Table Of Contents
1. How Should We Price This Product Or Feature? 2. Are Costs Growing Linearly With Customers, Utilization, And Other Growth Metrics? 3. Should We Decommission This Feature? 4. What Are Our Margins On Different Product Lines?

On a day-to-day basis, both engineering and product management in software companies involves constant trade-offs. Everyone has a long backlog of tasks and needs to make decisions about what to prioritize on a daily, weekly, and monthly basis.

Figuring out what to tackle first, what to put off for later, and what to say no to is critical both to managing daily workloads as well as to creating product roadmaps that reflect what customers want.

These decisions often are made based on feedback from customers, the company’s positioning, and overall strategic goals. But in too many cases, the conversation around product strategy lacks an important data point: The cost to build and operate the features.

Cloud costs should not be the only data point in discussions about product roadmaps. Without context, cloud costs are meaningless: The fact that Feature A costs $10,000 per month to operate seems like a lot … unless that same feature drives $500,000 in monthly revenue.

The cost of operating a feature should definitely be part of the product strategy conversation, however. Without cost information, it’s difficult or impossible to make educated decisions about the best SaaS pricing strategies, how much to charge customers or whether or not it makes sense to offer a feature in the first place.

Here are just a few of the ways cloud costs can influence product strategy decisions.

1. How Should We Price This Product Or Feature?

For SaaS companies, figuring out the right pricing structure — as well as the right price point and what features to include in each tier — is key to profitability. There are different ways to structure the pricing tiers, and many companies have one tier that is free forever. The question is: What features should be available in each tier?

In many companies, these decisions are based essentially on guesswork. Business leaders think about which features they think the customers will value more than others, but there is very little data that goes into determining either which features belong in each tier or what the price of each option should be.

Ultimately, how much you can charge for a product absolutely depends on how much your customers value it. But businesses also need to know whether or not it is going to be profitable to offer any given feature. Getting information about the costs of offering a specific feature is an important data point in the discussion on how much to charge for it or which tier to include it in — if it turns out a feature is very expensive to operate, putting it in the free tier may not make sense.


2. Are Costs Growing Linearly With Customers, Utilization, And Other Growth Metrics?

It’s also important to understand how growth will impact both total costs as well as per-unit costs. Costs don’t always scale linearly: Some costs, like storage, might be relatively fixed regardless of the number of users, while others, like data transfer, will increase in a fairly predictable pattern as the number of customers grow.

It’s also important to understand customer usage patterns. Do some customers end up using the product more heavily than others, in a way that drives costs up? Is there a pricing strategy that’s based on usage, rather than number of users, that might be more appropriate? These kinds of questions are important to consider as companies determine how the product should evolve and what pricing model provides the best value for customers and the most profit for the company.

3. Should We Decommission This Feature?

Discussions about product roadmaps often focus on adding new features — just like discussions about scaling are often focused on scaling up, not down. But there are plenty of cases when decommissioning a capability is smart.

If a particular feature doesn’t get a lot of use but is expensive to operate, even if it’s not being used, it makes sense to end-of-life it, offer it only to certain customers or to offer it as a paid add-on rather than as part of a pre-packaged option. This will not only save the money you spend delivering the feature, but will also let you redeploy the engineering resources to other, more impactful work.

4. What Are Our Margins On Different Product Lines?

The more product options a company has, the more important — and challenging — to get detailed cost data. Most companies know how much they spend, total, on compute and storage every month. Most companies don’t know how much of that went towards Product A and how much went to Product B. Yet that information is incredibly important when deciding how much to charge for each product, which product to prioritize and whether one product needs to be re-architected to bring cost down.

Going by net revenue numbers isn’t enough, either: It’s entirely possible for the more expensive product to be less profitable. Without granular cost information, that information might be hidden.

Companies ignore cost information at their peril. An application that costs too much to operate is tech debt of the most literal kind. Unprofitable applications and features are worse the more customers you have, and can lead to rushed cost-reduction efforts that are done in the dark and without context.

With CloudZero, engineers and product managers have the information they need to take costs into consideration proactively and iteratively. While software companies are constantly faced with trade-offs, with the right information they don’t have to compromise on speed or user satisfaction in order to increase their profitability.

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