Executive Summary
Do you know that acquiring new customers is 5x to 6x more expensive than retaining existing ones?
However, in this new, rapidly changing world where customer preferences switch in a few clicks, markets shift overnight, and there is fierce competition, digital publishing houses face an eminent challenge in retaining their existing customers.
BOSC Tech Labs partnered with the digital publishing house to revolutionize their customer retention with AI and machine learning. As a leading news app development company, we proposed an AI/ML solution that used a mix of predictive and prescriptive analytics to predict customer behavior and align business and user experience accordingly.
One such company was struggling to keep control of their subscriber churn. The digital publishing house had difficulty resolving the challenges with their decreasing subscriber-based readers. With a churn rate of 8%, they were facing a loss of approximately $500,000 in revenue. The reasons can be several. But the most prominent ones were content saturation, shifting reader preferences, new competitors launching in the market, poor user experience, lack of value in the content, unfit pricing strategy, miscalculated target audience, and attracting the wrong audience.
By combining predictive and prescriptive analytics, we reduced churn by 25% in 6 months, increased retention by 15%, and saved £200,000 in annual revenue.
In this case study, we will look at how our AI solution, backed by predictive and prescriptive analytics, helped them discover the pattern behind why customers leave, identify high-risk disengaged customers, and offer targeted re-engagement campaigns to reduce churn.
See how the digital publishing house converted an 8% churn rate into a $200,000 retention win in 6 months with our AI solution.
Introduction
A leading digital publishing house was known for its insightful articles, unique approach to the latest global news, and precise dissection of world happenings. Founded in 2015, the customers loved how they delivered the fastest and most accurate news content and editorials, which took an in-depth view of developments around the world and their impact on common people. From political news to government policies, sports, finance, technology, and entertainment, it was a credible and trusted platform for all.
Also read: ChatGPT vs. Search Engine: Everything you need to know about
However, in the last decade, we saw a major shift in the digital media industry with free content providers, news apps, social media news platforms, newsletters, and podcasts. The reader’s attention went from reading high-value paid content to consuming more spicy and free content easily available online.
The digital publishing industry faces challenges like:
- Content Saturation: The readers’ engagement is volatile, and attention span is quite short due to the sheer volume of online content that includes quick social media updates, podcasts, news videos, and social media shorts. The majority of readers now prefer quick and short news updates, especially multimedia-rich ones, over detailed editorials.
- Content Personalization: Not everyone wants to read about finance, sports, or governments. Every reader has their unique interests and prefers content platforms that deliver news related to their field of interest.
- Subcription Pricing: Customers are wary of paying a huge lump of money for news they could get for free on other platforms. If they are paying, they search for value they wouldn’t get as a free reader. The key is to optimize pricing strategy and offer unique value like access to interviews, podcasts, and early updates to subscribers.
All these challenges not only reduce the subscriber rate but also eventually impact the traffic on the platform. The need of the hour is to understand reader preferences, market dynamics, and competitors’ unique propositions to optimize your offerings for staying relevant and profitable.
Why Customer Retention Matters?
Customer retention is very critical in times when acquiring new customers is getting more difficult and expensive.
Several studies show that acquiring new customers can cost you 5 to 25 times more than retaining existing ones. This is because retaining new customers requires fewer resources than attracting and converting new ones. To retain your present readers, you will most probably make content changes, website UI alterations, and pricing changes. However, to convert a new reader, you will have to spend a fortune on digital marketing, social media ads, Google ads, and sales. It can be a more tiring, expensive, and long process than retention.
Also, reports highlight that a mere 5% increase in customer retention converts to 25% to 95% in profit growth. This shows the lifetime value of long-term customers, who are most likely to spend more than new ones. Because you already have their trust, now you only need to offer rich experience and personalized content.
These customers are more likely to try out your new products and make repeat purchases. Plus, they serve as the perfect marketing agents, promoting the goodness of your brand to others. Also, they give you stable revenue streams, enabling you to keep running your business as intended, plan for future expansion, and allocate resources effectively.
How Predictive & Prescriptive Analytics Can Help?
Predictive and prescriptive analytics can help businesses better understand their customers’ preferences and behaviour and provide recommendations to optimize user experience, service delivery, and business strategy accordingly to improve churn rates.
Predictive analytics predicts future outcomes by analyzing historical data, customer engagement patterns, declining subscription renewals, reducing engagement with premium content, and identifying high-risk subscribers. Prescriptive analytics uses the insights from predictive analysis to offer recommendations such as having more subscription offerings at different pricing, personalized content delivery, limited-time offers, premium content add-ons, and more re-engagement campaigns to improve customer loyalty and experience.
BOSC Tech Labs helped the digital publishing house to integrate this AI solution into their business model, helping them forecast churn rates and automate targeted interventions.
Problem Statement
The digital publishing house was in a fix, suffering huge losses and high churn rates before implementing our solution. They knew they needed a new customer retention strategy and to change their content offerings, but the question was how.
The challenges they were facing:
- High Churn Rates: A monthly churn rate of 8%, which was a result of 40% departing users due to content fatigue and 30% had pricing concerns.
- Revenue Loss: The company was facing a huge $500,000 loss in annual revenue.
- Low CLTV: The customer lifetime value graph slumped by 18% in two years.
- Less Profit: Profit margins eroded as CAC climbed up to $45 per user.
- Declining Content Engagement: Subscribers were reading a few articles every month, with a fraction of them not even clicking the articles, showing no or less engagement.
- Manual Retention Strategy: Traditional retention strategies (like generic email discounts) without real-time insights were ineffective.
- Unified Content Approach: A unified content strategy failed to deliver up to the reader’s diverse interests and expectations.
AI-powered Predictive & Prescriptive Solutions
BOSC Tech Labs partnered with them to elevate its 360-degree view of the customers and apply recommended automation strategies to retain them. The merge of predictive analytics and prescriptive analytics offers high-risk customer identification, retention challenge prediction, and tailored strategies for high churn prevention.
Predictive AI: Anticipating Churn Before It Happens
Predictive AI analyzes customer engagement patterns, email open rates, payment history, reading frequency, profile logged in rates, and more to identify the potential issues customers face and identify high-risk readers on the verge of unsubscribing.
Our predictive AI system:
- Offers real-time insights into customer preferences, behaviour, age, geographical location, and online engagement patterns.
- Flags the readers who show signs of disengagement and alerts you before they cancel.
- Identifies potential reasons for customer disengagement and high churn rates.
Prescriptive AI: Optimizing Retention Strategies
While our predictive AI forecasts the churn, the predictive AI system planned the best strategies to combat the churn and make customers stay with you. Based on the insights from predictive analytics, prescriptive analytics creates a roadmap suggesting where you should intervene in the reader journey to enhance it further. From optimizing content to pricing and running re-engagement campaigns, prescriptive AI will tell you how to win back your customers.
Our prescriptive AI system recommends:
- Personalizing content offerings for your customers
- Optimizing subscription pricing strategies to target a wider audience
- Offering limited-time discounts or unique subscription models to get specific niche news as per the interests of the customers
- Starting email campaigns to target customers who haven’t logged in recently
- Reaching out to high-value clients directly to resolve their pain points, take in feedback, and make improvements accordingly
- Automated interventions over manual for high accuracy and efficiency
The digital publishing house with our AI solution was able to address high churn rates proactively and put a stop to it before the issues escalated further. Our predictive and prescriptive analytics solution transformed their customer retention strategy, reduced retention costs ,and improved targeting efficiency.
Implementation Process
We took a holistic approach to understanding the issues the digital publishing house was facing, identified a set of solutions to combat the challenges, and found AI-powered predictive and prescriptive solutions best suited to control the churn and smartly retain existing customers.
We devised a result-oriented development process that focused on creating a solution that met client expectations, fulfilled business goals, and delivered results as intended. Our AI solution development process included:
- Data Collection: We aggregated 12 months of user data, support tickets, payment history, profile updates, survey responses, and more that will help us train our system.
- Tool Selection: We used Large Language Models (LLMs) and data analytics tools for data processing and intelligent process automation.
- Model Development: Our team used 80% of the historical business data to train the AI model and 20% to test for its accuracy and efficiency. After a considerable 3 to 4 rounds of iterations, we achieved an 89% accuracy in churn prediction.
- Testing & Improvements: Our team ran a pilot test with 10,000 high-risk subscribers and precisely predicted the churn and offered tailored retention strategies. In the pilot test, we were able to reduce churn by 18%. The developers made further improvements in the AI model for more accurate predictions, recommendations, and smart automation.
- Team Training: Our service didn’t stop at integrating the AI solution into their system; we also held a 2-week workshop for employees. Our experts trained their employees on how to leverage AI dashboards into their workflow.
Timeline: We were able to deliver the entire AI solution from ideation to development and integration in about 3.5 months. This was possible due to our team of core AI experts, who are well versed in ML techniques, AI model,s and deep learning algorithms. Their years of experience and expertise in the domain helped us deliver a custom solution that met our client’s business needs.
Results & Key Outcomes
BOSC Tech Labs’ dedicated AI development team joined hands with the digital publishing house to build a robust AI solution that gives them an eagle’s view of their customers and strategies for improving customer retention rates.
With our advanced predictive and prescriptive solution, they were able to:
- Reduce monthly churn rates from 8% to 5%
- Improved retention rates in 6 months by 15%
- Saved $300,000 annually from unnecessary retention costs and losses due to churn
- Boosted the engagement of 20% of high-risk subscribers
- Enabled smart automation to reduce manual work by 30%, freeing up employees for more strategic tasks
Improved subscriber renewals by 20% - Increased operational efficiency by 40% with AI automation
Challenges & Solutions
Our team faced several challenges while developing the AI solution for the digital publishing house. However, with our team’s proficiency in AI and problem-solving mindset, we were able to overcome these challenges and deliver the solution within the timeline.
Some of the key challenges that we encountered were:
- Data Quality Issues:
Problem: 25% of user profiles had incomplete data.
Solution: Implement automated data validation and third-party enrichment tools. - Resistance to AI Adoption:
Problem: 40% of staff doubted AI’s reliability.
Solution: Launch the “AI Champions” program with hands-on training. - Privacy Concerns:
Problem: GDPR compliance risks with personalized campaigns.
Solution: Added double opt-ins and anonymized data processing. - Model Accuracy:
Problem: Initial false-positive rate of 22%.
Solution: Enrich training data with social media sentiment scores.
Conclusion
The digital publishing house’s adoption of AI-powered predictive analytics and prescriptive analytics solutions to predict churn, increase engagement, and stop revenue loss highlights that with the AI solution, you can cater to business challenges early and achieve desired results.
The key takeaway is to detect the source of high churn rates early, identify disengagement patterns, and tailor re-engagement strategies to stop the churn before it impacts your business. Similar to digital media publishing houses, the same solution can be applied to businesses in SaaS, e-commerce, retail, and digital streaming platforms where customer retention is critical for the success of the company.
Explore how our AI solutions can reduce your churn rates and win back existing customers. Contact Today!
