Why Facebook Interest Data Is Flawed and How Spotify Fixed It

Every time you go online, you generate "interest" data. Interest data is any personally identifiable data point that indicates someone is interested in a particular brand, topic or idea. It's what powers digital ad campaign targeting, suggested content and news feed algorithms. If you’re a marketer, interest data is music to your ears 🎶. After...
Why Facebook Interest Data is Flawed and How Spotify Fixed It

Every time you go online, you generate "interest" data. Interest data is any personally identifiable data point that indicates someone is interested in a particular brand, topic or idea. It's what powers digital ad campaign targeting, suggested content and news feed algorithms.

If you’re a marketer, interest data is music to your ears 🎶. After all, you can leverage it to target ads based on very precise interests, right? Theoretically, yes - but not all interest data is created equally.

Facebook is renowned for its big interest data - and rightly so. With over 1.86 billion monthly active users, it's hard to beat the breadth of user interests it can collect. But more data does not necessarily mean better data...

Spotify, however - known as the driving force of innovation in music - is carving its own niche in the data world. That said, Spotify's whopping 140 million active users is mere peanuts compared to Facebook.

So whose interest data is better? What even defines "better interest data"?

The 3 R's of quality interest data are:

1. Recent - Was the data gathered or initiated recently?
2. Relevant - Is it relevant for your specific marketing needs?
3. Reliable - Did the fan expressly declare the interest?

If you can answer yes to three essential targeting questions, then you know the interest data is valuable and ready to put into action.

Now that we know how to define quality interest data, let's explore what Facebook and Spotify can offer.

Flaws in Facebook Interest Targeting

Facebook is famous for letting advertisers target ads to potential leads based on their interests. They claim to know fans better than themselves - using clicks, follows, likes, shares, messages and even pauses in scrolling to define what each of their users cares about.

But, is the passive analysis of user behaviour enough? Do actions really speak louder than words?

Facebook Ad Targeting - Relevant

One major strength of Facebook's platform is the ability to identify specific interests that are relevant to your business. Whether you're looking for recently engaged couples, expectant mothers or people with a passion for igneous rocks - Facebook offers the option to target them.

The actual mechanism for choosing interests relevant to your business wins by far compared to other platforms like Twitter and LinkedIn. However, just because you can select a relevant target option, doesn't mean that the data informing that target is accurate.

Page Follows - Not Recent

One of the ways that Facebook derives users’ interest is from Page Follows. Although this action is explicit and thus reliable, this information is historical - often way, way historical. When was the last time you even followed a Facebook page? Also, we're sure you aren't still interested in the Facebook pages that you liked years ago. Avril Lavigne, Fall Out Boy and Nickelback ring a bell? I bet you still follow their pages.

This source of interest data rapidly degenerates in quality, often to downright inaccuracy. You don't want to bank your precious ad dollars on decades-old data.

Ad Interactions - Not Reliable

Another way that Facebook derives interests is through users’ interactions with ads. Facebook generates an "interests profile" for each user based on their behaviour.

All it takes is a quick scroll through your own "Facebook interests" to see just how inaccurate these indirect assignments can be. Although some will be accurate, most are super random or just plain wrong.

Click here to discover your interests on Facebook.

Mentions - Not Reliable

Facebook also derives interest data from the people or brands that they’ve mentioned in posts. However, this may have the opposite indication than intended.

Take the 2016 Donald Trump vs. Hillary Clinton election campaign for example. This electoral push generated a lot of social media buzz, but not all of the mentions for Trump and Clinton were positive.

People around the world mentioned Trump and Clinton on social out of sheer animosity. Therefore, Facebook’s algorithm may have inaccurately assigned these individuals as "interested in Trump or Clinton" based on these humorous or hostile mentions.

It is clear that mentioning a brand, artist or person does not always signify affection. Therefore, interest data from mentions does not meet the third fundamental factor of interest data.

This doesn't mean Facebook is a failure at ad targeting by interests. All this means is that we need to layer more recent and reliable data on top of Facebook's big interests data. This will finally make the best use of their relevant ad targeting engine.

Spotify Interest Targeting - Quality Data

Let's explore the smaller but mightier platform for mining interest data: Spotify.

Latest Listens - Recent

Spotify interests are generated from users’ most recent listens (i.e. last 100 listens). This data is recent because, rather than using historical data, interests are refreshed in real time while users listen. Therefore, that Avril Lavigne or Nickelback phase you went through years ago will not resurface in ads targeted to you or your audience.

Interests, Moods and Activities - Relevant

You might be thinking - if I'm not a musician or music promoter, how is Spotify data relevant to my business? What people listen to indicates more than just their musical tastes. As a result, the interests derived from fans' listens can be relevant for marketers looking to tap into user's current emotional state - an important driver for conversions.

In addition to signifying favourite artists and genres, Spotify listening data can indicate a fan's mood and favourite activities. This is decided through Spotify's categorized playlists like workout, party, relaxation and travel mixes. Spotify users choose these playlists to amplify their current state of mind, thus directly indicating their present interest in that field.

If you are a musician or promoter, you can go beyond fans interested in your own music to discover new audiences. Spotify's complex "related artist" algorithms span beyond genre and actually indicate groups of fans who listen to multiple artists, regardless of their sound. This becomes extremely helpful for music promoters looking to discover the next upcoming hits.

Selected Content - Reliable

When a song comes on that you don't like, how long does it take you to change it? 1 second, 5 seconds? I bet you've never sat through an entire song you hated.

Therefore, it's safe to say that if a fan is listening to an entire song or album, they're actively interested in that genre, artist, mood or activity. Interest data derived from listens is therefore extremely reliable because it's direct - both from an acceptance and rejection standpoint.

Although recent Facebook follows may be a reliable indication of a new interest, they are flawed because people don't go back and "unlike" things unless they are reminded that they liked them. All you need on Spotify is one "skip" button for fans to tell you they no longer like something - that's powerful.

Based on the three R's of interest data, it's clear that Facebook could learn a few things from Spotify.

That being said - assuming you want ads across multiple platforms - more than simply Spotify Audio Ads) - how do you use Spotify’s interest data for ad targeting on other platforms?

Affinity Targeting - Combining Facebook’s Relevance with Spotify’s Recency and Reliability

In summary - although Facebook boasts a ton of data, much of it is outdated or unreliable. Spotify has quality interest data, but nowhere near to Facebook's scale. So how can we get the best of both worlds? The answer: a Fan CRM with affinity.

Affinity tools combine multiple interest data sources to quantify exact affinity (interest) at any given time for any given fan. Cross-referencing fans' social posts, listening patterns and behaviours on Facebook creates a master affinity metric that is always recent, relevant and reliable.

Through lead-generating campaigns, social authorizations and advanced tracking, affinity tools pull data across multiple platforms into a centralized Fan CRM system. Once all your data is in one place, you can create precise and auto-updating audiences for ad targeting on any network.

Thus, you can rest assured that your ad targeting and interest data will always be recent, relevant and reliable.

Want to see our affinity tool in action? Book a free consultation to see how interest data can help your business.

Source: tradablebits.com