An Understanding of Data-Driven Targeted Advertising Basics & Effectiveness

 

The word “data” has been part of marketers’ lives for several years now, and you could be forgiven for thinking you’ve heard everything there is to know about it. Data-driven advertising has revolutionized digital marketing, with its ability to track users’ online activities, follow them around the media they access, and target them with ads about products and services they have previously researched.

 

The Concept of Data-Driven Digital Display Advertising

Display advertising is what digital users see practically every time they open a web browser. Unless they have an ad blocker enabled, images and video banners start showing them advertisements the moment they reach a specific page. The ads displayed are personalized for each user, based on the preferences they have shown for information on particular topics, as well as the data the marketer has available about them.

 

How Targeting Works

Data-driven ads are targeted at individual prospects. When a user visits a company’s website, it records and stores information in the form of cookies. Online advertising networks also store similar user information, and the more sources of data available, the better the targeting is.

The data is based on variables, including the user’s location and previous online behavior such as the length of time spent on websites, pages viewed and online searches. From this information, the database determines the level of interest the user has in a particular topic, and delivers ads from sellers who have paid to use the network’s resources.

Types of Data-Driven Advertising

Data can be used to drive several types of advertising available currently, including:

  • Programmatic ad buying. This is an automated method of purchasing digital media in real-time that is easily adjustable. Because of the accuracy marketers can achieve with programmatic advertising, it has gained traction in the industry to the point that more than $46 billion will be spent on it in the U.S. in 2018, according to eMarketer. That’s about $10 billion more than was spent in 2017, and 82.5% of all digital display ads will be automated.
  • Addressable TV advertising. This refers to the use of data to identify target audiences through the television programs they watch, and then cross-referencing this information with the websites they visit and the devices they use.
  • Retargeting. This is the term used when a brand employs data to follow a prospective customer as they move from one website to another, including competitors. The prospect is shown ads that remind them of what they saw on the brand’s site, regardless of whatever they are researching subsequently. Retargeting is also used to offer additional, hyper-relevant products, such as suggesting accessories like socks for a user who recently viewed running shoes.
  • Paid search. Users spend less time researching now than they did previously, because thanks to social media and the ultra-fast search engines they get results much faster. Knowing what they search for enables marketers to identify the keywords used by their target audience as well as the terms their competitors rank for. They can then use the data to develop more relevant content for clients, optimize their sites accordingly and drive more viable traffic to their websites.
  • Email marketing is a huge portion of most marketing strategies, and because it goes directly to consumers inboxes it’s imperative that communications are as personalized and relevant as possible. Delivering information based on the prospect’s specific preferences is the best way for brands to generate interest and loyalty with their audience over the long term.

The modern marketer’s mantra is to deliver the right message, to the right people, at the right time, and this is simply not possible without having sophisticated data available to inform it.

 

Where the Data Comes From, and What’s Collected

Most of the data is gathered as users browse the web. Basic data is reported to the sites they visit, such as the browser and type of device they’re using, their IP address and their entry point to the internet, which—unless a virtual private network is enabled—provides an approximate geographical location. By adding cookies to the user’s system, websites can track returning visitors.

While individual companies can only make use of their own cookies, third-party ad networks track the cookies of all their advertisers and combine this with information from other sources. Ultimately, this collection of data is analyzed to compile a profile of each user that determines where you’re from, what products they are interested in and even the methods they use to make purchases. These profiles enable advertisers to target their ads at users who are most likely to perform a particular purchasing action at a specific time.

 

Effectiveness and Benefits

With consumers becoming increasingly particular about the marketing messages they consume, the more advertising is personalized the better the results. The availability of data on which to understand their audiences and predict future behaviors enables them to optimize marketing budgets and spend their time and money where it is most effective. Benefits of this approach are:

1. Insights and Personalization

Knowing the customer is a vital aspect of any digital marketing strategy. Data gives you the demographics, location, and preferences of various audience clusters, which enables you to plan directed communications. With the right quality customer insights, marketers can segment their audiences and develop customized campaigns aimed at individual or niche groups. A 2017 study showed companies that met and exceeded their revenue goals used personalization tactics 83% of the time.

2. Targeting Accuracy and Funnel Efficiency

The more companies learn about the target audience and their behaviors, the better the business—and marketing—decisions they are able to make. Data not only tells advertisers who to market to, but also the type of information to provide and the way a product is perceived in the marketplace. The ability to identify which advertisements move buyers through the stages of the sales funnel makes it possible to differentiate segments and align campaigns with their position in the funnel.

3. Enhanced Customer Experiences

Data-driven advertising campaigns often include customer satisfaction surveys, which help companies gain an understanding of improvements required to achieve customer satisfaction. Whether these are product improvements or altered marketing methods, by applying the information to the marketing strategy companies can improve customers’ experiences from the outset.

4. Customer Retention

It’s common knowledge it costs more to attract new clients than to retain existing ones, but a company’s current customer base is only valuable if they actually continue to make purchases. Cross-selling and upselling are critical for achieving ongoing sales to existing clients, and the collection and use of data can identify customers’ preferences, lifestyles, and products they like to use. This helps to target them with items they are likely to purchase, based on previous activities.

Knowing precisely which consumers to target and how best to reach them enables advertisers to eliminate a lot of the “guesswork” from media planning and buying. Algorithms and machine learning do the work of analyzing the approach to take, and this puts advertising dollars to their best possible use.

For more information on data-driven targeted advertising and its benefits, please schedule a call with us at 215-315-7780.

 

 

About Paul Mosenson

NuSpark Marketing Founder, Chief Lead Generation Strategist and Online Media Director An experienced B2B and B2C marketer, Paul has been helping clients generate leads and grow their businesses for over 25 years. Paul helps plan and optimize marketing and lead generation programs.