How enterprises use their products to manage and make sense of all their data

Written by Pippa Armes  | 

5 min

 

In the digital age, everyone is facing the same dilemma: What’s a company to do with all that data?

While data management is a common consideration for companies of all sizes and stages of maturity, its complexity compounds at enterprise scale. With robust tech stacks; complicated org structures; and huge rosters of customers, clients, and employees; enterprise organizations are overflowing with data (yes, you can have too much of it)—posing both actionability challenges and security risks.

On average, enterprise organizations use upwards of 175 different software-as-a-service (SaaS) applications across their business. This SaaS sprawl leaves organizations swimming in a sea of user data, with no easy way to synthesize and make sense of it. And without the right tools or governance, teams have no way to ensure all of that information is shared and used by the right stakeholders—resulting in wasted (or duplicative) efforts across the organization, and even causing the dreaded “analysis paralysis.” 

With a product-led approach, enterprise organizations can take control of all the data at their disposal, and create a single source of truth for product and user health. This cohesive strategy, leveraging both qualitative and quantitative inputs, allows product and IT leaders to make better decisions and more easily extract themes from all the noise. It also helps them unify their internal teams, so that everyone feels empowered (rather than overwhelmed) with data and understands how their role contributes to the organization’s success.

 

They align and empower their internal teams

Product and IT leaders can help align their entire organization around a shared understanding of usage and engagement by putting product analytics at the center of their operations. With a product experience or digital adoption platform like Pendo, they can make this information easily accessible (and digestible) for non-technical teams—empowering others outside product and IT to dig into the data and find ways to steer ideal user behaviors. At enterprise scale, housing all your product and portfolio data in one place also creates reporting consistency across product lines—which ultimately saves time and resources, and drives more efficient development and iteration.

The best product-led organizations go a step further by using their product operations (product ops) function to help optimize the way the business uses product data. Particularly in the enterprise, product managers (PMs) across various product lines may rarely, if ever, interact with product teams outside their own. The product ops team plays a critical role in proactively collecting, organizing, and analyzing product data—from multiple sources and across myriad teams—and bringing it together so it’s readily available for anyone who needs to see it.

By making data the shared foundation from which all decisions are made across the organization, enterprises create a common language that unites teams across the business and empowers groups beyond just product or IT alone to confidently talk about and influence the customer and employee experience.

 

They use qualitative and quantitative data

To build the best products and digital workplaces possible, it’s not enough to just collect quantitative analytics data. You also need to tap into qualitative user sentiment to understand how customers and employees feel about your product or brand experience. The most strategic enterprises unify this effort under a voice of the customer (VoC) program, and they use their products as a primary channel through which to solicit user input. Bringing qualitative feedback collection in-app not only increases response rates, but also improves the quality of the feedback provided since it’s requested while the product experience is front and center.

At enterprise scale—where information is often scattered across platforms and teams—being able to analyze this qualitative data alongside objective usage analytics is invaluable for helping product, engineering, and IT teams operate and innovate more efficiently. It gives them the full context behind user behavioral trends and helps them prioritize their focus and resources. 

This combination of analytics and feedback is also critical for validating whether what’s on the roadmap or release plan will actually be useful for—and wanted by—customers and employees. Without this insight, internal teams risk wasting valuable time and resources pursuing the wrong initiatives that ultimately won’t return value for the organization.

 

Businesses of all sizes benefit from adopting product-led strategies—but the payoff is magnified tenfold when these tactics are leveraged at enterprise scale. Read the full white paper, 4 enterprise challenges you didn’t know your product could solve, to deep-dive into each of these four areas of friction and learn how to overcome them. 

Or if you’re ready to take your product-led learning to the next level, check out our new Product-led Certification Course, available for free for a limited time.