Updated: January 9, 2025- 11 min read
Software monetization strategy is defined as the various actions a software provider takes to extract value from their IP and maximize profitability. When equipping your users with SaaS analytics, seamless embedding is the best way to quickly empower your users with greater insights, delivering added value. Embedding is also the best approach for offering self-service analytics. If you choose the SaaS pricing strategy of charging additional fees, such as by offering tiered pricing, embedded analytics delivers faster time to revenue.
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What Is Embedded Analytics?
Embedded analytics is the technological capability to include analytics features and functions as an inherent part of another application. Embedded analytics enables users of a SaaS application to harness the power of business intelligence to analyze the data they create inside that app in a seamless way.
SaaS analytics can impact your revenue by increasing customer retention and win rates. When you empower users to create their own dashboards and reports, they can build their own value and gain a sense of ownership, making your app stickier. You can also boost revenue directly if you charge additional fees for advanced tiers.
SaaS Pricing Strategies to Monetize Embedded Analytics
According to the Revenera Monetization Monitor, subscription/term monetization continues to be popular among software suppliers and their customers, with a total of 88% using it at least moderately. When customers purchase a subscription to your SaaS app, your pricing strategy can include offering the following types of pricing models.
1. Freemium Model
Offering basic analytics module for free
Charging for advanced or premium features
Upselling and cross-selling opportunities
2. Tiered Pricing Model
Creating multiple pricing tiers based on feature complexity
Differentiating pricing based on usage limits or data volume
Providing scalable options to accommodate different user requirements
3. Add-On or Upsell Model
Offering analytics modules as optional add-ons
Bundling analytics modules with other premium services
Leveraging the value of analytics and modules to drive increased usage
4. Customization and consulting services
Providing tailored analytics solutions for specific customer needs
Offering consulting services to help users leverage analytics effectively
Charging for implementation, training, and support services
Charging Additional Fees for Embedded Analytics
Many SaaS organizations are struggling with monetization. Nearly half of respondents to the Revenera Monetization Monitor, 44%, lack insights to monetize the most valuable features of their software. 33% of survey respondents cited inability to adopt/ implement new monetization models as barrier to growing Annual Recurring Revenue.
Amidst these challenges and a difficult economy, it can be a bit daunting to consider raising the cost of your base offering. However, most companies are trying to be strategic about their expenditures, as opposed to merely slashing budgets indiscriminately. In other words, if your app is adding sufficient value, charging more can be an effective SaaS pricing strategy. In most cases, analytics falls in the ‘must-have’ category.
The Path to ROI for Embedded Analytics
The journey to launching embedded analytics is not monolithic. It's multifaceted, often consisting of multiple production drops. Examining Qrvey customers and the progress of their deployments, we’ve identified five key events.
Targeted POC
Demo to current customers to build excitement, also a good sales toolInteractive Data Views
Interactive analytics over a tabular view of the data, users can move columns, filter, sort, etc.
Customizable Managed Dashboards
Pre-built baseline dashboards that end users can fully customize. This is typically a phase at which a SaaS provider would make an announcement.
Self-Service Analytics
End users can create, modify, and share custom charts and dashboards. This is the full MVP release.
Data Alerts & Report Subscription
End users can create custom data threshold alerts, as well as deliver reports to a subscriber group on a scheduled basis
Types of SaaS Pricing Strategies
As technology providers, we at Qrvey recognize how complicated it is to determine what new features to add and when to consider charging for extra functionality. The following are some metrics on which to base SaaS pricing strategies.
1. Volume-based pricing
There are multiple ways to configure volume-based pricing, including:
Data footprint: The amount of data that your customers bring into your platform
Lines of business: Total business areas that are using your tool, which is particularly well-suited for larger enterprise customers
Total integrations: Number of application integration touch points, for example, if your users embed your platform within multiple product lines
2. Value-based pricing
In place of any volume metrics, value-based pricing is based on the value your app delivers.
Capabilities and features
Organization type and size
Forecasted revenue: Additional forecasted revenue generated as a result of your platform
Case study: Value-based SaaS pricing
This second Qrvey customer success case recognized that embedded analytics was a competitive differentiator, delivering valuable capabilities that their customers had never had access to before. They established three subscription tiers, with some analytics included at all levels. They use value-based pricing to charge for additional analytics functionality.
Tier one is a set of interactive prebuilt baseline dashboards with access to historical data. Tier two offered more types of data, the ability to analyze different data sets, and real time data streams. Tier three delivers full self-service analysis capability.
To set prices, the organization calculated the average price customers had been paying and, with the inclusion of embedded analytics, sought to achieve at least 2X, ideally 5X within about one year. This is not a volume-based pricing model, so there are no limits on the amount of content that users can create.
3. Tiered SaaS analytics subscription model
Potential distinctions between your various tiers can include:
1. Core value proposition: The least expensive tier
2. Enhanced features and capabilities: Over and above what’s delivered in tier one
3. Content volume & scalability: Could be based on the amount of content created within your platform, data brought into it, or the total users interacting with the system
Case study: Tiered SaaS pricing
TCP Software is a real-world success case. Product Manager Joshua Rastetter explained how they uncovered the need for embedded analytics. “We polled existing customers and did some churn and win/loss analysis and determined that reporting was one of the shortcomings in our platform.”
After partnering with Qrvey for embedded analytics, TCP Software now offers three tiers: Essentials, Professional, and Enterprise. The company’s Sr. Director of Product Management, Chris Henz, said, “As Qrvey delivers advanced capabilities, such as predictive analytics and generative AI, we anticipate having the opportunity to offer that to some of our larger customers for an additional cost.”
Tiered SaaS pricing challenges
SaaS providers face numerous challenges with SaaS pricing strategies, including determining how to construct pricing models that best align value to dollars. A tiered subscription model tends to work well, ideally with two or three tiers. Extending beyond three tiers can bring challenges for sales and marketing to describe and differentiate them all. Additionally, at your least expensive tier, customers should never feel as though they're not getting anything substantive or anything of value.
To effectively monetize your app, being able to run market tests from a pricing standpoint is just as important as testing technical features. Managing multiple tiers can bring administrative challenges if you’re unable to reliably control access to functionality.
4. Usage-based pricing
Many software applications deliver value that’s not dependent upon the quantity of users. With innovations such as gen AI and automations, organizations can benefit from apps even without users being involved. OpenView’s “The State of Usage-Based Pricing, Second Edition,” stated, “The value is in the API– software talking directly to other software- rather than the UI.”
OpenView wrote, “In a usage-based pricing model, you share in your customer’s success. Your revenue grows—but only when they grow.” The OpenView survey found that usage-based businesses outperform the broader SaaS index on all metrics evaluated: YoY revenue growth, net dollar retention, revenue scale, and rule of 40. However, usage-based businesses face greater volatility in growth rates.
The Growth of Usage-Based Pricing
Usage-based pricing also benefits SaaS providers, since the expenses of delivering software vary when using public cloud providers for hosting. Public companies that use consumption-based pricing are experiencing 38% faster revenue growth over their SaaS peers and 50% higher revenue multiples, based on research from OpenView. According to the Revenera Monetization Monitor, usage-based models are used at least moderately by 79% of respondents. Rather than simply subscription or usage-based pricing, many SaaS companies today are offering more complex hybrid models.
Case study: Banded, flat-rate volume-based SaaS pricing strategy
Another successful Qrvey customer discovered that user-based volume was not a suitable pricing metric because it puts pressure on their customers to determine exact usage needs, while also leading to unpredictable pricing. Instead, they decided to use volume-based pricing, and established pricing bands based on the total employee count of each customer. This metric correlates with both the size of an organization and likely also correlates with the amount of data to be analyzed in the platform.
Next, they had to determine the actual prices and chose to charge based on a percentage of their customer’s total ARR. But rather than having a total ARR different for every individual customer, they simplified the pricing strategy by defining two bands. Prices were then set based on the largest total ARR within each band. This pricing model also factors in platform hosting costs and license costs to cover data volume, as well as onboarding and maintenance costs. Both packages included all the functionality of embedded analytics, but the base package imposed limits on the volume of content that users can create, whereas the enterprise package had no limits.
What Is Self-Service Analytics?
Self-service analytics deliver “DIY” functionality to non-technical end users. Users can interact with self-service analytics, change filters, and combine data in different ways. Ultimately, users can build their own forms, charts, reports, metrics, or even workflow automations – and without heavy reliance on support teams or data scientists.
How self-service analytics create value
Data by nature is a complex phenomenon. There are many ways to look at it and many techniques to analyze it. Every user approaches their analysis differently. The goal of self-service analytics is for users to serve their own specific needs and answer their own questions.
Self-service analytics remove technical barriers, so no technical skills or advanced data science insights are required. They are also the fastest way for your users to help themselves to the information and insights they need to make better, faster, more informed decisions.
Monetizing self-service analytics
Advanced functionality such as self-service analytics, advanced analysis, and workflows, can boost productivity and empower workers to make more intelligent decisions, enhancing the value of your app.
Whether SaaS providers charge additional fees or not, embedded self-service analytics also boost customer retention, dramatically reducing churn. Self-service reporting delivers actionable insight to end users, optimized to their particular workflow. Users who have developed a series of reports to obtain the information they need are less likely to leave for another vendor where they’d need to start over.
Invest in Customer Education
Whatever SaaS pricing strategies you choose to offer, you should essentially ‘sell’ the functionality to existing customers so they can understand what is available, and how to take full advantage of it.
Your customer success initiatives must exceed mere support tasks like bug fixes and responding to inbound inquiries. Help content should also expand beyond explaining how to execute a specific task and also tell them what they ought to do. Inspire customers to explore the numerous possibilities your new embedded analytics offer. Instead of only simple step-by-step instructions, also include best practices and ways users can optimize their business with your app.
Embedded analytics can boost your revenue and retention rates. Analytics can be monetized by charging additional fees, but SaaS providers must tackle the challenges of delineating tiers and setting prices. In particular, usage-based pricing is shown to drive success, with public companies that use it experiencing faster revenue growth. Finally, self-service analytics further drive revenue and retention by removing technical barriers and empowering users to answer their own questions.
Qrvey can help you quickly and seamlessly embed analytics into your app in order to access new monetization strategies. Dig into these monetization strategies and more in our Product School workshop:
Updated: January 9, 2025
