Shirli Zelcer, head of data and analytics at Merkle, explains the impact of privacy regulations around data collection and the deprecation of the third-party cookie and why both trends arecausing marketers to completely reevaluate approaches to customer experience.
October 21, 2021 by Shirli Zelcer
Over the past 24 months, the world of marketing, customer experiences, and data has gone through some seismic shifts that few could have imagined.
The pandemic has forced consumers to interact with brands through digital channels at significantly higher rates compared to previous years. At the same time, privacy regulations around data collection and the deprecation of the third-party cookie are causing marketers to completely reevaluate their approach and meet consumer requirements for relevant and meaningful experiences.
The ongoing collapse of third-party cookie tracking means that brands will no longer have the ability to use this type of cookie data for marketing purposes. This data typically contained a variety of behavioral and demographic data attributes that could be used for more precise targeting and personalization. Data collected through cookies often had challenges with accuracy and was not always sourced with full consumer consent and transparency.
First-party data is that which is collected directly by an advertiser on its customers. It is becoming increasingly important, as third-party cookie-based data sources come under scrutiny due to compliance and accuracy limitations. It is critical that brands collect this data from consumers intentionally, with their full consent, and with transparency as to how it will be utilized and the ways it will benefit the consumers who provide it. First-party data can include transactions, preferences, and behaviors, as well as identity signals such as name, address, phone number, etc. It is highly accurate, given that marketers don't have to infer customer preferences or behavior, but are instead explicitly provided this information directly by the consumer.
While consumers might willingly volunteer their personal information, marketers should look to develop programs that create a value exchange to further incentivize consumers and create satisfaction for giving this information back to the advertiser. These value exchange programs could include rewards from loyalty programs, unique promotional experiences, preferred access to products, or personalized content to drive better engagement. These efforts lead to consumers consenting to share more of their first-party data with advertisers, which can then lead to brands refining their approach to personalization using this data. It creates a virtuous cycle and drives growth of consented first-party data for the brand.
The demise of third-party cookie data marketplaces has also led marketers to look at ways to complement their first-party data with additional insights on their consumers based on interactions with other brands. Second-party data is data that brands gain access to from another brand for mutually beneficial marketing outcomes. Second-party data can provide brands with unique insights on how consumers are interacting with other partner organizations. It can help advertisers understand consumers' needs and use those insights to craft meaningful and relevant communications back to them. Examples of these partnerships are credit card providers working with airlines and other travel partners to identify travel-intending audiences across their portfolio and providing them with unique offers crafted based on their specific usage of the travel products. While the opportunities for marketers to use second-party data are endless, it is important to take consumer choice and consent into account. Brands should be transparent about how the customer data is being utilized and provide an option for consumers to opt out of these programs.
In addition to first- and second-party data, marketers still have access to high-quality third-party data at a person level to augment their first-party data and enrich their understanding of customers from a demographic, financial, lifestyle, and life stage perspective. This data is important in developing a 360-degree view of consumers, generating insights, applying machine learning, and driving highly personalized creative, messaging, and offers to consumers.
The ability to identify relevant audiences and drive personalized experiences to them is a core competency that brands need to possess today to be competitive. Data is at the center of this ability; however, it is equally critical for brands to not lose the trust of their customers by misusing their data. Data clean rooms have been around for a while, originating around the regulated usage of credit data for marketing, as well as in the healthcare space for complying with privacy regulations related to the analysis of patient data. This idea is now relevant for the analysis of online and offline customer data in a privacy-safe and secure manner. Data clean rooms do not contain any personally identifiable information in these environments, nor can anyone reverse engineer the data into PII. There is a high degree of data governance built into these solutions that restricts access to sensitive data sets as well. Data clean rooms simplify privacy compliance and significantly reduce risk associated with the misuse of consumer data. Brands looking to develop second-party data sharing can also look to data clean rooms as a secure way to share data.
Overall, data clean rooms enable organizations to generate meaningful insights across the entire journey of their consumers and deliver high-quality, personalized experiences to them while not compromising on data security and privacy.
Shirli Zelcer is head of data and analytics at Merkle
At Merkle she has worked with a variety of different clients including Disney, Dell, Universal Parks and Resorts, Royal Caribbean, Marriott, and Nike, and has led projects for both consumer and B2B segments. Projects Shirli has managed include enterprise segmentations, customer journey development, lifetime value, omni channel integration, contact strategy optimization, acquisition and customer targeting and next best models, propensity models, and media mix modeling and attribution.