The Econsultancy 2019 Digital Trends report recently revealed how harnessing customer data is now a dominant marketing trend. 55% of respondents, according to an Econsultancy survey, intended to make better use of their data in order to create more effective audience segments.
The implementation of customer data, also known as first-party data, has long been the preferred ammunition of personalization for digital marketers. However, survey respondents also acknowledged its limitations when a whopping 44% admitted that getting a more holistic view of their customer base was still a significant challenge.
To better understand the benefits and perceived limitations of first-party data, then, we need to identify its value-add for your online marketing efforts. Just as important, we also need to track how media targeting has evolved over the years, which in turn ultimately made alternative sources of data (second- and third-party data) less attractive, especially when it comes to custom audiences.
The Evolution of Media Targeting
Traditional ads (the golden age of advertising), such as billboards, radio, and television, focused on the sale and, therefore, placed products at the forefront of most marketing campaigns. With the introduction of new channels and mediums associated with online advertising, however, everything changed as marketers’ focus shifted toward direct response and identifying consumer problems and offering solutions to them.
Direct response marketing, then, saw the onset of trends starting with broad demographics-based targeting that incorporates age, gender, education, and income. In time, targeting was further refined with interest and behavior-based targeting incorporating consumer actions into the mix and attaining greater responses from purchase data, time spent on online stores, identification of clicks, and more. These two trends are still present and dominant today and are used in a variety of ways in the constant pursuit of the right time, right place, right message marketing.
The shift to online advertising created new opportunities for marketers, but it also required constant adaptation as businesses responded to the demands of these new technological mediums as well as their newly identified audiences. Improved personalization through 1:1 advertising campaigns proved to be one notable example of those efforts, which ultimately produced higher response rates for businesses across the country.
Internet giants such as Facebook and Google, for example, seized upon this opportunity to collect user data. They then created ad services for businesses looking to take advantage of 1:1 advertising.
What Data do Facebook and Google Collect?
Facebook and Google collect copious amounts of user data, which makes them an attractive platform for paid media since advertisers can use the aggregated data to their advantage.
Here's a quick run-down of how this process works.
Facebook collects data through websites and apps that use Facebook services. This includes information that users input when subscribing to their platform. Facebook then uses this data to subsequently improve the user experience.
For example, let's say you were shopping on a website, clicked on a pair of shoes that you liked, and added them to a shopping cart. But then your phone dies. After recharging your phone and logging back into Facebook, you find an advertisement for that exact same pair of shoes. The shoe ad is targeted for individuals like you because of something called the Facebook pixel, which triggers cookie data.
A Facebook pixel is an analytics tool that allows advertisers to measure the effectiveness of their ads by understanding the actions people take on your website. This tool is typically added to websites so that when interested shoppers take an action on your site (like adding a pair of shoes to a shopping cart) it fires off and makes it available for analysis in the Events Manager where advertisers can maximize on said actions.
Pixels trigger cookie data, which are files that contain small pieces of anonymous information that are exchanged between a user’s device and a web server that identifies a specific user while also enhancing their browsing experience. The cookie stores the interested shoppers’ behavior in the browser and guides future ad placements, an experience that’s similar to the shoe scenario we mentioned earlier.
Similarly, Google also collects information that simultaneously enhances the user experience by presenting ads that focus on a user’s interests. Google collects data from sites and apps that share information. And if you use any Google product, such as Gmail or Google Search, they also harvest personal information that includes your name, gender, date of birth, google searches, visited websites, and geographic location. Google also has a pixel that fires off when users click on a campaign and then visit certain pages on your website.
The plethora of data collected by these two widely used platforms gives advertisers the power, if they so choose, to enhance personalization even more. In doing so, Google and Facebook became the preferred advertising platforms for e-commerce merchants. Moreover, the introduction of pixels and cookies revolutionized targeting by allowing advertisers to track users and their online movements and habits.
Cookies, for many businesses, paved the way for more personalized solutions in advertising, however, the introduction of the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) coupled with Google’s announcement of the two-year cookie phase-out made them less attractive since both ad platforms attained personalization through aggregated data also known as third-party data.
New laws and ad platform decisions rocked advertisers everywhere as it forced them to rethink the foundations of their ads, but it also opened the door to first-party data and its many advantages.
First-party data vs. third-party data.
When it comes to data, quality should always outweigh quantity. And when it comes to quality, first-party data is the clear favorite. Here's why:
First-party data is data that you collect directly from your customers and audiences. It's by far the most accurate and value-building source as customers will continue to strengthen it with every behavior they take with your brand, whether it's a purchase from your online store, a subscription to your email, or surveys and reviews.
Third-party data is data that's aggregated from various platforms and combined into a larger data set. There are many unknowns associated with third-party data, and that makes it less attractive as it's data that has no direct relationship with your customer. Additionally, it's data that many businesses use, so there's a high possibility that your competitors are using the same data.
While first-party data’s value is well-known, it’s still a resource that has yet to be exploited in the same ways that third-party data. However, the e-Commerce marketers that are using it have recognized two things about first-party data that has given them a competitive advantage.
- First-party data allows advertisers to more fully analyze a customer base’s value and demographics, thereby helping inform and strengthen campaign strategies.
- First-party data increases relevance scores through improved match rates within ad platforms which allows advertisers to leverage both their customer database and the plethora of data that ad platforms offer.
These two discoveries get at a few key points, one of which is getting a holistic view of your customer base and the other is improving your personalization game further. Through the use of first-party data, advanced e-Commerce marketers can successfully attain a birdseye view of their storefront while also improving their targeting with better match rates.
Facebook match rates are a part of a service they offer called Custom Audiences. Custom Audiences are types of audiences that you can create from customer lists to help build your reach. When you upload a customer list into Facebook to create a Custom Audience there’s a process called matching where the information that you upload is used to match Facebook profiles. Match rates are affected by both the quality and quantity of data as the more accurate information you can provide, the better the match rate will be. First-party data helps with this because, again, it’s information that comes directly from your customers.
Google also allows marketers to use their first-party data and has a similar process called Customer Match. Customer Match lets marketers use online (google’s database) and offline data (your first-party data) to reach and re-engage with your customers across Search, Shopping, Gmail, YouTube, and Display. Through the use of their Audience Manager you can upload a customer list into Google Ads, and similarly to Facebook, Google then searches through it’s database to match emails, addresses, and other information and when there’s a match, it adds the corresponding Google account to your Customer Match audience.
First-party data is something that all e-Commerce merchants have at their disposal but due to the nature of exports, lack of know-how, and various key performance indicators (KPIs) needed to define and track success it remains an untapped gold mine for the masses. As such, oftentimes only advanced marketing strategists rely upon it as they’re creating and implementing marketing campaigns.
Using first-party data as a basis for marketing campaigns is advantageous because it allows ad platform algorithms to learn directly from your customers in order to:
- Strengthen relationships with existing customers.
- Encourage repurchasing.
- Attract new customers that are similar to your current customers.
In a first-party data marketing world, understanding and updating your algorithms is critical to your success because they’re programmed to create personalized marketing campaigns by targeting individuals with the most appropriate advertisements in order to enable the best possible user experience. We see this in Ad Auction, Facebook's ad algorithm and Google Ads’ Smart Bidding.
On the Facebook side, Ad Auctions determines the order in which an ad appears in a newsfeed relative to other ads. So, if you and your competitors target the same audience pool, you'll want to make sure that your ad appears before your competitors’ by “winning” the auction.
Google’s Smart Bidding uses machine learning to amend bids based on a wide range of real-time signals including device, location, time of day, remarketing list, language, and operating system. This machine learning can be influenced by your customers through the use of first-party data to tailor bidding strategies for your target audience.
Put your first-party data to good use.
Combined, Facebook and Google have a whopping 4.6 billion users and to enhance their users’ experience within their platforms they use algorithms that determine the best ads to show audiences. Through the use of relevance scores, they determine whether or not the ads in question match audience preferences.
As we previously discussed, when it comes to data, quality is essential, and first-party data is clearly higher quality data because it comes directly from the source—your customers. Using a customer list will directly impact your relevance score, which is a rating from 1-10 that estimates how well your target audience responds to your ad.
Both platforms’ revant scores work similarly and have the same score range (1-10). A relevant score 1, for example, is low. In contrast, ads with scores of 10 are very relevant. And when your ad relevance score is high, it's more likely to be shown to your target audience. So ensuring a higher relevance score is essential when creating a marketing campaign. And using a customer list can get you to that coveted score of 10 as they improve your match rate.
Using a customer list has historically been enough to see an uptick in campaign performance as it's proven to beat competitors and yield good responses. Still, there are also other ways to improve a relevance score and make your customer lists even better. Segmenting your customer list, for example, into value-based lists that are continuously updated will seriously strengthen an ad campaign, and DataQ can help you accomplish this!
DataQ + First-Party Data + Ad Platforms
At DataQ, we understand the importance of first-party data, but we also understand that you might need help strengthening your customer list quality in order to more fully harness the potential power of all your first-party data. We can help any marketer take advantage of their data-wells through a suite of segmenting tools and pre-populated value-based audience templates.
DataQ can now be your secret to marketing success. With our one-click integrations, you can connect your online store to our platform and improve relevance scores with our value-based audience templates, which include:
- High-Value: customers that have a lifetime value that’s higher than your storefront average.
- Win Back: customers that have purchased once in the past year, but have not placed an order in the last 90 days.
- Big Spenders: customers who have an average order value (AOV) higher than your storefront average.
- Holiday-based templates for all major U.S. holidays.
These samples of the customer subsets that DataQ can help you identify and target on Facebook and Google to help you improve your match rates and leverage its database with your customer information.
Tie it All Together
Paid media has come a long way, improving consumer experiences with each new medium and channel. Just as important, advertisers have also made significant strides in identifying surfacing trends, learning new skills and acquiring new tools to improve campaigns, and predicting future trends and developments, as demonstrated by the E-consultancy Digital Trends Report that stated two notable points:
- The importance of harnessing first-party data in order to create more effective audience segments.
- Getting a holistic view of your customer base to better understand your audience and their needs.
Taking inventory and continuously assessing the things that work will undoubtedly keep you on the right track. But just like in any other sector, complacency is a recipe for disaster, and here at DataQ, we want you to redefine your 1:1 advertising experience by helping you exploit all the databases at your disposal.
So sign up for a free 14-day trial today and integrate your online store and data platforms to leverage the power of the two and target like never before.