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Happy Halloween! It’s now shopping season…
It’s time to talk turkey because brands are gearing up for BFCM (Black Friday Cyber Monday). But don’t about treat yo self and Q5 (which is a dumb name).
According to TikTok, Q5 (“the small but mighty post-holiday shopping period between Christmas and mid-January”) means:
More shopping: 79% of TikTok users are likely to continue shopping in Q5.
I have one client where we plan for a big BFCM and Q5 with minimal activity in between. Don’t sleep on it. And don’t underestimate the allure of self-gifting.

Goblins of GA4: Data Thresholding
The Google Analytics 4 transition has been less than enjoyable for many a marketer and analyst. But one of the biggest (remaining) headaches has got to be data thresholding.

What is data thresholding?
Google Analytics has applied thresholding to this card and will only display the data when the data meets the minimum aggregation thresholds.
Say what now?
Thresholding is applied when the data could be granular enough for an analyst to theoretically identify individuals from the reporting. The reason this is new to GA4 is because of the shift from session-first reporting to user-first reporting the transition from Universal Analytics (GA3?) signaled.
Sampling Side Note
If you click the red triangle of death dropdown, you may notice a mention of data sampling (hopefully via an item that says "unsampled card"). What is data sampling?
Analytics uses data sampling when the number of events returned by an exploration or funnel report exceeds the limit for your property type (i.e., a standard or 360 property).
The quota limit is 10 million events for users of the free Google Analytics product and up to 1 billion events for Google Analytics 360 users.
If you're racking up a lot of events, you should either consider shelling out for 360 or investigating GA alternatives
Now, back to our regularly scheduled goblin...
Data Thresholding In Practice
If you see the red triangle of death at the top of your report, know that you aren't seeing all the data. This is especially discomforting if the report you're looking at is related to a metric your performance is measured on.
The quickest way I've seen to get hit by the thresholding goblin is by using a short time frame or by using dimensions closely tied to user information (demographic data and search query information are 2 of the 3 threshold triggers mentioned by Google).
But it can be sneaky too. If an event didn't fire enough in the time frame you chose (maybe because it's new), it may get hidden by the thresholding goblin. And you're left to wonder if you set it up wrong or if no one is taking the action that triggers the event.
How To Fix Thresholding
The easiest way is to "adjust the date range" (as mentioned above).
Data may be withheld when viewing a report or exploration within a narrow date range if you have low user or event counts in that date range. Expanding the date range may increase the number of users who triggered an event, enabling you to see the previously thresholded data.
You can also export to BigQuery. The reason this works is Google Signals, the true source of this goblin.
Back in the UA days, Google Signals was a set-and-forget toggle in the admin to (theoretically) make your Google Ads better by tying your site activity to logged in Google user accounts. Essentially Google's version of the Meta pixel. But GA4's user-centric approach to measurement causes Signals to unleash the thresholding goblin.
Google just recently launched a simple solution: turn off "Include Google signals in reporting identity" in the admin.

That's it. It's that simple. I wrote over 500 words for the payoff of one screenshot telling you to click one toggle. Isn't GA4 fun?
If for some reason that approach doesn't work for you, or you want to keep that data included in reporting, or you just want to delve deeper into GA4's settings, there is another option: change your Reporting Identity.
You can find this in the Admin under Data Display. The default is Blended, which includes all the toys Google can pack in. But hidden under the nondescript "Show all" at the bottom right of the 2 option table is a third option: Device Based.
I'll try for a deeper dive on the differences between these 3 options at a later date, but prior to the Google Signals reporting toggle, this was Google's recommended way around the thresholding goblin. The recommendation included switching back to one of the other 2 options after you were finished with your reporting needs, but it's not clear why you would need to do that if you are just going to switch back to device-based every time you open GA4 to pull data.
Anyway, TL;DR:
Data thresholding occurs when your reporting view could be used to identify individual users either because you don't have enough data in the time frame or you're using dimensions closely tied to users' personally identifiable information (PII).
Data thresholding can prevent data from showing in impacted reports, meaning you don't have a full view of what's happening on your site (and potentially driving you insane if entire events are "missing).
The best way to avoid the thresholding goblin is to turn off "Include Google signals in reporting identity" in the data collection section of the admin.
Here's to better reporting and analysis.
An everything is customer service anecdote
There is a doctor’s office at Johns Hopkins that is difficult to get an appointment with, but every one who calls to make one is offered an appointment that day.
Only 4% of patients accept the same day appointment.
But 100% of them feel like well-connected VIPs for being offered an immediate appointment when they call.
Yes, this would backfire if everyone agreed. But they have the data to know they won’t. What they do have is a first-touch experience that causes delight.
This idea from Adam Grant (~44:16) is (also) great reasoning for why generations as marketing personas should stop.
We should stop defining people by their group membership. Instead of assuming that just because people came from a particular background that they had the same degree of difficulty and adversity. We should actually get to know the individual to find out the obstacles they face and adjust expectations.
Know your actual customers and fans. Use that to create an aspirational persona you market too.
Generation groups are lazy and dumb.
AI isn’t going to replace people, but it will replace people that don’t use AI.
via Manton Reece
The future is centaurs.
The more important it is to meet your numbers, the more important it is to stop concentrating on your numbers and start concentrating on the clients' numbers.
via Josh Spector
We might have reached peak vertical video:
Have consumers started to cool towards short-form video? That’s certainly one read from Google and Snap results.
If anything this serves as a good reminder to not go all in on one content format based on the platforms’ push du jour (just ask news publishers about social video). Different businesses do different forms of content better than others and different forms work better for different purposes.
Don’t give up on vertical video. But don’t go all in on it either.
I’ve been waiting for streaming to make TV advertising easier and more accessible, Amazon is giving it a shot.
Amazon Ads announced Sponsored TV, a new self-service advertising product that allows all brands that sell on Amazon in the U.S. to reach audiences on streaming TV, including on Amazon Freevee, Twitch and third-party services through Fire TV apps.
More ways Amazon is trying to connect its various platforms and generate more ad revenue.
This is my kind of lateral thinking:
Disproving
Based on the idea that the majority is always wrong (as suggested by Henrik Ibsen and by John Kenneth Galbraith), take anything that is obvious and generally accepted as “goes without saying”, question it, take an opposite view, and try to convincingly disprove it.
Podcasts are coming to TV.
This is partly Amazon connecting the dots between existing parts to get more mileage out of content and channels and add more ad slots to the mix.
Partly due to the rise of video in podcasting. (Thanks YouTube!)
And maybe partly due to the Smartless show on (HBO) Max (which might have been embarrassing for Amazon since it’s a Wondery show).
Community & Curiosity: Pod Notes
The Philosophy of Community™ (~7:10):
Can you bring groups together and create a sense of belonging and then you inherit the credibility of bringing that group together and having that sense of belonging.
And that can happen lots of different places in your marketing journey. There could be customer communities. There could be non-customer communities. It could be you infiltrating communities that already exist.
But it's almost more of a philosophical approach to marketing than a program.
If you decide to join a community, how you join as a brand—and whether or not you should join as a brand or whether you leverage folks at your company—is a make or break situation.
I'm ending here mostly so I don't end up transcribing half the episode, it's worth a listen. They go from here into influencers and marketing as a connective tissue for your organization (~9:10).
But that first part, about bringing groups together, that's sports teams.
That's this:

Next, curiosity! (~14:45)
When all of these buying behaviors and channels and things switch underneath us, the curiosity that I have is what things are remaining as consistent human behaviors—of how we buy things and take chances and how we spread recommendations amongst each other and all of those traditional things that humans have always done—what piece of this remains versus what piece of this gets thrown out in the trash?
That's well-placed curiosity. And we're all about that sort of thing here.
According to Sprout Social:
Nearly three-quarters (74%) of consumers say they’re likely to reach out to a brand on social over the holidays
This is why I wrote:
The true social media use case for brands now is customer service. These are the channels customers want to talk to you via. Your customer support/service/success team should have access to answer comments and messages.
McDonald’s “I’m Lovin’ It” jingle has been getting lodged in brains for 20 years.
Why is it so successful?
After reading the names of the prior jingles, I had the same thought shared by Garrett Crosby later in the post:
shifting from “you” and “we” language in prior jingles to first-person in “I’m Lovin’ It” may have helped its longevity.
Your marketing shouldn’t be about you. You’re a platform for your fans.
‘Pause Ads’ Creep Onto Hulu, Peacock and Max as Streamers Seek New Revenue
This is a placement type that opens up TV ads to a wider crop of businesses, namely those that can’t (or don’t want to) produce “TV-quality” video spots. And monetizes “dead space” in a way that should minimally impact the viewing experience.
According to Martech:
Shoppable ads are beginning to make an impact on smart TV audiences, with 55% in a new survey sample recalling seeing shoppable ads and 50% admitting to interacting with them.
The shift to streaming has made this ad type more widely experienced and it’s been around long enough that the novelty has worn off. I think that’s the point when new ad types start to gain performance traction (or don’t).
I would guess the TikTok QR code Super Bowl commercial was the tipping point for the viability or interactive TV ads.
Goblins of GA4: Data Lag
Despite solid realtime reporting, it can take up to 24 (and maybe even 48) hours for data to fully populate the reports throughout GA4.

I haven’t found a reliable way around this (other than paying for 360), so this is just a PSA. Processing time is inconsistent too, especially when Google services are unstable (like they are now).
This table is from Google's official data freshness documentation:
Interval | Typical processing time | Properties | Data limits per property | Query coverage |
---|---|---|---|---|
Realtime | Less than 1 minute | 360, Standard | None | Limited to a few dimensions and metrics |
360 intraday | About 1 hour | 360 | Premium Normal and Premium Large as defined here | All reports and API queries, except these |
Standard intraday | 4-8 hours | Standard | Standard Normal | All reports and API queries, except these |
Daily | 12 hours | 360, Standard | Standard, Premium Normal | All reports and API queries |
Daily | 18 hours | 360, Standard | Premium Large | All reports and API queries |
Daily | 24+ hours | 360, Standard | Premium XLarge | All reports and API queries |
Be wary of yesterday’s numbers in your reporting. If something seems off, you’ll need to wait a day or exclude the prior day and do trend analysis to see if anything jumps out.
For immediate peace of mind, use realtime reporting or Tag Assistant to do a quick check, making sure things look to be firing as they should.
Henry Ford’s “any color as long as it’s black” choice may have been too minimalist, but more, more, more isn’t always better.
Studies have found that there is a choice cliff where sales drop when too much choice is present.
Too many choices can lead to procrastination, dissatisfaction, and suboptimal decisions.
Reducing the number of choices you offer can also decrease your costs.