How Data Analytics Can Help SaaS Startups Grow Their Business

Diverse group of business professionals discussing digital and printed charts at a table.

As a data analytics company, we collaborate with SaaS startups to help them develop their data analytics strategy.

Common Misconceptions in SaaS Startups

One common misconception in this space is that startup companies should use the limited access to good full-stack developers who work on developing new app features and solving bug to implement analytics as well. When their customers and investors demand analytics, the startups try to code the graphs themselves using web app technologies, rather than working with data analytics companies. This can lead to inefficiencies and a lack of focus on core business activities. Instead, by working with a data analytics company, startups can put in place all the necessary reporting and receive advice on proper architecture and data structure.

This ensures that they can record all the important data needed to create robust reports and dashboards that will help them grow their business. This can be particularly beneficial for SaaS startups in industries such as car rentals, call center management, marketplace management, and horeca, where potential investors, startups themselves, and customers would be interested in various reports and metrics, such as:

  1. For potential investors:
  • Monthly recurring revenue (MRR) growth rate
  • Customer acquisition cost (CAC) and lifetime value (LTV)
  • Gross and net churn rate
  • Monthly active users (MAU)
  • Average revenue per user (ARPU)

2. For the startups themselves:

  • Adoption rate of the product and individual features
  • Time to resolve bugs or customer issues
  • Customer engagement metrics, such as time spent on the platform, frequency of logins, and feature usage
  • Conversion rates from free trials to paying customers
  • Employee productivity and workload

3. For customers in various industries:

  • Car rental fleet utilization rates and vehicle turnaround time
  • Call center metrics, such as call resolution times, customer satisfaction scores, and agent performance
  • Marketplace metrics, such as number of listings, seller responsiveness, and buyer retention rates
  • Horeca metrics, such as order fulfillment accuracy, delivery times, and supplier responsiveness
  • User feedback on ease of use, reliability, and overall satisfaction with the platform.

Startups often struggle to find a balance between developing new features and providing analytics to their customers and investors. Customers want to understand more details about their accounts, stats, performance, subscription, available budget, and more. Investors want to understand details about the user base, retention, active users, paying users, recurring revenue, churn, and more.

Rapid Iteration with BI Dashboards

By working with us, startups can put in place all the necessary reporting, allowing them to focus on developing features. Developing BI dashboards is a more rapid way of iterating, showing stats to customers and investors, gathering feedback, and implementing that feedback by creating new charts and adjusting them. Additionally, the interactivity and drill-down capabilities of BI tools are superior to web dev technologies like D3.

Proper Architecture, Data Structure and Data Collection

Furthermore, working with a data analytics company can help startups with the proper architecture and data structure. Most of their apps use NoSQL databases, which are not suited for reporting. This means that they don’t build the product with analytics in mind and might have to change the logic and structure of the database to be able to collect data from it later on. When we try to report and create dashboards using their data, we can either flag any bad database design early on or advise them from the very beginning regarding the database structure or data collection methods, ensuring that they record all the important data.

For example, imagine an ecommerce app that only records submitted shopping carts. This way, they will have no way down the line to send retargeting messages for customers who are abandoning a cart before submitting it. By working with a data analytics company from the beginning, they can make sure they are collecting all the necessary data to create robust reports and dashboards that will help them grow their business.

Conclusion

In conclusion, SaaS startups need to balance their time between developing new features and providing analytics to their customers and investors. By working with a data analytics company, startups can put in place all the necessary reporting, receive advice on the proper architecture and data structure, and ensure that they are capturing all critical data points from the get-go. This, in turn, allows them to derive valuable insights and make data-driven decisions, while also satisfying the analytics needs of their customers and investors.

Ultimately, leveraging the expertise of a data analytics company is not merely a nice-to-have for SaaS startups – it’s an essential strategy that can supercharge their growth and success in a competitive market. Embracing this partnership ensures that startups can focus on what they do best, while also providing detailed, valuable analytics to those who need it. With a data-driven approach, SaaS startups can scale effectively, optimize their operations, and deliver superior value to their customers, employees, and investors alike.

*the article has been written with the assistance of ChatGPT and the image has been generated using Midjourney

witanalytica

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