation work that made me want to start a company in the first place.

And in order to be good at innovating what a marketplace will need, you tend to have to be good at predicting where the marketplace is going.

Last year we shared a bunch of sound clips (Part 1 & Part 2) from a talk I gave of predictions around what the analytics market will look like over the course of 2021. It’s always weird to look at things you did in the past (in particular listening to my own voice…shudder), but I think in general I got the right things, but the wrong timeframes. 

Let’s review.

I want to focus particularly on clips 7 and 8, as I think they are the most important for analysts and marketers in 2022.  Here’s the sound file for clip 7:

And here’s the transcript if you’d rather read than listen:

Question 7 –   Thinking ahead to 2021, you’ve talked about some things you think are  going to have a big impact. What about things like artificial intelligence or machine learning? I keep hearing those terms come up again and again. I didn’t really see a lot of it in 2020. Do you agree with that? Do you think there will be more in 2021 or is the industry just thinking about ML and AI in the wrong way when it comes to how to get the most value out of data? 

The overall industry, not just the analytics industry is doing all kinds of neat things with ML and AI, we’re just getting invited to the wrong cocktail parties. We tend to specialize in marketing organizations – specifically the digital marketing part of the organization, and inside those types of organizations, ML and AI is really, in my opinion  only being used to do two things:

One, to provide some high level reporting for executive meetings, specifically butt covering propensity analysis. We’re not seeing clients use ML and AI to understand who the people are they can strategically market to,  it’s more “Sales are down or I don’t understand why sales aren’t working, can you do something  sophisticated in terms of an ML model to help us understand what happened”. The more data driven question would be “help us understand what we should do.”

Two,  in our universe, the primary use case for ML and AI is for digital media buying. For example,  creating more sophisticated audiences that can be marketed to. If you look at the data science  practices from the other resellers of GA 360, the majority of the ML and AI work is around audience creation or advanced ad buying use cases. If you look at the industry at large, there are all kinds of neat things happening with ML and AI.  We’re just at the edges of it. As our business, especially in 2021, starts to evolve from not just digital marketing and digital media to just digital, and over time to just data, we are going to start being embraced into all sorts of neat stuff because the things we’re building will start  to blend into other initiatives in the business. So I wouldn’t say ML and AI have been non starters, they’ve just been a little bit under utilized in our corner of the room. 

Sound file for clip 8:

Question 8: What are your predictions for the world of analytics in 2021? And related to that, what is the one thing you believe will happen in the world of analytics this year that  most anyone else doesn’t believe?

Something I think will happen this year is that marketers will have less data they can work with.   Chrome will make the updates to cookies –  they are really the last big browser to not do it,  so 2021 will be the beginning of the  cookieless world. That is going to be a big problem for a lot of businesses. I think it is going to come as a  huge shock to the majority of the marketplace, including agencies and big organizations who have made this tomorrow’s problem when  tomorrow turns out to probably be this summer. 

So, a cookieless world. And for any business that uses Google Analytics, GA4. This is going to be the year for early adopters. I don’t think we are going to see every single business immediately jump into GA4.  The thing that is going to be a bit of an accelerator of adoption in this instance are the browser changes. A lot of businesses are going to realize they are going to have to do a bunch of things differently or they aren’t going to be able to do the marketing they used to do. But GA4, and some of the ways in which it’s optimally deployed will better set those businesses up to  live in that cookieless world. So I think the size of that early adopter category will be bigger than with normal releases. 

The other thing that may not be a popularly held idea is I think the importance of tag management is going to go up in 2021. When you see this circuitous “new type of tool comes in and kills old type of tool”.  There will be media tools this year that will replace programmatic media tools because they work on third party cookies.  CDPs(?) for example,  are being considered by many businesses  as something that  will replace  the digital analytics tool. This is  because the data fill  for a CDP  does a lot of things that a first party data set does. There still isn’t a single tool or even feature set of an existing new class of tool  that does what a tag manager does. 

It is the only type of product that creates a development environment for AdTech and MarTech with the  proper kind of enterprise workflows.  Nothing else does what a tag manager does. Not a lot of people agree,tag manager has been around forever, it’s been perceived that other things can replace it, but I don’t think anything does what a good TMS does and I don’t think anything will because it’s very important but also relatively niche. 

In 2021 expect a lot more ML/AI, Google getting rid of cookies, businesses finally investing in digital analytics infrastructure to cope.

All my predictions were wrong.

I get stuff wrong all the time, after all making predictions is similar to how Dilbert describes marketing, “Liquor and Guessing”.  That said, in this instance I stand by all the items listed, I just got the timing wrong.

One of the really standout things about the pandemic is how much it has messed with our sense of time.  I don’t know about you, but I feel like it’s been either two days or two decades since March 2020.  This time machine effect has been discussed at length in areas where acceleration has happened, for example eCommerce has done about a decade’s worth of growth in the last 18 months.  Many areas have decelerated however, and one of them has been investment in analytics infrastructure.  Generally, businesses have just had other priorities, and they’ve been looking at their competitors to see what they are going to do for martech and adtech.

And why were adtech and martech less of a priority in 2021 than I thought?  One simple reason: Google never killed the cookie.  The first half of last year was certainly full of conversations, speculation, and whiteboard level planning on what to do when Chrome updated and Third Party Cookies went away.  There was no concrete “Do this instead” plan for cookie deprecation, but there are a number of things that can be done to get ready.  Expect future content from me on First Party Data asset management if you want to understand our approach.

In June, Google pushed FLOC out to the end of 2023, signaling at least 2 more years of business as usual for media buyers.  All the pressure to prepare for the cookieless world went away, and data programs got benched.

My predictions for 2022 are therefore pretty similar to last year:

  • Expect a lot of investment in deployments of the new Google Analytics, connecting first party analytics tools to owned cloud data systems,
  • and preparing for the (eventual) new world of cookieless digital marketing.

One thing I know for sure is that the Napkyn team is prepared to keep helping our customers stay ahead of the game and gain competitive advantage.  We’ve done over 100 GA4 deployments, connected countless customers’ marketing data to Google Cloud, and turned that data into cutting edge insights and audiences with machine learning.

Any insights I missed?  Agree or disagree with any of my points?  Hit us up on Linkedin or Twitter and let’s chat!  On behalf of the whole team at Napkyn, we hope you, your families and your teams are having a safe start to ‘22, and we look forward to working with you.



Jim Cain

Chief Innovation Officer & Founder, Napkyn Analytics

Founding CEO of Napkyn Inc., it was Jim’s curiosity about how data can be leveraged by marketers that led to him establishing the company in 2009. He ideated, delivered and iterated all of the early services delivered by Napkyn to enterprise clients. Jim has a unique ability to connect the dots for where the industry and individual brands will and can go with their data-driven initiatives.

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