Do you really know your customers?
There are many questions that need to be answered to run a successful subscription business:
What are your customer service consumption patterns?
Are the customers happy with your offerings/packages?
Do you have insights into your customer needs? Understanding the needs of existing customers and new customers are two sides of the subscription business. On one side, companies need to retain existing customers to recover Customer Acquisition Costs (CAC), upsell to increase ARPU, and maximize Customer Lifetime Value (CLV). On the other side, they need to understand the ever-changing consumer requirements and create innovative offers to acquire new customers.
The business support systems (BSS) collect and hold tons of data. Most of the BSS applications come with an inbuilt reporting module that would suffice the data reporting needs. However, BSS usually doesn’t come with analytics capabilities to provide usable info about the collected data. An AI/ML based advanced analytics application can do that for you. It can work on top of your digital BSS and helps make sense of the data.
The role of data analytics application is to provide organizations an easy way to uncover insights from the available data. It analyses, it looks for trends, and helps gain better understanding of customer behavior. This can be used to provide superior customer experience, increase customer loyalty, and increase customer base. The application also allows businesses to analyze important metrics like Monthly Recurring Revenue (MRR), customer churn, etc. that are essential for the success of a subscription business. Let’s look at some use cases where a data analytics solution can help.
1. Dynamic customer segmentation for campaigns – Personalized offers for marketing & campaigns can be created by segmenting subscribers based on different criteria.
2. Customer Lifetime Value (CLV) tracker - CLV can be improved by taking proactive measures by understanding the bottom-line profit contribution of different customer segments. E.g.: Analyzing customer consumption patterns to provide real-time recommendations.
3. Detect churn and craft retention programs – Analysis of service usage history can help identify customers who are likely to cancel the subscription. Retention actions can then be taken based on targeted insights for higher conversions.
4. Customer behavior analysis for upselling - Operator can analyze customer behaviour based on multiple attributes like recency, frequency, purchase pattern, etc. Smart recommendations can help operators target customers with right offerings and thereby increase revenues.
Investment on AI/ML based smart data and cloud technology is a must for subscription businesses. Such organizations simply can’t afford to be left behind. Covalensedigital’s Aspen-AI is an AI/ML based data analytics solution that analyzes business metrics in real time and derives insights. This helps businesses in taking smarter decisions, reduce risks, understand customer behavior, and customize offerings accordingly. For more information about the role of data analytics in subscription business, contact our team of data intelligence experts today.