Disappearing Data? Don't Fear The Death of Third Party Cookies

Data ownership is no longer a competitive advantage–it's now a mandatory part of surviving as an online business. eCommerce success depends on customer-driven analytics, but with 3rd party cookies going away, personal data collection has changed overnight. Here’s everything you need to know to protect your data access before it's too late.

You may have been hearing a lot of buzz lately in the advertising world surrounding user tracking and the death of third party cookies due to privacy issues. 

Personal information collection is a tactic that has been used for many years to allow advertisers and other stakeholders to glean information about users that help them personalize their targeting and offers to consumers. 

However, with the rise in concerns about data sharing between these stakeholders and if consumer privacy is actually being respected in that exchange (Facebook, we’re looking at you), new policies and updates are rapidly changing the fabric that makes up the current landscape of digital data collection. 

A data privacy timeline

Personal Data Privacy Timeline | Tadpull

April 2016 - General Data Protection Regulation (GDPR), a statute in EU law, is passed

September 2017 - Safari creates Intelligent Tracking Prevention, creating the first avenues to blocking third-party cookies on their platform

January 2018 - California Consumer Privacy Act is enacted. CCPA and cookie consent begin to gain traction in the clickstream

September 2019 - Firefox begins blocking third party cookies

January 2020 - Google joins Safari and Firefox in announcing they will phase out third-party cookies, offers Google FLoC as a potential replacement

June 2020 - Apple introduces iOS 14 updates, including App Tracking Transparency that requires apps to get permission to collect user data instead of automatically opting them in

Spring 2021 - iOS 14.5 (the update with user tracking changes) set to be released

These developments have important implications for businesses who rely on Facebook, Google, Instagram, or other third parties for data on their customers’ behavior and/or advertising campaign performance. In fact, the data collection update included in iOS 14.5 will likely cause the most monumental industry shift in the past 20 years of online activity.

TLDR: Anyone who advertises on Facebook is going to be cut off from seeing important metrics that their eCommerce marketing team relies on.


So how do all these changes actually work, and what can be done to safeguard against losing this vital customer data? How can consumer privacy be respected while business visibility remains, especially in the quickly growing world of eCommerce? 

Cue first-party data: a new marketing data pipeline that is not only safe from all these regulations, but is also more powerful than any existing third party data sources (Facebook, Google, etc.). Read on to discover everything you need to know about what these updates mean for your business, the obstacles they create for finding the right customers at the right time, and how you can avoid the ensuing chaos and frustration with a first party data-driven strategy.


First party vs. Third party cookies

How does personal information collection work?

Advertisers rely heavily on the data that is collected by various sources on what users visit certain websites and what their onsite behavior is (did they look at specific products, did they add anything to their cart, did they click around to more than 3 pages, etc.).

This information is then fed back into their ad engines and/or reporting metrics for the business that wants to advertise, and traditionally has fueled personalization for better targeted ads. You may have heard of a cookie before, but very few people understand what purpose cookies actually serve. 

A cookie, in its most basic sense, is a small text file that is stored on your computer with an ID assigned specifically to your device when you visit a page. Think of it as a crumb that you leave behind when you browse a website. 

These cookies keep track of your movements and store that information so that the website server that assigned the cookie to you can access that information again if you revisit the site. An example of this is when you revisit a website and it already has your username and password saved for you to login. 

While your personal information isn’t stored by the cookie, it can still recognize your movements by remembering the ID that was associated with your first interaction. Each time a browser recognizes a cookie from your device, it can store more and more information about your online activity. 

The ability to recognize and catalog a complete stranger’s online movements sounds scary, but isn’t inherently bad–especially if the only cookie that is tracking you is stored directly on the desired website you are perusing.

However, privacy issues arise when third party cookies are involved–these trackers can share your browsing behavior with just about anyone if they are placed strategically. For example, an advertiser might be able to store information about users who visit any website where their display or banner ads are placed through a third party tracking mechanism.

Why is privacy important?

Let’s use another example. Say you hop online one day to look at a pair of sneakers you’re thinking of buying from Nike. You might have used Google Chrome to get to the Nike online store or perhaps the Nike app on your iPhone. Most likely, Nike will automatically store a first party cookie for you based on your browsing session, or might even have one on file already if you’ve previously looked at their site.

However, at the same time, third party cookies coming from advertisers on Chrome or the Nike app would also be able to pick up your trail and log your activity for future advertising purposes. Companies like Google and Apple previously were able to share that data with more advertisers, like Facebook or TikTok–and magically a few days later you get an ad on Instagram for the exact same pair of sneakers that you have waiting in your cart in the Nike app. 

Here’s where the privacy issue comes in. The ad that pops up a few days later isn’t from Nike–it came from ASOS, trying to sell you the Nike products they have on their website. Naturally, people started to question why those companies should be allowed to tap into data collected from your behavior on a competitor’s website and use it to deliver you ads that are super personalized. Well, ASOS actually is no more than the meager messenger in the middle of Big Tech’s web–the red privacy flags are mostly due to major advertising platforms like Google, Apple, and Facebook.

This is the root of why third party cookies are becoming obsolete. Sharing data across that many platforms and users creates loopholes, raises ethicality concerns, and requires massive security infrastructure. Plus, there’s always the possibility that a cyberattacker hijacks third party cookie data and is able to obtain sensitive details about you, such as personal information or payment information that might be stored in cookies.

The death of third party cookies

iPhone data sharing will be blocked following iOS 14 updates

The rollout of iOS 14.5 and its removal of automatic opt-ins for data collection signals the final blow to the dynasty of the third party cookie.

In the latest iPhone/iPad update, Apple will now require apps to ask users if they consent to being tracked with cookies that might be shared across other websites or with other companies. In the past, your iPhone or iPad would automatically share that information anyways. Apple’s statement about the change gets straight to the heart of it: 

“App Tracking Transparency will require apps to get the user’s permission before tracking their data across apps or websites owned by other companies.”

But Apple is actually pretty late to the bandwagon in terms of phasing out third party data sharing. Most websites already are required to ask permission to track users on their site at all, known as the concept of cookie consent (or those annoying little bars that pop up at the bottom of your screen while you’re on a website and glaringly ask you to click ‘yes, track me, please!’). 

Following this pattern, as of January 2020, Chrome, Safari, and Firefox all block third party cookies by default. Google has slowly rolled pieces into place for what is their working solution to the issue of personalized advertising without third party data, which they call the Federated Learning of Cohorts or FLoC.

Essentially, instead of using a cookie to track movements by an individual and share their specific individual data points with advertisers, Google is relying on their own first-party data to track behavioral patterns and consistencies in members of the online population. They have then aggregated those clumps of similar-behaving people into more general, anonymized cohorts for advertisers to target their messaging towards. 

They’ve been seeing good results thus far, too: their first tests came back with about 95% of the conversions per dollar spent (aka ROAS) compared the old method of cookie-based advertising.

But wait, we need to back up for a second. Google is relying on their what to track behavioral patterns? They’re using their own first-party database that is securely gathered end-to-end. But what does that mean? Let’s dive further into what first party data really means.

What is first party data?

First party data, also known as a 1:1 dataset, is the answer to personal information collection in a digital world that is rapidly becoming more exclusive with behavioral tracking metrics. Any company can install a tracker, kind of like Facebook’s Pixel or LinkedIn’s Insight Tag, directly on their website that will start collecting data about the users that visit the site. That information never leaves the hands of the company that owns the domain, so it is invariably more secure than a third party tracker.

First party data allows companies to directly understand and interact with their customers as their website visitors interact with their business online. With the disappearance of third party personalization from popular advertisers, it is now more important than ever to be building a 1:1 dataset so you can continue to personalize your offerings to target audiences without sacrificing their privacy in the process. 

Let’s walk through a few of the ways this data can be used to improve marketing efficiency, help eCommerce companies scale with confidence, and lay the foundation for direct relationships with customers in order to foster a stronger sense of loyalty in an online environment.


Why is data ownership important?

Multi-channel attribution

The typical online shopper takes a long and complicated journey to purchase that involves many touchpoints as they bounce between multiple digital channels, almost like a pinball. This ‘messy middle’ of the customer journey leaves behind a complicated web to unravel when attempting to understand the motivating factors behind their final decision to buy.

Without an owned dataset that allows for customer behavior analysis, it will very soon be impossible to cross-check your email list and Facebook ad reports with Google Analytics to know which campaigns are converting the best, let alone break those results down by cohort to know what users convert higher on one channel versus another. So what does the future of knowing how to measure marketing campaign results look like?

With an owned 1:1 dataset, you hold all of that personal data on your customers already, so while everyone else flounders in the next few months to attribute their marketing campaigns to direct online activity, you could be able to easily paint a picture of a customer’s entire path to purchase from start to finish. Aggregate these insights from lots of your customers and you could easily know which channels deserve more of your attention and/or marketing budget.

Tadpull’s software Pond is a unique solution to the need for data unification and sharing in a world increasingly populated by information and data silos. The ability to connect all of your disparate data sources from each channel (Klaviyo, MailChimp, Google, Facebook, LinkedIn, etc.) is already incredibly valuable and even more important now that third-party data sharing is coming to an end.

However, Pond not only unifies and organizes all your data inputs, but it can also measure the success of each channel against specific website sessions and cross-analyze it with order information from Shopify, BigCommerce, WooCommerce, etc. It’s a customer data platform built to be the one place to run eCommerce off of first party analytics. If you’d like to learn more about Pond, you can check it out here.

Customer behavior analytics

Understanding how your customers move through the conversion funnel until they finally reach your site and potentially turn into a sale is one valuable aspect of owning your data, but the next step in understanding your customers and anticipating their needs is knowing how they interact with your store itself.

Google Analytics has some of this functionality already–you can see how many users are visiting your site, how many bounce, how many add an item to their cart but then abandon it, etc. However, while knowing these aggregate numbers might give you a necessary edge piece in the puzzle of customer behavior, it is simply unable to reveal the entire picture.

A customer data platform (CDP) that uses first party audience data can not only track far more refined characteristics about users’ onsite activity, but powerful CDPs like Pond can also integrate your inventory data with customer pathways so you can see exactly which products are converting the worst/best, which customer cohorts have the highest rate of cart abandonment, what pages and/or products tend to draw new users’ attention most, and so on.

The possibilities for customer insights are endless, especially with a platform that pulls meaningful discoveries from that information and sends it to you automatically… so you can avoid having to search never-ending pivot tables or spreadsheets of monotonous numbers for patterns that could possibly be hiding a kernel of an insight, let alone anything actionable.

Owning those rows is one thing, but the fastest and most profitable method for turning customer data into marketing insight takes things a step further by using machine learning to comb your behavioral data to tell you what actually matters.

ROAS and customer profitability analysis

Because Facebook and other advertisers will no longer have full access to information about users’ onsite behavior, attributing conversion rates beyond CTR to your paid ads is soon going to be near obsolete. That means you can say goodbye to the nifty little ROAS calculation in your Facebook reports, among many other reporting tools. If you are interested in prepping your Facebook Ad Account for these changes anyways, we put together a quick checklist for you here.

Knowing how much you’re spending on ads and what return on your budget they are delivering is an incredibly important metric in the scope of scaling an eCommerce business. If you want to preserve your access to this ROAS calculation, you really have no other option than to start collecting 1:1 data.

By using UTM link tagging in your ads, you can track converting sessions right down to the specific campaign, adset, or even creative that results in a dollar value to your business. Otherwise, you’ll be throwing money into the dark without knowing which campaigns might be giving you the highest profit margins that you should be optimizing for.

But ROAS isn’t the only measure of profitability that 1st party data can help with. If you have enough information on your customers and their spending habits, you can begin to do customer profitability analysis and determine the average lifetime value of your customer segments to determine which are more valuable for your business. There are an abundance of ways that CLV analysis can help you make more informed business decisions and reduce customer churn. We go more into detail on LTV models and methods in this blog if you’re interested in learning more.


How to own your own data

So you made it this far. Hopefully by now, you understand the intrinsic value and necessity of a first-party data strategy. But before you can start transforming your eCommerce analytics from data to decisions, you’ll need to get started by getting your user tracking system set up.

Preparing a data collection warehouse

Unless you’re an expert at Google Tag Manager, coding, or database management, you’ll likely want to start by seeking some external help to guide you through the complicated process of installing a tracker that can pull first party data and can provide somewhere secure to store that data for you as well.

Surprisingly, not many solution providers are equipped to help you through this stage, but at Tadpull, we pride ourselves on our wide range of knowledge and experience with first party data. We care about making sure Big Tech companies like Apple, Facebook, and Amazon aren’t the only ones with the ability to do results powered marketing at scale, and we’re prepared to equip you with the data ownership tools that are key to surviving in the future of the digital world. Trust us, you won’t want to wait any longer to hop on the 1st party data bandwagon. You can get started by dropping us a line here.

Image from: freepik

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