As a SaaS company leader, you’re constantly making decisions that have long-term effects on your company and your products. One of the biggest decisions facing product leaders will always be the build vs buy scenario. Should we build or buy? I’m sure our team can build it for a fraction of the cost right?

It’s an easy trap to fall into when you don’t have direct experience with the advanced functionality you need in your product to stay competitive. Analytics is easily one of the most under-estimated features in the build vs buy scenario.

In the case of Embedded Analytics, there’s actually more to it, however. I’ve been watching companies for 20 years struggle to get off the ground with their analytics offering, especially now that nearly all tech companies are SaaS companies. In reality, there are multiple phases to fully achieving their product goals, but most haven’t been able to reach the pinnacle with the traditional BI vendors. Here I outline four phases:

Phase 1: Build the components

This is the natural place to start. Most SaaS companies think they can build their own components or take some off-the-shelf charting library and call it a day. Customers are smarter than that though. If you offer a half-baked solution, they know it and they’ll call you out on it.

Phase 2: Embed the components

Embedded BI was supposed to be the answer to this solution. The traditional BI vendors began offering embedded analytics software features to their legacy products. So, many tried to integrate these monolithic solutions, built for single-tenant data structures into SaaS platforms with multi-tenant data security needs. It never went well. They’re still advertising these benefits on Linkedin today, but most are just static dashboards with some filters that can be changed while viewing. SaaS leaders deserve more.

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Phase 3: Embed the builders

A handful of these traditional BI vendors that made a move into embedded BI began offering their dashboard builders as embeddable components. (I won’t use the term “widget” because that implies it’s simple, and this is anything but simple.)

This had potential, but there’s one big gap in this strategy: it doesn’t account for the data layer. The embedded builders are just that: a builder. Not a full-stack data solution and certainly not an end-to-end solution to offer their customers.

There is still a need for a data processing layer that has to transform data for multi-tenant security and analysis. The graveyard is littered with companies that attempted this route only to abandon their efforts or cut bait and try a different approach.

Phase 4: An integrated no-code solution

SaaS companies are oftentimes B2B2B software companies. They have another layer of end-users to account for. So while the company that builds the platform has the customer accounts, the OEM software providers (like Qrvey), have to design a system that is easily usable for the SaaS platform’s customer’s end users….the end-users within each account/tenant.

That’s where the no-code revolution comes into play. Easy to use, drag-and-drop interfaces that SaaS end users can use to make custom analysis and automation processes specific to their business needs. That right there is the holy grail for SaaS companies offering advanced analytics.

To build on that point, a third-party solution is only successful when it offers real value to the product teams building the platform AND the customers of that platform. A successful solution has four primary characteristics: Security is a top priority. In a multi-tenant environment, your customers are assuming a great deal of risk.

Therefore, security in terms of storage and retrieval along with integrated authentication and authorization are a must-have. No way around it. Tight integration. This will become part of your SaaS platform, not an external site you send people to.

As data comes into your platform, it needs to be readily available for analysis, but also must stay up-to-date with changes on your platform. It looks like your system.

On the topic of tight integration, a customizable look and feel is also necessary. Users are supposed to think it’s all one platform and that can’t be achieved without UI customization capabilities.

Embedded Analytics should be self-hosted. This may seem counterintuitive considering how much I talk about SaaS companies, but this is truly the strategy to achieving the previous three items. When a third-party solution is hosted within a SaaS environment, it offers the tightest integration and security options available. (Not to mention the most cost efficient) It’s really not an “embedded” solution without this characteristic.


I hope you can begin to understand there’s more to this topic than most people think. SaaS leaders are waking up to this fact as well as we see how many are searching for better solutions to their analytics problem.

Where are you in this analytics journey?

Have you tried or watched others try and get stuck in one of these four phases?  

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