Data loss in marketing and the impact of black box ad platforms

Data loss is a significant concern for digital marketers. In fact, 73% of marketers say they're seriously worried that privacy laws will negatively impact their analytics efforts. These concerns are only growing as the industry relies more and more on black box advertising platforms like Performance Max and Meta's Advantage+. 

1. What is Performance Max? 

Performance Max campaigns let marketers access all of their Google Ads inventory from a single campaign. These campaigns are designed to complement marketers' keyword-based search campaigns. As a result, Performance Max helps marketers find more converting customers across all of Google's channels, including:

• YouTube
• Display
• Search
• Discover
• Gmail
• Maps 

Some of the benefits of Performance Max campaigns include:

• Finding more converting customers
• Unlocking new audiences across Google's channels and networks
• Driving better performance against your goals
• Unlocking more transparent insights
• Simplifying campaign management and easily optimize ads

2. What is Advantage+?

Meta's Advantage+ includes a suite of advanced advertising tools that are designed to help marketers better understand and target their audiences across Meta's platforms, including Facebook and Instagram. The platform uses machine learning to power its features.

Some of the benefits of using this suite of tools include:

• Advanced audience targeting
• Creative ways to optimize campaigns
• Real-time reporting
• Customization
• Budget optimization
• Creation of fully automated campaigns

3. The problem with black box advertising

Black box algorithms can prevent marketers from fully understanding how their campaigns are performing, how their target audience is responding, and gleaning other critical data insights.

Without access to this data, marketers may struggle to effectively target their ads or make the necessary adjustments to improve campaign performance on the fly.

What's more, the lack of transparency creates a sense of distrust and skepticism among consumers, which can impact not only the success of online sales and your marketing campaigns but also your overall brand image and reputation, making it extremely difficult to connect with your target audience and achieve your marketing goals.

Take a balanced approach 

You should never put all of your advertising eggs (budget) into one basket (channel). This is wise advice to avoid the perils of black box advertising. Take a balanced approach to your ad spending rather than allocating large chunks of your budget on Performance Max campaigns and other black box algorithms that don't give you transparency and control over your ad placements.

Instead, consider running local campaigns using a mix of tools and platforms that prioritize consumer privacy and give you the ability to build trust with your target audience. Two great options to achieve this are Google Ads and Facebook Ads Manager, which provide robust features and capabilities to help you optimize your campaigns for better results.

With Google Ads, you can tap into the company's massive search and display networks to reach a broad audience of internet users searching for the products and services you provide. The platform offers a broad range of tools and ad formats to help you create engaging text, image, and video ads.

Facebook Ads Manager is a helpful tool for creating ads that will be shown on Facebook and Instagram feeds. With this platform, you can target users based on a variety of factors, including age, location, interests, and behaviors. 

A combination of these tools can help you gain valuable data insights into your target audience while enabling you to create highly personalized ad experiences. This approach can also help you optimize your campaigns for maximum impact and ensure that your ads are showing up where your target audience is online.   

The death of third-party data

Third-party data refers to information that's collected by companies that don't have direct contact with consumers. Basically, advertisers or aggregators collect data from various websites and other sources and use it to inform their ad spend and track consumers' behavior on the web and mobile devices. This helped marketers deliver highly-targeted ads that were precisely aligned with what consumers were looking for. 

As privacy concerns take center stage, however, it's getting harder and harder to use third-party data to target savvy consumers who care about their online privacy and safety. A recent survey even found that 86% of consumers are worried about data privacy.

Now, as third-party cookies prepare to crumble as a result of the increased focus on user privacy, marketers and tech companies need to start focusing on first-party data collection. This is data that's collected directly from consumers. One of the biggest benefits of first-party data is that it's seen as more of a value exchange.

For example, instead of unknowingly having their internet activities tracked by third-party data, a customer chooses to provide a brand with their first-party data. This is often done when they willingly give their email address to sign up for a discount code or loyalty program.

This is a critical step to stay ahead in the evolving landscape, because consumers are fed up with not having control over their personal data. But you shouldn't view this as an unwelcome change. The shift toward first-party data can actually benefit marketers in the long run. By prioritizing transparency and consent in their data collection processes, marketers can build direct relationships with their customers, gain their trust, and improve their brand reputation — a win-win-win!

Advanced analytics solutions

Marketers can use advanced analytics solutions like marketing mix modeling (MMM) and incrementality analysis to address data loss. These solutions can help you get a better understanding of campaign performance and identify which channels are delivering the best results to relevant audiences. 

1. What is marketing mix modeling?

Marketing mix modeling, or MMM, is a very useful tool that marketers can use to make better decisions about how to allocate their ad spend. Basically, MMM helps you figure out which marketing channels are driving the most sales so you can focus your efforts and your budget on the ones that are really working.

There are a number of factors that MMM works to analyze that could be impacting your sales, including advertising, promotions, and more. Being able to see how all of these factors work together gives marketers a complete view of what's driving sales and how they can keep optimizing their marketing strategy.

Marketing mix modeling will help you make better decisions about where you should invest your marketing dollars while also making sure you're not wasting ad spend on channels that aren't performing.

Learn more about marketing mix modeling with Funnel on YouTube.

2. What is incrementality analysis?

In marketing, incrementally is an increase in the desired outcome from marketing activities. It measures the additional impact or value that a marketing campaign generates beyond what potential customers would have naturally done without a single campaign. Incrementality analysis measures a campaign's effectiveness at driving incremental conversion, sales, and other desired outcomes.

In a nutshell, incrementality in marketing is an increase in the desired outcome from marketing activities.

By isolating the impact of the campaign, incrementality analysis helps marketers understand the true impact of their campaigns and make data-driven decisions about how to optimize their marketing strategies.

Both MMM and incrementality analysis require advanced analytics skills and tools to implement, but they can provide valuable insights into the performance of marketing campaigns. 

3. Use technologies to your advantage 

Investing in advanced technologies can be a key strategy for marketers to mitigate the impact of data loss and gain valuable insights from their first-party data when third-party data is no longer an option. For example, Google Analytics 4 (GA4) offers powerful machine learning systems that can help marketers analyze and activate their first-party data more effectively. 

One example is the audiences tool, which uses machine learning algorithms to identify patterns and insights about audience signals within a company's first-party data, allowing marketers to mine audience signals to create more targeted and personalized campaigns.

Frequently asked questions

What is data loss?

In the marketing world, data loss can happen when consumer data is lost, stolen, or made inaccessible through data deprecation or any other means. When this happens, it's hard for marketers to share data and use consumer data to inform their campaigns.

There are many causes of data loss, including:

• Hardware failure
• Software corruption
• Software failure
• Cyberattack
• Hacking
• Computer viruses 
• Accidental deletion
• Human error

In the context of marketing, data loss takes on a slightly different meaning. It refers to the loss of access to user and customer data due to indirect factors. This includes new privacy laws like the California Consumer Privacy Act and GDPR, which limit marketers' ability to drop cookies onto user browsers without their consent. It also includes the upcoming "cookie-apocalypse," where third-party cookies will be phased out, and corporate moves like Apple's restrictions on advertising platforms' ability to track users across devices. 

2. What is data loss prevention?

Data loss prevention (DLP) refers to strategies and/or products that are used to mitigate or prevent data loss. The goal of DLP is to protect confidential and sensitive data from unauthorized people who could mishandle or maliciously share it.

There are a number of data loss prevention strategies, including:

• Regular data backups.
• Controlling who has access to sensitive data.
• Encrypting sensitive data.
• Classifying data based on its level of sensitivity.
• Security training.
• Monitoring and auditing.

Final thoughts

While implementing technologies like GA4, incrementality analysis, and MMM can require significant investment in terms of time, resources, and expertise, they can ultimately provide significant benefits in terms of better targeting, higher ROI, and more effective use of first-party data. By leveraging these technologies to their advantage, marketers can mitigate the impact of data loss and ensure that they are making the most of the data they do have.