Use Practical Predictive Analytics Examples to Gain a Competitive Edge

Predictive analytics examples

April 16, 2019

Deeply understanding your customers is vital to your long-term business success. Gather and analyze the right information and you’ll turn statistics into powerful predictive analytics that give you a true competitive edge.

This isn’t just a theory. We know that the right predictive analytics examples can illuminate your customer base, significantly reduce churn, maximize your revenue and profitability, reduce waste, and help you operate more efficiently.

We’ll show you how.

Why Predictive Analytics Really Matter to Subscription Businesses

Naturally, every organization wants to acquire and retain customers. But it’s especially important for a subscription business—here’s why:

  • Lots of competition in the subscription business space: There are new subscription businesses starting all the time, which means everyone’s chasing after a limited market share. With so much choice, analyzing and understanding customer needs is a necessity.
  • Loss leaders in the early part of the customer relationship: Many subscription businesses will endure up-front losses to acquire and onboard customers because the lifetime value (LTV) of that customer is so high. Because of that loss leader, you need to understand and boost retention rates to sustain growth.
  • Aggressive marketing and high costs to acquire new customers: Subscription businesses, whether they’re membership boxes, SaaS companies, or something else, are willing to spend big to acquire customers. To keep marketing budgets under control, it’s much cheaper and more profitable to learn the best ways of retaining existing customers than to keep growing purely through acquiring to replace churn.
  • Customer churn is a fact of life: Every subscription business experiences churn. Predictive analytics helps you find and solve the underlying issues that cause customers to leave, which means more revenue in your pocket.

  • Streamline operations for lower costs: Growth can often mean inefficiency and waste. Predictive analytics help you understand where processes aren’t working and can inform the methods you use to fix them.

That’s why you need the competitive edge that the right predictive analytics examples can provide. It helps you focus resources on the areas that are winners for attracting and keeping customers, while reducing waste and expenses.

The Future of Predictive Analytics is through AI and Machine Learning

Traditional analytics focuses exclusively on the past, or what has already happened. While that’s useful for understanding historic performance and context, it’s only part of the puzzle. Predictive analytics looks to the future, using artificial intelligence and machine learning to forecast what’s likely to happen with your subscription business.

Sophisticated algorithms make it easier than ever to model future customer behavior, sales, business performance, and more. Even better, these models improve over time as they learn from data and test previous predictions against actual outcomes and self adjust if necessary. You can even feed in external data from areas like CRM tools, third-party datasets, marketing information, and more for a complete picture of what your future predictive analytics will look like.

Examples of How Predictive Analytics Can Transform Your Subscription Business

The best way to understand how predictive analytics can enhance customer interactions, revenues, and business processes is by understanding how they answer the industry’s most burning questions.

What Do Predictive Sales Analytics Tell You About Meeting Future Subscription Revenue Targets?

Forecast likely sales, revenue, and profitability figures for the next month, quarter or year. Apply various modelling algorithms and predictions so you can plan for low, medium, or high growth. Improve predictive sales analytics over time as the system learns about customer attributes, product usage, operational interactions, external factors, and other influences.

What Actions Can You Take for Each Customer to Increase Their Loyalty?

Use the data to micro-segment your customers into different groups based on the factors that really drive their behaviors. Target specific actions for each group that has been proven to enhance their loyalty and increase product usage and customer stickiness.

What Lifetime Value are You Getting for Each Dollar You Spend on Acquisition?

Conversion rates are only the first part of the customer journey. Link that cost of conversion to the overall customer LTV to understand where it’s best to spend money for long-term growth. See if various customer success or support programs impact retention and churn rates.

How Engaged Are Your Customers With You, and How Engaged are Your Internal Teams With Your Customers?

Tracking the level of your customers’ and internal teams’ engagement and activity stream over time is a huge clue as to what is likely to happen once it comes to subscription renewal time. It will also help make sure you know who the players are, and you’re deploying the right resources at the right time.

How is Your Customer Using and Getting Value From Your Product?

Tracking individual customer product usage over time gives you visibility into their level of product value attainment, and what you can do to move them further up the customer maturity curve. Value is a two-way street–customers getting high-value are much more likely to stick with you for the long-haul, and will likely increase their spend over time.

What Difference Does Pricing, Including Paying Monthly or Annually, Make to Retention?

Discover if the slight loss of income for an annual subscription makes sense compared to conversion and retention rates for month-to-month subscriptions. Carry out effective testing to find the price points that lead to the highest revenues, based on the number of sign-ups and the value of each one.

How Do Support Tickets Impact on Customer Retention Rates?

Discover the main issues that customers are facing with using your products or services. Identify if the number and severity of support tickets has a measurable effect on churn. Prioritize product updates or service improvements based on their impact on retention.

How Does Product Usage Predict Retention Rates?

Learn how product usage (features, time spent, input, output, etc.) translates to customer retention. Prioritize customer success and sales efforts to promote the product features most strongly tied to retention. Focus development on functionality that retains customers.

What Customer Subscription Accounts Are At Risk of Not Renewing?

Based on retention rate risk factors you’ve discovered elsewhere, learn how that affects the chance a customer is likely to leave. Provide personalized support, training, implementation assistance, discounts, or other incentives to encourage specific customers to stay. Identify and resolve common risk factors across the business.

What Are the Most Effective Cross Selling and Upselling Initiatives and Products?

Understand how customers react to cross-selling and upselling of products and services across your subscription business. See if there’s a connection between existing product usage and a desire to buy other products or services. Combine this with marketing data for a picture of the customer selling and onboarding journey.

What Business Processes Are Not Delivering As Expected?

Measure and analyze your business processes to identify issues with speed, quality, accuracy, efficiency or other factors. Put fixes in place and track future metrics so you can introduce controls if processes start to fail again.

Predictive analytics is the future of any successful subscription business. From predicting sales to customer service, or conversion to churn, they give you the insight you need to make smarter business decisions. Get a competitive advantage, and answer the burning questions which could be holding you back.


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