SaaS Brings Opportunities for Your Business, but Check Before You Buy
- Zohar Strinka
- May 27
- 6 min read
Updated: Jun 10
How SaaS data can deliver value
Software-as-a-Service (SaaS) solutions have changed how many of our clients do business. The underlying data has huge potential value, and it can be surprisingly affordable and easy to take advantage of it.
However, your ability to extract that value can be severely limited by who you decide to buy from and how they have designed their solution.
This is the first article in our three-part series about building analytics on top of SaaS. Zohar Strinka digs into five claims you will hear from vendors during sales or implementation. She covers how the data in these systems can benefit your organization in surprising ways, and explores the limitations of buying instead of building yourself.
Claim 1: Just set up the connections and start optimizing your business.
SaaS brings more options than ever to improve the efficiency and effectiveness of your business. If you need a new CRM, forecasting solution, data platform, or AI tool, you can turn it on with a few clicks and a credit card number.
Many of these SaaS tools perform impressively compared to more traditional software, and they can be intuitive and feature-packed.
However, integrating these systems into your business depends not only on the technical side, but the people side too. The process integration is usually harder to pull off, especially if you forget to include users into the buying process along with leadership. Other times we have seen that the technical implementation side is what leads to a project failure.
The goal for many SaaS solutions is to integrate effortlessly with other key tools despite their independence. CRMs that make it easy to populate estimates into your finance software. Forecasting straight off the data in your ERP. All the data warehousing tools that connect effortlessly with dozens or hundreds of systems.
The widespread availability and affordability of these tools means that if your business could benefit from more targeted marketing to your customers, you can easily gain that capability. If your ERP has a sub-par forecasting option, you can often level up with a best-in-class solution to quickly and easily optimize your inventory choices. As a rule, there’s probably something out there worth testing to see how much benefit it will provide your business.
But testing is that key first step that will allow you to discover if a given system will integrate into your business.
Claim 2: Cloud infrastructure means we can easily scale with your business.
We’re now many years into the cloud revolution. Historically there was a much larger cost to develop and ultimately implement software for new customers. For years now though, it’s been trivially easy to spin up the structure for a new SaaS solution.
As a result of the cloud shift, anyone with an idea can build software tools. It’s also easier than ever to onboard new customers and scale. We are in a much more competitive landscape of software tools for addressing a range of business challenges.
Because of the lower barrier to entry though, a lot of the SaaS options out there are a lot more experimental than they would have been in the past. There are a lot of moving parts for these tools, and if you rely on this tool for your daily operations, you want to make sure it will work correctly when you need it to.
In our experience helping SaaS companies build out their platforms, we have seen how much of the work comes down to data. The vendors’ choice of which systems or structures are going to be part of their core data model has a significant impact on how much value you can squeeze from the data.
SaaS companies might decide to ask their customers to meet a design spec built on several customers’ worth of interviews. Or they might create a standard model assuming certain sources are used by everyone in their target market and in a specific way. Some vendors avoid the whole thing and create a data model based on their own view of the world and merely provide a UI for the customer to input that information.
No matter what model the SaaS vendor chooses, they need to offer something special to attract and retain customers. We find that SaaS companies can look across a range of customers and find patterns that can provide your business with a real edge in the market. SaaS solutions also have the benefit of scale - just one person can create analytics solutions for dozens or hundreds of customers when they build a single SaaS tool.
Claim 3: The forecast isn’t wrong, you just need to fix your data.
Despite the benefits of centralization that cloud and SaaS solutions are built on, there are also significant challenges. The key fact to remember is that every business is unique. While your company’s financial system might be the 17th example the SaaS vendor has implemented, your way of using it might be unique.
When these sorts of tools are built in-house, your team will be able to peek behind the curtain to see what’s going on and why. When you outsource that logic to a SaaS vendor, you split expertise into two teams: your people understand your business and data, while the vendor understands how their models use what you put in.
If all goes well, the issues that are unique to your business won’t change the functionality of the SaaS tool. In most cases though, your primary task when testing a solution is confirming your company fits the mold the vendor designed to get the most you possibly can out of the solution.
When there are gaps, it can be hard to determine the best next step. Switching to some other vendor might be a good option, but you might run into the same issues next time too. A forecast-in-a-box might have worked perfectly for all the vendor’s previous customers who sold via e-comm, but if your business also has an important brick-and-mortar presence, that breaks the models.
However, it can be hard to see if the issue is stemming from your data and processes or if the vendor’s model of business doesn’t fit you.
In a perfect world, your vendor knows how to both diagnose and address the problems in the context of their solution. You also might realize you need to change your organization and processes to fit a particular SaaS solution based on your internal expertise. Either way, the split of knowledge may be a stumbling block in the implementation of a SaaS tool.
Claim 4: That’s not on our product roadmap right now, but you can submit a community request.
When our clients select a SaaS vendor to help solve a particular business need, the selection process is based primarily on cost and how well the tool solves their current business problem.
Unfortunately, there are often several issues that come up later as the tool is being implemented or used. In some cases, the vendor has a work-around for the moment and a clear plan to build the missing functionality soon. Usually though, our clients find the feature that feels crucial to them is just not a priority for their vendor.
The kinds of needs vary immensely. Perhaps the SaaS tool that best meets your needs does not integrate with your other systems and you need a custom solution. Other times the models are a good starting point, but you need another layer of customization before they can be used by your teams. A third possibility is that what you truly need is a blend of data across several systems to get a 360-degree picture of your business.
At that point, you should start looking for outside-the-box options. Maybe you need to add yet another SaaS solution to cover this new need. You may also decide that the only way to have the customization you need is to start down the path of developing in-house analytics solutions.
Claim 5: This tool is game changing for our customers.
Affordable and best-in-class SaaS solutions have allowed our clients to improve their business operations in many ways. Still, the challenges with implementation and missing functionality can sometimes make you wish you had built this toolset the old-fashioned way, where one team serves as experts both for your business and for the models under the covers in the SaaS tool.
In the next article in this series, we’ll dig into what we think is the best of both worlds. We will explore the ease of use and sophisticated models of these tools, as well as some of the key challenges of extracting your data back out of a SaaS tool.
We hope this has been an informative survey of the benefits and risks as you consider adding a new SaaS solution. We at Analytics Strategies are happy to help you get the most out of your data. Click here to schedule an exploratory call.
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