Data has real value if it’s put to work. It can be used for many end goals, and businesses across every sector are waking up to the fact that their data can be used to drive greater success or to acquire and maintain a greater market share.
Many people assume that because Software as a Service (SaaS) and Tech companies deal extensively in data that they are actively using it to optimize their businesses and generate more income. Ironically, despite generating and retaining so much data, software companies are often not using it effectively.
While some companies certainly do invest in using their data, it is remarkably less common than often assumed. Software companies could be missing out on one of the greatest opportunities for reducing costs, increasing income, and fueling sustained growth.
Why SaaS companies need a data-driven culture
Data-derived insights have real-world value because they go beyond the numerical and embody the actual.
Insights are something that can be directly used because they draw the connections between seemingly unrelated data points. These patterns can then inform which actions or changes will have the optimum effect. Insights like these are used by the leading companies in SaaS and Tech to stay ahead of the competition.
The argument for extensive data use is particularly strong for this sector. It can be utilized for numerous end-purposes, all of which can directly contribute to reduced churn, better customer acquisition rates, and higher margins. The result is a better business, with a stronger growth potential in the longer-term.
Potential uses of data insights in the SaaS and Tech sector:
- Identifying bottlenecks that limit scalability
- Determine user behavior patterns that predict successful strategies
- Identify which features are most in demand
- See what factors contribute to churn rate
- Discover new ways of lowering Customer Acquisition Cost (CAC)
- Learn how to extend product lifespan
- Optimize internal processes to accelerate development or reduce cost
- Analyze internal operations to see where problems frequently occur
- Create internal skills maps that maximize productivity
- Identify successful tactics for customer retention
…and there are many more besides. Almost every area of operations can be optimized using data-derived insights, yet this rarely appears to be a priority for many SaaS companies.
Why aren’t we using our data more?
With so many good reasons for SaaS companies to use their data, it is even more perplexing that they’re not making better use of this resource.
After all, it’s already available and sitting there - just waiting to be used.
Of course, it isn’t that simple. Turning data into insights isn’t as straightforward as ordering a pizza: it takes time and resources to create a system that can work with the available data. Each software product will create its own unique data with its own various properties, structures, and formats. Creating a single data model that can integrate all these possibilities could become a never-ending project, and the benefits might not be achieved for some time. Similarly, building multiple data models for every single project would fail to generate return-on-investment in a meaningful way.
It's a question of priorities
SaaS companies live a fast and furious life. Especially start-ups. The clamoring priorities of ‘agility’ and ‘leanness’ are the biggest reason why more companies don’t invest time and money in a ‘clever system that might generate some value at some point’.
The #1 focus for SaaS companies is to grow - and quickly. Key terms like ‘Minimal Viable Product’ and ‘Time to Market’ tell us a lot about the way priorities are determined, and why companies like these don’t like to spend time on extraneous projects. Their livelihood depends on raising the next round of funding, and this will be determined by how quickly they get their product to market - and scale it.
Software products require an organization that possesses a particular ‘functional structure’. This structure ensures that all actions serve their ultimate goal: rapid development and growth. As a result, SaaS companies are built to Design, Make, and Market products as quickly and effectively as possible. Teams are frequently organized using the Scrum/Agile methodology with the sole purpose of generating a marketable product as quickly as possible.
With the ‘Time to Market’ being a leading guide for company behavior, it’s understandable that time isn’t devoted to creating value from old data.
When there is spare cash available, this is used to fuel more growth as quickly as possible – often with new customer acquisition schemes. Typically, in their first three years, successful SaaS companies spend between 80% to 120% of their revenue on Sales and Marketing offensives. This priority on fast growth usually remains in place for the first five years of a SaaS product or company. It is only after this period they start to realize that they should have invested earlier in data utilization.
The Rule of 40 is stupid
‘The Rule of 40’ is widely seen as an important goal for SaaS companies. Investors are particularly attracted to this metric, which indicates that the combined growth rate and free cash/profit rate should equal 40%.
As investors see this as an important indicator of future success, SaaS companies in turn often strive to attain it - even though just one-third of SaaS companies ever achieve this metric.
Despite this fact, many of these companies are still putting every available dollar and cent into fueling rapid, imeediate growth via new customer acquisition and rapid scaling. They do this even though it’s four times cheaper to upsell to existing customers instead of acquiring new ones.
Upselling costs just $0.28 to gain $1 of new revenue – but you need data to do this effectively.
While the smart use of data should certainly belong in the stack of ‘growth tools’, it rarely features as a priority. The perceived payback period is longer than other ‘quick and dirty’ methods for driving rapid growth. But this perception is flawed, as we will see in a moment.
No more excuses
Those are the excuses, but they’re still not a good reason. There are a lot of reasons, however, why data has value and why it should be utilized.
Leaders in software companies need to adopt a more nuanced perspective - one which balances the need for rapid growth, with investing in long-term success. Data can help companies to make better products from the very start, which makes their job much easier. Once you’re up and running, historical data can then become a playbook for future success. This has values that investors can appreciate, especially once it is demonstrated.
Some of the most successful companies, notably Amazon, have devoted resources to using data since their very inception. Since it began, the company started accruing and leveraging data to provide profitable insights. Using their data, Amazon is able to reduce shipping costs by 10-40%, and automatically update the prices of more than 2.5 million products every day to keep ahead of the competition. They’re even able to predict which products you’re likely to buy. That’s some value.
Looking at the most successful SaaS and Tech companies today – the ones that have persisted and outlasted the competition – all of them use their data extensively.
The active collection and use of data is an excellent predictor for the long-term success of a SaaS business. For investors looking at SaaS companies today, one leading metric will certainly be: are they using data-driven insights?
The solution: Something you can implement and benefit from immediately
So, we’ve established three facts:
- Data has incredible value to any business, and especially for SaaS companies.
- SaaS companies have an urgent priority for rapid growth
- It takes a lot of time and money to build the tools needed to turn data into insights
Except one of these facts is a lie: It doesn’t need to take a prohibitive amount of time or resources to turn data into insights.
We have finally reached a point in human evolution where these tools are now available for immediate implementation. This means SaaS and Technology companies can start integrating their data straight away, and start gaining insights to make better decisions, higher margins, and happier customers.
Weaver Technologies has developed the wvr.io platform so that anyone can clean and integrate data, and then use it across multiple data models. Best of all, it has been built to enable the transformation of complex data into easy to grasp Knowledge Graphs. This is the perfect tool for making better decisions.
The wvr.io platform has been designed by data experts to accommodate any data source, type, format, application, or file.
This means that SaaS companies can continue focusing on doing what they do best – but doing it better, using the guidance of data-derived insights.
Interested in learning how it works? Click here.