Revenue monitoring not only involves monitoring huge amounts of data in real-time but also finding correlations between thousands, if not millions, of customer experience and other metrics. Are traditional monitoring methods capable of detecting a correlation between a drop in user log-ins and a drop in revenue as it’s happening? For many reasons, the answer is no.

There’s no question that subscription-based businesses are an incredibly popular revenue model in today’s economy. While single transaction revenue models tend to fluctuate due to the seasonality of markets, subscription plans offer much more consistent and predictable revenues. Although the subscription revenue model can certainly be advantageous over one-off transactions, these businesses are also notoriously challenging to keep subscribers active on their plan.

As the COVID-19 outbreak progressively impacts the world, many companies are grappling with the strain. It’s a very uncertain time for business right now. Even with so many factors out of your control, but there are a few things you can do proactively to protect your business. Keep your customers happy. Do everything you can to provide the best customer experience and remedy leaks early.

With this click-bait title and an answer as short as “more leads, better leads and cheaper leads”, I could wrap this article up in one sentence. Yet, even though that answer would not be very far from the truth for many startups, there is a lot more to it. Marketing is all about measurable results. The days when you could buy a billboard next to a football field without asking a few critical ROI questions are long gone.

Do you still find yourself visually monitoring dashboards for anomalies? That leaves catching revenue-related issues to chance. It’s become humanly impossible to catch incidents on streaming data. This is why many eCommerce and data-driven companies have adopted automated anomaly detection.

Having spoken with many companies, I’ve learned that while they all monitor their application performance, infrastructure, product usage, conversion rates and a variety of other user experience parameters, very few monitor the actual transactions from their payment provider.

“If you can’t measure it, you can’t improve it” …this quote by Peter Drucker and the philosophy behind it is a key driving force behind modern management and the introduction of BI solutions to support the scaling and increased complexity of businesses. Analytics tools were developed to enable metric measurement and business monitoring across large scale, complex systems and to enable continuous improvements of business performance.

Today’s business needs make it virtually impossible to function without relying on an extensive network of partners and third-party providers. An IBM study found that 70 percent of businesses were looking to increase their external partnerships.

An emerging field of data science uses time series metrics to develop an educated estimate of future developments in business such as revenue, sales, and demand for resources and product deliverables. A forecast is based on historical data of a given metric plus other relevant factors. Accurate forecasts are an important aspect of corporate planning.