Third-party cookies are going away. The loss will mean marketers and advertisers will need to find creative solutions to target and connect with their audiences. At the same time, new technology for unlocking the value of first-party data now offers a powerful alternative to third-party cookie-based marketing that can give brands more control of their customer retention and acquisition.
So what does this look like in practice?
In this article, you’ll learn:
- The four major trends to guide your strategy
- A deeper look at how to make the most of first-party data to strengthen your position
- Recommendations for what to get started on today
Content Summary
How might the landscape change when third-party cookies are gone?
Moving toward more efficient retention & acquisition
Use all your firstparty data — including anonymous customer data.
Building a test & learn infrastructure
Your action plan
Third-party cookies are going away.
But you probably already knew that. The question is, how to adapt?
Quick definition: third-party cookies are tracking files stored on a web visitor’s browser, generated by a website other than your own (hence, third-party). They’re often managed by advertising providers that service a vast array of sites, making it possible for marketers to reach people with custom ads anywhere they go online.
Citing concerns about consumer privacy, the most popular web browsers have been phasing out the use of third-party cookies — first Safari and Firefox, and soon Chrome, where they will no longer work starting in 2022.
In a world with no third-party cookies, there are two big challenges for marketers who have relied on them until now:
Targeting gets trickier
Losing the ability to target means that ads are less effective, leading to challenges in driving revenue.
Measurement gets messier
Losing the ability to measure how people interact with ads across sites makes it hard to know how to allocate marketing dollars and complicates justifying ad spend. If you think measurement is hard today, it will be even tougher with no thirdparty cookies.
How might the landscape change when third-party cookies are gone?
Losing third-party cookies makes it harder to advertise on the open web. It has less of an effect on advertising in walled gardens — ecosystems that require a log-in, like Facebook or Google, which don’t need third-party cookies within their environments to enable targeting and measurement. These environments will, however, be more reliant on the data that you provide them, since they won’t have cookie data from outside their walls to supplement.
And what about on the rest of the internet, all the publishers and content sites that marketers also use to advertise? That’s a nontrivial amount of potential audience, as much as 35% of the money spent on digital advertising.
Continuing to make the most of your opportunities to reach your audience follows four key themes:
- First-Party Reigns: Your first party data will inform everything you do, so making sure it’s robust, reliable, and accessible is a bit like taking command of your own destiny. Increasing collection and use of firstparty identity and data will help provide the best personalized experiences across your own channels, and it will also improve the effectiveness of partnering with other channels and networks.
- Quality Matters: High quality PII (personally identifiable information) continues to be important — data like current and former names, email, home address, phone number, birthdate, etc. The more PII you have and the more accurate it is, the better you’ll be able to engage with the right person on your owned channels and the higher the match rate when working with targeters and ad networks.
- Privacy-Compliant Data Sharing: Developing and deepening direct relationships with advertising and marketing partners, including other brands, helps to extend reach, targetability, and measurement and increase options within channels outside your own.
- More Experimentation: By developing the process and infrastructure to test and measure new types of campaigns on both existing and new channels, brands will be able to fill in gaps from the departure of the third-party cookie and strengthen themselves for the future. New channels to experiment with include connected TV, emerging platforms like TikTok, and contextual targeting.
Moving toward more efficient retention & acquisition
Fewer options for targeting and reaching the right audiences means that brands will have to re-evaluate their approach to both retention and acquisition. But this actually presents an opportunity to move toward a healthier and more profitable model.
More effectively engaging and retaining your existing customers via your owned channels allows you to break free from reacquiring your own customers via paid channels that are getting more expensive — and, with the third-party cookie going away, less effective.
Instead, you could be using your first-party data to drive engagement and retention within your owned channels, and also use it to more efficiently acquire new customers via paid channels.
By structuring your customer experience to collect the highest quality, richest data about your customers, you can better learn about the behaviors, interests, and preferences of your most valuable customers. This first-party data is also the foundation in ensuring the efficacy of the predictive models you have running.
The combination of historical and predictive insights helps you communicate better with your customers, leading to increases in engagement, spend, customer satisfaction, retention, and loyalty to your brand, driving up the return on the investment you made to acquire those customers in the first place.
For acquiring new customers, that rich first party data provides better seed audiences for lookalike targeting in paid channels. Rather than just sending a broad segment of your most valuable customers as seed data to a paid channel, you can divide it up into more granular sub-segments of your most valuable customers (e.g. product category preference, personas, demographics etc), thereby increasing the likelihood that your ads are finding receptive audiences.
To make the most of your first-party customer data, you need to be able to pull together the relevant data from all the disparate sources (including second and third party sources) in a cost-effective way and assemble it into a Customer 360 database that lets you put the data into action.
Contextual marketing requires knowing your customers well
With third-party cookies going away, interest in contextual advertising will grow. However, identifying the types of content, sites, and apps where you’re most likely find your new customers requires you to first understand your existing customers deeply, and then use that insight to extrapolate to where you will likely find your future customers.
Say your brand sells running shoes. Without third-party cookies to help target ads, it might make sense to advertise on running-related sites and other places runners might browse online. But that limits your options a fair bit, given that you used to be able to advertise to runners anywhere on the internet.
Luckily, there are contextual signals within the data — the type of shoes they buy, how frequently, what accessories they browse, etc. These might suggest to you if they’re a marathoner, or if they like trail running, or if they have knee problems. By mining the transactions and engagements in your first-party data to create rich, detailed profiles on your top customers that include things like product affinities, demographics, psychographics, and other interests, you can find similar audiences across a variety of walled gardens and publishers, without having to rely on opaque cookies or third-party data sets.
Use all your firstparty data — including anonymous customer data.
Anonymous data is your largest first-party data set. Don’t let it go to waste.
Brands typically collect data on anonymous users by dropping a first-party cookie on them as they browse the company site, but then anonymous data from that cookie stays in a web analytics system rather than being incorporated into a Customer 360 database along with known customers.
A better practice is to build on the anonymous records. Instead of letting anonymous data sit in silos, bringing it into the overall customer database means you can augment the profiles as customers interact further, engaging throughout the lifecycle of a profile from anonymous to partiallyknown to fully-known.
This involves using a multi-source graph that incorporates ID, PII, and device data and helps to manage data source, usage rights, permissioning, and opt-ins. It results in expanding your marketable base of known customers, so you can connect with more people and give them the great experiences that will keep them coming back to your brand.
First-party PII continues to be the critical link
The digital advertising ecosystem evolved with third-party cookies, so there’s no way to avoid some change when they go away. You’ll still be using a mix of owned channels and paid channels, and you’ll still be sending data to walled gardens to match audiences, but there will be shifts in how it all fits together.
Exactly how connections and processes will reshape after third-party cookies are no longer in use remains to be seen, but one thing won’t change: no matter how the new ecosystem develops, the input from your own system will be first-party PII. Higher quality PII will result in better match rates, making your advertising in paid channels more effective. First-party data will be used for activation, suppression, and measurement, replacing third-party tag-based measurement.
Robust first-party PII will put you in the strongest position to make the most of both existing and new channels. It’s a matter of being prepared.
Cross-brand data sharing becomes more prevalent
Partnering with other brands to pool certain elements of your customer data with theirs can help fill gaps around reach, targetability, measurement, and analytics left by the departure of third-party cookies. This involves using a special “clean room” to combine data while redacting PII and restricting access, to protect the privacy of the relationship between the brands and their respective customers.
By using a safe environment for sharing and conducting the kinds of joint analysis listed below, it’s possible to build a shared data foundation to benefit all brands involved. Along with measuring advertising performance across the brands, this shared data foundation can drive joint marketing campaigns, promote loyalty acquisition, inform the innovation of new experiences, and help work with existing and emerging walled gardens.
Building a test & learn infrastructure
The loss of a central element of the advertising ecosystem like the third-party cookie means that marketers and brands will need to expand their toolkit and try out different methods.
In practice this involves:
- New campaigns on existing channels
- New campaigns on new channels
The shift in the ecosystem could prove to be a stimulus for significant growth, if you have the right infrastructure and approach to quickly figure out what works and what doesn’t, and to double down on the methods that show promise.
This means having all your customer data at your fingertips in a Customer Data Platform (CDP) so that you can analyze behaviors and come up with new hypotheses to test. You test your hypotheses by being able to quickly pull audiences and run campaigns in the existing or new channel. Then you work with downstream measurement tools or partners to see the level of engagement and determine what leads to good experiences for customers and good results for the business.
The demise of the third-party cookie may be the motivating spark that gets you here, but building this kind of enduring test and learn infrastructure and playbook will last far beyond this shift and put you in a stronger position no matter what twists and turns the market takes.
Examples of new channels to experiment with:
- Emerging audience platforms like TikTok, Substack, Clubhouse
- Connected TV and content streaming services
- Large brands functioning as walled gardens — Walmart, Home Depot, Kroger, Target, etc.
- Collaborations with complimentary brands
Key infrastructure elements:
- Customer 360 database to make your data accessible and actionable
- Behavioral data to feed into measurement tools or partners to connect the dots and measure efficacy
Your action plan
Start preparing today for a post-third-party cookie world
Develop a first-party data strategy, including:
- First-party identity resolution
- First-party data collection
- PII hygiene processes
Ensure you have a CDP and that it can:
- Handle messy and multi-sourced PII at scale
- Adapt to market changes with a flexible data model, configurable machine learning models, and customizable data merge rules
Develop targeting and measurement strategies:
- Create strategies for current and new marketing channels in a post-third-party-cookie world where targeting and measurement are powered by firstparty data
Discuss the forecast with your ad-tech vendors:
- For example, ask what they see as the future of re-targeting and how they plan to be proactive in managing the change
Build a test and learn infrastructure and process:
- Analyze behavioral data in your Customer 360 database to develop hypotheses
- Try out new campaigns on both existing and new channels
- Adjust based on results
Studies in Preparation
The brands Amperity works with know how important it is to make the most of their first-party data so they can become more effective at retaining and engaging their customers, both through their owned channels and when advertising in the broader digital ecosystem.
Shoring up their first-party data foundations and building a Customer 360 database puts them in a stronger position to adapt once third-party cookies go away.
A travel brand uses personalized emails to bring more customers into their loyalty program, customizing based on continuously refreshed profiles showing recent trips, mileage, and dozens of attributes.
Results:
- + 47% lift in email open rate
- + 307% increase in clickthrough rate
- + 198% increase in conversion rate
A fitness retailer consolidated siloed data into a Customer 360 that lets them segment their audience and personalize messaging, driving store visits and increasing engagement.
Results:
- + 260% click-through rate in paid search
- + 128% increase in ROAS
- + 49% increase in conversion rate in paid social
- + 150% average increase in paid social engagement metrics
- + Up to 16X increase in click in email
- + 2.4X email open rate
An automative retailer built a data foundation to unlock smarter segmentation and more nuanced lifecycle marketing across all channels.
Results:
- + Open rates 220% above industry average for automotive
- + Click through rates 255% above industry average for automotive
An automative retailer uses custom attributes from a Customer 360 to segment their audience and personalize messaging to online-only shoppers, promoting store visits.
Results:
- + 227% increase in annual spend from these customers
- + 2.4x increase in annual visits from these customers