Build Vs Buy Analytics: Pros, Cons and Cost Considerations

Let’s cut to the chase: do you build your own customer-facing analytics, or let someone else do the heavy lifting? At first, building sounds like the obvious choice—nobody knows your app better than you, right? But here’s the plot twist: multi-tenant analytic platform gets messy. Fast. Before you know it, you’re neck-deep in complexity. Building feels less like a savvy move and more like trying to assemble IKEA furniture without the instructions.

This guide dives into the key considerations of whether SaaS companies should build or buy their analytics solution. We’ve added a healthy dose of humor and practical advice to help you make an informed decision.

Key Takeaways

• Building your custom solution gives you full control but comes with serious headaches: time, cost, and ongoing maintenance.
• Buying is faster, easier, and often cheaper in the long run—but comes with trade-offs like dependency on a vendor.
• Analytics isn’t just charts and graphs; it’s complex, resource-intensive, and requires specialized expertise in data engineering.
• The decision hinges on your goals, timeline, and budget—regardless of how much you enjoy DIY projects.

Why Consider Building vs Buying Analytics?

Here’s the deal: at some point, every SaaS company hits the “we need analytics” wall. What is embedded analytics anyway? In brief, embedded analytics means adding data analysis tools into apps your customers already use, so they don’t need extra software to run analysis.

Customers want insights, competitors have flashy dashboards, and your product feels naked without data. SaaS products in particular need data analytics to thrive. Whether you’re trying to stand out in a crowded market or retain demanding customers, analytics has shifted from a ‘nice-to-have’ to a ‘must-have’ feature. But what exactly is SaaS analytics? It refers to the process of collecting, analyzing, and interpreting data to help Software-as-a-Service businesses improve their products, enhance user experience, and drive better decision-making.

Building means you’re in full control, tailoring every pixel and feature to your app. But buying gets you to market faster with less risk and fewer headaches. The trick is figuring out what makes sense for your business — and weighing the risks and rewards of both build and buy strategies

See how our analytics works for every industry.

Why Build Your Own Analytics?

Building analytics in-house has one key benefit: total control. You get to decide how it looks, feels, and functions. If your product is super niche, this can be a game-changer.

But here’s the catch—building analytics capabilities is hard. It’s not just dashboards; it’s data pipelines, security, and constant updates. It’s especially hard when you’re dealing with multi-tenant analytics. Unless you’ve got a team of data wizards (and infinite patience), building your own might be more trouble than it’s worth.

Why Buy an Analytics Solution?

Buying analytics is like ordering takeout: it’s fast, convenient, and comes with fewer surprises. Pre-built solutions are designed to scale, packed with advanced features like self-service analytics, and maintained by experts so you don’t have to.

The downside? You’re tied to a vendor’s roadmap and licensing fees. But for most SaaS companies, the trade-off is worth it. Your customers will be happy and you’ll have an easier time retaining them. After all, why build a spaceship when someone’s already selling them?

Considerations and Feature Requirements When Deciding to Build or Buy Analytics

When making the build-or-buy call, keep these factors in mind:

Data Security

Building your own solution means you can customize security… but it also means you’re on the hook for compliance, audits, and fixing anything that breaks. Data Security in Multi-Tenant Analytics is an important aspect to consider in this case. Buying gives you pre-baked security features, often certified and ready to roll.

Customization

Building wins on customization, hands down. But modern embedded analytics platforms come pretty close, offering flexible dashboards, automated workflows, a well-designed user interface, and white labeling options for a great user experience.

Cost

Building advanced analytics capabilities isn’t cheap. Between developer salaries, tools, and maintenance, costs can skyrocket. Buying spreads the expense over time and often costs less overall.

Development Time

Let’s be honest: building takes forever. For many, it ends up taking years. Buying means you’re up and running with an MVP in weeks.

Build vs Buy Analytics Benefits Comparison Table

Factor	Build	Buy
Costs	High upfront costs; ongoing maintenance expenses.	Predictable licensing fees; lower total cost of ownership.
Support/Training	Requires in-house expertise and training programs.	Comprehensive support and training included.
Advantages	Complete control over features and design.	Speed, scalability, and continuous updates.
ROI	High potential ROI if resources and time are well-managed.	Faster ROI due to quicker deployment and pre-built features.
Resources	Heavy reliance on internal teams and long-term dedication.	Minimal internal resources required; vendor handles updates.

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Hear from Qrvey’s CEO on 4 deciding factors in this video.

Drawbacks of Building an Analytics Solution

Let’s talk about the cons of building multi-tenant analyticg… because building isn’t all rainbows and unicorns.

Development Costs

Building your own analytics solution isn’t just expensive—it’s unpredictably expensive. Initial costs may be reasonable but the budget can quickly spiral out of control, often doubling or tripling when unforeseen challenges arise, leaving you with significant financial strain.

Maintenance and Updates

Congratulations, you’ve built your analytics solution! Now get ready for the never-ending task of maintaining it. From updates and bug fixes to adding new features, your team will be tied up indefinitely just to keep it running smoothly. That’s not to mention the dedicated support teams you’ll need to address questions.

Delayed Time-to-Market

Time is your most valuable resource, and building analytics from scratch eats up a lot of it. Every hour your development team spends on analytics features is an hour not spent improving your core product. This delay slows your roadmap and pushes back your time-to-market, while competitors who choose third-party solutions are already winning customers with sleek dashboards and features.

Lack of Expertise

Creating robust analytics isn’t something you can fake. It requires core competencies in data modeling, visualization, and security. Hiring and retaining experts in these areas is both costly and time-consuming, stretching your resources thin, and you face opportunity costs for not investing in something you are an expert in.

Limited Functionality and Scalability

As your SaaS business grows, so do your analytics demands. In-house solutions often can’t keep up with advanced features like predictive analytics, diverse visualizations, and handling many concurrent users. Embedded analytics platforms, by contrast, are built to scale and come packed with advanced capabilities to support your growth.

Restricted Growth and Adaptability

The world of data evolves rapidly, and in-house solutions can leave you stuck with outdated frameworks that are hard to upgrade. Embedded analytics platforms are designed to adapt to new technologies and data sources, giving you the flexibility to grow and innovate without being held back.

Drawbacks of Buying an Analytics Solution

Buying isn’t perfect either. Here are a few downsides:

Vendor Dependency

When you buy, you’re tied to someone else’s roadmap. If they lag on updates or support, it can hurt your product.

Limited Customization

Even the best platforms have limitations. If you need something truly unique, you might feel boxed in without your in-house team to create it.

Licensing Costs

Recurring fees can add up, especially as your user base grows. It’s important to factor this into your long-term budget.

ROI Calculation for Buying vs Building Embedded Analytics

Let’s talk numbers. Building might seem like the cheaper option upfront, but the hidden costs—time, maintenance, and unexpected overruns—can eat into your ROI fast. Buying, on the other hand, delivers quicker wins by getting you to market faster with a polished product.

Time to run a cost-benefit analysis. To build the required functionality, you need a developer. Let’s say this developer takes a full year to complete the project and has an annual salary of $140,000. But don’t forget what comes after launch: maintenance. Let’s estimate that maintaining and improving the solution would take 30% of their time each year, adding $45,000 in ongoing costs. With expected benefits of $140,000 each year after the initial investment, you’d achieve a return on investment (ROI) of 18% over three years, breaking even after 2.7 years.

Now, consider the “buy” option instead. It slashes development time in half, costing just $70,000 upfront and $22,000 annually to maintain. Add $48,000 a year for software, $5,000 for support, and $4,000 for first-year training.Guess what? You go to market six months sooner, gaining $70,000 in additional benefits in the first year alone. This faster time boosts your ROI to 27% over three years. You’ll break-even in under two years.

Not convinced?

Use this build vs buy calculator to uncover the hidden costs and find your ROI.

Deciding Whether to Build or Buy Embedded Analytics

Here’s the bottom line: if you have unlimited resources, a rockstar team, no real delivery deadlines, and a deep love for complex projects, building might be for you. But for everyone else, buying a proven analytics platform is the smarter, faster, and less stressful choice.

Curious about potential vendors?

Let Qrvey Handle the Heavy Lifting: Our embedded analytics platform is built to scale, packed with features, and ready when you are. Learn more today.