As a SaaS founder, you’ve probably heard that leveraging data can help you make better strategic decisions than relying on intuition. These strategic decisions can increase profits, reduce churn rates, and improve productivity.
With SaaS products, actionable data is now more readily accessible than ever. Whether it’s churn or activation rates, these metrics can help you make decisions that positively impact your future growth.
Even though data is readily accessible, it’s essential to use it correctly. Some SaaS founders may misinterpret the data, focus on the wrong data or put the data they are gathering into the wrong context. This can lead you to make bad data-driven decisions that may hurt your future growth.
This article will show you how to use data to make effective decisions for your SaaS business.
1. Identify your business goals and prioritize
Every decision you make is always driven toward achieving a specific goal. For example, you may want more people from South America to use your SaaS product. So this means your priority would be to increase the number of signups from the continent.
Because you are a data-driven company, you will go through the customer acquisition data for your SaaS. You find out that 67% of your premium subscriptions come from Brazil, only 15% come from Argentina, and Mexico comes last at 10%. Your goal will now be to increase subscriptions in Argentina and Mexico because you have data to support it.
Begin with a business goal and then prioritize where to focus based on the available data. This is the first step to making data-driven decisions.
2. Collect relevant data
After identifying the problem you intend to solve and the decision you’re going to make, it’s time to find relevant data that will support your decision.
The critical point to remember here is relevance. You want to spend hours researching and analyzing data that will impact your final decision. So focus on data that is related to your objective.
Using our example of deciding to prioritize subscriptions from Argentina and Mexico, we can find relevant data in sources such as:
- Website analytics
- CRM software
- Customer feedback
- Business intelligence platforms
You can use proxies to scrape the needed data from websites, such as business intelligence platforms. Web scraping enables you to rapidly scrape many websites simultaneously without having to watch and control every single request.
Customer feedback is critical when making business decisions because it presents what customers think about your brand. If people in Mexico and Argentina are excited about trying your product, it will be easy to decide to intensify your marketing campaigns there.
3. Draw conclusions from the data
Look at the data you collected in the past and look for patterns. For example, when you wanted to increase subscriptions in Germany, you hired a native German social media marketer to create posts targeting your prospects. You noticed a rise in engagement levels, which resulted in more signups and demo requests from the region.
Hiring a native speaker from Mexico for your marketing campaigns in the region may work because you have data to prove the idea.
4. Plan your strategy
You’ve identified a business goal, found relevant data, and drawn conclusions supporting your idea. The next step is to create a strategy to implement your decision.
Clarify your goal, define the deliverables, and determine who will implement the project and the timeline.
For example, your strategy to increase subscriptions in Mexico may go like this. “We will hire a Mexican social media marketer to create content in the local Mexican language that shows how our target customers can use our product to solve their problems. They will create content for 6 months on social media platforms where our prospects hang out and give us results every month on the progress. This will increase our subscribers in Mexico by 15%.”
5. Measure your results and share insights
You decided to do something based on data, and now the results are out! The next step is to compare the results with the data you used when deciding to act on your goal.
Determine if your initial decision led to a positive result. If you ended up with good results, then the data you used to make your initial decision was accurate. This makes you a data-driven SaaS founder!
Sometimes the results you get may not match your initial data. For example, the social media marketer may not deliver subscribers as you had projected. In this case, you have to change your business strategy because social media marketing doesn’t work in Mexico.
Conclusion
Data-driven decision-making involves using data at the core of your decision-making process to reduce costs and increase profits. Next time you want to make business decisions, ensure it’s supported by data to avoid making mistakes.