Advancement in cloud computing and successes of SaaS business model; when combined with the progression in artificial intelligence, has shown startling outcomes — automating repetitive tasks, identifying security threats and the security breach has led to advancement in strategic efficiency to mitigate issues in real-time.

In keeping up with the shift from manufacturing to service economy the businesses are evolving to incorporate usage-based product models. Software as a Service (SaaS) applications is one such model that facilitates self subscriptions to their customers, at the same time providing flexibility in payment methods — be it weekly, monthly or annually. The subscription offerings are further made exciting by playing along with price models for packaged services, these price models are tailored to reduce software costs for the user.

The software service is frequently billed as a pay-as-you-go basis; turning out to be a popular billing method for its simplicity and convenience. The cloud-based platform also provides the convenience of tracking usage metrics of revenue earned, customer retention, conversion rate and customer churn out.

AI In SaaS Subscription Management

AI integrated SaaS Subscription Management systems store data and automate repetitive processes — from sending invoices, recurring payments, billing, tracking signups, demo requests and free trials.

At a more advanced level, it manages cancellation, renewals and refunds, customising pricing plans as per user’s needs, monitor discounts, generation of coupon codes and much more.

In retrospect, Machine Learning and Saas successfully understood, interpreted and identified user behaviour and patterns in structured data-sets. Now, the inception of deep learning and big data analytics has led AI to predict and forecast user behaviour, investment outcomes, growth in revenue and more.

1. Manage Recurring Billing and Payments

SaaS, a subscription-based business charging its customers on a recurring interval, with the application of AI and ML ensures an encrypted, instant and secure recurring payment process throughout the subscription term of the user. One effective way to ensure that the customer doesn’t default on payments is the application of Machine Learning in recurring billing to auto-debit the subscription charge, on a prescribed date and time. This can be further optimized by ML and AI to ensure an increased number of successful transactions.

Introduction of Artificial intelligence in the billing, payment processors and payment gateways reduce the risk of fraud and data theft by enhancing online protection of the transaction with monitoring, end-to-end encryption and AI-led analysis of the historical data.

2. Sales and Marketing Management

Artificial Intelligence and ML are central to marketing for SaaS businesses to scale revenue by offering better products with a personalized customer experience. One of the biggest growth factors behind the adoption of AI within these companies is — personalized content feed and customer experience.

On the sales front, AI is helping companies to boost the lead volumes with compelling closure rate, and vitalizing overall sales performance.

3. End-To-End Revenue Management

SaaS businesses are adopting AI to identify and eliminate unproductive customer discounts and segments. This frees both the financial resources and time to contribute to profits. Another application is of automating and optimizing pricing with advanced techniques in revenue management systems. Insights on transactional data are making businesses more competitive by looking for patterns in pricing, volume and measurable results. Many businesses are successfully combining transactional and product mix data using AI to deliver real-time price optimization.

4. Customize SaaS Dashboard for Real-Time Monitoring and Reporting

AI customized dashboards perform the tasks that are performed by human beings. It connects data from multiple sources for creating a single point of truth, performs advanced analytics and BI reporting and further communicates insights effectively through multiple visualization options (maps, statistical plots, charts.) These dashboards are capable of reporting real-time insights via mails or app notifications.

5. Forecast and fine-tune SaaS Business Revenue growth

Bergen Adair, a Market Analyst, says, “The best way to gain a competitive edge in any industry is by knowing more about your operations and the market dynamics affecting them better than your competitors. Competing with greater intensity and the ability to get more done in less time is what differentiates market leaders from other companies.” With predictive analytics, SaaS business can take advantage of the opportunities to participate proactively and anticipate outcomes to stay ahead of trends in the market. Accordingly, they can cross-sell or up-sell their services based on previous performances.

69% of decision-makers believe analytics will be crucial for business success in 2020, and 15% consider it essential for operating their businesses today.


Today, AI is understood beyond identifying and structuring data sets in prospect information and a customer database. It is playing central in managing recurring bills and payments, writing personalized emails, providing personalised content feed, devising strategies, predicting customer behavior, forecasting revenue, optimizing pricing, analyzing risks, detecting security breaches and taking risk-mitigating actions and much more to give SaaS businesses a competitive edge.



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Maitri Dwivedi

I put words to ideas, interested in functional products, consumer psychology, forms of human articulation, design, and art.