How data clean rooms reinvent media TMT business models: PwC

In a recent PwC Pulse Survey, only 63% of CMO respondents said data clean rooms (DCRs) — secure data collaborative environments — are one of their top two investments. It should have been 100%. Here’s why.

Businesses need better data signals and models to drive the next generation of customer experience and optimize how marketers unleash growth. They also face expanding data privacy regulations that are fueling demand for secure data sharing and for collaboration with trusted data providers.

Additionally, consumers increasingly expect more relevant service experiences. Emerging tech can help deliver the hyper-personalization needed to meet these expectations by leveraging advanced data analytics and machine learning. This is an opportunity for marketing leaders, especially those in media companies, to drive growth by working with data officers and harnessing the tech that enables data sharing with trusted business collaborators to deliver value.

_{Q: Thinking about marketing and advertising technologies, which of the following applications do you plan to use in the next 12 months? Top 2 box (Have already done/Have a plan in place) .

Source: PwC Pulse Survey, August 22, 2023.}

Enter data clean rooms. As privacy-compliant solutions that allow various parties — like publishers, advertisers and service providers — to share data, clean rooms can:

Enhance first-party data for precise ad targeting
Improve understanding of consumer behavior
Optimize marketing spend
Create new monetization channels
Provide companies with a competitive edge

With emerging tech like generative AI that can further that advantage by supporting new business models overall, anticipating evolving needs and accelerating the build of industry models can foster hyper-personalization efforts at scale. And it can do so in ways that help reduce costs and boost sales and topline growth — while still protecting customer data privacy and maintaining compliance.

Get funding onboard: The challenges of data clean room adoption

Data clean rooms can be part of a larger data collaboration strategy that opens opportunities for media and telecommunications companies. But budgetary buy-in is key. Despite the benefits these technologies can deliver, adoption often lags in marketing functions operating under tight budgets or anticipating spending constraints — especially given broader economic factors. Without immediate pressure to fund long-term collaboration technologies, like data clean rooms and other marketing technologies, short-term CFO focus tends to be on campaign spending and optimizing marketing dollars.

The onus falls on CMOs and other marketing leaders to be ambassadors for longer-term investments and strategies that can help their companies adapt as the advertising landscape evolves.

Until third-party cookies are completely gone, and marketers feel like they’re just guessing, it may seem tempting to wait for a clear front runner solution before moving forward. But given the complexities of data clean room implementation — and tying it to a broader tech-enabled, human-powered marketing strategy — a wait-and-see approach isn’t a very good idea.

Clean rooms help use data collaboration tech to reinvent your business

Looking ahead can drive impact. Early adopters of data clean rooms are more likely to have better data models trained on more use cases to deliver AI-powered insights. A company that’s able to test and learn ahead of the curve can position marketing investments to drive value when other attribution and measurement models like third-party cookies are deprecated. Making this shift means leaning into first-party data for essentials like ad targeting, evolving data collection and management practices.

As marketers look for more support from peers, industry groups, agencies, vendors and consultants, opportunities abound for their companies to unlock new revenue models. Contextual advertising — where ads are targeted based on the content of the webpage rather than user behavior — is on the rise. And we’re also likely to see strategic collaboration become more commonplace.

Data clean rooms could offer avenues for data monetization, a task that many media and telecommunications companies can find daunting. Yet tools with bottom-line impact are powerful in CFO discussions. In PwC’s recent Pulse Survey, 46% of technology, media and telecommunication (TMT) executives told us they view data monetization as one of the most significant challenges impacting their business strategy in the next few years. However, by unlocking data’s value and developing effective data collaboration strategies, media and telecom companies can overcome existing barriers and potential to generate new revenue streams.

Unlocking new revenue models for media companies

Media companies can capitalize on data clean room technology to enhance collaboration, gain valuable insights and fuel business growth within the advertising ecosystem. By helping expand business models, data clean rooms make it easier to forge strategic relationships that allow for a holistic understanding of customers and markets as well as the sharing of data and insights — all while still safeguarding existing investments in data and intellectual property by enabling secure data sharing without compromising proprietary code or models.

Data clean rooms can be a part of this revenue expansion because they can...

Provide direct access to a vast amount and wide variety of data that would otherwise be difficult to obtain, enabling valuable insights into customers, markets and competitors.
Automate various data analysis tasks, including data cleaning, feature engineering and model training, saving time and money and enhancing the accuracy and efficiency of data analysis.
Enable faster insights discovery and improve data analysis processes that can help boost efficiency and productivity while reducing costs.

So, what could using a data clean room with a strategic business partner look like in practice?

An ad agency and a streaming service can join forces, for example, in a data clean room to improve their advertising campaigns. They can analyze viewer data and ad performance together, gaining insights into audience preferences and improving targeting strategies. This collaboration enables them to create more personalized, relevant and effective ads without compromising viewer privacy or sharing sensitive data — and it can allow them to deduplicate campaign reach and frequency and independently measure performance across platforms.

We’ve also seen data clean rooms used successfully in the sports industry. Teams use customer insights gleaned from data clean rooms to better understand how fans respond to advertising — and to identify common characteristics, enabling sponsors to target promotions to relevant demographic groups. They can then personalize offers and avoid sending irrelevant marketing messages. And they can do so with customer consent and the commitment to adhering to privacy regulations.

How can DCRs provide new revenue streams for telecoms?

According to PwC’s Global CEO Survey, 52% of telecom CEOs believe their current path is not sustainable. Reevaluating their traditional vertically integrated carrier model and considering distinct business layers could open up possibilities — and help them stay viable. A telecommunications company’s extensive data assets and data analysis and management capabilities put them in a prime position to capitalize on the growing demand for data-driven insights. Data clean rooms can be a valuable tool for generating new revenue streams and help companies get future-ready.

With their access to vast amounts of customer data — including call records, internet usage, location data and so on — telecoms can use data clean rooms to analyze and extract valuable insights from this data while maintaining compliance. Telecoms can then package these insights as services and solutions to business partners in the form of targeted advertising, market research, customer segmentation and personalized offerings.

Designing a high impact marketing function

Instead of simply waiting to see who wins the identity and measurement solutions race, get proactive. This involves mastering your first-party data from the start. The goal is to understand possible gaps in your consumer insights and identify where third-party data can round-out customer acquisition, engagement and optimization efforts.

The right balance of first-party and third-party data can be a game-changer for predictive modeling. It offers transparency and valuable insights directly from customers and prospects. Still, working to properly categorize identity roles can be complex and daunting. It requires dedicated efforts in data management, organization and analytics. Rather than solely focusing on tactical approaches, consider investing in developing audiences and orchestrating journeys. While these efforts demand significant resources and commitment, adopting a holistic approach at the get-go — rather than getting stuck in channel tactics — is more likely to pay off.

PwC can help you break down data silos, enable data collaboration and reimagine your marketing function. We can work with your team to implement DCRs, reconsider your business model and explore possibilities like strategic relationships and new revenue streams. Customer Link, a PwC product, can be integrated with data clean rooms and can enrich your first-party data so you can build a 360-degree view of your customers, build compelling high-efficacy campaigns and deepen relationships.

Broadcasting your company’s safeguards and compliance efforts is key to building trust, and this is increasingly important in an era when leveraging emerging technologies, including GenAI, is becoming a business imperative for scaling personalization. We can help clients use GenAI to transform their business within the guardrails of careful strategy, governance and a responsible approach.

Delivering personalized experiences can go a long way toward cultivating customer loyalty. And creating great tech-enabled experiences while also handling customer data responsibly helps build trust in your brand.