Back by popular demand! This week, we’re taking a deeper dive into the world of third-party cookies, and adapting to a world without them.

Solving that cookie conundrum

With third-party cookies meeting their demise, here’s a more detailed look at solutions to thrive without them.

Clint Bauer

Technology

Technology

5 minute read

What impact will the demise of third-party cookies have on brands?
Brands that are reliant on third-party cookies have less than a year to plan for a future without them. Earlier this year, Google announced plans to kill third-party cookies in Chrome by 2022 – and with Chrome’s 64.47% market share across devices1, Google’s decision is the final nail in the coffin for third-party cookies. This move, regardless of Google’s intentions (and combined with Apple and Firefox’s third-party blocking, which they’ve been doing for a while now), has firmly opened the doors for the next wave of innovation in digital advertising.

Brands need to look at this fundamental shift as a massive opportunity to formulate a future-orientated CX and data strategy that delivers new and innovative ways to genuinely connect, establish trust and foster a deeper understanding of their customers.

Brands will be forced to change how they approach online advertising. It will necessitate the creation of an owned, scalable, privacy-compliant ecosystem for how they progressively capture, store and use their own zero and first-party data combined with second-party data. And, if appropriate, how they leverage proposed alternatives to third-party cookies, like Project Rearc, Google’s Privacy Sandbox and other universal identity solutions.

But a word of caution: Media agencies and technology vendors that have been overly reliant on third-party cookies for targeting and performance tracking will now undoubtedly be touting their newly developed methods and solutions to solve for the impending changes. It’s in a brand’s self-interest to sense check and have a healthy scepticism in this regard. Brands need to arm themselves with a thorough knowledge of all pertinent regulations and compliance requirements, plus a comprehensive understanding of available methods, techniques and software solutions, to objectively evaluate and decide on a way forward.

Additionally, when assessing future advertising and campaign activity, it’s crucial that brands insist on total transparency with how cohorts or audiences are being generated, targeted and reached.
First, second and third-party – what's the difference?
Cookies are generally based on who created them. If you're still not sure about the difference, here's a quick breakdown:

First-party cookies
are created and placed directly on the customer’s device by the website they are interacting with. Website owners use first-party cookies to preserve login status, save communication and content preferences, collect analytics data, and provide a seamless user experience. Brands often don’t fully utilise the enormous potential in first-party data and should make this a core component of their data strategy moving forward.

Third-party cookies are created and placed by a company other than the one that owns the website the customer is visiting – hence the name ‘third party’. These cookies are used for behavioural targeting, cross-device and cross-site tracking, and retargeting. As of 2022, no major browser will support this type of tracking technique.

Second-party cookies technically don’t exist but rather come into existence when a company transfers its own first-party cookie data to another company, usually via a data exchange or a direct data partnership.

In addition to the above specific cookie classifications, which all ladder up into their broader first, second and third-party data categories, there is also the relatively new concept of zero-party data.

Zero-party data could technically be classified as a subset of first-party data. However, as this is specific information that a customer proactively, intentionally and freely shares with a brand, it’s now attracted its own label. While first-party data is rich with behavioural data and implied interest, zero-party data provides an extremely valuable and accurate insight into explicit interests and preferences. Brands own their own first-party data, but do not own zero-party data. This ownership remains with the customer. Instead, customers permit a brand the right to use their zero-party data for a specific purpose or value exchange. This consent should be respected in the context that it was given, and its use restricted as such.
What will the future solution look like without third-party cookies?
Some companies are trying methods such as Universal IDs and digital fingerprinting. However, obtaining the user’s consent moving forward is mandatory, and such methods only serve to magnify the customer’s distrust rather than deepen connections. To date, there is no consensus on what the new method/s and replacement technologies will be.

In our opinion, the answer isn’t as simple as developing new methods that perpetuate the same intrusive tracking behaviour – we need a genuine step change. It’s time for brands to curate and take control of their zero and first-party data and work together with customers to create a powerful experience ecosystem that delivers a more valuable, contextually-sensitive, coherent and consent-driven brand experience.

This should be governed by three main tenants:

  • providing greater control for users;

  • ensuring greater transparency; and

  • respecting privacy, consent and anonymity.
So, what should brands do to adjust to the new reality?

Firstly, keep calm and cookie on. As we mentioned, we see this as a huge opportunity for forward-thinking brands to broaden and deepen their relationships with customers.

We recommend that brands focus on the following core initiatives:

 

  1. Get the basics right. Build customer relationships by developing a consent-driven CRM database – this allows brands to collect and master their zero and first-party customer data.

  2. Continue to use existing closed media ecosystems (walled gardens) like Google and Facebook, and form direct partnerships with publishers and retailers, like Amazon, to access their first-party data (second-party data to the brand).

  3. Make use of tried-and-tested methods like contextual targeting, which will continue to reach consumers at key moments of research and inspiration.

  4. Use predictive analytics and machine learning to fill in the missing blanks.

  5. Look at in-housing of core data and media functions.

A breakdown of our five key recommendations:
1. Mastering the basics and first-party data
Brands need to keep up with their customers by creating and maintaining a high-quality and high-performance CRM database. This will form the foundation on which everything else is built. A CRM database excels at collecting, governing, transforming, and sharing customer information – its power lies in curating and using the right data from a trustworthy source (zero and first-party data) to communicate the right message to the customer at the right time.

Customer trust is one of the most powerful brand assets that a company can own, and investing in and effectively managing customer consent is increasingly important. This ensures brands are able to get more value out of their zero and first-party customer data while respecting the privacy and preferences of customers.

However, the challenges of understanding and connecting customer data across multiple channels and touchpoints can still be an obstacle. Brands will need to consider investing in a customer data platform that can provide a full view of the customer across marketing, product, customer service, sales and other touchpoints.

In leveraging these data tools, combined with zero and first-party data and other consent-driven customer identifiers, you can innovate and constantly improve your customer experience. This creates a true and reciprocal value exchange, which is the foundation of a long-term, trusted customer relationship.
2. Closed media ecosystems (walled gardens) and direct content partnerships
Closed media ecosystems or ‘walled gardens’ are proprietary publishing platforms where the owner controls the publishing of and access to applications, content and media within its environment. Examples of these closed ecosystems are Google and Facebook. Amazon, with the release of their advertising division, is now also a player in this space and has something extra that Google and Facebook don’t – purchase data. Combining this with its treasure trove of first-party data creates a clear differentiator for Amazon.

Many brands are not taking full advantage of the capabilities that these ecosystems can provide – an added benefit being that these ecosystems will not be as impacted by the move away from third-party cookies as the rest of the programmatic landscape.

However, walled gardens are not the solution by any means. They’re essentially a black hole, as they don’t allow brands to take any data back into their own business. This means that if you serve an ad via a walled garden and want to follow up with your prospect on another channel, you won’t be able to do that in a data-driven way.

There are certainly times when it’s perfectly fine to leverage the rich data already available in walled garden platforms to achieve maximum reach. However, for brands that want to make individual, personalised connections, the best approach is use the power of your own zero and first-party data as signals to orchestrate journeys in real time across channels, rather than relying on the data contained within the walled garden.

For brands with large customer databases, availing themselves of the opportunity to use their own first-party data and match that against the rich data sets owned by publishers is a prudent, effective technique – especially in a constantly changing market landscape with a looming scarcity of quality audience intelligence.
3. Contextual targeting and AI
With cookie-driven behavioural analysis being phased out as a targeting methodology, there’s a renewed interest in and appreciation of the power of contextual targeting and its ability to produce highly effective results by placing relevant, compelling content and other digital assets in-situ during a customer’s online journey.

Contextual targeting takes the keywords and content of the visited webpage into consideration to display relevant content, assets and ads, instead of relying on a user’s behavioural attributes, cookies or other identifiers. The ads are placed on web pages depending on the content of those pages, rather than being reliant on third-party data about the consumer’s online behaviour.

The approach to contextual targeting has been given a turbo boost with the broad adoption and use of AI and its subsets of machine and deep learning. This innovative approach to contextual targeting can now leverage advanced AI analysis and recognition services to analyse image, video and text content on a site to create contextual targeting audiences. These are then matched to advertiser requirements, ensuring that the appropriate advertising content appears in the relevant and appropriate location.

Contextual targeting has several clear advantages: it’s not reliant on third-party cookies, it mitigates the privacy and governance risk brands now face, and it improves ROI on advertising spend.

Contextual targeting provides brands’ marketers with a clear path forward to form genuine consumer connections, allowing them to communicate at scale in a meaningful way, in the right place and at the right time.
4. Predictive analytics and machine learning to help fill in the blanks
Predictive analytics is fast becoming a critical component of data-driven marketing and is gaining momentum as the scale and breadth of data we capture is increasing exponentially. Not only can predictive analytics consolidate and simplify data, it makes data useful and valuable by producing insights you can use to acquire and retain customers and maximise profits.

As third-party cookies are phased out, it’s anticipated that data sparsity will become the new norm, and we’ll be more reliant on machine learning to fill in the data gaps that inhibit intelligent marketing activities. However, with a proper data strategy, predictive techniques, and machine learning technologies, marketers can start to fill in these data gaps and use AI-derived insights to make the marketing landscape more vivid and readable.

An example of this is found in the latest release of Google Analytics (GA4), which has machine learning at its core to automatically surface helpful insights and close gaps left by industry changes to cookies and identifiers – thereby providing marketers with a more complete view of customers across devices and platforms.
5. In-housing
Traditionally, most brands have outsourced their performance media (including content, analytics and technology) to external media agencies and technology vendors. A sizeable proportion of these suppliers have a reputation for not providing full visibility and transparency into marketing practices, data collection methods, performance metrics and analytics, and are classified as a ‘black box’. Changing privacy and governance regulations now present brands with an opportunity to form a direct relationship with their customers, creating a deeper level of trust and stronger, consent-driven relationships moving forward.

The new accountability and importance placed on curating, managing and consensually using zero and first-party data, coupled with the ever-changing technology and media landscape, requires companies to invest in their own subject matter experts. To be effective, brands should consider in-housing core data, governance and media functions such as customer analytics, media strategy and buying. This can be accomplished in a variety of ways, from hiring full-time employees, to partnering with other companies who work with an agile in-housing model to provide these core functions on-premises. This ensures the ongoing development and consolidation of your brand’s data and intellectual property, removing the overt reliance on totally outsourcing these critical services.

In conclusion, a massive opportunity now exists for brands to create a privacy-centric, compliant, scalable and future-proof data solution that allows marketers to build out audiences and use their own zero and first-party data and identifiers across channels and platforms. In addition to the above, marketers should embrace other targeting methods, like contextual advertising and using direct partnerships and closed media ecosystems, to enhance their marketing activity.

We also advise that brands, as far as possible, remain technology agnostic and wait until the dust settles on who and what will be the next best ad tech and targeting method for use in advertising.
References
Statcounter, Browser Market Share Worldwide (April 2021) GlobalStats.
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