3 First-Party Data Stats You Need to Know
First-party data is the name of the game when it comes to targeted ads in the future of advertising — here are stats to prove it (+ what you need to do now). Click here to read on.
The good thing about advertising online is that brands can find just about anyone, with any interest, and in any segment, they're looking for. For example, if a business sells vegan leather wallets and wants to target men with disposable income and that have an interest in environmentally sustainable products, they can find them!
Amazingly, with breakthroughs in digital marketing, brands have the flexibility to reach vast groups of customers, and then, in turn, target specific audience segments. However, there is a consequence to this level of freedom — an added layer of complexity to your marketing strategy. In the “old days” of marketing, it was enough to create catchy, engaging creative and put it in the newspaper, a billboard, or the radio.
Times have changed. With the power of hyper-targeting comes the responsibility to use it wisely, thoughtfully identify audiences, and communicate with them in personalized ways. Brands who do this well stand out from the competition, endear themselves to their customers, and reap the benefits of profitable long-term customer relationships.
Think about it. Let’s say a brand is selling high-end Bluetooth speakers. These speakers are seriously technologically advanced and equipped with features that true speaker-heads will fully appreciate. They also come with designs to blend in with any environment from home to office and more. They’re also priced to suit their high-end nature, starting at $400.
The brand's campaign creative (both static and video) features their beautiful, sleek speakers and has a few selling points. These ads are linked to a landing page that contains all of the relevant details and makes the purchase easy. However, since the brand has little insight into their target audiences, they set up some general targeting with no real restrictions on age, gender, interest, income, and so on.
The campaign runs for a while and, while the results are okay, the brand is stumped as to why they're not better. They want to increase their click-through rate (CTR), boost site traffic, decrease their bounce rate, and improve their ROI — but they're not sure how to do it.
The solution is to carefully strategize for an exact target audience. People don’t want to feel marketed to — they want to be communicated with. There’s a large difference between those two things, and the key is in creating personalized experiences through ads, landing pages, and yes, specific targeting.
If any of this resonates, then this article will be right up your alley. In the preceding sections, we'll go over:
Customers are open to advertising, as long as the ads aren’t invasive, and they derive some value from them. The Interactive Advertising Bureau (IAB) found that 3 out of 4 people wanted fewer, yet more personalized ads. Brands that invest in ad personalization, including highly targeted advertising experiences, have the opportunity to create and cultivate profitable relationships with their customers that grow lifetime value (LTV), over time.
Personalization is a broad topic that can include emails, sites, and ads. In this instance, we're referring to creating highly personalized advertising experiences by putting target audiences into meaningful segments and distributing ads to those segments, based on their defining motivations, characteristics, and needs. For instance, let’s look at a business that sells teapots, tea, and tea accessories. They might divide their audience into segments that represent different personas, like the:
· On-the-go tea drinker: This person mostly consumes their tea at work or on their way to and from work. This person drinks tea as a healthier, lower-calorie alternative to soda or a latte. They are most likely to be between the ages of 25 and 50 and have a career. For this person, you would target them with quick, easy to brew varieties of tea and travel mugs or desk-friendly options. In your creative, you want to emphasize the health benefits and travel-friendly features.
· Slow sipper: This person enjoys the ritual of their daily cup of tea. They want the experience of a beautiful pot, a nice cup, and a well-brewed cup of tea. This segment is 75% female, 25% male, generally has more disposable income than average and enjoys things like yoga, tai chi, poetry, and hiking. You would target this person with messaging and products that reflect their need for peace, reflection, and a hot cup of tea.
These are just two of the many ways audiences could be segmented. Imagine audience segments specifically for health-interested people, just women interested in floral options, people who want the energy boost of green tea, etc.
These two audiences could be further segmented to create more personalized experiences. For instance, the on-the-go tea drinker segment could be split into travel mugs and desk-friendly options, loose leaf travel mugs and options specific to tea bags, specific design options generally more appealing to women and those that are more appealing to men, etc. The options are truly endless. It’s in a marketer's hands to determine how granularly they want to target, which segments they want to explore, and which products they want to promote.
In this instance, we're referring to creating highly personalized advertising experiences by putting target audiences into meaningful segments and distributing ads to those segments, based on their defining motivations, characteristics, and needs.
Now that your mind is buzzing with all of the possibilities for creating personalized advertising experiences, let’s get into some tips for creating customer segments backed by data.
Ideally, identifying who a customer will be, at least preliminary, will happen in the very early stages of developing a business or product. However, identifying a target audience isn’t a one-time event. It’s something that should be refined frequently using the data at a brand's disposal. Some ways you can identify audiences could be:
If marketing is all about building relationships (hint: it is), then listening is the key to success. Building systems that center around listening to customers, learning more about them, and implementing what you learn will cost hardly anything, but pay big dividends in your ability to build profitable long-term relationships with customers.
So you’ve identified a few ideas for audiences and have personalized creative. Now it’s time to set up highly-targeted campaigns.
First, a quick background on how targeting works. Whether it's placing ads through Facebook, Instagram, or Google, these platforms can identify a fairly specific idea of who is using a device. They can tell the age, gender, location, and even interests that a person has by monitoring pages they visit, things they purchase, their social posts, likes, and more. None of this is completely fallible, but the algorithms that go out and create profiles for people are quite sophisticated.
These profiles are broken down into a variety of attributes. So, in basic terms, a profile might look something like:
Each profile is a mix of demographics (gender, age, location) and interests (hobbies, family, food).
Note: this is just a very basic explanation that works for our purposes in this article.
Beyond demographic and interest targeting, marketers can also target contextually and for lookalike audiences. Below is an explanation of each type of targeting, where it’s useful and the unique drawbacks.
This is one of the most basic forms of targeting and includes options for a geographic region, age, gender, annual income, and more. Targeting an audience using demographics is fairly straightforward. Generally, a brand creates products with a certain customer in mind, meaning that they're equipped with the insights to create one or two basic demographic profiles for in-market audiences.
The main drawback of demographic targeting is that there's still an enormous amount of variety even among people who look the same demographically. That makes it difficult to create truly personalized experiences because an audience can still be fairly broad.
Interest targeting can still be straightforward (simply select some interests that a target audience has) but does require more forethought and strategic planning. While you can probably determine some basic interests for a target audience right out of the gates, digging just a little bit deeper into data can yield some interesting insights.
The drawback of interest targeting is an important one — privacy concerns. We’ve all heard the news and seen legislation like the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA) come into effect. While the future of these targeting options is unsure, it does seem clear that at least some audience will be unavailable by either demographic or interest targeting.
Contextual targeting is a perfect option for brands that want to control where their ads are placed online. Brands can reach customers on the websites their target audiences already visit and those that coincide with their values. Additionally, ads can be excluded from certain websites that are deemed inappropriate. This is the perfect option for the privacy-conscious business that falls under restrictions from CCPA or GDPR.
The drawback of contextual targeting is that it’s slightly less specific than the others and may also require extra digging to define exactly what type of content or sites are resonating with audiences.
The other options entail doing research, selecting alternatives, monitoring them, and optimizing accordingly. Lookalike targeting doesn’t require any of that. Brands can depend on AI technology to do the heavy lifting for them.
Each platform has a slightly different take on lookalike targeting, but the basic explanation is that the system takes a look at current website traffic, who is coming to a site, and those who are most likely to convert or perform any specific goal. Then, the AI goes out and identifies people who are similar to current customers and shows them ads. With this option, it learns as it goes and accommodates any changes in product, traffic, and so on.
The only downside with lookalike targeting is that it doesn’t give much control over who is targeted. That, in turn, doesn’t allow you to use targeting to test new audiences that may look or behave differently than who you’re currently targeting.
Lookalike targeting doesn’t require any of that. Brands can depend on AI technology to do the heavy lifting for them.
Each of these forms of targeting has strengths and weaknesses that should be taken into account when structuring any ad campaign. As such, in most cases, it’s recommended that brands use a combination of all of these options. Use demographic, interest, and contextual targeting to pick and choose a specific audience and let the sophisticated AI technology behind lookalike targeting identify the audiences that might otherwise be missed.
Now that you understand the basics of identifying, finding, and communicating with an ideal audience, it’s time to put all of those ideas into motion. Below are some helpful resources to help identify an audience, create campaign assets that will resonate with them, measure your impact, and optimize your campaigns.
Who is your customer?
Measure & optimize
Last updated on October 28th, 2022.