The Role of Predictive Analytics in Subscription Revenue Software

When forecasting subscription software revenue, do you find it a time-consuming process that never quite hits the mark? What if you had the ability to forecast revenue with precision? Now you can! Combining predictive analytics with subscription revenue software is a growing discipline. It’s rapidly being adopted by subscription management organizations! In fact, a report recently published by Markets and Markets projects the market to reach $28.1 billion by the end of 2026.

Does this mean that the guesswork associated with forecasting revenue will become a thing of the past? This blog looks at what predictive analytics is and how it’s different from business intelligence (BI), why you should use predictive analytics for sales forecasting/revenue generation, and the role of predictive analytics in subscription revenue software.

Predictive Analytics: The What, Why and How

Investopedia defines predictive analytics as a form of technology that makes predictions about certain unknowns in the future. It does this by looking at current and historical data patterns to determine if those patterns are likely to emerge again. Predictive analytics accomplishes this by drawing on a series of techniques to make these determinations, including artificial intelligence (AI), data mining, machine learning (ML), modeling, and statistics.

The terms BI and predictive analytics are often used interchangeably, but there are significant differences. BI is considered an umbrella term that includes predictive analytics, and both provide methods and tools for handling and understanding the data you accumulate.

BI provides answers to questions such as how many software licenses were sold the previous quarter; whereas predictive analytics will provide insight as to the number of software licenses that you can expect to sell in future quarters. Basically, BI provides historical information and predictive analytics takes previous trends, analyzes patterns, etc. to help organizations look beyond understanding what happened in the past and determine what will occur in the future.

Let’s look at the predictive analytics steps you should take to forecast sales.

1: Collect Historical Data

1. Identify data sources, relevant variables, and performance metrics.
2. Collect sales data on your most popular software.
3. Gather data on total sales and identify the peaks in your sales funnel.
4. Determine the time period for the data you’re collecting, e.g., weekly, monthly, quarterly, annually.

2: Identify Trends

1. Examine your historical data to identify sales patterns.
2. Determine when (seasons, days, months, etc.) sales peak and what periods sales dipped.

3: Use the predictive modeling techniques adopted

1. Analyze the patterns found in historical and current data.
2. Determine future sales predictions

Note: This step uses ML and data mining to examine patterns and trends within specific, predetermined conditions to ascertain the most likely future outcome.

4: Develop the sales forecast

1. Use the predictive analysis process to generate reports.
2. Generate a sales forecast.
3. Share the results of the predictive analysis with sales and supporting team members.
4. Use the results to measure progress/KPIs, take preventative measures if sales are predicted to decrease, and improve the sales process.

While the above focused on predicting future sales volumes, using predictive analytics with subscription revenue software has numerous other revenue generating possibilities, including the ability to:

• Predict changes in demand for your software and prepare for fluctuations in revenue.
• Identify pricing optimization opportunities based on having a better understanding of customer behaviors such as spending patterns, product preferences, and what motivates them to purchase your software.
• Predict churn risk and proactively address at risk customers.
• Identify pricing optimization opportunities. This way you’ll gain a better understanding of customer behaviors. Look at spending patterns, product preferences, and what motivates customers to purchase your software.
• Identify new customer segments and markets.

The subscription revenue software insights provided by predictive analytics enable organizations to make informed decisions – giving them a competitive edge. It enables businesses to transform data into actionable insights.

Benefits of Adopting Predictive Analytics

Adopting predictive analytics can bring many benefits to sales and revenue forecasting. Let’s look at some of them.

• Forecast sales/revenue with precision: Use your subscription revenue software to look at industry trends, previous sales, competitors, economic changes, and other criteria. Predictive analytics helps you gain the ability to accurately forecast future sales and revenue potential. It also enables you to create SMART goals. These are specific, measurable, attainable, relevant, and time-specific. Accurately measuring data sets provides actionable insights.
• Optimize campaigns: Predictive analytics not only enables you to create campaigns that appeal to your target market but gives you the ability to design customized campaign messages that speak to individual prospects.
• Know your customers: Customer’s attitude towards your subscription revenue software can change quickly. Predictive analytics enables you to keep your finger on the pulse of customer needs by providing you with changes in their requirements, an understanding of customer lifetime value (CLV), and customer satisfaction levels to better gauge customer churn and proactively reverse the process.
• Become more efficient: With a comprehensive view of both human and non-human assets, you’re able to identify business process bottlenecks and make improvements before they become revenue draining.

Predictive analytics enables organizations to transform subscription revenue software data into the insights needed to make data-driven decisions. Then you can improve the customer experience and gain a competitive advantage. By using the data at your disposal, you can optimize many processes and performance. You’ll be able to prioritize workloads, monitor and adjust KPIs, improve collaboration between teams, and quickly detect and identify suspicious trends and behaviors (like fraudulent or malicious activities).

Monetize all Subscription Revenue Software Opportunities

Not a one-and-done initiative, predictive analytics is an ongoing process. You need to regularly refresh the process, and determine the data to collect. Today, data comes from many sources and in different formats. Normalizing the data is critical to providing the necessary insights. Only then can your business truly monetize all subscription software revenue opportunities.

BillingPlatform delivers a powerful meditation engine that enables you to aggregate and analyze usage data from any source and transform it into revenue potential. Our enterprise-grade platform was built from the ground up with design principles that deliver a high throughput, low latency solution that is accurate, durable, and scalable. Are you ready to leverage the full revenue potential of the data you collect? Contact our team to learn how!