Tools can certainly help teams work better and more efficiently—but they alone won’t get your team where it needs to be. We know from experience that if you don’t address relationship challenges directly, your transformation effort won’t truly be transformative at all. We set out to solve this problem by making collaboration patterns tangible in a way that we could track and measure over time.

For a multinational pharmaceutical client, inefficiencies in team collaboration resulted in overburdened/underutilized teams, as well as creative delays between the in-house team and third-party vendors. “We found that rules of engagement hadn’t been defined,” says Vice President of Enterprise Consulting Matt Lentz. “So our solution lied in looking at emails received within Media.Monks servers, as well as the quantity of messages received from different sources, to help us develop a methodology to track rules of engagement.”

Lentz wrote a brief for our service automation team, which continually seeks out ways to build solutions that add value or enable a business unit by cutting time and costs internally or for our clients. Lead Technical Solutions Engineer in Media Dylan McBurnett answered the call by developing a tool that could assess communication patterns at scale. The communication analysis tool captures send-receive data from Media.Monks email servers. The data is then used to visually map out all of the communications between the client team and its partners—essentially capturing a snapshot of collaboration and connection across the in-housing effort.

The data helped enforce rules of engagement and proactively eliminate security breaches by identifying those who were not authorized to email media buyers independently. But perhaps even more compelling, data visualizations supplied a 10,000-foot view of what communication looked like throughout the organization—and how those relationships were changing over time as communication became more streamlined and efficient.

Use Data to Design Better Workflows

Every brand is sitting on oceans of data that can help them work smarter—they just might not always realize it. And giving structure to this data can do far more than simply enforce rules of engagement; it can help you proactively avoid the obstacles that inhibit transformation mentioned above. Below are some of the key recommendations we were able to make for our client based on the output of our tool.

Ease burnout by finding people overwhelmed with communications. Emails shared between people implied ways of working together. We created a centrality score to measure which nodes (or people) on the network had the highest association with others. Having a 40% higher centrality score than the next person on the graph suggested an individual may be getting overwhelmed and burnt out. This data gave us the rationale to recommend hiring to ease the burden on some team members.

Build new bridges that help connect teams. While some teams were overburdened, others were underutilized. “We found that some teams and organizations our client had partnered with throughout the in-housing effort were very siloed and uncoordinated,” said Lentz. Likewise, when it comes to in-housing in particular, a common challenge is that new teams may lack the relationships they need with third-party vendors. Visualizations made it easy to spot these gaps, as nodes on the periphery illustrated a lack of connectivity with the rest of the network.

Assess communication improvements over time. The beautiful thing about data visualization is that you can quite literally see change right before your eyes. “Through network analysis and strict communication guidelines, we could see a shift in overall relationship patterns within the organization,” says Lentz. The core team’s increased centrality in the network—indicating high connectivity—emphasized it had achieved the interdependence required for successful media operations.

You can see how sets of communication data can help identify and influence better ways of working. No matter your approach to organizational transformation, relationship building is key. The best tech and tools won’t get you there alone; with the right insights, you’ll have fuel to carry you down the path toward transformation success.

But the product is not the subject of the ruling; the transfer of data, its use and safeguarding measures must warrant scrutiny. If Google Analytics is held to be illegal, the verdict will also have an immediate impact on all products and services that transfer data outside of the EU.

While this article is not intended to be legal advice, I intend to share potential future areas of discussion for EU-US data transfer—and immediate steps to take in light of the recent decision from Austria.

The Evolution of Privacy Regulations

Understanding how and why calls for a history lesson. Long before GDPR came into effect, there was the “Safe Harbor” agreement made between the EU and the US. The 2000 agreement allowed companies to self-certify they would protect EU citizens’ data if storing it within US data centers. The agreement stood for 15 years until it was invalidated by the European Court of Justice.

Safe Harbor was followed by the “Privacy Shield” agreement in 2016, which imposed stronger restrictions on US businesses in accessing and transferring EU citizens’ data. But in 2020, the Privacy Shield met the same fate at the hands of the Court of Justice via resolution C-11/18— colloquially called “Schrems II,” a reference to Austrian lawyer and privacy rights advocate Max Schrems.

Schrems began his privacy battle based on the testimony of Edward Snowden in 2013, regarding the PRISM program that gave the United States National Security Agency (NSA) unfettered access to data. Schrems argued that Facebook aided the NSA, violating the rights of EU citizens to have their data processed fairly.

At this time, the basic principle is that when personal data leaves the EU, the law travels with it. It’s referred to as the transfer of personal data to third countries. For example, Third Countries might be the US, Australia, the UK or anywhere outside the European Union. Recent violations of GDPR, then, are not specific to Google or even data housed in the US; it’s equally applicable to Adobe, Facebook, Amazon and all third parties who function as data collectors across geographical boundaries.

What Does This Mean for the Internet and Data?

The issue that Schrems II (PDF) raises fundamentally applies to the internet as a whole: analytics data collection uses basic internet technologies that are no different than those used when a browser loads an image. The image request still sends cookies and exposes the user’s IP address to the request endpoint.

Still, how analytics are used and how data is managed requires attention and respect for regulation. Increasingly, data protection authorities (DPAs) are ordering the suspension of personal data transfers to third countries. In March ’21, the Bavarian DPA found an unlawful transfer from Germany to the US by MailChimp. A month later, the Portuguese DPA ordered a suspension of personal data transfer to the US and other countries outside the EU by Cloudflare.

Ensure Your Data is GDPR-Compliant

How Google Analytics is used has always been subject to scrutiny and regulation. As a result, it is prudent to make sure all your data collection and activation is compliant with the most current regulations. Consider these basic steps as possible actions and repeat them at least each quarter:

1. Anonymize IP addresses in Google Analytics. This will impact geographic reporting, but is a relatively small trade-off.
2. Ensure your cloud data storage is located in the EU. This is an opportunity to review all data storage locations.
3. Make sure your consent banner is compliant. Implement an automated scanning process that runs on a regular cadence to quickly identify the setting of cookies without consent.
4. Review your cookie and privacy policies regularly for compliance.

Get third-party legal advice to ensure compliance or address any questions you have. A data partner like Media.Monks can also provide support in implementing changes to Google Analytics and providing automated solutions to measure and analyze data collection with respect to consent banner functionality.

Where Do We Go from Here?

The subject of the Austria DPA’s complaint is the transfer of personal data to the US that lacks adequate protection from US authorities who gain access to it. Standard Contractual Clauses (SCCs) have been used previously to allow data transfer, however, questions have been raised regarding the feasibility of SCCs with respect to FISA (PDF). New SCCs have been published that require supplementary measures that go beyond encryption, referring specifically to scrutiny of the destination country’s legal regime. Google maintains these measures have been met (PDF).

Currently, there appears to be difficulty where both encryption and transparency requirements seem to contradict each other. Revised SCCs or a successor to Safe Harbor and Privacy Shield appear to be the favored solution by Google, although the practicalities and timing of such solutions remain unclear. Until then, following the steps above to regularly review compliance goes a long way to ensure your brand remains in good graces.

What’s topical about Chrome’s Topics?

The Chrome browser currently has a strong market foothold with above 50% in market share, despite not really having a solution following Safari’s (Apple’s) crusade to kill third party cookies. While it hasn’t gone for marking the cookiecalypse yet, like Safari and other browsers have, Chrome has attempted to address the needs of marketers with ideas to alter some marketing capabilities to work in a privacy-safe way. 

Google has sought solutions which would enable some form of safe profiling and data exchange between martech players as ad revenues continue to be mission-critical for the health of many businesses. These solutions are going to be built into the Chrome browser, packaged as the Privacy Sandbox.  

The most recent announcement introduces Topics, which are an updated version of FLoC (federated learning of cohorts). The initial idea behind FLoC was to create a mechanism which would classify users based on their behavior into cohorts which guarantee privacy (through entropy). By design, cohorts would be more generic and would remove 1:1 targeting, but at the same time would restore interest-based targeting. The main issue of the initial solution was in mathematics, as algorithms were translating domain names into numbers without a clear understanding of “topicality” of the site. 

As FLoC did not win hearts of the industry, Google went to the drawing board and came back with Topics. The idea of cohorts still persists, though the mechanism of translating domain names into “topics” for further targeting was updated along with some privacy assumptions. Even though the proposal is not yet fully developed, there is a consistent approach of using domain names in order to classify users into cohorts. Google envisions some form of a dictionary and set of rules that determine which domain name translates to which topic. Current documentation points out that usage of sub domains is encouraged to support mapping into topics. 

How does the third-party cookie crumble crush my current domain name strategy? 

The main issue with third-party cookies is that they enable “foreign” actors to collect information about individuals as they travel between different sites. Though as everything in a binary word of computers, the definition of a foreigner is very black and white. All cookies set by a different domain are considered third parties. Computers do not care much about the structure of your organization, brands, subsidiaries and ownership. 

Multibrand businesses which operate across multiple domains face challenges in building user profiles without third-party cookies. As data management platforms (DMPs) and many marketing solutions struggle to exist without third-party cookies, it is becoming more difficult to create a single customer view across brands one may own. As first-party data strategies are picking up steam, there are some critical decisions to be made. To operate in a first-party cookie context and be able to exchange data between their own brands, brands need to operate under the same domain name. 

The most apparent manifestation of this situation are media outlets which own multiple mastheads. As publishers try to build value propositions around their audiences, every piece of information counts. Without a DMP or third-party cookie, it would be impossible to achieve scale across different sites they own today. 

So, how can I make a name for myself?

As it is possible to register your own top-level domains or TLDs (though they are expensive and it takes time), and we observe ongoing pressure on first-party data collection (meaning you need one universal domain across your whole business), it's time to consider your new universal domain name! 

Let's assume you run a business called “Example” together with two brands, “Big” and “Small.” It’s likely you have example.com, big.com and small.com as domain names. With the lack of third-party cookies, it is hard to exchange information about prospects between the sites. With help of a customer data platform (CDP) or a good data team, you may join first-party data between the sites to research the level of cannibalisation or overlap. 

To simplify your life (and data), you may want to consider big.example.com and small.example.com as primary addresses. This will enable all sorts of integration and will load your first-party data strategy with rocket fuel. If you are big enough, you can go for your own top-level domain to create something like big.from.example and small.from.example. Coming back to Topics, if your brands operate with multiple categories, more subdomains enables better profiling, like automotive.big.from.example or sport.big.example.com. 

How do I get started now?

Well, FLoC did not survive long enough to become a thing and Topics are still quite nascent themselves. Though everyone is pretty committed to getting rid of third-party cookies, and some businesses already operate in a world where over 80% of traffic comes from browsers that no longer support them by default. Google has postponed the moment of putting the final nail into the cookie’s coffin, so the timelines seem rather floaty. 

Today we operate with the assumption that hour 0 will come around next year or the year following. All things considered, there is not much time to prepare for such big decisions. Now, it’s time to plan.

Companies that don’t have privacy and transparency at the core of their data management strategy stand to have consumer trust hemorrhaging like a burst pipeline in the rain. While skepticism towards the collection and use of customer data grows, doubling down on earning users’ trust makes good marketing sense. 

At one of MMA’s Data Unplugged India Series, I was part of a panel discussion “Perspectives on the Evolving Online Data Environment” where we shared how businesses can prepare strategies for a user-first, privacy focused future. The following are my views on building users’ trust shared during the discussion, which I’m expanding on here.

Earning Users’ Trust

A recent survey by YouGov revealed that more than half of consumers are wary about sharing their data, as they don't want it to be misused surreptitiously. Consumers are tired of data breaches, invasive ads and opinion manipulation. Adding to that is the lack of knowledge on the use of cookies and how third-party tracking works. As a brand, if you can ethically convince your customers that they will benefit from the data exchange, they would be more likely to share. This revelation can help marketers in building their first-party strategies, on top of transparent forms of data collection such as loyalty programs, to establish long-term relationships between brands and their customers. 

However, before any first-party data (or 1P data) collection takes place, there must be a foundation of trust built with your audience and the onus falls on brands to keep users' data private and secure. A simple introspective exercise that I encourage my clients to follow whenever they aim to enhance customer profiles through data is to ask: what kinds of data are necessary, why and how it will be used, and whether it should be shared with an external party. 

My colleague Doug Hall, Senior Director of Analytics at Media.Monks, echoes this sentiment:  “Don’t just be legal, be righteous—it will give you a competitive advantage.” Privacy must be proactive and not reactive. It must also be preventative and not remedial. 

On a deeper level, it’s always a good practice to audit a business’s existing technology stack, no matter where the business is in its 1P data journey. An annual tech audit exercise helps businesses realign data priorities, get rid of redundant components or replace them with modern equivalents, and find opportunities in technology or skills that can boost 1P data capabilities.

Some areas to consider when auditing your tech stack for data privacy are:

• Storage - Investing in keeping data safe and private should be on the forefront of any data collection exercise. Businesses can weigh the pros and cons of engaging a cybersecurity partner or establishing an in-house data security team against the data collected and how and where it is stored. 
• Access - To address misuse of data, decide who are the essential personnel to have access to the data—is it marketing, data analysts or leadership? Hint: the fewer the better. Access can also be differentiated by the level of access (read or write) and scope of access (dashboard or entire list).
• Portability - 1P data may be collected off- or online and from various sources. Hence, the data collected may be scattered across multiple systems. Integrating data from all touchpoints into a centralized system can be better for marketers to understand the entire customer journey and offers better control over access to data.
• Activation - While modern martech systems are designed for customer data activation so that marketers can communicate with smart cohorts, the choice of method of activation matters greatly. Ingress and egress of unencrypted data into cloud stores or non-secured FTP (File Transfer Protocol) sites or email is considered the least safe. Using direct activation connectors between systems is considered the safest, followed by encrypted or private data exchange between trusted cloud systems.

Early Adoption and Smarter Practices

Like learning a new sport, the more you practice a privacy-minded approach to gathering user data, the more capable you will become. Early preparation can lead to greater learning and benefits further down the line as solutions become more sophisticated over time. Also, algorithms that have been trained on greater amounts of data over time instill more confidence and accuracy. Businesses operating with 1P data for longer will also enjoy more help and attention from key technology partners, which improves relationships with customers, partners and stakeholders. 

Privacy is an urgent yet evolving concern that requires everyone in our industry to get together and operate with consensus. By testing, evaluating and sharing new strategies, the faster we come to a common understanding of how privacy should work.

As we pivot to building and using 1P data to manage durability and scale, many may fear that prospecting will be negatively affected, since the decision to share 1P data is voluntary and lies in users’ hands. Building trust by being transparent, open and verifiable—and showing how the data exchange would help them with better customer experiences—encourages shareability. Furthermore, educating consumers about periodically reviewing their privacy settings and how the data is being used and deleted when the app’s life comes to an end further solidifies that faith. This is important as future engagements become first-party driven and businesses seek to become unreliant on unsustainable methods of personalization, such as cookies and resettable device identifiers. 

In scaling 1P data to increase the number of successful journeys, four actions need to be operating in a cycle. 

• First, marketers need to continuously invest in acquiring prospects and observe their journeys by collecting first-party and behavioral data at key checkpoints. 
• Once they have that data, they can optimize it by clearing bottlenecks and obstacles throughout the customer journey, such as misplaced calls-to-action or ambiguous navigation.
• Marketers must observe patterns in journeys that have successfully reached desired goals. This helps catalog and reason as to why some communications journeys perform better than the others.
• And finally, marketers should select the prospect cohorts that best match desired goals, then recreate successful journeys through prompts and navigation tools on their platforms. All these are contextual environmental variables that brands can still fine-tune to build more relevant and tailored experiences.

Bringing on Desirable Results

As a net impact, strong and responsible data practices can help an organization mature and transform into a better version of itself. First-party data is at the heart of any digital maturity and transformation journey. It helps you to get to know your customers, your markets and your business better. Auditing existing strategies by asking the right questions will guide you on the path to instilling trust in your audience. This can also lead to better data hygiene and evaluate policies on data usage. 

The pandemic has exacerbated and accentuated the way we see the world and how we experience it—more so on what’s wrong and how we can fix it. Privacy is a crucial demand today and is a compliance game changer. For those looking for more strategies and to get clued up on shifting attitudes and regulations surrounding privacy, we’ve put together a report on how brands can navigate imminent privacy changes and get up-to-speed with consumer conversations.

The team is led by Nick Fogler, Founder and CEO; and Sam Baron, COO. Founded in 2017, 4 Mile’s relationship with Looker runs deep: Fogler previously led Looker’s engineering team and supported the company’s transition into a larger-scale enterprise before founding his own. Since then, 4 Mile has supported some of the biggest brands to accelerate their strategic initiatives.

The Rising Need to Translate Analytics into Action

As brands transition away from third-party data to first, much has been said about effective data collection—but that’s only half the battle. Many brands are already sitting on mountains of data that isn’t actionable, and the value of that siloed or hard-to-access data pales in comparison to its frictionless counterparts. Throw in the fact that data platforms and dashboards are often overly technical and opaque, and it becomes clear that focusing merely on data collection—not its usability—simply isn’t enough.

Realizing this need, Looker has long been a favorite solution by our data and digital media practice. Others agree; Looker is now regarded as a core part of the Google Cloud Platform (GCP). What makes it special is that teams using the platform can easily integrate data from various sources into intuitive data experiences that are custom-built to their specific requirements. This functionality solves the crucial need of pulling together insights that are accessible and actionable not only to teams in marketing, but also those across the organization.

A Reputation for Excellence 

4 Mile’s significant history and relationship equity with Looker builds upon our own expertise with the platform. Before they worked directly with clients, 4 Mile was hired by Looker as an extension of its product development team. Through this partnership, they developed custom visualizations and third-party integrations in the Looker product code base, deepening their already intimate understanding of the platform. And while 4 Mile’s direct-client relationships continue to grow, solid collaboration with Looker Data Services remains a cornerstone of the business. 

Still, 4 Mile’s proficiency isn’t limited to Looker. By leveraging strong relationships with leading technology platforms like Fivetrain, DBT, Snowflake, Exasol and Keboola, the team has developed a wide breadth of solutions for the modern data stack:

• Designing and building custom data experiences that blend analytical and operational capabilities.
• Transforming raw data into business-ready data that allows end-users to explore, curate and take action on data insights.
• Designing and employing modern data warehouse solutions to support business intelligence.
• Orchestrating movement of high-volume batch and real-time data across the enterprise.

A Shared Human-Centric Approach

Both Media.Monks and 4 Mile believe that a human-centric approach to technology opens the path to better customer experiences. At the same time, successful data-driven strategies must begin with a strong foundation to build deeper, more meaningful connections with audiences. For 4 Mile, this principle has inspired a people-first mentality—valuing diversity, empathy and respect—that informs the team’s approach to partnership. This includes providing training and documentation to enable internal teams to execute new data solutions, as well as building products that realize specific use cases.

With 4 Mile now a part of our team, their existing clients will gain access to a global community of talent that excels not only in data and digital media, but also content creation and tech services. Meanwhile, Media.Monks clients gain even greater access to a powerful bench of analytics and machine learning experts, providing greater scale, deeper data analysis and more data-driven decision-making. This allows for an even more seamless activation of first-party data, unlocking highly effective and engaging experiences across the customer journey.

Challenges from all ends—government regulation, tech platforms and public sentiment alike—suggest 2022 will be the year in which modern brands must adapt their data strategies once and for all. Together with 4 Mile’s exceptional Looker and GCP expertise, we’re excited to empower brands on their journey to achieve top-line business goals at an even greater velocity.