Understanding Domo’s Total Cost of Ownership (TCO) for Your Data Stack
Selecting the right data technology is essential for maximizing both value and efficiency, but understanding long-term costs and return on investment can be difficult. Domo stands apart by prioritizing transparent pricing and aligning your costs to the true value you receive over time. With Domo, you’ll have visibility and predictability, so you grow your business confidently, knowing your investment always supports your goals.
When evaluating your data stack, consider the total cost of ownership and the lifetime value, not just the initial price. Domo’s total cost of ownership is based on your usage, not the number of licenses. Unlike other platforms that charge per user, Domo gives you unlimited users without additional fees. You only pay for what you use.
Our goal is to provide technology that fits your budget today and scales efficiently as your organization grows. By aligning costs with usage and value, Domo makes sure your investment works as hard as you do.
Breaking down the cost components
To truly understand total cost of ownership, it’s important to break down the factors that influence your investment with Domo. Four main components influence your ongoing costs:
- Data ingestion frequency: The frequency with which you bring data into Domo influences your costs. Each data ingestion job—whether it runs every minute or once a day—consumes credits per execution. To offer peace of mind, Domo offers built-in protections, so you won’t encounter surprise overages even as your integration needs grow.
- ETL transformation frequency: Every time you clean, blend, or transform data with Domo’s ELT/ETL tools, you consume credits based on each execution. Much like ingestion, built-in protections keep even complex or frequent transformations within your expected spend.
- Data storage location: Domo allows you to store your data in any data warehouse. If you don’t have an existing CDW and prefer Domo to manage storage on your behalf, we can do so at a predictable rate of one credit per two million virtual rows monthly or one credit per one million materialized storage rows monthly.
- AI and workflow usage: Domo lets you move from analyzing data to acting on it by using it to build, test, and deploy AI agents and automated workflows. Because every chat interaction and workflow step uses only a fractional credit, this becomes a predictable (and budget-friendly) cost. Teams can safely explore AI, iterate quickly, and deploy solutions without relying on outside vendors to build or maintain agents. To go deeper, you can read more about Domo AI’s tiered pricing and pricing per model.
With everything in one place, you can test new ideas, automate processes, and improve business results with confidence, knowing your spend scales with the value you create. Note that usage for some AI features, such as AI agents, are calculated as part of the AI Pro pricing plan.
By focusing on these usage-based drivers, Domo aligns costs with actual tool activity, giving you superior visibility and control over your total cost of ownership as your data strategy evolves.
Learn more: For a deeper dive into credits and your Domo investment, visit the consumption pricing breakdown page for complete details on usage and cost drivers for total cost of ownership.
Domo vs traditional BI tools: Cost structure and value compared
The price tag of a tech stack
Quantifying the average cost of a tech stack isn’t exactly an easy calculation because there’s not always agreement on what costs should be included. But Zylo, a Software as a Service (SaaS) management company, gives us a good place to start.
Zylo’s SaaS Management Index tabulated the average costs for SaaS in 2024. Last year, companies spent a little more than $4,800 per employee on SaaS. Businesses with 500 or fewer employees spent about $11.5 million, while average annual costs for SaaS in companies with 10,000 or more employees reached a whopping $284 million—both pricey bills in their own right.
Overall, spending on SaaS saw a more than 9 percent jump year over year, with one of the primary drivers being adoption of AI. In 2025, spending on AI-native applications increased by about 108 percent, with large enterprises increasing 393 percent year-over-year.
This could be good news for companies; they clearly feel confident that the new tools hitting the market can make a difference for their bottom lines. IT teams, on the other hand, may not be feeling the love. Zylo’s data shows that about half of the apps that were integrated into companies’ work streams were owned by individual lines of business, which can make it difficult for IT teams to maintain visibility of and control over the tech stack.
Therein lies some of the other pricey problems. As you build out a tech stack, you need to ask yourself whether you’re factoring in all of the costs:
- What are the pricing models for different tools? Are they subscription-based pricing models that allow everyone in your enterprise to access a tool or do you need individual licenses for unique users? Paying for a lot of licenses on tools that are used minimally can significantly raise costs over time.
- What level of staffing is needed to support the tools? You’ll obviously need people with data analysis expertise to effectively use your data stack. But you may also need people to integrate the platform into your systems, perform maintenance on it, train staff to use it, and ensure that the platform stays secure. You must think more broadly about ongoing expenses before adopting new technology, particularly as they relate to your organization’s headcount.
- Are you paying for functionality that you already have? Tech sprawl is real. As different parts of the business begin adding their own platforms or apps to the tech stack, it becomes increasingly difficult to determine whether your tools have overlapping capabilities. You could essentially be paying for the same tools two or three times over.
On the opposite side of these very practical costs, you also have to think about opportunity costs. Many new tools are, in fact, worth it. So if you decide to stick with your legacy systems that don’t offer all of the functionality that more advanced tech offers, you’ll have to eat the cost of manual reporting or the cost of slow decision-making. Downtime caused by lagging systems and more error-prone manual processes aren’t just silly nuisances; there is a cost of doing nothing.
The value of modern data stacks
Our pricing model also plays an important role in trimming down your expenses. With Domo, you only pay for what you use.
Domo offers credit-based pricing, so customers can purchase a credit package and access all of Domo’s features—for an unlimited number of users. Different capabilities use different numbers of credits, but if you need to scale up, all you have to do is purchase more of those credits. It’s a simple and cost-efficient way to work.
Freddy’s Frozen Custard & Steakburgers, one of the fastest-expanding fast casual franchises in the US, credits Domo’s consumption model for helping to drive its growth strategies. Being able to access the full Domo toolset has encouraged teams across the company to experiment more with data science in order to inform everything from their real estate strategy to the promotions that they run to the items that they offer on the menu.
“Previously, we were only able to do some simple modeling. Now, we can run our billions of rows of data through behavioral models to understand how our guests are ordering and why,” said Sean Thompson, vice president of IT at Freddy’s. “It’s like there was a giant stop sign in front of us, and now that stop sign is out of our way.”
Making a smart investment in your data future
Choosing Domo means choosing tools that grow with you, aligning costs to the value you create rather than locking you into rigid, outdated pricing models. By focusing on total cost of ownership and providing unmatched transparency, Domo empowers you to scale confidently, collaborate freely, and innovate without limits.
Frequently asked questions
How does Domo's pricing model work?
Domo uses a credit-based consumption model, meaning costs are tied to your tool usage rather than fixed pricing tiers. This ensures you only pay for what you use.
What activities consume credits in Domo?
Because Domo offers multiple technology components, we reduce the need for piecemeal solutions and specialized staff. With features like pre-built connectors, ETL tools, advanced analytics, and customizable dashboards, Domo can lower tech spend by an average of 20 percent and even reduce headcount requirements, resulting in a significantly lower total cost of ownership (TCO).
What is the ROI of investing in Domo?
According to Nucleus Research, for every dollar invested in Domo, companies see a return of $6.93, higher than the $6.20 average for general analytics technology. This is achieved through cost savings, streamlined operations, and faster, data-driven decision-making.
How does Domo’s pricing model work?
Domo uses a credit-based consumption pricing model, in which a customer's contract comes with credits that can be used for any component of our technology—and, by unlimited users. This flexible approach ensures you only pay for what you use and can scale up easily by purchasing additional credits.
How has Domo’s pricing model benefited other companies?
Freddy’s Frozen Custard & Steakburgers, a fast-growing franchise, credits Domo’s consumption model for enabling teams to experiment with data science and make informed decisions. This has helped them optimize strategies for real estate, promotions, and menu offerings, driving growth across the company.
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