This article first appeared on the Content Strategist.   Cookies have played a crucial role in content marketing, having been accepted as a standard method of tracking user behavior and obtaining information about targeted demographics. However, as technology advances, cookies are becoming less reliable. Known more technically as an “HTTP cookie,” a cookie is a small text file sent from a website and stored in a user’s web browser. Each subsequent time the user loads the website, the browser sends the cookie back to the web server to update the website with the user’s previous activity. While this has been the conventional way of tracking readers, given today’s mobile world, cookies are becoming outdated, and their limitations have prompted the rise of alternative solutions. shutterstock_120176053  

That’s How the Cookie Crumbles

B2B marketing teams often use cookies to track reader behavior and measure lead generation, and B2C brands may use cookies to track conversion rates, which could help their search retargeting efforts or contribute to user-specific demographic data. They can do this through services such as Marketo, which can help track content ROI. As explained on Quora, Marketo uses a cookie to track the reader’s browsing habits. However, publishers would be wise to start moving away from using cookies for a variety of reasons—the main one being advancing technology. In an article on Ad Age, Facebook’s VP of Ads Product Marketing and Atlas Brian Boland explains how he looked at 500 million cookies during a six-week window in November and December: “Over the six-week period, half of the people reached by an Atlas campaign were reached on more than one device.” Most users access the internet from myriad devices, which means that brands and advertisers are tracking users through seperate, disconnected cookies. This makes cookie-based tracking much less complete and reliable than it was just a few years ago. Moreover, the growing use of ad-blocking software makes it more difficult for brands to acquire new readers through advertising. Not only are they unable to track visitor data using cookies, but they also can’t display relevant advertisements. Cimino notes that the ratio of machines connected to the Internet to the number of machines that can be cookied has been dropping; it currently stands at around 50 percent. For example, privacy concerns over excessive storage of information has spawned movements like the Do-Not-Track technology and policy proposal, which enables users to opt out of tracking by websites they do not visit. If advertisers are forced by public opinion to honor Do-Not-Track requests, and as the number of users on ad-blocking software reaches critical mass, content distribution will suffer.  

Fortunately, several alternatives to cookies are currently available, and others are still being developed. The most significant amongst these are Known identifiers, Stable identifiers, and Statistical IDs. Let’s explore these three solutions further:  

Known Identifiers

Known identifiers are typically associated with some form of personal information, such as a name or email address. They are highly accurate forms of identification because the information stays consistent across multiple devices. Whereas cookies fail to inform websites accurately because they don’t link across devices, Known Identifiers create this connection. In the future, social networks such as Facebook or Twitter could open up their data to help publishers connect readers to their profile information.  

Stable Identifiers

Stable identifiers are usually associated with a particular device or browser, which means they don’t expire. They are anonymous and provide the option for users to opt out of being tracked. One example of a stable identifier is Apple’s IFA (or IDFA), which stands for “identifier for advertisers.” This identifier appears as a random, anonymous number that is assigned to a user and their device. It does not track 5h4 user personally, but rather provides aggregate audience data that advertisers can use to target consumers with ads. “IFA will allow advertisers to track the user all the way to ‘conversion’— which for most advertisers consists of an app download,” writes Jim Edwards in Entrepreneur magazine. “Previously, advertisers had no idea whether their ads actually drove people to download apps or buy things. Now IFA will tell them.” Similarly, Google created the AdID program that connects between Chrome and Android devices. AdID is still in development and will be accessible to advertisers and ad networks that agree to a basic set of guidelines. Since Chrome is the most-used browser, and Google is a crucial figure in the advertising landscape (earning 41% of digital advertising revenue), Google is in a particularly powerful position to make this change.  

Statistical IDs

Statistical IDs, also known as cross-device tracking, allow for a device to be tied to a likely single user through a device attribute. Typical device attributes include device type, operating system, user-agent, fonts, and IP addresses. An advantage of this method is these attributes can be updated over time to match device changes or technology advances. Startups like Tapad have built complex algorithms that match the location of the personal computer (determined by its IP address) and the location of the other devices (e.g., phone or tablet), which advertisers can see when people share their locations with apps. If marketers can observe enough of one user’s devices in the same place at the same time, they can make a reasonable guess that the devices belong to the same person.  

Closing Thoughts

As the cookie meets its demise, solutions like Known identifiers, Stable identifiers, and Statistical IDs are vying to become the new standards for helping brands track customer information. Brand publishers, take note. These solutions will be the key to gaining customer insights and elevating your publishing efforts.   Featured image from ShutterStock.