Ad Tech & Ad Ops

Ad Targeting: A Publisher’s Guide (with Pros And Cons)

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While shopping on an online platform, you checked out a pair of shoes. But didn’t purchase it and moved on. After a while, you saw the same pair of shoes on your social account as a sponsored ad. It’s a simple example of ad targeting that most us have experienced.

But marketers are not really interested in bombarding a visitors’ screen with multiple ads. Also, publishers do not want their visitors to be annoyed with unnecessary ads. They both want to display ads that get a valuable impression and conversion. For that, ads are needed to be placed strategically using audience targeting.

What Is Ad Targeting?

Display ads are created with intent to maximize the awareness for a brand or product. But showing same ad to everyone won’t do any good. It requires targeting and precision. Hence, display ads are now being targeted as per the visitors’ likes, thanks to technological evolution.

For that, marketers break the entire market into small segments and then work on each segment individually. Generally, targeting depends on business type. Due to which, marketers often create their own ad targeting methods. However, the basic types are:

  • Contextual targeting
  • Behavioral targeting
  • Demographic targeting
  • Technical targeting

These methods are combined to create advanced ad targeting techniques that might better suit a specific business.

Let’s start by understanding each of them:

Contextual Targeting

Visitors are targeted based on context of the website or webpage without collecting their information. The displayed ads are more or less similar to the content displayed on the web page. Contextual targeting is known by names viz. ‘in-text’ and ‘in-context’ targeting.

Suppose, you are visiting a car website and exploring through the various models. You see car insurance ads being displayed on that web page. This is a contextual ad based on the idea that people having cars might also want car insurance.

As you can see, these ads are being targeted based on the type of website and its content.

Pros:

  • Rich media ads can be placed as inventory gets valued impressions
  • Less disrupting and increases chances of getting clicks
  • Complements content, hence increases conversion
  • Collects minimal user’s information depending on the cookies policy of website
  • Publishers can sell inventories at better price using programmatic direct or private auctions

Cons:

  • Precise contextual targeting is not possible
  • Can’t be applicable on websites with broad context
  • Finding contextually relevant advertisers can be difficult for publishers

Behavioral Targeting

Here, users’ online behavioral data is collected and used to show relevant ads to them. This technique involves gathering data from a variety of sources about the potential customers’ online browsing and shopping behavior. The collected data can be:

  • Websites and pages viewed
  • Search history
  • Clicks (on ads, content, and links)
  • Purchase history
  • Frequently searched terms and visited websites
  • Previous interactions with publishers’ websites

In behavioral targeting, every visitor is considered unique. However, campaigns are designed by grouping visitors based on their similar behaviour. Most data is collected from 1st party i.e. publisher website cookies.

Pros:

  • High click through and conversion rate
  • A detailed customer profile can be created using collected data
  • Publishers have better chance to monetize their display inventory

Cons:

  • With General Data Protection Regulation (GDPR) in action, behavioral targeting might face security-related challenges
  • Some users are not comfortable with sharing their online activity
  • Ineffective when users have cookie blocking software on their device

Demographic Targeting

Demographic targeting works with a more personal aspect of the users. This method uses age, gender, location, education, languages known, educational background, etc. for ad targeting. The data is collected using cookies; almost the same as behavioral targeting.

Using this data, visitors are segmented and ads are targeted based on their demographics. For instance, if you are a woman athlete, then demographic targeting will make sure you don’t receive workout ads designed for men.

Pros:

  • Ads can be personalized as per users and get better impressions
  • Instantly grabs user attention
  • High click-through (CTRs) and conversion rates
  • A detailed customer profile can be created

Cons:

  • Raises privacy concerns
  • Not 100% accurate with users information
  • Ineffective when users have cookie blocking software on their device
  • As the information is collected using website cookies, publisher will face the consequences, in case of data leak.

Technical Targeting

Technical targeting concerns with the device type, operating system, network, and data connection of the users’ devices. The first and most important segmentation is based on device type i.e. desktop or smartphone. And then users are grouped based other technical aspects.

For example, Facebook has another application for users having slow internet connection. Using this information, Facebook shows minimal media ads that are easy to load on slow internet speed. While on the other hand, users with a good Wifi connection see rich-media advertisements.

Pros:

  • Utilizes rich media ads by showing them only where they get valuable impressions
  • Easily segments high-value customers
  • Collects minimal personal information of the users, hence avoids any privacy issues
  • Publishers can take benefit from technical targeting by optimizing their website for users with low network connections.

Cons:

  • Not effective for all business models
  • Only deals with the technical aspect of the user demographics
  • Impressions and click rates are unpredictable

Privacy Concern

Targeting in marketing is often associated with privacy concern. Many users are not comfortable with sharing personal information. But, to access the content, they are forced to accept cookies which is later used to extract their online behavior.

Publishers assures that the data collected by them are going to be stored with safety. However, we see numerous data leak cases, every year. Meaning, data fraud exists. And no matter what security measure is used, fraudsters will find their way in and cause harm to system.

But from publishers’ and marketers’ point of view, it is important to target users to uplift the revenue. The dilemma is real. However, for now, audience targeting is the best and most fruitful method in the ad industry.

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