Data is essential for modern marketing. But too often, «data» is used in the digital marketing space as a convenient catch-all term to convey complex information and procedures, with the implicit assumption that everyone understands its meaning. Many times, that couldn’t be further from the truth. «Data» ends up meaning different things to different people in different teams, departments, and organizations.
Arguably, this expansive definition of data is what makes it such a popular concept. When people talk about data in the digital marketing world, they often think of it as the solution to all marketing ROI problems, dissatisfied customers, disappointing product features, and other issues that contribute to poor overall performance. But while data IS extremely important, it is not a miracle cure that can fix everything that ails a business.
Achieving data-driven customer engagement requires planning… and the right martech stack.
For data to truly benefit your company, there needs to be a shared understanding across the organization about the details of your data strategy: where data is collected, how it is used and shared among teams, and—most importantly—data quality standards. That’s when «data» stops being just a buzzword and becomes a strategic asset of real importance.
Data enables customer engagement, but leveraging data without context is simply impossible. That’s why companies have placed so much importance on the technologies that make up their marketing technology stack—or martech stack—especially now that customers interact with brands across multiple devices and platforms.
Consumers expect brands to understand them and communicate seamlessly as they switch from one device to another. Any experience that isn’t completely frictionless falls short, and to achieve this, brands must have access to relevant, real-time customer data.
To fully understand and capitalize on how customers engage with your messages and digital properties, you need a top-tier martech stack or martech ecosystem. But before you can build one that fits your brand’s unique needs, you need to understand what’s possible today—and how we got here.
Customer Data Management: Where Are We, and How Did We Get Here?
When mobile devices entered the scene over a decade ago, they introduced an entirely new realm for customer engagement. Suddenly, customers could access apps and websites on the go and receive messages wherever they were. This transformed the customer experience and added layers upon layers of new data points that could be used to tailor messaging more effectively, driving better outcomes. However, enthusiasm for mobile marketing waned slightly when it became clear that collecting and using all these new types of data was not as simple as expected.
The Challenges of Mobile Marketing with a Web-Based Martech Stack
At the time, most companies viewed their mobile data strategy as an extension of their existing web-based data strategy. Unfortunately, while web-centric martech stacks could be adapted to work with mobile, their architecture was never designed with mobile in mind.
To make sense of all this new information, marketers and engineers attempted to manually piece together disparate data sources, pushing what they had assembled into other systems. (Imagine endless CSV files and countless hours cross-referencing datasets just to keep records up to date.)
As brands struggled to keep up with their mobile data, their customers were receiving emails, push notifications, and other messages that didn’t make sense to them. They also experienced increasing responsiveness issues due to apps being overloaded with third-party code.
Using a Single Provider (And Its Drawbacks)
Major marketing cloud providers argued that the problem was brands using too many different tools for different functions within their apps. Their solution? Rely on a single monolithic provider (i.e., themselves) for everything.
To realize this vision and quickly take over every aspect of their clients’ tech stack, major marketing clouds began acquiring existing vendors specializing in different customer-related functions, effectively assembling an all-in-one stack. This time-tested strategy allowed these large clouds to expand their service offerings much faster than they could have if they had built all that functionality in-house. However, they quickly encountered the same problem as the businesses they aimed to help: they couldn’t connect or coordinate data across their own systems.
Because the different tools they had acquired were developed independently and then bundled together, many simply weren’t capable of effectively transmitting information between them. This left brands back where they started (minus a significant amount of money). But the frustration of being unable to do something as basic as connecting data across tools had an unexpected benefit: it inspired others to find ways to create a truly functional system for collecting and using customer data across mobile, web, and beyond.
🏆 From Learners to Masters of 1:1 Engagement
That brings us to today. In the past few years, we’ve seen more changes in how we view and act on customer data than in the previous 30 years combined. This might seem like a bold statement, but just compare the ads and messages people received at the start of the decade to the hyper-relevant, responsive, and personalized customer experiences possible today—from location-based ads to dynamically adjusting push notifications based on in-app or website engagement.
So, what changed and how?
A major shift was the evolution of companies’ martech stacks. These data stacks have not only become more complex but also more efficient.
A Shift Toward Specialized Tools
Rather than providers trying to do a little bit of everything, the martech ecosystem has become highly specialized, offering brands more options for nearly every customer-related need.
Different teams within an organization have different requirements, and the rise of purpose-built data management, engagement, and marketing technologies has enabled brands to create unique technology ecosystems tailored to their teams’ specific business objectives.
These hybrid stacks—built with best-in-class components—have proven ideal for supporting today’s agile marketing and sales operations while paving the way for more personalized and impactful customer experiences.
You might be wondering how adding more tools to the equation could make it easier to connect and activate customer data. Your skepticism is understandable, given recent history. But while these tools are defined by their specialization, they also differ from past solutions in a key way: this new generation of tools was designed with data agility and connectivity in mind.
Solutions like Braze and Amplitude, for example, were built around the idea that customer data is only valuable if brands can use and learn from it effectively.
Using a Customer Data Platform (CDP) like Segment allows brands to collect customer data from every relevant tool, digital property, and touchpoint and centralize it. These data points are then cleaned and transformed so they can be seamlessly shared with an engagement platform like Braze. A CDP eliminates data silos and minimizes the need for manual data processing and uploads across multiple engagement channels.
Similarly, solutions like Amplitude provide access to a centralized data repository with an easy-to-use interface, ensuring that everyone within an organization can access collected data without relying on backend technical work. Giving teams access to data fosters a truly data-driven culture. A shared understanding of what data means and where it comes from allows everyone to use it for decision-making, enabling smarter collaboration and better results.
Adopting an integrated martech stack also benefits your digital properties by improving integration timelines and performance across the stack. A CDP can serve as a connecting layer between some or all of these technologies and the rest of your tech ecosystem, reducing dependencies without sacrificing the benefits of a top-tier martech stack. And, of course, connecting data from every touchpoint across the ecosystem to your customer engagement platform enables you to create and deliver personalized messages across mobile, email, web, and more—making the entire process worthwhile.
Building the Martech Stack That Fits Your Needs
Your company’s customer engagement needs are as unique as your customers. Different brands with different strategies and business models naturally require different tech ecosystems to meet their specific needs.
Conclusion
Your martech stack plays a crucial role in determining the long-term success of your engagement and retention efforts. Get it right, and you can deliver the relevant, personalized, data-driven experiences customers crave. Get it wrong, and your brand risks delivering frustrating experiences to your audience.
