The Marketers Guide to the Data-Verse: Being a More Sophisticated, Data-Centric Marketer
  • Colton Rice
  • Jul 08, 2022

The landscape around data and how it is being captured, shared, and used is undergoing a world of change. With privacy laws and data rights taking the stage, many organizations are going all-in on first-party data. But a first-party data strategy alone will not solve all marketers’ needs. With this blog post, we aim to help readers better understand the way data can be used, what data they need, and how they can leverage the data available to them in a responsible and effective way. Welcome to the marketer’s guide to the data-verse.

Let’s begin by talking about the different types of data. Knowing the roles of certain types of data can help you hone your marketing strategy while giving you the tools to choose partners with reliable, safe, and compliant data.

First-party data is data on a company’s customers that is collected and owned by that company, and stored in company-owned systems such as CRMs, data warehouses, etc., which keep track of customer interactions such as transactions, product registrations, loyalty programs, shopping cart activity, and more.   

Understanding first-party data is key to learning what attributes make up your VIP customers, and can help you better engage the customers you want to retain, while providing a foundation for lookalike modeling used to acquire new customers likely to be high value. 

Second-party data is data shared from a trusted partner. This data isn’t bought or sold, and can help companies grow and scale their marketing. When data is shared, each partner does not share the raw data, but instead matches unique IDs to data already owned so both companies can get additional insights while adhering to privacy requirements. Clear as mud? Let’s look at an example.

If I am a hotel chain and I share my first-party data with an airline, we both benefit from learning the additional insights the other company has about the same customers. As a hotel, by sharing the first-party data I have on John Smith and his hotel booking tendencies, and by the airline sharing back their information on the same John Smith, I now have information on John Smith’s airline bookings. My hotel can now serve John Smith custom campaigns that may align with a trip he has just booked, and the airline can then serve him curated advertisements leveraging my insights about John Smith as a hotel guest. 

That leaves third-party data. Third-party data has developed a pretty bad reputation in recent years, and the bad rap is not completely unfounded, it might be just a little misunderstood. We talked about this a little bit in our recent blog post, “The Future of Acquisition Marketing.” In the earlier days, data accuracy and quality were not as important and were tough metrics to prove, so scale and volume ran the show. Low prices for third-party cookie-based audiences, high scale, and getting the message out to as many people as possible was the name of the game. It was great for branding campaigns, but not great for precise targeting or consumer privacy. 

A Changing Marketing Landscape

Then, as now, Facebook and Google campaigns dominated the landscape. And until recently, both collected vast amounts of data they could sell to advertisers to segment and target net new audiences on their platforms. These were (and still are) black-box ecosystems that marketers cannot directly access. Marketers were stuck with trusting the ROI and attribution reporting from these systems, without being able to see the underpinning metrics directly. For example, Facebook once claimed they outperformed every other platform – according to their own self-reporting. It must have been pretty nice for them to grade their own homework. 

One wrench thrown into all this was a significant change to Apple’s iOS, when they released iOS 14.5, which allowed users to decide whether they wanted to be tracked. As one may guess, the tracking opt-in rates are very low; only about 5% according to CNET. This trend will only continue, especially as Google is poised to deprecate 3rd-party cookie tracking in their Chrome browser. And with less data being collected, the black box ecosystems will have less effective targeting and less effective attribution reporting. 

With these changes to third-party data collection, marketers are left to find other solutions to target advertisements to customers and prospects. Thankfully, there are solutions out there, but how do you know which one is right for you? It’s important to understand your options and priorities when choosing a partner to help enable and activate customer insights.

Making an informed decision

When evaluating a solution, we recommend that you take the following four steps to ensure your potential technology partner can meet your needs:

  1. Start by defining and prioritizing your use cases. Is your priority to acquire any new customers, or to ensure maximum lifetime value of those you do acquire, or both? Do you want to create a seamless experience for prospects seeing your ads across channels? Do you want to prevent churn? Use case prioritization will focus your evaluation on the right vendors. 
  2. Get a clear definition of your ideal customers, so you can be more effective at targeting and engaging them. When exploring your own first-party data to get this understanding, you can take advantage of data enrichment solutions to gain important insights that will drive your strategy. Customer data platforms are useful for unifying data across first-party systems. Analytical solutions like Windfall are useful for identifying precise segments of customers (such as your ideal customers) within your dataset. 
  3. Take advantage of machine learning and propensity modeling. Ask your potential service provider some pointed questions about what kind of machine learning they provide. Once you have a trustworthy, clean customer database, and a strong understanding of your ideal customer, machine learning can help you efficiently segment customers and prospects, identify new marketing opportunities, and give you insights at scale, with minimal effort required from your team. Models such as propensity to buy, look-alike, and lead scoring enable you to acquire and engage the right people, and prioritize your outreach. 
  4. Close the loop with attribution reporting and insights. Understand what campaigns are most impactful, and continue to optimize your campaigns as you go. 

The savviest marketers out there are choosing the best-of-the-best when it comes to marketing and analytics solutions. Marketers who are able to navigate these changing waters of first, second, and third-party data are going to be well-poised for success and it’s the opinion of this author that a strategy that unifies all three types of data is going to come out on top, namely a first-party data prioritized approach with augmentation of third-party enrichment and modeling. The more you learn about what makes your customers the best customers, the more easily you find your next best customer.

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