After working in various software companies for more than a decade, one thing is very clear to me: Vertical SaaS companies are primed for exponential growth.
Solutions to 3 Data Challenges for Vertical SaaS Companies
- Create an organized taxonomy around data and its use cases.
- Integrate data across mediums.
- View data transparency as part of your growth strategy, not a distraction.
In 2021, SaaS VC investment reached $94 billion spread across 4,459 deals and is expected to get bigger. Vertical SaaS founders are at a pivotal moment for technology to apply software to their chosen markets, build enduring growth and create industry-defining companies. Vertical SaaS growth has averaged 18 percent annually over the last decade.
Despite this amazing momentum and near-perfect positioning, many companies are still struggling to reach their full potential. Vertical SaaS suffers from a major problem: legacy paperwork that treats data as secondary to the document.
Data has always proved challenging for technology companies. We live in an age where the expectation is for information to be instantly accessible, yet entire verticals operate on paperwork where significant friction exists in converting the paperwork into usable data. How do we collect data in a way where it doesn’t require cleaning? How do we get it where it needs to go? How do we maintain a source of truth from many different sources?
Vertical SaaS companies are by nature building a bridge from the old way of doing things to the new way; they can’t just come in with their own processes that support clean data infrastructure. Here are three of the biggest data issues holding your vertical SaaS company back and how to solve them.
Data Overload
Not all data is created equal. Some are locked in a PDF and inaccessible. Of course you want to collect as much data as possible, especially given the fleeting nature of digital data. However, treating all data as equal makes for particularly frustrating challenges downstream. In the data hierarchy, you need to separate the data into a structure that is comprehensible. Gaining insights or automating processes becomes a practice in data spelunking, where weak threads are being drawn across a vast unintelligible data set.
Avoid capturing useless data by adding some structure from day one. Taking time to think through potential use cases for the data, properly labeling data and creating an organized taxonomy of the data is very important to having usable data at a later point in time.
Data Fragmentation Across Mediums
So you’ve figured out how you want to structure your stored data, now you have to figure out where you will be gathering the data. Important data points are easily lost when they fall through the cracks of a disjointed data management landscape. Many companies gather lots of information spread across systems and mediums like digital forms, PDFs, email, Slack and physical documents. The risk here is that the data becomes siloed within each medium and with whichever team is interacting with it, leading to a fragmented view of customer data, not to mention potential security risks.
This is partially why vertical SaaS companies have been able to disrupt the status quo and are still be able to build a bridge to legacy systems. These companies operate in industries with entrenched processes, regulatory requirements and resistant incumbents; furthermore, the piecemeal adoption of technology into these industries has resulted in a hodgepodge of workarounds requiring a human to assemble data across mediums.
A great success example is Vouch, an insurtech company that offers liability, business property and other types of insurance to startups. Vouch needs to provide the online experience their startup clients expect, use client data to tailor coverage to risk and then provide data to carriers on a PDF.
With a data-first mindset, Vouch implemented a workflow application that gathers clean, structured data from clients via an online form, automatically fills in the carrier PDFs with the information and simultaneously updates their CRM. By starting with a digital-first data collection solution and then syndicating the data across various mediums including PDFs, the company was able to break down the challenges posed by data fragmentation. Leveraging this solution, Vouch has increased its capacity to take on new clients by 33 percent.
Data Privacy and Security Concerns
There is more distrust between companies and their customers now than ever, and it’s all because of data.
According to Pew Research Center, 81 percent of Americans feel they have very little or no control over the data that companies collect about them, and 79 percent are very or somewhat concerned about how companies are using this information.
All of this stems from the fact that, in the very early days of online data collection, companies were being sneaky about collecting information without explicit consent. There were no rules and regulations, and when consumers finally caught on, they were distrustful. In an age when the ramifications of technology and data were barely understood, many companies took advantage of the circumstance.
Ultimately, data is at the core of a successful, efficient company.
Being transparent about your collection efforts goes a long way with customers. Vertical SaaS companies that go the extra mile to explicitly ask for information, explain why they need certain pieces of information and the security controls they have in place to protect the information will be better off in the long run.
This kind of transparency will go a long way as new regulations continue to come out and transform the digital landscape. If you’re honest about what you’re doing and you’re doing it ethically, there will be much less to worry about. As new regulations emerge, keep in mind your goals and continue to be transparent and compliant for the sake of your customers and your business.
Ultimately, data is at the core of a successful, efficient company. And while many vertical SaaS founders find themselves drowning in the muddy, unautomated and unregulated waters of data collection, that doesn’t mean that you have to. By collecting good data, having an efficient and automated process, and being transparent about the entire thing, you’re setting yourself up for success, leveraging a growing market and setting the foundation for a once-in-a-generation business.
