MSP Pricing Models: Strategy & Best Practices
Managed Service Providers (MSPs) face a significant challenge in developing pricing models that align with the latest technological advancements and customers’ evolving needs. With the popularity of the public cloud, containers, and serverless computing, traditional pricing models based on devices or users are less relevant. To address this issue, MSPs must adopt innovative pricing strategies that align with customer outcomes and value. This article explores some of the best practices for MSP pricing models to increase profitability, control costs, and deliver better value to customers.
Summary of key MSP pricing models
We summarize key MSP pricing models in the table below for reader reference.
|Flat-rate pricing model
|Charge clients a fixed monthly or annual fee for managing their cloud infrastructure, regardless of resource usage. This model offers simplicity and predictability for clients but won’t account for variations in consumption, so it may have to be re-negotiated every few months.
|Pay-as-you-go pricing model
|Bill clients based on their actual resource usage, measured in granular units such as compute hours, storage capacity, or data transfer. The pricing uses servers, containers, or serverless functions as its basis, depending on the application architecture. This model closely aligns with cloud providers’ pricing structures and offers clients more flexibility and cost control.
|Tiered pricing model
|Offer clients multiple pricing tiers, each with a predefined set of resources and services. Clients can choose the tier that best fits their needs and budget, while MSPs can upsell additional features or resources as necessary.
|Percentage management fee pricing model
|Charge clients a percentage of their total cloud spend as a management fee. This model naturally incurs a higher cost for managing larger environments but won’t incentivize the MSP to optimize cloud spending.
|Performance-based pricing model
|Set pricing based on the performance metrics or SLAs achieved by the MSP in managing the client’s cloud infrastructure. This model aligns the MSP’s incentives with the client’s desired outcomes and fosters a results-driven partnership.
|Value-based pricing model
|Value-based aligns the long-term interests of providers and increases the likelihood of beating competitors during bake-offs and obtaining financial sign-off on new projects. The approaches used under this model include basing fees as a percentage of realized savings or dividing a larger project into small value-based milestones.
|Partner with cloud FinOps tool vendors
|Managed Service Providers (MSPs) can also benefit from FinOps tools like CloudBolt to gain insights into their clients’ cloud usage, spending, and optimization opportunities.
#1 Flat-rate pricing model
A flat-rate pricing model is a straightforward approach to billing clients for managed services. This model involves charging a fixed monthly or annual fee for managing cloud infrastructure, regardless of fluctuations in resource consumption. In a flat-rate pricing model, MSPs can:
- Bundle essential cloud management services, such as monitoring, maintenance, and support, into a single package.
- Offer add-on services or custom packages at an additional flat rate for clients with specific requirements.
For example, an MSP managing a client’s Azure environment could charge a flat monthly fee that covers the management of virtual machines, storage accounts, and networking resources. The MSP would handle monitoring, patching, and ensuring the environment adheres to best practices. Similarly, an MSP managing AWS infrastructure might offer a flat fee that includes managing EC2 instances, RDS databases, and S3 storage buckets. Likewise, a GCP-focused MSP could provide a flat fee for managing services like Compute Engine, Cloud Storage, and BigQuery.
Pros and cons
The flat-rate MSP pricing model offers consistency and predictability. Clients can easily budget for their cloud expenses and clearly understand upcoming costs. In addition, they receive a comprehensive suite of services that fits budget considerations.
However, the flat-rate pricing model fails to account for variations in consumption, leading to potential billing inefficiencies for the MSP and the client. For example, a client with a rapidly scaling cloud environment may consume significantly more resources in the current month than the previous month yet pays the same price.
“The features and support CloudBolt provides will allow my team to spend more time focusing on the delivery of quality customer outcomes.”
#2 Pay-as-you-go pricing model
As the IT landscape evolves, traditional per-user and per-server pricing models are becoming less relevant. The pay-as-you-go pricing model directly aligns with the pricing structures of major cloud providers like AWS, Azure, and GCP. Under this model, clients are billed based on their actual resource usage, measured in granular units such as
- Compute hours
- Storage capacity
- Data transfer
You can monitor and track your clients’ usage of various services and resources. By analyzing the data, you can determine the appropriate percentage to base fees on, ensuring a fair and accurate representation of the value you deliver in managing contemporary IT environments.
As part of a pay-as-you-go pricing model, MSPs embrace usage-based pricing models aligned with application architectures. With the growing adoption of containers and serverless functions, MSPs can also focus on pricing models that align with modern application architectures.
In an AWS environment, for example, an MSP could bill a client based on the number of EC2 instance hours used, the amount of data stored in S3, or the data transferred through their VPC. Similarly, for clients using Microsoft Azure, an MSP could charge based on resources consumed in Azure Virtual Machines, storage in Azure Blob Storage, and data transfer through Azure ExpressRoute. With Google Cloud Platform, an MSP might bill clients for using Google Compute Engine instances, storage in Google Cloud Storage, and data transfer through Google Cloud Interconnect.
For example, if a client spends $10,000 monthly on AWS Lambda functions for serverless computing, an MSP charges a 5% management fee based on the client’s monthly spending, amounting to $500. This fee covers essential services such as provisioning, monitoring, incident management, and capacity planning.
In another scenario, an MSP managing a client’s containerized environment on Google Kubernetes Engine (GKE) charges a fee based on the number of nodes or the total vCPU and memory usage within the cluster. As the client scales their application up or down, the MSP’s fee adjusts accordingly, reflecting the changing resource consumption and the MSP’s involvement in managing the environment.
The Cluster Management, sometimes also referred to as “Master Node(s)”, or “Kubernetes API Server” (Purple). The nodes that will do the heavy lifting for you, also referred to as “Worker Node(s)” (Green)
One of the key benefits of the pay-as-you-go pricing model is its transparency. Clients can easily observe how resource usage directly affects their costs, enabling them to make more informed decisions about their infrastructure and budget allocation. By providing detailed billing reports that break down usage and associated costs, MSPs further increase transparency and aid clients in appreciating the value of the MSP’s services.
The granular approach also allows the client to see the direct impact of their resource usage on their overall costs and incentivizes them to optimize infrastructure for cost efficiency. Clients better understand their spending patterns and adjust their usage, ensuring they only pay for the necessary resources. The pay-as-you-go MSP pricing model fosters more robust client relationships, ultimately leading to higher customer satisfaction and long-term business success.
#3 Tiered pricing model
The tiered MSP pricing model is a versatile approach that caters to a diverse range of clients with varying needs and budgets. Under this model, MSPs offer multiple pricing tiers, each with a predefined set of resources and services. Clients choose the tier that best fits their requirements and budget, while MSPs upsell additional features or resources as necessary.
Types of tiers
MSPs usually offer three tiers of service. You can offer more or less and rename them to best suit your market requirements.
The entry-level tier includes essential monitoring and incident management for a limited cloud resources, such as a predefined number of virtual machines, storage, and data transfer. It is ideal for smaller businesses or those with minimal cloud infrastructure needs. The customers of this tier could be only entitled to requesting technical support by opening tickets online without any live help or dedicated account management.
The next tier offers enhanced monitoring, more comprehensive incident management, and additional services such as capacity planning and optimization. It caters to clients with more complex cloud environments and a greater need for specialized services. The customer support service available to customers of this tier may include a shared customer success manager who would coordinate live help for critical issues. This tier could also include FinOps reports identifying areas of savings but not include any help to capture those savings.
The highest tier provides a fully managed service, including advanced monitoring, incident management, capacity planning, optimization of resource utilization, and custom integrations with third-party tools. It suits larger organizations with extensive cloud infrastructure and more advanced requirements. In this tier, technical support may include light professional services provided by a dedicated team and coordinated by a dedicated account manager. Finally, this highest tier could include help from a shared FinOps team conducting monthly or quarterly reviews to identify and capture potential savings in cloud spending.
Example cloud services organized by tier
For instance, the Basic tier might cover a set number of EC2 instances, S3 storage buckets, and data transfer in an AWS context. In contrast, the Professional tier might include additional services such as AWS Lambda function management and RDS database management. Finally, the Enterprise tier could offer more comprehensive services, such as managing AWS Elasticsearch clusters and AWS Glue ETL jobs.
Similarly, for clients using Microsoft Azure, the tiers range from managing a limited number of Azure Virtual Machines and Blob Storage accounts to providing advanced management for Azure Functions, Logic Apps, and Cosmos DB.
With the Google Cloud Platform, an MSP could offer tiered services that cover essential management of Google Compute Engine instances and Cloud Storage up to comprehensive management of services like Google Kubernetes Engine, Cloud Pub/Sub, and BigQuery.
One of the main advantages of the tiered pricing model is its flexibility. Clients can select a tier that balances resources, services, and costs for their specific needs. As their requirements change, they can quickly move to a higher or lower tier, ensuring they always receive the most appropriate level of service. As a result, MSPs can cater to a wide range of clients and provide a clear and scalable pricing structure that aligns with their client’s needs, encouraging long-term partnerships and business growth.
#4 Percentage management fee pricing model
The percentage management fee model is where MSPs charge clients a percentage of their total cloud spend as a management fee. For example, if the client’s monthly spending amounts to $20,000, the MSP receives 10% or $2,000. However, if the MSP implements cost-saving measures that reduce the client’s monthly cloud spend to $18,000, the management fee is $1,800.
The scope of the services covered by the management fee must be defined for this model to work. For example, an MSP may not have skills to help with Azure Cosmos DB (NoSQL database platform) in which case it wouldn’t be appropriate to charge a fee even if the client currently uses that Azure service. MSPs are incentivized to hire experts in different areas so they can provide value-added support and configuration services to justify a management fee surcharge.
In environments where clients have complex, multi-cloud setups, the percentage management fee model encourages MSPs to streamline resource management and optimize costs across various cloud platforms, such as AWS, Azure, and GCP. This ensures the best balance between performance and cost, further solidifying the MSP’s reputation as a valuable partner.
Pros and cons
This MSP pricing model fosters trust and transparency between MSPs and their clients, as clients can see the MSP’s fees and the value they provide in terms of cost optimization. It also aligns the MSP’s interests with the client’s, incentivizing cost optimization and efficient resource management. By basing their fees on a client’s cloud expenditure, MSPs can directly scale with the growing size of the client environment, which usually translates into higher complexity. The flip side is that the MSP’s cost optimization efforts will reduce and not increase their monthly compensation, which seems counterintuitive.
However, the goodwill generated by prioritizing client savings will likely pay dividends in the long term. As MSPs demonstrate their expertise in optimizing costs and managing resources efficiently, they are more likely to attract new clients and retain existing ones, leading to long-term revenue growth. In addition, satisfied clients provide referrals, expanding the MSP’s client base and offsetting reduced revenue from individual clients.
#5 Performance-based pricing model
The performance-based pricing model is a strategy where MSPs set their pricing based on the performance metrics or Service Level Agreements (SLAs) they achieve in managing the client’s cloud infrastructure.
For example, an MSP might charge a base management fee of $5,000 per month and offer a 10% discount if they fail to maintain 99.9% uptime for the client’s cloud infrastructure. The client pays the full $5,000 base fee if the MSP meets this uptime target. On the other hand, if the MSP achieves 90% uptime, the client pays a slightly reduced price.
The performance-based pricing model aligns the MSP’s incentives with the client’s desired outcomes and fosters a results-driven partnership. By tying their fees to specific performance metrics or SLAs, MSPs demonstrate their commitment to delivering high-quality services that meet the client’s expectations.
The performance-based pricing model also promotes transparency and trust between MSPs and their clients, demonstrating the MSP’s commitment to delivering desired results. Clients feel confident that their MSP is focused on achieving the best possible performance for their cloud infrastructure, while MSPs have the opportunity to showcase their expertise and build a reputation for reliability and success.
#6 Value-based pricing model
The value-based pricing model is gaining traction in the market as an innovative way to align the interests of MSPs and their clients. In this strategy, the MSP’s value determines the pricing, ensuring that clients only pay for tangible results and upgrades to their cloud infrastructure. Value-based pricing comes in various forms, with some examples outlined below.
The MSP retains a portion of the savings made by implementing the MSP’s suggested cost-saving strategies, such as reserved and spot instances. The client and the MSP share the difference between the on-demand rate and the discounted rate the client pays after benefiting from these programs. This approach incentivizes MSPs to proactively identify and implement cost-saving opportunities, as their revenue is directly tied to the value they deliver regarding reduced cloud expenses.
The gain-sharing pricing model may be flat or tiered depending on the level of professional services involved in capturing the gains. For example, the MSP may capture 80% of the measurable gains incurred from modernizing a traditional client-server application to use Kubernetes or serverless functions instead of virtual machines since the MSP would need to recoup the engineering costs. However, the same MSP may only capture 20-30% of the gains from purchasing savings plans on behalf of their client because it’s relatively easy compared to modernizing an application or right-sizing computing resources.
Under this model, the MSP prices a project based on specific milestones. Then, they offer a percentage of the fees paid towards a prior milestone as a credit towards the next one, as mentioned in the client’s feedback. For example, the first milestone may involve evaluating potential savings, while the second milestone focuses on capturing those savings.
To encourage the client to continue with the project, the MSP offers a 10–15% credit of the fees paid for the initial phase if the client proceeds to the implementation phase. This approach allows clients to commit to small, incremental project milestones while enjoying incentives to continue working with the MSP.
Learn more about the growing complexity and the widening skills gap causing this dissatisfaction.
Value-based pricing models establish a results-driven partnership between MSPs and their clients, ensuring both parties are invested in the project’s success. By focusing on the value delivered, MSPs demonstrate their expertise and dedication to improving the client’s cloud infrastructure, ultimately fostering trust and long-lasting relationships.
Partner with cloud tooling vendors for pricing accuracy
Managed Service Providers (MSPs) benefit from FinOps tools to gain insights into their clients’ cloud usage, spending, and optimization opportunities. A detailed and standardized cost report is required across multiple cloud providers to accurately invoice the clients and measure the MSP’s gross profit margin. FinOps tools give MSPs insights and intelligence that they can act on, which can help them develop better pricing strategies.
Features of FinOps tools
CloudBolt is a cloud FinOps management platform for hybrid and multi-cloud that makes it easier to set up, manage, and govern cloud resources. CloudBolt’s FinOps tools provide the following functionality.
CloudBolt’s cost analytics feature lets MSPs learn much about how their clients spend money in the cloud, down to the resource, service, and account level.
Budgeting and forecasting
CloudBolt allows MSPs to set budgets and forecast cloud spending based on historical usage data and trends. This lets MSPs figure out their future costs and adjust their pricing strategies to match. They stay profitable while still meeting the needs of their clients.
The cost optimization features of CloudBolt tell MSPs to lower cloud costs by doing things like right-sizing instances, finding unused resources, and choosing the most cost-effective purchasing options. By following these suggestions, MSPs decrease the cloud costs of their clients and offer more competitive prices.
Chargeback and showback
CloudBolt’s chargeback and showback features are essential for MSPs to charge their clients the correct amount based on how much they use their resources. This ensures clients are billed relatively and transparently, fostering trust and long-term relationships.
MSP pricing model automation
CloudBolt’s automation covers different parts of cloud resource management, giving MSPs the tools they need to simplify and improve the hybrid cloud environments of their clients. Here are some specific examples of what CloudBolt can automate.
CloudBolt can automate the provisioning of virtual machines, containers, and applications across multiple cloud providers and on-premises environments, streamlining the deployment process and reducing the time it takes to get resources up and running.
With its built-in orchestration engine, CloudBolt enables MSPs to automate complex workflows, such as application deployment, infrastructure configuration, and security management. As a result, MSPs can ensure consistent and repeatable processes across their clients’ environments.
CloudBolt lets MSPs automatically scale the resources of their clients based on rules and thresholds they’ve set up ahead of time. This ensures that performance is at its best and costs are minimal since resources can be scaled up or down based on demand.
The platform automates various aspects of resource lifecycle management, including patching, updates, and decommissioning. MSPs maintain their clients’ environments more effectively and ensure that resources are always up-to-date and secure.
Compliance and governance
CloudBolt automatically enforces policies and standards across hybrid cloud environments, ensuring clients’ infrastructure and applications meet regulatory and organizational requirements.
By leveraging CloudBolt’s FinOps tools, MSPs gain valuable insights into their clients’ cloud spending and usage patterns. With this data and the insights from data analytics platforms like Power BI, Tableau, Azure Monitor, AWS CloudWatch, and Google Cloud Operations Suite, MSPs can create more accurate and competitive pricing models that match client needs and industry trends, ultimately leading to customer satisfaction and business growth.
Key MSP pricing model takeaways
Managed Service Providers (MSPs) are critical in helping businesses optimize their cloud infrastructure and control costs. To meet the diverse needs of their clients and remain competitive, MSPs must adopt innovative pricing strategies that are both flexible and transparent. By implementing various pricing models, MSPs can cater to clients with different usage patterns, budgets, and preferences.
It’s important to note that a mixture of pricing models may govern one client’s engagement. For example, the MSP may charge a flat fee to ensure that all servers have the latest security patch, use a gain-sharing pricing model to share the savings from purchasing reserved instances, and still offer technical support based on a tiered pricing model.
Innovative pricing models enable MSPs to
- Align their services with clients’ requirements and cloud usage.
- Promote transparency, incentivize cost optimization, and foster results-driven partnerships.
- Deliver greater value to their clients, helping them control costs and optimize resource consumption.
MSPs that can adapt their pricing strategies to match industry trends and client needs are better positioned for long-term success and growth.
As MSPs adopt innovative pricing models, it is essential for them to maintain close communication with clients and provide clear explanations of the value and benefits each pricing model offers. By engaging in ongoing dialogue and presenting clients with data-driven insights, MSPs can help clients make informed decisions about the best pricing model for their needs. This consultative approach strengthens the MSP-client relationship and helps clients better understand the value MSPs deliver through their services.
Additionally, you should continuously evaluate and refine your MSP pricing model as the cloud computing landscape evolves. Regularly assessing each model’s effectiveness, considering new cloud services, pricing structures from cloud providers, and the changing needs of clients, ensures that MSPs remain competitive and continue to deliver value.
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