Do demographics matter in media?
Content preferences and consumption are no longer defined by age, race, gender, income, location, etc.
Demographics have been used to target the “ideal” consumer for over 50 years in research studies, advertising, politics, and media. Prior to the internet, it was the primary research data that drove many an advertising or electoral campaign.
Using factors such as age, race, sex, income, education level, occupation, marital status, place of residence, and nationality, organizations honed their demographic-centered models to try and capture the lion’s share of a target market; and for years, it was enough.
But not anymore.
We are living in a shrinking world where the six degrees of separation between people has been reduced to a number closer to three. One look at Facebook and its growing population of over two billion members, and it’s not hard to imagine three degrees moving to two in the not-too-distant future.
That, in and of itself, may not seem like a big deal, but when the internet enabled a many-to-many connection between global citizens, it inadvertently also influenced our attitudes, values, personalities, opinions, interests, and lifestyles.
The web has distorted the characteristics within traditional demographic maps. In short, people today don’t behave as their demography would dictate.
I can still remember when the only news I got growing up was in the daily paper dropped in the mailbox or on the radio or TV. The digital revolution changed all that. Today we have almost unlimited choices in terms of content, distribution channels, and costs — choices we’re taking full advantage of. As a result, publishers are facing a brand crisis as readers, who access multiple sources of content every day on social media and other content aggregators, often can’t remember the source.
To thrive in this world of promiscuous audiences, publishers can’t continue to treat readers like silos of demographic data because content preferences and consumption are no longer defined by age, race, gender, income, location, etc.
Instead, they need to put people first and work at creating a relationship with each and every one of them by:
• Recognizing that demographics and segmentation cannot help them adequately curate content for their readers
• Seeing consumers as individuals that are constantly changing as the world evolves around them
• Digging deeper into the behaviors of each person — behaviors that can’t be measured just by what they share, but rather what they actually consume
• Adopting behavioral analytics that continually monitor individual users and then adapt their content, delivery mechanisms, and communications to meet the ever-changing needs of each and every person
• Accepting the fact that they need to be everywhere their audience is, and their audience is everywhere The most successful digital companies in the world already do all of this. Think: Amazon, Facebook, Apple, Google, Netflix, and Spotify, to name just a few.
Take for example, Spotify’s Discover Weekly playlist — a weekly collection of songs selected specifically for you. It is a great example of delivering personalized content to an audience, not based on demographics, but on an individual’s music tastes.
Spotify’s curation algorithm is a learning machine that uses one’s listening history, and that of other Spotify users with similar preferences in music, to generate for each a unique Discover Weekly playlist. The more a person uses the service, the better Spotify gets to know what that user likes and doesn’t like. What a great way to grow an amazing user experience over time and build loyalty!
It’s no wonder Spotify continues to grow in popularity worldwide, with over 60 million paying subscribers — more than any other streaming media service, including Apple Music. Spotify’s algorithm uses a combination of three content recommendation models.
The first is collaborative filtering, which continually monitors what one listens to so it can open up a whole new world of relevant songs they may never otherwise discover.
Second is Natural Language Processing, which scours the web for written content about music to learn what others are saying about specific songs and artists, and about the performers discussed alongside them.
Finally, Raw Audio Models analyze new tracks that may not yet be discussed online or have many listeners. It’s this indiscriminate analysis of content that allows unknown artists to show up next to popular musicians in Discovery Weekly.
Algorithms for curating content based on machine learning are everywhere and every content aggregator uses them. Why? Because people prefer algorithmic curation over human editors.
But what about people’s fear of giving access to their personal information to these sites? According to a 2016 study by Accenture:
• 70% of people are generally comfortable with news sites collecting personal data if the publisher is transparent about how it uses it
• 75% are comfortable if they can personally control how it was being used
• 68% are highly satisfied with streaming video services’ (e.g. Netflix) use of personal data (even though there is little transparency or user control in them) because it helps people discover shows they like
There is a fine line between using personal data for the good of an audience and abusing it for profit. Having relevant and quality content curated for you is magical; having ads follow you around the web, for weeks on end, is just plain creepy.
Many publishers think that news content is too ephemeral for a Spotify-like discovery algorithm, but I beg to differ.
Just take a look at Facebook’s curated newsfeed. Its algorithm is continually being enhanced to provide the most engaging experience for its users — one that will keep them on the site longer and coming back for more. Facebook news is as fleeting as a Snapchat photo.
Facebook’s mission is to “give people the power to build community and bring the world closer together.” It puts its members at the top of its agenda in everything it does. In October 2017, the average time spent on Facebook per person per visit was 20 minutes. Compare that to the
top US newspaper websites had an average visit time of less than 2.5 minutes. The numbers speak for themselves, so why aren’t more publishers listening?
Digital is just an enabler to connect
I have lost count of the number of times I’ve heard publishers refer to themselves as “digital-first.” As much as I appreciate them finally committing to 20th century technology 10 years after the internet became mainstream, it still amazes me that they don’t realize that their focus is misplaced. In the 21st century content is not king and neither is technology; readers are the rulers on this people-powered planet and they must come first.
Whether you’re in social, search, services, manufacturing, consumer packaged goods, healthcare, education, petroleum, finance… the list goes on, or publishing, unless you see your company as people business whose mission is to make life better for real people, you’ll have missed the proverbial gravy boat.
The internet connected us in ways we never dreamed about — a connection that is not just virtual, it’s social. If you want to be a successful digital company then forget the technology and focus on what really matters — people. Start a social movement that begins by connecting them with each other and with you through quality content.
Because demographics won’t help you reach your ideal customer; only a dedication to continually connecting with, and delighting, individuals will.
If you want to learn more about how machine learning can help you connect people through news, let’s talk!