Cookieless Advertising: What It Is and How to Prepare for a Cookieless Future | IBM

By IBM Watson Advertising

What is cookieless targeting?

Cookieless targeting refers to a number of audience-targeting methods in which cookies are not used, either because they don’t work, or the use of third-party cookies is not allowed. Cookieless advertising is gaining in popularity as privacy concerns continue to increase and data regulations regarding the use of personally identifiable information (PII) roll out globally. As the advertising industry continues to evolve, we can expect marketers to use new, cookieless ways to target audiences. One such method is through contextual advertising, which can be a highly effective AI-powered form of targeting that doesn’t require cookies.

What are cookies?

Cookies are small pieces of code that are placed within your browser whenever you visit a specific website. They typically contain two pieces of information: 1) the site name and, 2) a unique user ID. Cookies may capture details such as website configuration, language preferences, login information, or any products you’ve added to your online shopping cart.

How are cookies used?

Cookies collect user data such as page clicks, viewed pages, how you interact with a website, along with PII such as device ID, name, address, passwords, and even credit card numbers. Cookies were created with the intention of providing a targeted and personalized experience to those using the internet.

By using the data collected via cookies, advertisers sought to improve their decision-making process and maximize the user experience they created for audiences. There are two different uses of cookies to know about.

First-party cookies

First-party cookies are used to understand the behavior of visitors to a website and are created by the host domain or the domain a user is visiting. They are used to create a better user experience and keep a session going. First-party cookies can remember key behavioral information like usernames, language preferences, and what items have been added to shopping carts.

Third-party cookies

Third-party cookies are the backbone of programmatic advertising and are created by domains other than the one a user is visiting. They are mainly used for tracking purposes and online advertising.

How does cookieless advertising work?

There is often confusion surrounding how cookieless advertising can work. Here are a few ways to target audiences without the use of cookies.

Authenticated targeting

Authenticated solutions* work by getting explicit consent from a user to use their data. This can appear in a pop-up or login screen when a user enters a site and views the content.

Anonymous targeting

Anonymous targeting does not require explicit consent to identify and track users. Instead, alternative methods like contextual or aggregated targeting allow advertisers to target specific audiences anonymously.

What does cookieless targeting mean for consumers?

Apple’s decision to no longer support third-party cookies* will give consumers more control over the personal data they share with companies and organizations online. Moving forward, they’ll be required to give explicit consent for data to be collected and consumers will have a better understanding of which companies capture behavioral data.

One potential downside to the loss of cookies is that personalization of a website’s experience could become less common and result in more irrelevant ads being shown. However, personalization will certainly not go away completely as advertisers continue to utilize both new and old tactics, backed by AI and machine learning, to provide users a personalized and data-safe experience.

What does cookieless targeting mean for advertisers?

As an immediate effect, most third-party audience data will diminish in size. Audience data will still be available as first-party or second-party cookie data. However, we can expect this data to be completely clean of cookie-based third-party data and be GDPR compliant*.

Moving forward, advertisers will need to rely more heavily on cookieless tactics to segment and target audiences so that they can continue to provide them a personalized experience and leverage data that helps inform future decision-making.

Over-targeting and campaign effectiveness

Advertisers will often over-target individuals, while under-spending for basic brand building which would expose new potential customers to their products. Dollars are wasted on audiences that are not converting instead of new audiences, who may be looking for a solution.

However, by focusing on other data inputs, such as context, weather, and location, advertisers can deliver better ads to new target audiences. They can also use predictive analytics to gauge how likely a new or existing prospect is to take an action. AI can fill in the gap left in a cookieless world to produce even better and more relevant ads.

Cost savings and better outcomes

In addition to the cost savings that come from not needing fraud and brand safety detection vendors, doing away with cookies also means advertisers will have a unique opportunity to undo the digital marketing habits of the last decade.  

Is it possible to target ads without cookies?

The online advertising industry* has been focusing its energy and attention primarily on cookie-based targeting. Advances in machine learning and AI have opened up a new world of opportunities for intelligent targeting, which is privacy-friendly and doesn’t require user-profiling.

One way to do this is through contextual targeting, which gives advertisers the opportunity to see and react in real-time to insights derived from live content consumption. This dynamic data can be used to target and scale campaigns just as effectively as a cookie-based targeting method.

The future of a world without cookies: How can you manage the shift toward cookieless targeting?

As the shift toward cookieless targeting occurs, advertisers will wonder what their job will look like and the tools that’ll be used to fill the gap. Here are some ways to get started.

Predictive analytics and better messaging

Many organizations have vast amounts of information at their disposal. However, most executives struggle to gain insights in a timely manner. In fact, only 23 percent of those surveyed noted that their organization was strong in this category.

By leveraging machine learning in advertising, teams can reach conclusions faster to better determine the next course of action. AI in advertising also does not need cookies to be effective in crafting messaging because it can leverage algorithms to better identify what works and what doesn’t.

Using predictive messaging enabled by AI can help you personalize your advertising in a cookieless world. Additionally, predictive analytics can help segment audiences based on what messages they will respond to and what will resonate with them most.

Hyperlocal weather targeting

Understanding the local demand patterns requires tapping into the neighborhood characteristics of a given store and other factors outside retailers’ control like current events and weather conditions. With the ever-expanding network of The Weather Company, an IBM Business, to include sensors from cell phones and other sources, your team can go beyond airport data for more localized weather insights.

Additionally, by filtering in location data, you can gain a better understanding of how clients may react to specific types of weather. Sixty degrees in Southern Florida feels different to consumers than 60 degrees after a long winter in Maine.

Conversational marketing

Seventy-one percent* of customers expect companies to communicate with them in real-time and 79 percent of companies say that live chat* has had positive results for customer loyalty, sales and revenue. This can be explored through conversational marketing, which is a method that engages consumers in dialogue-driven, personalized experiences on a one-to-one level. This enables brands to listen and gain unique customer insights while providing value to the user. Just look at these conversational marketing examples to see how companies are finding success.

Apply personalization tactics

Personalization has become increasingly important to consumers. In fact, 80 percent* of those who classify themselves as frequent shoppers say they only shop with brands who personalize their experience. Campaigns applying deep personalization through clever geo-targeting and time-parting usually generate high engagement, although not widely used in the industry.

Improve first-party data collection

Implementation of data-capturing mechanisms helps ensure robust data is available as granular input for the targeting and personalization of users who have already engaged with your brand. Starting early is key because you might need time for data to build up before you see insightful information.

Enter direct relationships with large publishers

Partnering with larger, trusted publishers who collect first-party data can be a solid kickoff strategy where you can leverage alternative data without a major investment. Publishers and reviews sites have a great deal of information about the interests of audiences that they serve based on content consumption. You can enhance measurement and planning of marketing campaigns with this data.

Use contextual advertising 

Marketers can also use contextual advertising for upper-funnel goals such as awareness. Contextual advertising focuses on the information of a page instead of tracking a user.. It helps marketers to position their ads based on the webpage content, so users with certain collective behavioral attributes visit that page. This can take advertising beyond personal targeting - creating personalized marketing and minimizing the need for consent.

Cultural marketing

Another approach to ad relevance would be matching ads to current events. This is called “cultural marketing”. Although it cannot be used as consistently as other types of marketing, it can be helpful during certain cultural moments like the Olympics. These ads link a brand to front-page news, which can be very successful.  

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Why use IBM for cookieless targeting?

At IBM, AI is the backbone of our advertising solutions because we know how powerful and effective it can be. With AI advertising, you can analyze how a person behaves in the moment on a website. You can then use these insights to better anticipate their needs and preferences moving forward and put them in front of an advertisement they have an interest in.

The loss of cookies and other PII might be the best change that could happen to modern advertising. After all, cookies and other types of third-party data are often faulty, incomplete and unreliably sourced. Advanced contextual marketing cares less about past choices your customers and prospects have made and more about what matters to them at this moment.

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