Top 10 Sources of Hidden ROI in Embedded Analytics

Analytics play an important part in nearly every SaaS application. As user expectations for real-time analytics rise, your analytics experience becomes a critical feature.

If your development team is still building analytics features in-house, they may be feeling the pressure of meeting user expectations. That's common. Building multi-tenant analytics is hard, and incredibly time consuming.

Most executives realize the value third-party solutions offer in quickly delivering best-of-breed capability. Buying and embedding analytics means you no longer have to build, which saves time and frees up dev resources. But the returns SaaS providers can gain from investing in embedded analytics extend far beyond time savings. Following are 10 ways in which you can earn ROI on embedded analytics.

Cost Savings of Embedded Analytics

Our first four sources of hidden ROI pertain to the many ways you can reduce costs with embedded analytics.

1. Reduced development and engineering efforts

Your app contains data that your users will want to analyze. Sometimes it's data from custom properties or your out-of-the-box data sets. No two customers will want to analyze data the same way, either. Growing customer demands for reporting and analytics features quickly adds complexity for your development team.

Meanwhile, developers, data engineers, and software engineers are all in short supply. IDC reports that a lack of IT skills will affect nine out of ten organizations by 2026. This shortage could lead to $5.5 trillion in delays, quality problems, and lost revenue. The U.S. Bureau of Labor Statistics shows almost 200,000 developer jobs will need filling each year through the end of the decade.

Building analytics in-house to deliver insights requires building out a data pipeline. This pipeline must allow for data ingestion, transformation, and visualization, which takes a considerable investment in developer time.

On the other hand, embedded analytics delivers the entire data workflow, leveraging APIs to connect systems, automation to transform data, and visualizations to render output to end users.

Embedding analytics requires some development effort, but the embedding process can be completed in a tiny fraction of the time required to build everything from scratch. Compressing this timeline delivers faster time to value while reducing development costs.

2. Lower infrastructure costs with cloud-native technologies 

More people are using business applications than ever before. B2B SaaS applications must handle even more data as companies integrate an ever-increasing number of data sources. All the while, users continue demanding more capabilities.

For SaaS providers, that means your app must scale efficiently and cost effectively to enable profitable growth. Cloud-native apps are ideally suited for these challenges.

Public cloud infrastructure enables smooth growth with corresponding gradual increases in cost—and cloud-native applications take this value even further. Scalability with microservices is better since you can scale each component independently when and where it’s needed. This improves both efficiency and cost-effectiveness. 

Amazon Web Services (AWS) was the first public cloud provider. Amazon also pioneered cloud-native technology with the introduction of AWS Lambda, the first serverless platform, in 2014. (Many people probably don’t know Amazon was first created as an online bookstore. Yes, they shipped physical paper books to consumers.) An AWS Whitepaper explains, “AWS Lambda allows you to upload your code, automatically scaling and managing its execution with high availability. This eliminates the need for infrastructure management, so you can move quickly and focus on your business logic.”

By harnessing the power of cloud-native technology, embedded analytics solutions can also deliver scalability and cost-effectiveness.

3. Easier data compliance

Sending data between systems and platforms creates a security vulnerability. If you choose to embed third-party components, it’s important to select products that deploy directly into your own environment(s). With a self-hosted solution, your data never leaves your control; your analytics run entirely inside your environment, inheriting your security policies, which is ideal for data security and governance. 

This enables you to manage data security by ensuring data quality and governance, maintaining compliance with regulations like GDPR and HIPAA. Save time by eliminating the need to create and maintain custom multi-tenant security models.

Additionally, self-hosted analytics capabilities are faster to develop, test, and roll out. You’re also never beholden to another company’s release schedule or performance scaling. If your app is multi-tenant, make sure the security tools and features of your embedded analytics solution support this architecture, ideally inheriting your security model, including all of your rules and policies.

4. Control software maintenance and upgrades

Embedded analytics software deployed to your environment leaves you in control of software update schedules. Most SaaS companies deploy updates on a regular basis within their agile process (e.g. weekly, monthly, quarterly) so being able to deploy updates on your schedule is important.

Infrastructure also plays a role in the software development lifecycle, or SDLC. When you are forced to buy server licenses, it acts as a deterrent to standing up additional instances in lower development environments. Those testing and development environments are important to software development organizations, and they are so simple that pay-as-you-go infrastructure removes that barrier.

Monetization Opportunities

The ROI of embedded analytics consists not only of cost savings, but revenue gains. SaaS executives benefit from viewing their analytics offering as an opportunity for new revenue and growth, rather than another mere component of the road map. Analytics can transition from a cost center to a revenue center. We’ve outlined some common ways companies can monetize advanced analytics.

5. Upsell customer accounts

When adding new analytics functionality, you could offer it as a free value-add, increase overall cost, or offer optional analytics components for an additional license fee. You could also combine these tactics, such as providing new reports for free while also offering custom dashboard creation at higher license tiers. 

Advanced analytics, such as custom dashboard creation, are particularly well-suited to serve as a premium feature for an additional fee. With these upsell opportunities, you can increase revenue from your existing customer base. 

6. Offer professional services

A full-featured analytics offering should include self-service capabilities, such as custom dashboard creation. Ideally, such capabilities will also be easy to use. When equipped with a robust help center with clear instructions and videos, most users will be able to get up to speed quickly. However, sometimes, users appreciate a helping hand with even the most intuitive technologies.

When embedding analytics, you can also offer professional services to help users build dashboards, set up automation, or even help with initial data preparation functions. Professional services can become another avenue to grow account value as a source of non-recurring revenue. 

7. Increase customer lifetime value

With embedded analytics, you can provide users with a broader expanse of analytics by incorporating more data points, and even enabling reporting on customer-defined data. This expands the utility of your app, potentially making it useful to more employees within each customer’s organization. Spreading further into each user’s organization, you can increase Customer Lifetime Value among your existing customers.

8. Build competitive differentiation

Advanced analytics, whether offered for free or at higher-priced tiers, can differentiate your app, making it more competitive and increasing your win rate. Differentiation, especially in crowded markets, can have a powerful impact. When you get to market faster with a superior offering, your prospects will take notice, and your sales team will be grateful. And the more you can accelerate your growth, the faster your company valuation rises as a result.

Future Growth

In addition to direct monetization strategies, there are less quantifiable ways to build value with embedded analytics.

9. Focus on your core value proposition

Opportunity costs are often overlooked in ROI calculations. Building analytics unavoidably results in less time to build your core functionality. While it’s difficult to assign a dollar figure to this opportunity cost, there’s great value in focusing on your key strengths. Each company sets out to focus on a problem, but that is rarely an analytics problem. Engineering and product teams typically prefer to stay focused on their core mission. Buying and embedding third-party analytics instead of building in-house allows your product teams to keep that focus.

Every hour your team spends building analytics is an hour not spent staying ahead of your competition. Analytics is not your core competency, which means adding analytics will take you longer than you expect. It will also create drag for your entire product roadmap as valuable resources are slowly siphoned away.

10. Continue to Innovate with [nearly] zero effort

A SaaS roadmap is never “complete,” considering the perpetual need to innovate and improve the utility you deliver to users. Your analytics component is no different. In addition to regular maintenance and upgrades that your analytics components will require, you’ll need to deliver expanded and improved functionality to maintain parity with competitors.

But with third-party embedded analytics, you can gain the benefit of perpetual improvements without perpetual development effort.

Achieving an ROI with embedded analytics starts with a realization that building yourself is rarely the best option. SaaS companies that move beyond building everything in-house are free to open themselves up to new ways of working and new revenue streams.

Realizing an ROI with Qrvey does not require years to achieve. Combining cost savings with new monetization strategies creates an ROI that is easy to justify.

Learn how to ensure the ROI of your embedded analytics investment in our Product School workshop: