The Power of Subscriber Data: Why Many Companies Fail to Combat Churn Effectively
Churn has long been a challenge in media and entertainment, but recent research highlights its growing impact. Forbes found that 46% of US households canceled a streaming subscription within the last year due to costs, while Samba TV reports that 44% stick to just one or two platforms every six months. These statistics reflect a continued tightening of consumer budgets and a reduced resistance to canceling subscriptions. As a result, KPIs like revenue generation and customer lifetime value are now at the forefront, making retention strategies crucial to driving profitability.
While churn is not new, it’s important to note it’s rising
Churn rates have doubled since 2019, leaving broadcasters in a frenzy. This surge is driven by a multitude of factors, including an overwhelming array of platform choices, enticing promotions from competitors, and viewers frequently switching services to catch their preferred programs. And the solution? Data.
To effectively combat churn, broadcasters must harness the potential of their subscriber data
Data analytics can provide deep insights into viewer behavior, preferences, and habits, enabling broadcasters to anticipate potential churn and implement proactive measures. However, recent Omdia research reveals that only 13% of streaming services have consolidated their data across the organization, often relying on manual processes. This indicates that much of the streaming industry is lagging in advancing their subscriber data strategies to address churn effectively.
Here are three essential ways broadcasters can better leverage their data to combat churn.
- Making decisions based on unified, benchmarked data: For most OTT platforms, data is scattered across different departments or systems. This siloed approach often makes it difficult to understand customer behavior comprehensively. As a result, teams focus only on their specific area of responsibility, potentially overlooking broader trends that impact churn.
Leveraging unified data can help overcome this and provide a comprehensive understanding of customer interactions, from content consumption to billing and customer support. This can allow for a more accurate identification of churn drivers. By comparing the platform's churn rate to benchmarks, it can get easier to identify specific factors contributing to customer attrition. Together, this can help make informed decisions about content acquisition, pricing strategies, and customer retention initiatives.
For example, a high churn rate among subscribers who recently experienced technical difficulties might indicate a need for improved customer support.
By consolidating all subscriber data sources in one space, Cleeng’s ChurnIQ dashboard empowers teams to gain easier insights and develop effective cross-platform strategies for improved retention.
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- Leveraging purposeful segmentation & AI: Leveraging customer segmentation and machine learning can help build more accurate and personalized churn prediction models.
Technology can divide customers into distinct groups based on lifetime value, engagement levels, satisfaction ratings, subscription plans, and personal preferences. Machine learning algorithms can analyze the vast customer data, including churn history, viewing patterns, payment information, and lifecycle stage, to identify patterns and predict future behavior. With that, these models can help identify at-risk customers early on, allowing for proactively intervening with retention efforts tailored to specific customer segments. For example, you could offer a discount to a high-value customer nearing the end of their contract but showing signs of decreased engagement.
Cleeng’s brand new AI-ssistant uses generative AI to deliver broadcasters the answers they need instantly.
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- Identifying actionable opportunities and implementing targeted interventions:
Collecting and analyzing data across various stages of the subscriber journey—such as sign-up, trials, upgrades, churn, and win-back—enables the identification of high impact cohorts, including those susceptible to churn or likely to respond positively to personalized offers.
By integrating this data with engagement tools and executing targeted interventions dynamically and promptly, you can reduce churn and enhance subscriber retention. For instance, you can set up dynamic triggers to automatically offer relevant promotions or content recommendations based on individual customer behavior. Additionally, you may use A/B testing to experiment with different retention strategies and identify the most effective approaches.
This way, with data OTT platforms you can deliver personalized experiences and improve customer retention throughout the subscriber journey.
Bottom line: Lasting Subscriber Relationships are your Key to SVOD success
If profitability is your focus, you cannot afford to ignore retention. Following a strategic approach, leveraging data analytics and a supportive toolkit can prime you to reduce churn and build lasting relationships with your subscribers.
Cleeng offers a holistic subscriber management and retention perspective with its SRM® suite. You can leverage it to consolidate your journey, explore it from multiple angles, and act on findings. Specifically, ChurnIQ is a prime example of how subscriber data can be used to fight churn. It predicts churn with 95% accuracy, factoring in warning signs such as changes in viewing patterns, decreased engagement, or shifts in payment behavior. The latest ChurnIQ upgrades: ChurnIQ Studio, and ChurnIQ AI-ssistant combine personalized reporting with instant AI insights to empower broadcasters to swiftly identify at-risk subscribers and implement targeted retention strategies.
[Editor's note: This is a contributed article from Cleeng. Streaming Media accepts vendor bylines based solely on their value to our readers.]
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