It’s a fact of life within the SaaS world that some features will perform better or worse than others in terms of costs versus revenue. If it were possible to develop every single new release in a way that it would flawlessly maintain desired profit margins, everyone would be doing it.
What separates the major players from companies that struggle year after year is how they monitor and respond to changing circumstances as they arise, and whether they learn from past mistakes.
Successful SaaS businesses will know quickly if a particular release is efficient or if it’s bleeding money, and they will take steps to fix it right away. Less successful companies may have to find out the hard way, after a few months of cloud bills roll in and they’ve already taken the hit to their bottom lines.
So, which camp are you in?
- Would you notice right away if a new feature was eating away at your profits?
- Would you be able to root out the problem quickly by determining the drivers behind those costs and adjusting them to be more cost-efficient?
- Or are you more likely to operate with a general sense that something might not be right when your cloud costs seem too high for several months in a row?
If you’re closer to the latter than the former, you may want to start tracking your feature costs in finer detail.
Let’s talk about why it’s so important to monitor the granular costs of SaaS business features and how you can get started right away with a strategy that works for you.
Why Is It So Important To Keep Track Of Individual Feature Costs?
It’s difficult to keep a SaaS business profitable over the long term without thoroughly understanding your cloud spend at a granular level. You may get lucky with your first few product and feature releases, but eventually, you’ll lose track of how much each release costs and the revenue it brings in.
Past that point, knowing which products — and especially features — are worth the effort feels more like guesswork than actual strategy.
The good news is that almost everyone has the ability to view their cloud spend at least at a high level, which, as part of the overall expenditure picture, opens the doors for deeper analysis.
Whether you’re using AWS, GCP, or Azure, you can view what you’ve spent in total and over time and use that information to break your costs down into environmental categories: What are you spending on production, for example, versus on development or quality assurance?
These environmental or departmental costs can often be separated out easily based on account usage. What’s much tougher is to break those categories down even further to see the finer details of the picture. If you know your production spend, for instance, how do you determine which engineering choices are driving those costs?
Some companies do a decent job of understanding costs at the product level. Large products often have enough differences between them to distinguish which costs belong to which product under the umbrella of the total sum.
But only a small number of companies are able to adequately track costs at a feature level and determine whether a feature is cost-effective from a revenue standpoint or if it has become bloated or inefficient.
This is important because most SaaS apps today are extremely complex. You may have several different features, service tiers, and other variables offered within one single product. Each of those components might act similarly or completely differently from the others in terms of their effects on your profit margins.
One might change based on seasonality, while another may perform well with a certain type of customer but fail to be worth the cost with other customers. Each will also have a different schedule for how often engineers make changes, and those changes will almost always impact costs in some way.
There are so many moving parts, and yet each is a vital piece of the puzzle that, when assembled, can give you a clear picture of your cloud spending.
If you have no way to put the puzzle together — or if you can’t even figure out how to isolate each component and see them as individual disjointed pieces — you’ll never truly understand what’s driving your production costs.
And without understanding your production costs, you won’t know how to control them, reduce them, optimize them, or manipulate the growth curve in your favor.
Why Is It Usually So Difficult To Break Features Down Into Granular Cost Components?
The traditional way to associate costs with individual resources is to tag those resources so they can be separated out from the others. And if you get your tagging scheme exactly right the first time you deploy a new piece of infrastructure, you can indeed gather valuable information from this up-front effort.
The trouble happens when you must update those tags because you made a mistake, because circumstances have changed, or because you’ve switched directions and want to tag things differently.
Many headaches have been induced when one group tags resources in a certain way and another group does it differently, and someone has to go in and reconcile the differences.
Unless your tagging scheme is perfect from the outset, it’s likely to become a cumbersome, slow, tedious, and unexpectedly expensive way to track costs.
After all, the time an engineering team could spend developing new revenue-producing features would instead be wasted having those employees tag, retag, and update old tags. Over time, that can result in a considerable financial cost, even if it’s indirect.
Additionally, in today’s modern architectures, it’s rare for a single piece of the infrastructure to support only one feature. The resource may be a database that several features tap into, for example, or it could be a Kubernetes machine that’s running multiple containers, each for a different feature.
Even if you’re great at tagging, it’s tough to tag these shared resources clearly and effectively without knowing the exact details of what’s happening under the surface.
What Could You Do With Granular Information About Feature Costs Once You Can Access It?
If you waved a magic wand and suddenly gained access to the finer details of your cloud spending overnight — this is possible, and we’ll get to that — you’d have some incredibly powerful insights at your fingertips.
Let’s say you’ve examined your costs and determined that a particular feature is costing your business too much.
Here’s what you could do about it:
1. Pass cost information to the people who own the feature or component
Often, this is a particular engineer or group of engineers. The cliche that engineers don’t care about cloud costs quickly falls apart when you realize they actually care about costs and efficiency very much, they just never had the tools to see how their decisions affected costs before.
Engineers love solving problems — that’s why they’re engineers — and they often take great pride in their work.
If you pass in-depth cost data to your engineers, chances are they will make the effort to pinpoint potential problem areas and take the necessary actions to fix them, even without much hands-on management.
2. Learn from the mistake
Perhaps this was an avoidable inefficiency resulting from suboptimal choices. If so, it’s a reasonable goal to make smarter choices in the future based on your new cost data.
If the issue was not the fault of any one person or team, it might have just been the result of unforeseen circumstances. Perhaps the new feature was picked up by an unexpected customer demographic, and these customers churned through a particular resource at a much higher rate than predicted.
If you can see your costs clearly enough to know this is the reason behind the spike, you can take measures to mitigate the impact in the future.
For example, you could market more cost-effective features to your new demographic, choose different infrastructure that supports the resources in question more efficiently, or implement a higher pricing tier to recover some of the costs from power users.
Regardless of what caused the cost increase, if you can drill down and identify the reason, you can keep it in mind while building and releasing similar features in the future.
With your cost data at the forefront, you can make enough small, iterative improvements over time to right the ship and trim down inefficiencies — and prevent new ones from slipping through the cracks unnoticed.
CloudZero Is The Magic Wand That Can Reveal The Hidden Mysteries Of Your Cloud Costs
With advanced tracking and analysis, an intuitive and visual breakdown of your metrics, and a dedicated team to help you navigate the cost journey from beginner to advanced levels, CloudZero can help you quickly and easily gain visibility into the costs of your SaaS business features.
Plus, our experts can get you up and running in no time. While insights will become more valuable over time, you truly can begin tracking your cloud costs right away and begin answering your cost-related questions overnight.