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New Study Finds Facebook’s Interest Targeting is Inaccurate Around 30% of the Time

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New Study Finds Facebook's Interest Targeting is Inaccurate Around 30% of the Time


So how accurate are Facebook’s ad targeting options anyway?

The platform has made headlines in recent years over its intricate audience targeting process, which learns about your traits and interests based on in-app activity, then funnels that info into its ad targeting engine, enabling brands to present their offers to the most engaged, receptive audience through its various display options.

Political activists have reportedly used this to sway voter opinions, brands have been able to target users based on things that they may not even realize that they’re interested in themselves as yet. Some studies have even suggested that Facebook knows more about you than friends or family – but in reality, what’s the actual accuracy rate of Facebook’s ad targeting options, and what are the implications of false positives on ad spend?

That’s what a team from North Carolina State University sought to find out, with a new study that examined the specific performance of Facebook’s interest tracking, and how it allocates behaviors and topics to each user.

Their topline finding – around 30% of Facebook’s inferred interests are inaccurate or irrelevant, which could have significant implications for ad spend.

As explained in the study:

To obtain insights into how Facebook generates interests from a user’s Facebook activities, we performed controlled experiments by creating new accounts and systematically executing numerous planned activities. We found 33.22% of the inferred interests were inaccurate or irrelevant. To understand if our findings hold for a large and diverse sample, we conducted a user study where we recruited 146 participants (through Amazon Mechanical Turk) from different regions of the world to evaluate the accuracy of interests inferred by Facebook. We developed a browser extension to extract data from their own Facebook accounts and ask questions based on such data. Our participants reported a similar range (29%) of inaccuracy as observed in our controlled experiments.”

It is worth noting that this is a relatively small-scale study pool – Facebook has more than 2.9 billion monthly active users, so a group of 146 test subjects is only a fractional element.

But it’s process-focused the results likely hold nonetheless – as noted here, in the first element, the researchers conducted contained testing around how Facebook attributes interests based on activity, with the experimental profiles starting from blank, meaning they had no specific interests attached to begin with.

“Researchers created 14 new user accounts on Facebook. Researchers controlled the demographic data and behavior of each account, and tracked the list of interests that Facebook generated for each account. This experiment allowed us to see which activities were associated with Facebook inferring an interest, and the key finding here is that Facebook takes an aggressive approach to interest inference – even something as simple as scrolling through a page led to Facebook determining that a user has an interest in that subject.”

Of course, everyone knows that Facebook is tracking everything that you do in the app, but based on this study, even the smallest action can cause an inference in your ad targeting profile, which can lead to inaccurate targeting.

The researchers also note that Facebook’s system often doesn’t distinguish between positive and negative interactions, which can also lead to inaccuracies.

For instance, we commented negatively on a Harry Potter page and received interests in Harry Potter and Daniel Radcliffe (the lead actor in the Harry Potter movies).”

The study also showed that, at times, Facebook’s system will incorrectly attribute entities:

“For example, upon visiting the Apple (Tech company) page, Apple (fruit) was inferred as an interest.”

There would be varying degrees of errors within this type of matching, and these are just some examples of how your interests are sometimes misattributed in the app – which is probably not overly surprising, but the scale of inaccurate results is worthy of note.

Could this be because of Apple’s ATT update?

It’s possible that, due to Facebook losing data insight, as more users cut it off from tracking on iOS as a result of Apple’s ATT prompts, that Facebook is now putting more emphasis on in-app signals to fuel its audience segmentation instead. We don’t have comparative data on this, as the majority of this study was conducted after the implementation of Apple’s ATT alerts (in April 2021), but that could be another element at play, which could skew Facebook’s tracking.

But either way, it’s an interesting consideration. Up till now, Facebook’s data-gathering machine has been viewed as the most comprehensive tracking system ever created, and a powerful audience targeting engine. But if it’s not accurate 1/3 of the time, that’s a concern, which could reduce advertising performance.

So what do you do about it? Well, as an advertiser, there’s not much that you can do.

Using Lookalike Audiences and similar matching should improve accuracy, based on a range of factors, as opposed to singular topic matching – but really, you’re putting trust in Facebook’s systems to drive the best results, which means that if there are errors in attribution, that will impact your performance.

Meta is always working to improve its systems in this respect, and more recent feedback has been that Facebook ad targeting and performance is improving, so it could also be that these errors are being ironed out over time. But it really comes down to tracking your ad performance, and refining based on the results that you see. Facebook ads require a learning phase to maximize performance, and you would hope, within that, that it’s also weeding out false positives like this.

But it’s an interesting study either way, which could provide additional insight into your campaign performance.

You can read the full study and summary here, while you can check out what Facebook thinks your interests are here.   



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Publicis Performance Marketing Unit Acquires Influencer Platform Perlu 01/30/2023

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Publicis Performance Marketing Unit Acquires Influencer Platform Perlu 01/30/2023

Publicis Groupe-owned performance marketing agency CJ, which specializes in affiliate marketing, has acquired Perlu, a Syracuse, New York-based influencer networking and technology platform.
Perlu’s platform enables companies to activate, network, and collaborate with a community of influencers.   

Perlu will initially retain its name and organization as it is
integrated …



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Reports Show that Facebook Usage is Up, as Meta Continues to Develop its AI Targeting Models

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Reports Show that Facebook Usage is Up, as Meta Continues to Develop its AI Targeting Models

While Facebook is no longer the cool app, especially among younger audiences, it remains a key platform for many users, and its capacity to keep people updated on important updates from friends and family is likely to ensure that many continue to return to the app every day for some time yet.

But more than that, Facebook usage is actually increasing, according to internal insights viewed by The Wall Street Journal, which also include some interesting notes on overall Facebook and Instagram usage trends.

As per WSJ:

Data gathered in the middle of the fourth quarter showed that time spent on [Facebook] was up worldwide, including in developed markets, over the course of a year.”

Which seems unusual, given the subsequent rise of TikTok, and short form video more generally. But actually, Facebook has been able to successfully use the short-form video trend to drive more usage – despite much criticism of the platform’s copycat Reels feature.

Indeed, Reels consumption is up 20%, and has become a key element in Meta’s resurgence.  

How is it finding success? Increased investment in AI, which has driven big improvements in the relevance models that fuel both Reels and its ads, which are also now driving better response.

On Reels, Meta’s systems are getting much better at showing users the Reels content that they’re most likely to be interested in. You’ve likely noticed this yourself – what was initially a mess of random clips inserted into your Facebook feed has now become more focused, and you’re probably finding yourself expanding a Reels clip every now and then, just to see what it’s about.

Reels has actually been too successful:

“Because ads in Reels videos don’t currently sell for as much as those sold against regular posts and stories, Reels’ growing share of content consumption was denting ad revenue. To protect the company’s earnings, the company cut back on promoting Reels, which lowered watch time by 12%.

So again, while Meta has been criticized for stealing TikTok’s format, it’s once again shown, just as it did with Stories, that this is a viable and beneficial pathway to keeping users engaged in its apps.

You might not like it, but replication works in this respect.

But for marketers, it’s likely the development of Meta’s AI targeting tools for ads that’s of most interest.

Over time, many performance advertisers have been increasingly recommending that marketers trust Meta’s AI targeting, with newer offerings like Advantage+ driving strong results, with far less manual targeting effort.

Advantage+ puts almost total trust in Meta’s AI targeting systems. You can choose a couple of targeting options for your campaigns, but for the most part, the process is designed to limit manual impact, in order to let Meta’s systems determine the right audience for your ads.

Which may feel like you’re ceding too much control, but according to Meta, its continued AI investment is now driving better results.

Heavy investment in artificial intelligence tools has enabled the company to improve ad-targeting systems to make better predictions based on less data, according to the interviews and documents […] That, along with shifting to forms of advertising less dependent on harvesting user data from off its platforms, are key to the company’s plans to overcome an Apple privacy change that restricted Meta’s capacity to gather information about what its users do outside its platforms’ walls, the documents show.”

That’s likely worth considering in your process, putting more trust in Meta’s targeting systems to drive better results. At the least, it may be worth experimenting with Meta’s evolving AI for ad targeting. 

It’s not all good news. Meta also notes that while time spent in its apps is on the rise, creation and engagement is declining, with fewer people posting to both Facebook and Instagram than they have in the past.

That’s particularly true among younger audiences, while notably, usage of Instagram Stories is also in decline, down 10% on previous levels.

So while Meta is driving more engagement from Reels, which draws on content from across the app, as opposed to the people and Pages you follow, that’s also led to a decline in user posting.

Is that a bad thing? I mean, logically, engagement is important in keeping people interested in the app, and Meta also relies on those signals to help refine its ad targeting. So it does need users to be sharing their own content too, but if it can get more people spending more time in its apps, that will help it maintain advertiser interest.

In essence, despite all of the reports of Facebook’s demise, it remains a key connective platform, in various ways, while Meta’s improving ad targeting systems are also helping to drive better results, which will keep it as a staple for brands moving forward.

If you were thinking of diversifying your social media marketing spend this year, maybe don’t reduce Facebook investment just yet.

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Effective Ways To Personalize Your Customer Touch Points Even More In 2023

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Effective Ways To Personalize Your Customer Touch Points Even More In 2023

Will 2023 be the year of personalization? Consumers hope so. For the past two years, shoppers have been craving the personal touch: In 2021, McKinsey & Company noted that 71% of customers expected companies to deliver personalization. In 2022, a Salesforce survey found that 73% of people expected brands to understand their needs and expectations. So, this year is looking like one where personalization can no longer be seen as a “nice to have.”

The problem, of course, is how to get more personalized. Many companies have already started to dabble in this. They greet shoppers by name on landing pages. They rely on CRMs and other tools to use historical information to send shoppers customized recommendations. They offer personalized, real-time discounts to help buyers convert their abandoned shopping cart items to actual purchases.

These are all great ideas. The only problem is that they’ve become widespread. They don’t move the needle on the customer experience anymore. Instead, they’re standard, expected, and kind of forgettable. That doesn’t mean you can afford to stop doing them. It just means you must devise other ways to pepper personalization throughout your consumer interactions.

If you are scratching your head on how to outdo 2022’s personalization in 2023, try implementing the following strategies:

1. Go for full-blown engagement on social media.

One easy way to give the personal touch is through your social media business pages. Social media use just keeps growing. In 2022, there were about 266 million monthly active users (or MUAs) on Facebook, one billion on Instagram, and 755 million on TikTok. Not all these active users will fall into your target audiences, but plenty of them will.

Make engaging with your social followers one of this year’s goals. People spend a lot of time on social media. It’s where many of them “live,” so it only makes sense that it should be a place to drive personalization.

One quick way to ratchet up your company’s personal touch on social media is to personalize all your retargeted ads. Quizzes can also offer a chance for personalization. Simply set up an engaging quiz and allow people to share their results. It’s a fun way to build brand recognition and bond with consumers. Of course, there’s nothing wrong with going very personal and answering all comments. Depending on your team’s size and the number of comments you receive, this might be a viable option.

2. Leverage AI to go beyond basic demographics.

Most companies rely on customer demographic information to bolster personalization efforts. The only trouble with this tactic is that demographics can’t tell the whole story. It’s impossible to get a lot of context about individual users (such as their lifestyles, personal preferences, and motivators) just from knowing their age, gender, or location. Though demographic data is beneficial, it can cause some significant misses.

Michael Scharff, CEO and cofounder of Evolv AI, explains the workaround for this problem: “The most natural, and therefore productive, personalization efforts use demographics as a foundation and then layer in user likes, dislikes, behaviors, and values.”

You can leverage AI’s predictive and insightful capabilities to uncover real-time user insights. Scharff recommends this technique because it allows you to stay in sync with the fast-moving pace of consumer behavior changes. He adds that AI can be particularly beneficial with the coming limits to third-party cookie access because it can be a first-party data source, allowing you to maintain customer knowledge and connection.

To flesh out your organization’s strategy, look to other companies that have gone beyond demographics. Take Netflix, for example, which constantly tweaks its AI algorithm to help improve personalized content recommendations. Bottom line? Going deeper than surface information makes all the sense in the world if you want to show customers you know them well.

3. Keep your data spotless.

The better your data, the better your personalization efforts. Period. Unfortunately, you are probably sitting on a lot of unstructured or otherwise tricky-to-use (or impossible-to-use) data. One recent Great Expectations survey revealed that 77% of data practitioners have data quality problems, and 91% say that this is wreaking havoc on their companies’ performance.

You can’t personalize anything with corrupt or questionable data. So, do your best to find ways to clean your data promptly and routinely. For example, you might want to invest in a more centralized data system, particularly if the personalization data you rely on is scattered in various places. Having one repository of data truth makes it easier to know if the information on hand is ready to use.

Another way to tame your data is to automate as many data processes as possible. Reducing manual manipulation of data lessens the chance of human error. And you’ll feel more confident with all your personalization efforts if you can trust the reliability and health of your data.

4. Go for nontechnical personalization.

It’s the digital age, but that doesn’t mean every touchpoint has to be digitized. Consumers often react with delight and positivity when they receive personalization in decidedly nontech forms. (Yes, you can use tech to keep track of everything. Just don’t make it part of the actual personalized exchange!)

Consider writing handwritten thank-you notes to customers after they’ve called in for support or emailed your team, for instance. Or send an extra personalized gift to buyers who make a specific number of purchases. These interactions aren’t technical but can differentiate your customer experience from your competitors’ experiences.

A groundbreaking Deloitte snapshot taken right before the pandemic showed that people were hungry for connection. By folding nondigital experiences into your personalization with customers, you’re showing them that you see them first as valued humans. That’s compelling and appealing, making them more apt to give you their loyalty in return.

Putting a personal spin on all your consumer interactions takes a little time. It’s worth your energy, though. You’ll wind up with stronger brand-buyer connections, helping you edge ahead of your competitors even more.

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