5 Reasons Why You Shouldn’t Build Multi-Tenant Analytics Yourself

Learn why you shouldn’t build multi-tenant analytics in-house and how a third-party embedded analytics solution enhances a SaaS product.

Every startup founder and their engineers dream of the day their brilliant idea takes flight and the company soars to new heights, but the path to product-market fit is fraught with turbulence. Only a single miscalculation can send a scrappy, determined team spiraling out of control before it’s too late to recover.

Software as a service (SaaS) companies are often tempted to minimize expenses by building everything internally. Developers’ salaries are a flat expense, and they’re usually equipped with the skill set to add analytics to a SaaS product, so founders and leadership think they’re the right choice over a third-party solution.

SaaS analytics requirements are different because they must work in a multi-tenant architecture. SaaS is multi-tenancy by nature, meaning multiple users or groups of users, also known as ‘tenants,’ need to securely access and analyze their data within a SaaS platform. Each tenant’s data remains private and separate from others in a SaaS app. Building and managing multi-tenant analytics is difficult, costly, and time-consuming. 

Choosing between building and buying is a difficult decision. But with limited resources and little room for error, investing in multi-tenant analytics from a third party always comes out on top.

What Might’ve Worked Then Doesn’t Work Now

As SaaS companies grow, they reach pivotal moments where certain decisions made in the past carry an immediate, massive impact.

For example, if you onboard only one new customer weekly, your customer success team can afford to do a lot of hand-holding. However, when growing rapidly and onboarding new customers regularly, you’ll struggle without built-in self-service capabilities like a help center.

Remember this when approaching multi-tenant analytics, too.

Once you’ve established a reliable customer base, the amount of end users leveraging reporting capabilities accelerates. End users quickly discover limitations—and you’ll be met with a never-ending list of requests. That leaves you struggling to quickly build and release more capabilities to ward off impending churn.

Facing this struggle as your product gets off the ground drags it back down. Instead of focusing on introducing new features and capabilities throughout the product, you’re stuck pouring resources into analytics functionality that could’ve been integrated from an embedded analytics vendor.

Don’t Build Multi-Tenant Analytics In-House: Here’s Why

Calculate the return on investment (ROI) of building versus buying an embedded analytics solution, and remember that time to market and customer satisfaction (CSAT) is at stake. Yes, embedded analytics significantly impacts CSAT and whether end users feel empowered by the data insights they uncover from your SaaS product or want to switch to a competitor.

Here’s why you shouldn’t build multi-tenant analytics for a SaaS product yourself.

#1. Opportunity cost

Time is your most valuable resource, especially during the earlier stages of growth. Building multi-tenant analytics in-house requires a significant investment of development time and effort. Every hour your team spends on analytics is an hour they’re not spending on developing core features, fixing bugs, or improving your product’s overall user experience (UX).

As a result, building multi-tenant analytics yourself leads to delays in your product roadmap and a slower time to market.

Building your own analytics solution also limits your ability to effectively monetize the product. With a third-party embedded analytics solution, you can experiment with different pricing models and packaging options. You can offer analytics as a value-add, include it in a premium package, or create a separate pricing tier for advanced analytic capabilities, whereas building in-house locks you into a specific approach and makes it harder to adapt to market demands.

Dan Balcauski, Founder of Product Tranquility, points out, “Organizations are absolutely not dedicating enough time to pricing. No one’s getting a bill on their desk saying, ‘You missed out on all this revenue because you’re massively underpriced.’ It’s an invisible opportunity cost.” So don’t fall victim to this by diverting resources from your core product and limiting your monetization options.

#2. Limited functionality and scalability

After introducing analytics functionality you’ve built in-house, you’ll quickly realize that your end users want more. As such, you’ll struggle to keep pace with user needs, falling into the endless trap of needing more resources while still taking on more requests.

Building a comprehensive analytics solution requires a broad range of functionalities, including:

• Diverse data visualization options: Key performance indicators (KPIs), charts, graphs, dashboards, and more
• Interactive features: Filtering, drill-downs, and data exploration capabilities
• Support for various data sources: Relational databases, NoSQL databases, and APIs
• Advanced analytics capabilities: Predictive modeling, machine learning, and artificial intelligence (AI)-powered insights
• Customization options: Personalized dashboards, custom reports, and white-labeling

Developing all of these features in-house is a daunting task, especially if you’re with limited resources and expertise. In contrast, a third-party embedded analytics platform offers a rich set of features out-of-the-box, along with ongoing updates and enhancements to ensure you stay ahead of the curve.

Further, data volume multiplies significantly as your user base increases, meaning your analytics solution needs to scale seamlessly. Building in-house, scalable analytics infrastructure is complex and expensive. However, a third-party vendor can tackle large datasets and high user concurrency to ensure zero impact on performance even as data volume increases.

#3. Maintenance burden

Building multi-tenant analytics isn’t a one-time project. Instead, it’s an ongoing commitment. Once you’ve built a solution, you’ll need to maintain it, update it, and ensure its compatibility with your product and infrastructure, which can be a significant drain on development resources, diverting them from building new features and innovating the core product.

As software development company Onix estimates, “The cost of maintenance and data-driven improvements by a couple of developers, design, and QA specialists will start from $10K per month.” It’s an ongoing cost you can (and should) avoid while ensuring your analytics solution is always up-to-date and performing optimally.

Third-party embedded analytics platforms take care of the maintenance burden. A platform handles bug fixes, security updates, and infrastructure upgrades, freeing your development resources to focus on high-impact projects.

#4. Lack of expertise to navigate development

At the very least, building a robust, user-friendly analytics solution requires specialized expertise in data visualization, data modeling, and user interface (UI) design.

SaaS companies don’t typically have this expertise in-house, and hiring and retaining specialized talent is time-consuming (and expensive). Third-party embedded analytics platforms, on the other hand, are built by teams of experts with deep knowledge of analytics and data visualization. By leveraging their expertise, you can ensure your customer-facing analytics functionality is built on a trusted foundation.

#5. Restricted growth and adaptability

The data landscape is constantly evolving—new data sources emerge, data formats change, and disruptive technologies reshape how we collect and analyze data. Building an analytics solution yourself locks you into a specific set of technologies and data sources, making it challenging to adapt outside these parameters.

Third-party embedded analytics platforms are designed to be flexible, supporting a wide range of data sources and integrating with technologies to unlock new insights and drive innovation for customers.

By choosing a third-party platform, your SaaS product’s analytics functionality is future-proofed. You can easily integrate new data sources, adopt new technologies, and expand capabilities without rebuilding the entire solution from scratch.

Choose an Embedded Analytics Platform to Build Less & Deliver More

While building in-house multi-tenant analytics might seem attractive initially, it’s important to recognize the significant challenges and opportunity costs associated.

By leveraging a third-party embedded analytics platform, like Qrvey, you gain access to a comprehensive, scalable, and maintainable solution without diverting valuable resources away from your core product. You also unlock new monetization opportunities, enhance user engagement, and drive innovation through the expertise and technology of a dedicated white-label solution.

Focusing on your strengths and leveraging specialized partners is essential in an increasingly competitive environment for SaaS companies, so when developing a SaaS product, choosing an embedded analytics platform from a partner with deep expertise often proves to be one of the most strategic decisions you can make.

Preparing to decide between building or buying? Get a deeper dive into what you need to know with Qrvey’s guide, Build vs Buy: Embedded Analytics for SaaS Providers.