The Future of Data-Based Experiences

Like most everything else, the pandemic marks a turning point for data and marketing sciences.

As pandemic-related changes in consumer behavior fueled the expansion of digital retail services and new technologies, it created new opportunities related to using customer data – along with challenges and debates around its appropriate use. This timeline coincided with recent or anticipated changes to data privacy in the wake of increased scrutiny and legislative action, such as GDPR in Europe and CCPA in California.

We believe that promoting democratization in data access can bring about new solutions and better relationships that can help us create a more human future, while protecting consumer privacy. Looking ahead at how data trends may continue to unfold, we foresee three main challenges and opportunities for innovation in the areas of integration, experimentation, and generating real value.

Integrating data is more necessary than ever

Starting from various stages of evolution, brands are accelerating the adoption of technologies that were previously niche, as well as creating teams and processes to manage data.

The measures taken by the big tech companies around data privacy will force all industries to evolve how digital marketing, segmentation, measurement, and attribution work. One significant change is that since iOS14, Apple updates require all apps to ask their users for permission before collecting and then sharing their data–essentially, a shift from “opt-out” to “opt-in.”

Another major change has been on the horizon for some time: Google’s plans to move away from third party cookies, anticipated by the end of 2022. Google has been working on Topic, after abandoning FLoC, its initial, widely unpopular plan to replace cookies. The new offering would group users into topical “flocks” based on their browsing, allowing users to remove given “topics” to which they’ve been assigned. Critics have pointed out that Google will still be sharing their data with advertisers, just in a different way.

And in January, the Chinese government announced major changes to its web policy, to be enacted in March, which will give the country’s internet users more control over how they are targeted by companies and the ability to turn off recommendation services.

All brands should be preparing for a scenario in which the collection of first-party data from their own platforms complements the use of cookies (especially in light of Google’s upcoming changes) through the configuration of persistent IDs (such as those that arise when generating a registration or login by users through sites, apps, or stores).

This will not necessarily limit the possibilities that brands have. Those that see these changes as an opportunity to adapt and innovate their approach – adopting new technologies with greater agility and flexibility – will stay a step ahead as the data privacy landscape shifts.

For example, many of our clients are beginning to review their consent policies towards users and configure secure integrated repositories for the data coming from their own platforms.

Until a few years ago, building a large collection of usable consumer data and a data management system was an epic task only available to large companies with huge budgets. However, as with many technologies, its application is now much more democratic and accessible, even for small and medium-sized companies.

According to an October 2021 eMarketer survey, for more than 40% of marketers who work with martech, the usability and ability to integrate with the company’s technology are the two most important criteria when choosing data management solutions.

There are no magic recipes or one-size-fits-all solutions to solve all challenges, the best solutions take specific business challenges into account while allowing a company to evolve and adapt to future changes.

Experimenting and iterating is the new growth pillar for business

Users, who increasingly have higher expectations for shopping experiences, require agile services and solutions for their needs at every touchpoint. Talking about omnichannel–and even moreso, “digital vs offline”– seems like an out-of-date approach when people expect streamlined experiences across all platforms.

It’s time to implement strategies to improve consumer experience in each interaction with the brand or product, to complement marketing approaches focused on attracting relevant audiences by experimenting with and adapting strategies throughout customers’ experiences with the brand. A/B testing techniques and the scientific method are worthwhile pursuits for brands to validate approaches to everything from new landing pages and modules, to even simple changes to images or website copy. Statistical techniques like personalized attribution models and marketing mix modeling are regaining value as well, with the goal of measuring the incremental impacts such campaigns can have on results.

Startups or digital native companies have been pioneers in implementing many of these methodologies, but their adoption is quickly spreading to other industries. For example, at R/GA we are developing such approaches for large clients globally in industries ranging from apparel to financial and insurance tech, and this is by no means a comprehensive representation of their expansion. As these methodologies spread, it’s increasingly clear that consumer experience can play a vital role in incremental growth strategies for all sorts of businesses.

Generating a fair value exchange between data and specific services or solutions is key

Technological advances allow us to capture more and more data and process it at a higher speed or greater scale through AI and machine learning. However, there is a fine line between what is useful and what is ethical when working with user information – and practices which may be legal can still be ethically dubious, potentially eroding consumers’ trust.

At R/GA, we design experiences to create real value with transparency, and ultimately empower the client to control their own data ecosystem.

The real challenge today is not amassing large quantities of data, it’s ensuring the right data is collected in the right way. Above all, the most important aspect is to have an ethical treatment of the most sensitive data (PII, or personally identifiable information).

Many brands understand that if this data is processed and transformed into intelligence or solutions that make life easier for users, giving them more agile, personalized access to desired solutions, or additional benefits, then they can create a fair value exchange for customers. Many users are open to this type of agreement when done transparently, with consumers across generational lines viewing access to special offers or discounts as the best incentive.

This is why we are seeing a resurgence in the perceived value of CRM platforms and the development of loyalty and membership programs. For example, during the pandemic, we’ve deepened our work with global brands such as Samsung, Nike, or Spotify to redesign their global long-term customer engagement strategy. These types of programs have become crucial to promote new launches and achieve greater efficiency, especially with millennial and Gen Z users. Making the most of these programs requires data solutions which respect users’ data autonomy and offer a meaningful value exchange, which can ultimately lead to lasting relationships.

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