Ravi Ganesh
Feb 25, 2020

The purge of the third-party cookie: 10 implications for marketers

From targeting to consolidation to measurement, Havas Group India's head of data and analytics lays out how the ad industry will be impacted by the end of cookies.

The purge of the third-party cookie: 10 implications for marketers

The phasing out of the third-party cookie by Google Chrome, changes which have already been implemented in part or full by Firefox and Safari, heralds a new era for digital advertising. Of course, we have a headroom of two years to begin with until this gets rolled out.

The root cause of these changes is increasing concerns over data privacy. Many adtech companies have flourished over the past decade not obtaining user consent for use of consumer data and attempting to monetise this data without explicit consent.

Here's 10 implications of the crumbling of the third-party cookie for marketers:

1. Digital comes full circle

From first-party data to third-party data and back to first-party data. The dawn of the digital era happened in the 2000s when there was a focus on first-party data, inbound marketing, user design and collaboration. With the advent and growth of the smartphone in the 2010s, the focus of marketing efforts shifted to outbound marketing using third-party cookie data. The 2020s will see a re-shift in focus from third-party data to first-party data

2. The rise of data management platforms (DMPs)

As first-party data increases in significance, having a localised DMP and a data maturity plan becomes a must for marketers. Marketers who have questioned the need for investing behind a full-fledged data management platform and who have been investing in a marketing stack or a CDP will find it critical to invest in harnessing first-party data. Investments behind shared infrastructure, such as shared DMP, will also increase, and agencies might be at the forefront of these efforts. Among different first-party data, CRM will become mainstream and be fully integrated into marketing efforts.

3. Re-emergence of non-ID based data and market research industry

Google has already announced the development of a set of open standards known as the Privacy Sandbox. This is aggregated anonymised data which will be available for use by advertisers. This also heralds the re-emergence of the market research industry. Third-party cookies had stifled the growth of the traditional market research industry. The next decade will see the re-emergence of the traditional form of market research, which is aggregated anonymised data, backed by the ESOMAR code. Personally identifiable data will no longer have a place in the adtech space.

4. Increasing control of big data owners

The already existing walled gardens—Google, Facebook, Amazon and Apple—will become even more powerful as they will have full control over ID-based data. Besides these, any big data owner or partner, such as ZAPR or Zeotap, which has a partnership with a telecom player, such as Jio or Airtel, or with an app-based service, such as Hotstar or Zee5, will wield some control. Publishers that use third-party cookies will have to rely on ID-based data to gather insights about users. As such, there will be an increased reliance on one-click APIs of these big data owners as they try to become synonymous with a universal ID. In the long-term universal ID based platforms such as the IAB Digitrust ID can emerge as the new norms for programmatic advertising.

5. Disruption of affiliates and smaller DSPs (demand-side platforms)

The move signals bad news for affiliates and smaller DSPs, particularly those who are in the business of distributing content rather than creating content. Compliance costs will significantly increase, and this will disrupt businesses of DSPs and meta DSPs. From an advertiser perspective, there have been concerns over legitimacy, brand safety and efficacy. Correspondingly, there will be an increase in transparency and an assurance of compliance if a universal ID emerges. The impact on original content creators will be much less as they continue to wield a loyal audience base. We might see a consolidation of smaller original content creators through mergers and acquisitions to form a larger unit as they might see value in coming together than in partnering a DSP.

6. UX will get better as user consent on data increases

From consumers opting out of ads through ad blocking to explicitly opting in for ads, GDPR regulations will ensure that consumers know how much information to share with which publisher. In parallel, the IAB Transparency and Consent Framework will facilitate the growth of Consent Management Platforms. In turn, the growth of consent management platforms and ID-based data will mean that publishers can do away with a lot of tracking pixels on their digital assets, which will improve overall user experience.

7. Increase in data persistency changes marketing and conversion cycles

The quality of data will improve as the data persistency of ID-based data will be much greater than that of cookie-based data. Efforts put into acquiring ID-based data will be on mobile or email address, both of which have a longer persistency than cookies. This change in data persistency will bring about a radical change in marketing and conversion cycles as marketing efforts can now be more sustained and pre-empt consumer decision journeys. As the quality of data increases and the quantum of measurement goes down, cost benchmarks will undergo a revision with a significant potential upside.

8. Focus of marketing efforts on the top of the funnel

There will be a shift from monitoring impressions, which lie at the bottom of the funnel, to monitoring conversion rates and consumer engagement, which is all about strengthening the marketing funnel. As such, lead forms on digital will need to be shortened for optimal performance.

9. Creativity bounces back as 'datavity'

As the importance of engagement planning increases significantly, so does the role of content and creativity. The efficacy of creativity will be measured on its ability to generate first-party data rather than vanity metrics. Expert pundits, who had predicted the death of creative outfits in the 2010s, will bite the dust. Creativity will re-emerge as 'datavity' and will herald an era where data and creativity will have to necessarily work together.

10. Disruption in digital media planning and buying

From an agency perspective, campaign targeting, optimisation and performance measurement will be affected. Attribution methodologies will change, and brand attribution mix models (BAMMs) will take center stage.

  • Targeting: The move signifies the death of remarketing as we know it, which is purely based on third-party cookies. Lookalike marketing based on cookie pool will also be disrupted and will need to transform to ID-based lookalikes. This means that only big data owners will be able to create lookalikes. Non-ID based lookalike creation will rely on algorithmic, machine-learning, data-engineering techniques. The days ahead will also see an increase in location-based targeting efforts as the location of the consumer will emerge as an important targeting variable in the absence of the third-party cookie.
  • Optimisation: Measurement tools that rely on third-party cookies will be disrupted. Frequency setting across multiple walled gardens and/or multiple publisher conglomerates will become impossible.
  • Performance measurement: With engagement planning CPM-based buying will slowly transition into CPC/CPT-based buying. Agencies that manage cookie pools for improved audience reach will be disrupted.
  • Attribution: The way we attribute will change. Walled gardens will provide attribution within their publishing domain. Present attribution models including the Google model rely on a fixed attribution window and largely neglect brand effects of media campaigns. With the increase in automation on individual publisher networks and limited levers to control marketing spend, there will be a need for learning-based attribution techniques that quantify the brand-building efforts. These will emerge as BAMMs (brand attribution mix models).

Ravi Ganesh is head of data and analytics at Havas Group India.

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