You can tell what generation (demographic joke not intended) a marketer or business executive started in when they ask about the demographics of their customer base and then uses them to make decisions.
Demographics is still a powerful tool and nice information to know but with all the web tools and technology available today, there are better mechanisms for identifying and serving your marketing to help you drive more conversions for your business.
In this blog article, we’ll discuss a bit of the history of marketing demographics, why you should be looking at customer behavior instead, and how you can set your business website up to help you track customer behavior.
“Know Your Customer”- The previous use case for demographics
Back in the day, purchasing behavior was much different than what we know today. Things seemed to be a lot more black and white.
People had tremendous loyalty to brands. For example, baby boomers might have driven Ford their entire life and won’t even consider any other car make that isn’t a Ford.
Brands were able to build their customer base by using age, gender, salary, location, etc – based on United States census data or any other compilation of information they can find on people. They were then able to analyze who exactly is purchasing their products and identified demographic trends in their data.
One classic example of “knowing your customer” was Coca-Cola and Pepsi.
Coca-Cola and Pepsi Case Demographic Case Study
Coca-Cola has been around for well over a hundred years and throughout its history had centered its marketing campaigns on different demographics of people.
During the early 1900s, the brand positioned the beverage as a component of a wealthy lifestyle for elitists. It can be assumed that elitist back then was mostly of white American descent.
In the 1930s to 1960s, Coca-Cola was marketed to working-class people as a refreshing beverage to quench their thirst during work breaks which again skewed towards white Americans.
With that said, Pepsi, a competitor of Coca Cola was marketed heavily to African Americans.
To this day, Pepsi continues to heavily market to minorities here in America by having used influential brand ambassadors such as Beyonce, Michael Jackson, Ray Charles, and Mariah Carey in their campaigns.
No Internet means less access to customer behavior
The main idea is that brands used to make product decisions based on demographics alone. They took broad swoops of audiences and made vast campaigns to target a particular group of people.
The reasoning behind that was that they didn’t have wide access to the steps a consumer took to make a purchasing decision because there was no internet back then.
Companies had to really “know their customer”. It would’ve been a waste of advertising spending to try to target everyone in the world. So narrowing it down based on race, gender or financial status or any other information available made a lot of sense.
Why Demographics aren’t really effective anymore?
There is more actionable information available
The issue with demographic data is that it’s fairly static and you only get what someone tells you.
Demographic data is only collected here in the United States once every 10 years during the U.S census. By the time the data is collected and processed, it might be two or three years old.
It can still be fairly accurate however, world events like a natural disaster or war can cause a group of people to migrate to the United States and affect a census count.
You also have to consider that there is a fair share of people in the United States that are here illegally and won’t get counted in the census. According to data pulled in 2016, there were roughly 10.7 million undocumented immigrants in the United States which made up 3.3 of the total population.
That means that right off the bat if you are marketing a product that targets everyone in the United States, you are using only 97% of the available data to make decisions. That 3% can also be using your product or might even be the power user of your product or service and you won’t even know.
Also, people can fluff the census by lying about the information they provide.
With the technology available today, the preferred method to make marketing decisions is to use consumer behavior data. This is data taken in from user interactions with your website.
Through cookies, pixels, and CDPs like Twilio’s Segment and Rudderstack, websites can essentially track and log every one of your keystrokes and actions on a website and provide the insights to help you segment and make decisions based on the users’ actions.
Demographic information will soon be going away with data privacy
With all the data privacy laws coming into play in the next few years, it’s getting harder and harder to identify users.
Applications like Google Analytics have already taken action on this by very much limiting the demographic details it releases for its reports.
Universal Analytics which is being phased out in July 2023, only gives you age and gender demographic.
With Google Analytics 4 being the replacement for Universal Analytics, you don’t even have the option to access your demographic details anymore. GA4 wants you to create custom audiences based on behavioral characteristics your website visitors take on your website.
It’s simply not as accurate as behavior-based information
It’s hard to make marketing decisions based on demographics because it’s so open-ended. See the meme below to explain this concept.
Demographics can’t be used reliably to analyze your audience and target similar persons that meet that same demographic. There are too few distinguishing demographic characteristics amongst people to actively be able to make marketing decisions.
The more reliable measure to determine how people interact with your website is through actual behavior captured from your website. People are creatures of habit. If you identify a string of actions that you can determine is a pattern, you can build a dynamic website to account for those patterns and increase the chance of a conversion.
At that point, that’s when you turn behavior into a math problem and implement machine learning to allow AI to make decisions for you and in the best interest of the visitors to your website.
You should look at customer actions through modeling
What is a customer behavior model?
We’ve already covered buyer personas in an earlier blog article. The best way to define a customer behavior model is to think of it like a buyer persona but based on user actions performed on your website.
For example, you can create a customer behavior model that includes some demographics. You might notice that your audience might skew to people below 50 or people that make $75000 or more.
But the main driving factor in a model is the behaviors your converting customers take.
The model would consider things like keywords converting customer uses on a Google Search, how many emails someone needs to open before they convert, or what time of day someone visits your website and converts.
All these factors are packaged together into a model that can be applied to different aspects of your marketing mix.
Who uses customer behavior models?
Facebook and Google Ads
One of the more identifiable users of a customer behavior model would be Facebook Ads and Google Ads.
When you use these ad platforms for campaigns, they usually tell you to get started by running a normal conversion campaign. Once enough conversions come through that campaign you can then change the campaign type to “optimize for conversions” to enhance results.
This is because Google and Facebook are taken a snapshot of the customer behavior associated with your campaigns, and use machine learning to better serve your ads to customers who are most likely to convert.
Lookalike Audiences
They also could use your conversion data to make a lookalike audience. When Facebook or Google makes a lookalike audience, they are taking inventory of those people who have converted to your website and try to distinguish characteristics about them, and serve your ads to people just like them with the expectation that they will also convert to your service or product.
Other Use Cases
In reality, customer behavior models can be applied to just about anything related to marketing.
If you notice that most of your customers are converting after 4 emails, you might want to narrow the number of emails to that number to increase your chance of a conversion.
Your model might tell you that a significant number of users are visiting your Facebook page, then googling your brand, and then converting to your site.
That might prompt you to run Facebook or Google Remarketing ads, to better nurture the user in an attempt to get more people to purchase your offer.
How do you create a customer behavior model?
You can outsource
This is a preferred option especially if you have the budget to do so. If you are a bootstrapped business, you’ll most likely need a software engineer, a data scientist, and someone well-versed in machine learning.
There are companies out there that can take your data and create a model for you.
You can also browse marketplaces like Fiverr or Upwork if you are willing to hire someone part-time and take the risk of sacrificing the cheaper option for potentially lower-quality of work.
You would also need warehouses of data collected by your company. Learning or having someone well-versed in SQL databases, amazon web servers, etc will help you conquer this hurdle.
Use a CDP
As already mentioned, a customer data platform is a very important tool that can allow you to make customer behavior-based decisions.
All you would need to do is to hook up whichever CDP platform you use to your website through a javascript code and let the tool do the work for you.
You will need to go into the CDP tool and configure it to events on your websites like form submissions and button clicks. Again a little bit of code can be accomplished. Next, you’ll have to integrate it with all your marketing tools.
For example, your CDP can help you fill in the blanks that your email tool can’t. Based on events like button clicks, you would be able to create a list or segment of individuals that click a button and send them an email personalized to them.
Google Analytics 4 and Google Tag Manager
Now, if you are looking for a free option to collect customer behavior data, then Google Analytics 4 will be your best friend because it was built for this purpose.
As already defined, Universal Google Analytics was designed when online data privacy was not as enforced as it is today. With data privacy coming to the forefront, Google released its next version of the platform, Google Analytics 4 – which focuses more on the events taking place on your website and mobile app.
When using GA4, I would recommend using Google Tag Manager in conjunction with the analytics program.
To measure events like button clicks, all you need to do is hook up GA4 to Google Tag Manager and then create button tags to fire whenever an event takes place. For example, to set up an event tag for form submission, you might set up the tag to fire when someone visits the thank you page associated with the form.
After the event tag fires, you can go look into Google Analytics 4 and look at the real-time data and look for the event in the event’s section of the report page.
You can set that event as a conversion and even create custom audiences based on that event.
The idea behind this is that you can now segment your audience based on the events happening on their website sessions and make more informed decisions according to this new view you have access to.
Conclusion
It would be far from true to say that demographics have no role in marketing. Making decisions that affect customers might be better suited in this day and age with customer behavior-based data.
There are many tools and resources out there, some that cost money like outsourcing to a modeling agency or using a customer data platform. There are also more accessible resources out there like Google Analytics 4 that can allow you to make customer behavior-based decisions for free.
