Why Streaming Data is Key to Reducing Customer Churn

Thought Leadership

By Evan Situ | October 18, 2021

I’m Evan Situ, the Head of Data at Apply Digital. I support our teams by leveraging data and advanced analytics to ensure seamless digital adoption of our clients’ products. Data is at the center of everything we do and creates the foundation for intelligent decision-making.

Customer churn is becoming more common amid growing competition and an increasing number of digital consumer products. In my ten years of experience, I’ve observed how customers leaving the business can crush revenue. But this can be prevented through the smart application of data and analytics.

Customer churn — the critical business challenge

In the US alone, companies lose $1.6 trillion due to customer churn annually. The typical response to high churn rates is to attract new customers, but retaining the existing ones is a bigger triumph. Why? Because acquiring a customer is five times more expensive than retaining an existing one.

It is vital to find out why a customer would choose to end their relationship with us and then make the right moves to change their minds by meeting their expectations.

What do customers expect? Best-in-class customer service, smooth onboarding, ongoing customer satisfaction. What can we do? Our clients’ products should be able to support customers in their changing needs and goals, our customers should be able to sign up smoothly and be able to enjoy initial success with our clients’ products so that they can look forward to more, our customers should seamlessly adapt to new features and product updates that are beyond what the competitors already offer.

Mapping Key Customer Expectations to Your Digital Product Goals

We can learn about ongoing customer expectations by observing a client’s customer behavior data gained through Customer Journey Management (CJM). CJM is the process of determining what information a customer needs throughout their journey and then defining the right types of messages to deliver to the customer to effectively engage them in each phase of the buying process.

Customer behavior means different things for each digital product but has one thing in common — it helps us understand why a customer would choose to end their service. For example, in my previous endeavor at a telecom giant, we predicted customer behavior with the help of customer complaint analytics and predictive modeling. We used these insights to redirect customers towards automated corrective actions by informing them of better features and offers. Automated communication through emails, text messages, or push notifications helped us reduce churn, saving the company millions of dollars per year.

Quick, actionable insights gained with the help of streaming data made this possible. Unlike batch data processing where the processing happens for blocks of data at recurring intervals that have already been stored over a period of time, streaming data processing allows us to feed data from customer touchpoints such as web or mobile applications into decision engines as soon as it’s generated and can be used for instant analysis.

Business agility comes from real-time responsiveness. We cannot wait for batch data updates to learn about a problem or opportunity. We require the entire process to be automated and optimized using raw streaming data that can be converted into the full data value stream in real-time.

Working along the same lines, we were able to turn the table around and retain customers who were on the verge of churn. That’s the power of data.

Reimagining customer experience with streaming data

At Apply Digital, we use data and analytics to unlock possibilities for unmatched customer experience through the digital solutions that we build.

While building a mobile app for a real-estate client who wanted to take their customer experience to the next level, we discovered opportunities to increase the monthly active users (MAU) and registered users. We examined the streaming data captured from a customer touchpoint — in this case, the mobile app — using analytics.

We noticed that the number of initially acquired users was reduced as they moved from adoption to engagement and finally to churn in ongoing typical user journeys. So, we proposed measuring the users’ data throughout their journeys to gain insights and help build a more engaging community around our client’s application.

The following three stages of typical user journeys helped us capture the user data:

  • Digital adoption: The percentage of invited users who fully signed up

  • User engagement range: The time period between two continuous user engagements

  • Churn: The time period in which users stop using the platform, and are most likely not to return

Using the insights gained from user journeys, we identified two key strategic opportunities:

The actions involved in determining key opportunities using insights from streaming data include observation, insight, recommendation, and result. The first strategic opportunity includes adoption data showing us that more than 75% of the users download the app within the first 24 hours of receiving campaign communication, email/text-driven communication enables product adoption — increasing the frequency of such communication will expand the initial adoption window, send an email/text message reminder to customers after 24 hours to increase the adoption, and increase in application adoptions by 8%. The second strategic opportunity includes engagement data showing us that 77% of users used the app twice within 90 days, 90 days is the ‘sweet spot’ for customer churn, and we can increase monthly active users (MAU) by campaigning to reactivate the existing users at this stage by increasing their engagement, implementing a retention strategy based on automated journey-based notifications and use in-app push messages to increase customer engagement further, increases in MAU by ~30%

Determining Key Opportunities Using Insights from Streaming Data

Additionally, it is vital to incorporate customers’ voices into our strategies to help improve their journeys. Customer Experience Measurement (CEM) acts as a guide to finding more opportunities to enhance the product and service, refine marketing messages, and inform strategies that reinforce brand preference and image. The most popular metrics to measure CEM include Net Promoter Score (NPS), Customer Satisfaction (CSAT), and Customer Effort Score (CES). We recommend creating and piloting a CEM program for all our clients' applications.

Final word

We know that customer churn takes place in the blink of an eye in the current and highly competitive digital market. That’s why instead of static batch data, we use streaming data that is constantly flowing so that corrective actions can take place in real or near time.

Data streaming provides companies with variety, volume, and velocity of data, made available through an infinite cadre of devices that send and receive data instantaneously. Organizations that react to valuable information streaming in from their customers’ devices in real-time can respond to customer needs by analyzing streaming and historical data with zero latency. This paints a real-time picture that takes the entire profile of the customer or situation into account.

It enables us to respond effectively and in the moment to gain control over the market, keeping our customers beyond satisfied.

If you would like to reduce customer churn and improve customer experience by leveraging streaming data and other leading data analytics strategies, reach out to us at hello@applydigital.com.

Co-Written by Rashika Srivastava