AWS Public Sector Blog

4 steps EdTechs can take to grow their profitability on AWS

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The education technology (EdTech) sector is rapidly evolving, leveraging the latest technical capabilities to continuously improve student learning and institutional objectives. The sector received huge investment from venture capital, private equity firms, and IPOs (initial public offerings) on the back of the rise in hybrid learning. However, as HolonIQ reports in its 2024 Global Education Outlook, funding sources slowed across the board in 2023, dropping 59% from 2022 levels. EdTech leaders must strike the right balance of investment to drive growth, and a return on investment for their owners.

This blog post outlines the profitability framework that Amazon Web Services (AWS) uses with customers. The AWS framework helps EdTechs improve cost efficiency, assess functionality expansion, and grow market share, by aligning pricing with solution value to students and institutions. Around the world, AWS teams help customers like Doping Hafiza, Alef Education, and BriBooks use cloud as an enabler for continuous innovation, product differentiation, and business growth. More than 4,500 EdTechs globally turn to the scalability and security of AWS to deliver their solutions. At AWS, we believe that optimizing IT costs (including cloud) helps unlock budget to invest in more innovation.

Understanding the challenge

EdTech leaders regularly ask us to support their growth and profitability by enabling their innovation agendas. Successful EdTechs balance innovation (for example, new features or technology, like generative artificial intelligence (AI)) with managing costs – both of product development and of operating costs for customer environments. This tradeoff works best when organizations embrace FinOps, Cloud Financial Management (CFM) best practices that take a data-driven approach to maximizing business value from cloud spend.

The following framework demonstrates how EdTechs can improve their understanding of cost and profit drivers. Visibility into ‘unit costs’ (for example, the cost-per-student of a solution) helps budget and product owners demonstrate a connection between the demand for an application and how this demand influences cost. This will result in more accurate cost forecasting, and drive viable business models and pricing strategies.

Applying the CFM framework in your company

The methodology follows a four-step, data-driven approach:

1. Identify the ‘unit-measure’ for each of your applications, meaning the actions that users take that relate directly to your solution’s value proposition. Some examples of this include cost-per-module, cost-per-student, and cost-per-platform-usage-minute.

2. Review your application’s cloud cost structure. Use tools like AWS Cost Explorer, and AWS Cost and Usage Reports (CUR) to get a granular understanding of your costs and understand what factors have most impact on the total cost. Here are some areas to investigate:

  • Identify if application costs are fixed or variable, in line with levels of usage based on the ‘action’ metrics identified. Most EdTech solutions have variable usage: peaks during the day, if used within a classroom setting; usage peaking in evenings and weekends if they support self-study; or perhaps peaking in the run up to exams or at the start of a new term.
  • Assess your application’s efficiency by comparing the application usage pattern to the cost profile. If user activity varies, then cloud costs should ideally be variable, reflecting that cloud resources are scaling with demand.
  • Derive the ‘unit cost’ of your application using the costs and usage metrics to understand how ‘variable’ this cost is.
  • Combine insights from the Cloud Intelligence Dashboards in Amazon QuickSight with your unit volume data to develop a unit cost dashboard, similar to the table and graph below.

Consider the following three fictional application scenarios to understand why unit cost matters. For each illustrative application, student demand peaks during the day and tails off through the evening and into the night.

table that demonstrates comparison of unit cost per student for three different scenarios of cloud spend and variability

Figure 1. This table compares the unit cost per student across three fictional applications, each with different levels of cloud spend and variability.

Now, let’s compare the cost efficiencies of each application:

Application A has a fixed cost of $400, so when demand is low the ‘unit cost’ per student is high.

Application B has more variability of cost, in line with usage, but unit costs are still higher when fewer students are using the application, as some costs are fixed.

Application C is the most variable and highly scalable, and therefore the unit cost is very consistent, and costs are very efficient – around one-third of application A.

The following graph shows the difference in cost variability by application across consistent usage.

bar graph displaying peak users and unit cost across three example applications

Figure 2. This graph depicts the difference between unit costs per user across the three fictional example applications.

3. Review your sales pricing model. Use your understanding of unit costs and variable usage patterns to reevaluate your pricing model.

  • How do you charge customers? For example, per usage, per student, per seat, or by flat charge with add-on options for additional functionality?
  • If you have a freemium model, what’s the conversion ratio of free to paid? How much do free tier users cost you? What user volume would you need to reach (at current unit cost) to break even? If you could reduce unit cost, how much sooner would you reach the break-even point?
  • What changes do you need to make to your pricing model, for current or future customers, to remain competitive? Do you consider the extra cost of adding new functionality and consider cost as part of product design decisions?

4. Enhance your forecasting model. Use the preceding inputs to refine and develop your forecasting model.

  • Compare the unit costs, usage volumes, and pricing structure to calculate customer or contract profitability.
  • Use the forecasting model to set a plan with your technical team for application modernization. For example, serverless computing technologies feature automatic scaling, built-in high availability, and a pay-for-use billing model to increase agility and optimize costs.

How customers are applying CFM to improve their profitability

Wonde is a global provider of data integration solutions for schools’ management information systems (MIS). Wonde develops innovative solutions and high-quality services so schools can operate with confidence in the security and accuracy of their data. More than 29,000 schools enhance connectivity using Wonde’s technology, managing pupil and application data in a simple and secure way.

The Wonde team approached AWS for help conducting a high-level analysis of costs and usage, specifically focusing on API costs. Jon Clatworthy, Wonde’s global strategic partnership manager, said, “Our aim was to have better transparency and understanding around the costs to Wonde for using AWS services so that Wonde continues to provide the best possible solutions for our customers and partners. AWS’s cost management guidance will be immensely valuable as we plan and prioritize our business decisions.”


This data-driven approach to your application costs will enrich your understanding of your AWS costs, how AWS resource usage drives cost, and how demand for your application influences this resource usage. These insights will help you to better assess your application’s resource efficiency. They will also help you improve cost and revenue forecasting granularity and accuracy, and provide a foundation for adding new features and functionality, vital components for growing your EdTech profitability.

AWS works with EdTechs to invest in the right features to support their business growth goals, like increasing their customer base and driving more customer loyalty. Get started today by contacting your account team for support, and download the ebook, AWS Cloud Financial Management Guide, to learn more about how to evolve your financial processes for cloud.

Kevin Long

Kevin Long

Kevin is a principal FinOps strategist at Amazon Web Services (AWS), focused on public sector organizations in the EMEA region. He advises executive stakeholders with developing a robust approach to Cloud Financial Management and the development of FinOps capability. Kevin is a chartered accountant (ICAEW, FCA) and has worked in the technology sector for most of his career, with a focus on using data to deliver tangible business outcomes.

Mazen Abdallah

Mazen Abdallah

Mazen is an education technology (EdTech) and publisher industry business development manager at Amazon Web Services (AWS). He supports EMEA (Europe, Middle East, and Africa) customers with strategies to grow and innovate on top of the AWS Cloud. Mazen has more than 15 years of experience as a business leader and IT executive in different geographies in the Middle East and US.

Maryclaire Abowd

Maryclaire Abowd

Maryclaire is a business development manager for worldwide public sector global education at Amazon Web Services (AWS).