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How to make the most of cohort analysis

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With third-party data going the way of the dodo bird, digital marketers are looking for ways to do without cookies. Call it “data dieting.” But something must replace those bits and bytes of third-party sweetness. If you can’t drop a cookie, track a cohort.

Any group of customers engaging your web site can be counted as a cohort, provided you are tracking what they do. Are they just going as far as the landing page? Are they filling the cart, but not checking out? Did they buy something before, but haven’t shopped lately?

Churn, drop-off, customer lifetime value — all can be tracked as cohorts. But the online vendor must know what measures are most relevant to their business to make the most of cohort analysis.

(Segment [cohort]): Get it?

“Segments” and “cohorts” are terms sometimes used interchangeably, but that would be incorrect.

Google defined cohort this way: A cohort is a group of users who share a common characteristic. “For example, all users with the same Acquisition Date belong to the same cohort. The Cohort Analysis report lets you isolate and analyze cohort behavior.”

In contrast, segmentation means organizing groups of users around common characteristics, like demographics, geography, personality, or value. It can also group customers using more than one characteristic.

“A cohort is a form of a segment. All cohorts are segments, but not all segments are cohorts,” said Eric Sloan, director of strategy at performance marketing agency Thrive Digital. Cohorts can be understood as “time-based segments”, for example, a set of users signing on at a web site at a particular time.

Sometimes the two terms get mixed up because of the analytical tool being used by the vendor or analyst, noted Adam Greco, product evangelist for digital optimization platform Amplitude. A cohort is “a group of like users based on interest,” he said. Segmentation “is like a filter,” Greco continued. A segment is an activity. Cohorts are people. And a “cohort depends on identity resolution”, he said.

Simply identifying a cohort is not enough. The analyst will have to drill down further to identify cause-and-effect. “It’s the only way to make cohort analysis meaningful,” Sloan said. The biggest pitfall is just assuming “the time-based cohort caused what you are looking at,” he said.

Asking the right questions

Which leads to the data. There is an answer in there somewhere, provided you ask the right question to get it.

“We spend time using data to figure out the cohort that is meaningful for the business,” Greco said. Take the example of a cohort defined by behavior — customers going through a multi-step process to complete a transaction.

“You need the right data to build the right cohort,” Greco said. You don’t need to worry about tracking people who add items to the cart. “Just because you can track something does not mean you should.” He added. “Too few companies start with the end in mind.” If you start by listing the relevant cohorts you want to track, and work backwards, then you are more likely to be successful, he pointed out.

For Sloan, the cohort is part and parcel of root-cause analysis. “[When] you see KPIs change, you look at all the different factors that caused the change.” Again, correlation is not causation, he stressed, but you keep drilling down through the cycles and ask intuitive or logical questions, finding the data that answers the question.

“Start with a cohort. See if it is time-based.” Sloan said. Spot the drop-off from period to period. Include new visitors as older ones drop off. Look at the face value of all behaviors and events, going through the initial period, then to 30, 60 and 90-day increments. “A cohort is the first step in eliminating some of the noise,” he said, as the analyst tries to measure the customer experience with the web site.

Greco offered other paths. One approach uses the data to isolate groups of identified users so that groups can be compared. He called this a “persistent cohort.” For example, tracking the number of online shoppers for a seven-day period. New users will naturally enter this cohort while others exit it after the time set. Those who purchase are counted while those who don’t buy are tallied as drop-offs.

Then Greco outlined the “predictive cohort”. One example is looking at the number of shoppers who visit the web site to make another purchase. There may be a group that is 90% likely to buy something next week; another that is 80-90% likely to make a purchase, yet another group that is 70-80% as likely to acquire an item. The marketer can use that data to offer discounts to each cohort, only increasing the discount to entice shoppers in the next group less likely to buy something. “You use the cohort in combination with marketing and promotion to get people to convert,” he explained.

Making the most of data

Cohort analysis is an approach that requires marketers to change their thinking to make the most of their data. Our experts have the same starting point, but pursue their goals along different lines.

To use cohort analysis, “start with the question.” Sloan said. “Tie back to business results that are possible to answer…Understand where and how to drill down…Make sure the KPIs are meaningful.” Make sure the data you are analyzing reflects reality, he added. Data can skew if the same online shopper is accessing the same web site using different devices at different times, he cautioned.

Greco framed cohort analysis as a competitive necessity. In the e-commerce realm, every online shopper is just a “click or a swipe away”, he noted. The burden is on the marketer “to figure out how they are losing people and bring them back.” The faster problems are solved and fixed, the more likely an online web site will be successful.


About The Author

William Terdoslavich is a freelance writer with a long background covering information technology. Prior to writing for Martech, he also covered digital marketing for DMN. A seasoned generalist, William covered employment in the IT industry for Insights.Dice.com, big data for Information Week, and software-as-a-service for SaaSintheEnterprise.com. He also worked as a features editor for Mobile Computing and Communication, as well as feature section editor for CRN, where he had to deal with 20 to 30 different tech topics over the course of an editorial year. Ironically, it is the human factor that draws William into writing about technology. No matter how much people try to organize and control information, it never quite works out the way they want to.

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Is Twitter Still a Thing for Content Marketers in 2023?

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Is Twitter Still a Thing for Content Marketers in 2023?

The world survived the first three months of Elon Musk’s Twitter takeover.

But what are marketers doing now? Did your brand follow the shift Dennis Shiao made for his personal brand? As he recently shared, he switched his primary platform from Twitter to LinkedIn after the 2022 ownership change. (He still uses Twitter but posts less frequently.)

Are those brands that altered their strategy after the new ownership maintaining that plan? What impact do Twitter’s service changes (think Twitter Blue subscriptions) have?

We took those questions to the marketing community. No big surprise? Most still use Twitter. But from there, their responses vary from doing nothing to moving away from the platform.

Lowest points

At the beginning of the Elon era, more than 500 big-name advertisers stopped buying from the platform. Some (like Amazon and Apple) resumed their buys before the end of 2022. Brand accounts’ organic activity seems similar.

In November, Emplifi research found a 26% dip in organic posting behavior by U.S. and Canadian brands the week following a significant spike in the negative sentiment of an Elon tweet. But that drop in posting wasn’t a one-time thing.

Kyle Wong, chief strategy officer at Emplifi, shares a longer analysis of well-known fast-food brands. When comparing December 2021 to December 2022 activity, the brands posted 74% less, and December was the least active month of 2022.

Fast-food brands posted 74% less on @Twitter in December 2022 than they did in December 2021, according to @emplifi_io analysis via @AnnGynn @CMIContent. Click To Tweet

When Emplifi analyzed brand accounts across industries (2,330 from U.S. and Canada and 6,991 elsewhere in the world), their weekly Twitter activity also fell to low points in November and December. But by the end of the year, their activity was inching up.

“While the percentage of brands posting weekly is on the rise once again, the number is still lower than the consistent posting seen in earlier months,” Kyle says.

Quiet-quitting Twitter

Lacey Reichwald, marketing manager at Aha Media Group, says the company has been quiet-quitting Twitter for two months, simply monitoring and posting the occasional link. “It seems like the turmoil has settled down, but the overall impact of Twitter for brands has not recovered,” she says.

@ahamediagroup quietly quit @Twitter for two months and saw their follower count go up, says Lacey Reichwald via @AnnGynn @CMIContent. Click To Tweet

She points to their firm’s experience as a potential explanation. Though they haven’t been posting, their follower count has gone up, and many of those new follower accounts don’t seem relevant to their topic or botty. At the same time, Aha Media saw engagement and follows from active accounts in the customer segment drop.

Blue bonus

One change at Twitter has piqued some brands’ interest in the platform, says Dan Gray, CEO of Vendry, a platform for helping companies find agency partners to help them scale.

“Now that getting a blue checkmark is as easy as paying a monthly fee, brands are seeing this as an opportunity to build thought leadership quickly,” he says.

Though it remains to be seen if that strategy is viable in the long term, some companies, particularly those in the SaaS and tech space, are reallocating resources to energize their previously dormant accounts.

Automatic verification for @TwitterBlue subscribers led some brands to renew their interest in the platform, says Dan Gray of Vendry via @AnnGynn @CMIContent. Click To Tweet

These reenergized accounts also are seeing an increase in followers, though Dan says it’s difficult to tell if it’s an effect of the blue checkmark or their renewed emphasis on content. “Engagement is definitely up, and clients and agencies have both noted the algorithm seems to be favoring their content more,” he says.

New horizon

Faizan Fahim, marketing manager at Breeze, is focused on the future. They’re producing videos for small screens as part of their Twitter strategy. “We are guessing soon Elon Musk is going to turn Twitter into TikTok/YouTube to create more buzz,” he says. “We would get the first moving advantage in our niche.”

He’s not the only one who thinks video is Twitter’s next bet. Bradley Thompson, director of marketing at DigiHype Media and marketing professor at Conestoga College, thinks video content will be the next big thing. Until then, text remains king.

“The approach is the same, which is a focus on creating and sharing high-quality content relevant to the industry,” Bradley says. “Until Twitter comes out with drastically new features, then marketing and managing brands on Twitter will remain the same.

James Coulter, digital marketing director at Sole Strategies, says, “Twitter definitely still has a space in the game. The question is can they keep it, or will they be phased out in favor of a more reliable platform.”

Interestingly given the thoughts of Faizan and Bradley, James sees businesses turning to video as they limit their reliance on Twitter and diversify their social media platforms. They are now willing to invest in the resource-intensive format given the exploding popularity of TikTok, Instagram Reels, and other short-form video content.

“We’ve seen a really big push on getting vendors to help curate video content with the help of staff. Requesting so much media requires building a new (social media) infrastructure, but once the expectations and deliverables are in place, it quickly becomes engrained in the weekly workflow,” James says.

What now

“We are waiting to see what happens before making any strong decisions,” says Baruch Labunski, CEO at Rank Secure. But they aren’t sitting idly by. “We’ve moved a lot of our social media efforts to other platforms while some of these things iron themselves out.”

What is your brand doing with Twitter? Are you stepping up, stepping out, or standing still? I’d love to know. Please share in the comments.

Want more content marketing tips, insights, and examples? Subscribe to workday or weekly emails from CMI.

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Cover image by Joseph Kalinowski/Content Marketing Institute



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45 Free Content Writing Tools to Love [for Writing, Editing & Content Creation]

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45 Free Content Writing Tools to Love [for Writing, Editing & Content Creation]

Creating content isn’t always a walk in the park. (In fact, it can sometimes feel more like trying to swim against the current.)

While other parts of business and marketing are becoming increasingly automated, content creation is still a very manual job. (more…)

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How data clean rooms might help keep the internet open

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How data clean rooms might help keep the internet open

Are data clean rooms the solution to what IAB CEO David Cohen has called the “slow-motion train wreck” of addressability? Voices at the IAB will tell you that they have a big role to play.

“The issue with addressability is that once cookies go away, and with the loss of identifiers, about 80% of the addressable market will become unknown audiences which is why there is a need for privacy-centric consent and a better consent-value exchange,” said Jeffrey Bustos, VP, measurement, addressability and data at the IAB.

“Everyone’s talking about first-party data, and it is very valuable,” he explained, “but most publishers who don’t have sign-on, they have about 3 to 10% of their readership’s first-party data.” First-party data, from the perspective of advertisers who want to reach relevant and audiences, and publishers who want to offer valuable inventory, just isn’t enough.

Why we care. Two years ago, who was talking about data clean rooms? The surge of interest is recent and significant, according to the IAB. DCRs have the potential, at least, to keep brands in touch with their audiences on the open internet; to maintain viability for publishers’ inventories; and to provide sophisticated measurement capabilities.

How data clean rooms can help. DCRs are a type of privacy-enhancing technology that allows data owners (including brands and publishers) to share customer first-party data in a privacy-compliant way. Clean rooms are secure spaces where first-party data from a number of sources can be resolved to the same customer’s profile while that profile remains anonymized.

In other words, a DCR is a kind of Switzerland — a space where a truce is called on competition while first-party data is enriched without compromising privacy.

“The value of a data clean room is that a publisher is able to collaborate with a brand across both their data sources and the brand is able to understand audience behavior,” said Bestos. For example, a brand selling eye-glasses might know nothing about their customers except basic transactional data — and that they wear glasses. Matching profiles with a publisher’s behavioral data provides enrichment.

“If you’re able to understand behavioral context, you’re able to understand what your customers are reading, what they’re interested in, what their hobbies are,” said Bustos. Armed with those insights, a brand has a better idea of what kind of content they want to advertise against.

The publisher does need to have a certain level of first-party data for the matching to take place, even if it doesn’t have a universal requirement for sign-ins like The New York Times. A publisher may be able to match only a small percentage of the eye-glass vendor’s customers, but if they like reading the sports and arts sections, at least that gives some directional guidance as to what audience the vendor should target.

Dig deeper: Why we care about data clean rooms

What counts as good matching? In its “State of Data 2023” report, which focuses almost exclusively on data clean rooms, concern is expressed that DCR efficacy might be threatened by poor match rates. Average match rates hover around 50% (less for some types of DCR).

Bustos is keen to put this into context. “When you are matching data from a cookie perspective, match rates are usually about 70-ish percent,” he said, so 50% isn’t terrible, although there’s room for improvement.

One obstacle is a persistent lack of interoperability between identity solutions — although it does exist; LiveRamp’s RampID is interoperable, for example, with The Trade Desk’s UID2.

Nevertheless, said Bustos, “it’s incredibly difficult for publishers. They have a bunch of identity pixels firing for all these different things. You don’t know which identity provider to use. Definitely a long road ahead to make sure there’s interoperability.”

Maintaining an open internet. If DCRs can contribute to solving the addressability problem they will also contribute to the challenge of keeping the internet open. Walled gardens like Facebook do have rich troves of first-party and behavioral data; brands can access those audiences, but with very limited visibility into them.

“The reason CTV is a really valuable proposition for advertisers is that you are able to identify the user 1:1 which is really powerful,” Bustos said. “Your standard news or editorial publisher doesn’t have that. I mean, the New York Times has moved to that and it’s been incredibly successful for them.” In order to compete with the walled gardens and streaming services, publishers need to offer some degree of addressability — and without relying on cookies.

But DCRs are a heavy lift. Data maturity is an important qualification for getting the most out of a DCR. The IAB report shows that, of the brands evaluating or using DCRs, over 70% have other data-related technologies like CDPs and DMPs.

“If you want a data clean room,” Bustos explained, “there are a lot of other technological solutions you have to have in place before. You need to make sure you have strong data assets.” He also recommends starting out by asking what you want to achieve, not what technology would be nice to have. “The first question is, what do you want to accomplish? You may not need a DCR. ‘I want to do this,’ then see what tools would get you to that.”

Understand also that implementation is going to require talent. “It is a demanding project in terms of the set-up,” said Bustos, “and there’s been significant growth in consulting companies and agencies helping set up these data clean rooms. You do need a lot of people, so it’s more efficient to hire outside help for the set up, and then just have a maintenance crew in-house.”

Underuse of measurement capabilities. One key finding in the IAB’s research is that DCR users are exploiting the audience matching capabilities much more than realizing the potential for measurement and attribution. “You need very strong data scientists and engineers to build advanced models,” Bustos said.

“A lot of brands that look into this say, ‘I want to be able to do a predictive analysis of my high lifetime value customers that are going to buy in the next 90 days.’ Or ‘I want to be able to measure which channels are driving the most incremental lift.’ It’s very complex analyses they want to do; but they don’t really have a reason as to why. What is the point? Understand your outcome and develop a sequential data strategy.”

Trying to understand incremental lift from your marketing can take a long time, he warned. “But you can easily do a reach and frequency and overlap analysis.” That will identify wasted investment in channels and as a by-product suggest where incremental lift is occurring. “There’s a need for companies to know what they want, identify what the outcome is, and then there are steps that are going to get you there. That’s also going to help to prove out ROI.”

Dig deeper: Failure to get the most out of data clean rooms is costing marketers money


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