Churn prevention – the basics: Nine ways to prevent churn that businesses need to know

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  1. Introduction
  2. What is churn?
  3. Types of churn
  4. Why churn matters so much for businesses
  5. Common reasons why churn happens
  6. Nine ways to prevent churn
    1. Understand customer needs and expectations
    2. Improve customer onboarding
    3. Provide exceptional customer service
    4. Offer personalised experiences
    5. Monitor customer behaviour and usage patterns
    6. Use all available data
    7. Communicate with customers regularly
    8. Address customer problems straight away
    9. Be strategic – and transparent – about pricing
  7. How Stripe can help

Preventing churn is the goal for many businesses, especially those that operate on a subscription model. Below, we'll discuss what you need to know about why churn happens, the types of churn, and things your business can do to minimise churn as much as possible. For most businesses, some churn is inevitable, but there are many strategies for preventing and reducing it.

What's in this article?

  • What is churn?
  • Types of churn
  • Why churn matters so much for businesses
  • Common reasons why churn happens
  • Nine ways to prevent churn
  • How Stripe can help

What is churn?

Churn refers to the process of customers or subscribers leaving a service or business over a certain period. It is an important metric – especially for businesses that rely on subscription-based models, such as telecom services, streaming platforms and software-as-a-service (SaaS) products.

Churn is often expressed as a percentage rate, indicating the proportion of customers who discontinue their subscriptions or stop using a service within a given time. A high churn rate can be a warning sign for a business because it indicates a loss of customers and potentially points to issues with customer satisfaction, product quality or market competition.

Types of churn

There are several types of churn. Each is a reflection of the type of business and an indication of the reasons a customer has left. These are the main types of churn:

  • Voluntary churn: This occurs when customers actively choose to leave a service or cancel their subscription. Reasons might include dissatisfaction with the product or service, better offers from competitors, or changes in the customer's needs or financial situation.

  • Involuntary churn: Involuntary churn happens when customers are lost because of reasons beyond their control. Examples include credit card expiry or failure, non-payment because of financial constraints, or technical issues preventing subscription renewal.

  • Revenue churn: Revenue churn is related to the loss of revenue rather than the loss of customers. Even if the number of customers remains relatively stable, a business may experience revenue churn if subscribers switch to cheaper plans or if there's a reduction in upselling or cross-selling opportunities.

  • Customer churn: This is the most straightforward type, indicating the loss of customers or subscribers. It's typically measured by the percentage of customers who leave a service over a specific period.

  • Early churn: This refers to customers who leave a service or cancel a subscription shortly after joining. For business-to-business (B2B) software customers, insufficient access to customer support and personalised training may prompt early churn. Mismatches between customer expectations and the service provided could also cause churn.

  • Contractual churn: Relevant in businesses where customers are bound by a contract, this type of churn occurs when customers choose not to renew their contracts upon expiry.

  • Non-contractual churn: In non-contractual settings, where customers are not bound by long-term agreements, churn happens when customers stop purchasing or using the service without any formal cancellation process.

Why churn matters so much for businesses

There's effectively no part of a business that is unaffected by churn. Here are some ways in which a business might be affected:

  • Financial health: Churn directly affects a business's finances. Constantly losing customers means a steady drain on revenue streams. For subscription-based models, churn must be addressed at the source.

  • Market perception and brand image: High churn rates can be a red flag for potential customers and investors. They suggest that something might be off about the business, whether it's the product quality, customer service or brand experience. This perception can shape market position and influence stakeholder decisions.

  • Customer acquisition costs: Retaining a customer is generally more cost effective than acquiring a new one. High churn rates force businesses to spend more on marketing and acquisition strategies, often without a guaranteed return on investment.

  • Product development and innovation: Churn can signal the need for product refinement or innovation. It pushes businesses to ask whether they're meeting customer needs and whether their product is evolving with market demands.

  • Employee morale and work culture: High churn rates can damage employee morale in the workplace. It's challenging for teams to constantly adapt to losing customers and to the pressure of meeting acquisition targets. This environment can reduce job satisfaction and potentially lead to higher employee turnover.

  • Long-term growth and scalability: Churn affects a business's growth. Sustainable growth and scalability rely on a stable, growing customer base. High churn rates challenge this foundation, making it difficult to project performance and plan for expansion.

Common reasons why churn happens

Churn happens for a wide range of reasons, and some are easier to address than others. Further below, we'll explain how you can prevent churn, but first let's look at the reasons it tends to happen in the first place:

  • Dissatisfaction with product or service: One of the primary reasons customers leave is because of dissatisfaction with the product or service. This can include issues with quality or performance or a feeling that expectations are not being met.

  • Poor customer service: When customers feel neglected or face poor customer service, their likelihood of churning increases. Quick, empathetic, effective responses are key to retaining customers.

  • Better alternatives available: The emergence of more appealing alternatives can lead customers to switch. This could be because of better pricing, features or value proposition offered by competitors.

  • Pricing issues: Customers are sensitive to price changes or may find the pricing not worth the value they receive. This is especially true in highly competitive markets where similar options are available at different price points.

  • Lack of engagement or connection: If customers do not feel involved or connected with your brand, they might not see a reason to stay. Building a strong relationship and community can reduce churn.

  • Changing needs: As their needs evolve, customers might find that your product or service no longer fits their requirements. Businesses must stay attuned to changing market trends and customer preferences.

  • Technical problems: Frequent bugs, downtime or technical issues with your product or service can frustrate customers and drive them away.

  • Lack of perceived value: If customers do not perceive enough value in your product or service, whether because of lack of features, benefits or differentiation, they may seek alternatives.

  • Inadequate onboarding or education: Customers who do not understand how to fully use your product or service are more likely to leave. Effective onboarding and continuous education can mitigate this risk.

  • Contract or subscription expiry: Sometimes churn is a result of a natural end to a contract or subscription, when customers opt not to renew for various reasons.

Nine ways to prevent churn

Understand customer needs and expectations

  • Gathering feedback: This involves using surveys, feedback forms and direct customer interviews to gather insights. It's important to approach a diverse range of customers, including those who are less vocal, to get a comprehensive view of their needs and expectations.

  • Analysing customer interactions: Review interactions that customers have with your service or support teams. These interactions are rich with insights about what customers are struggling with and what they appreciate.

  • Monitoring social media and online reviews: Customers often share their experiences on social media and review platforms. Monitoring these can provide real-time feedback about customer sentiment and highlight areas needing attention.

  • Using analytics tools: Tools that analyse customer behaviour on your website or app can reveal what features are used most, where customers spend the most time and where they face difficulties. This data is invaluable in understanding how customers interact with your product.

  • Segmenting customers: Not all customers have the same needs. Segmenting them based on factors such as usage patterns, purchase history and demographics can help in discerning different groups' requirements.

  • Customer journey mapping: Mapping the customer journey from start to finish can highlight challenges and moments of delight. This helps you get a sense of the customer's experience through their eyes.

  • Regularly updating customer personas: As your product and market evolve, so do your customers. Revise customer personas regularly to make sure they match customer profiles.

  • Predictive analysis: Using historical data to predict customer behaviour can help in anticipating needs and creating strategies to meet those needs before they become issues.

Improve customer onboarding

  • Simplifying the sign-up process: The initial sign-up or purchase process should be as straightforward as possible. Minimising steps and requiring only necessary information can reduce friction and prevent potential customers from getting discouraged.

  • Clear initial communication: After sign-up, guide the new customer with immediate communication. This could be in the form of a welcome email or a series of introductory messages, clearly explaining what to expect and how to get started.

  • Interactive tutorials and guides: Providing interactive tutorials or step-by-step guides can help customers work out how to use your product effectively. These resources should be easily accessible and customised to address common questions and challenges that new customers might face.

  • Personalised onboarding experience: Tailor the onboarding experience to individual customer needs. For example, different onboarding paths can be created for different types of customer, based on their position, industry or level of experience.

  • Intuitive user interface: Designing your product with an intuitive user interface that guides customers naturally through processes is key to a smooth onboarding experience.

  • Accessible support: Making support easily accessible during the onboarding process helps new customers feel that your business is meeting their needs. This could be through live chat, an easily navigable FAQ section or a dedicated customer support hotline.

  • Initial success milestones: Setting up early milestones or goals can give new customers a sense of achievement and progress. These could be simple tasks or actions within the product that encourage customers to explore.

  • Regular check-ins during onboarding: Sending regular, automated check-ins or reminders can keep new customers engaged and on track. These communications should be friendly and helpful, giving assistance if the customer appears to be inactive or stuck.

  • Resource availability: Making a comprehensive resource library available, including FAQs, how-to articles and video tutorials, allows customers to take a self-service approach at their own pace. This library should be easy to use and search.

  • Monitoring early usage patterns: Watching how new customers interact with your product can lead to insights into which aspects of the onboarding process are working well and which might need improvement.

Provide exceptional customer service

  • Anticipatory service: Instead of simply reacting to issues, anticipate potential challenges that customers might face and address them proactively. This can involve analysing usage patterns to identify common obstacles and getting in touch with solutions before the customer even recognises the problem.

  • Personalised interactions: Customise your interactions with customers based on their history and preferences. Use data intelligently to get a sense of their specific context and give more meaningful and relevant support.

  • Providing customers with self-service options: Develop comprehensive self-service tools, such as advanced knowledge bases and intelligent chatbots, enabling customers to find solutions quickly on their own. This empowers customers and frees up your support team to focus on more complex questions.

  • Rapid resolution processes: Develop a system for rapid issue resolution, which involves identifying the most common issues and creating pathways to resolve them. This could include automation tools or specialised support teams for certain types of problem.

  • Using technology for efficiency and personalisation: Implement advanced customer relationship management (CRM) systems and artificial intelligence (AI) tools to manage customer interactions more effectively. These tools can help in categorising issues, predicting customer needs and providing a personalised service at scale.

  • Building a customer-centric culture: Foster a culture within your organisation in which every team member – not just those in customer-facing roles – knows the importance of customer satisfaction and its impact on the business.

  • Continuous improvement based on advanced analytics: Use sophisticated analytics to continuously assess the effectiveness of your customer service. Look for patterns in customer enquiries and resolutions to find areas for improvement.

  • Creating emotional connections: Train your team to resolve issues and also connect with customers emotionally. Understanding and empathy can transform a standard service interaction into an exceptional one.

  • Seamless multichannel support: Give consistent support across channels (phone, email, social media and chat). Customers should receive the same level of service regardless of the channel.

  • Regularly surprising and delighting customers: Go above and beyond the expected service as often as possible. Small gestures of appreciation or unexpected levels of support can create memorable experiences and deepen customer loyalty.

Offer personalised experiences

  • Advanced data analysis for hyper-personalisation: Use sophisticated data analytics tools to dissect customer data. This includes analysing purchases, browsing behaviours and user history to create highly personalised experiences that resonate with each customer.

  • Dynamic content customisation: Implement technology that dynamically alters the content a customer sees on your platforms based on their behaviour and preferences. This could mean customising homepages, product recommendations and communication styles to match individual customer profiles.

  • Using AI for predictive personalisation: Employ AI algorithms to analyse past behaviour and also predict customer needs and preferences. This predictive approach allows for pre-emptive personalisation – providing what customers need before they ask for it.

  • Context-aware interactions: Create systems that can identify the context of each customer interaction. Whether it's recognising their stage in the customer lifecycle or the circumstances of their question, context-aware personalisation can improve the customer experience.

  • Segmentation at scale: Rather than broad segmentation, use granular customer data to create micro-segments. This allows for more precise targeting and personalised experiences that feel more relevant to each customer.

  • Personalised omnichannel experience: Consistent personalisation across all channels helps customers feel recognised and understood, whether they are interacting with your brand online, via an app, in store or through customer service.

  • Individualised loyalty programmes: Tailor loyalty programmes to individual customer preferences and behaviours through personalised rewards, exclusive content or special offers.

  • Customised communication strategies: Develop communication strategies that can be adapted to each customer's preferences in terms of frequency, channel and messaging. This includes personalising email marketing, push notifications and social media interactions.

  • Creating experiences based on emotional intelligence: Use emotional intelligence to personalise experiences. This involves picking up on emotional cues from customers and responding in a way that matches their emotional state and preferences.

  • Continuous evolution of personalisation strategies: Revisit and refine your personalisation strategies regularly to adapt to changing customer preferences and emerging technologies. Personalisation is not a one-off strategy; it requires ongoing adjustment and innovation.

Monitor customer behaviour and usage patterns

  • Implementing sophisticated tracking tools: Use advanced analytics tools to track customer interactions with your product or service. This includes monitoring click-through rates, usage duration, feature usage levels and other relevant metrics to understand customer behaviour deeply.

  • Behavioural segmentation: Go beyond traditional demographic segmentation by grouping customers based on their behavioural patterns. This can reveal more nuanced customer segments, each with distinct needs, preferences and behaviours.

  • Predictive behaviour modelling: Use machine-learning algorithms to analyse historical data and predict customer behaviours. This can help in anticipating needs, identifying potential churn risks and creating targeted interventions.

  • Heatmaps and user journey analysis: Use heatmaps and user journey analysis tools to visualise how customers navigate your product. This visual representation can highlight areas where customers experience confusion or drop-off, guiding improvements to the user interface and experience.

  • A/B testing for behavioural insights: Conduct A/B testing on different aspects of your product or service. By analysing how different customer segments respond to these variations, you can gain insights into preferences and fine-tune the customer experience accordingly.

  • Real-time behaviour monitoring: Use tools that generate real-time insights into customer behaviour. This enables immediate responses to emerging trends, issues or opportunities, allowing for adaptation of response strategies.

  • Integrating cross-platform data: Integrate data from various platforms (e.g. website, mobile app, social media, customer service interactions). This comprehensive view allows for a more complete picture of the customer's experience and behaviour across different touch points.

  • Sentiment analysis: Incorporate sentiment analysis to gauge customer emotions and attitudes. This can be done by analysing the language in customer reviews, social media posts and support interactions, providing an additional layer of insight into customer behaviour.

  • Usage of Internet of Things (IoT) and smart data: For businesses with physical products, using IoT can provide detailed usage data. This smart data can supply insights into how products are used in real time, leading to more informed product development and customer support strategies.

  • Advanced reporting dashboards: Develop or use sophisticated dashboards that present behavioural data in an actionable format. These dashboards should allow for easy interpretation of complex datasets, enabling quick decision-making and strategy adjustment.

Use all available data

  • Data consolidation: Consolidate data from various sources – sales, customer service, social media, web analytics and more – to create a unified view of each customer. This integration allows for a more holistic understanding of customer behaviours and preferences.

  • Advanced analytics for deeper insights: Use advanced analytical techniques, such as machine learning and predictive analytics, to extract deeper insights from your data. This can involve identifying patterns, predicting behaviours and finding hidden relationships within the data.

  • Data-driven personalisation: Use the collected data to personalise every aspect of the customer experience. From customised marketing messages to tailored product recommendations, data-driven personalisation can make for more engaged and satisfied customers.

  • Real-time data utilisation: Use systems that can process and act on data in real time. This allows for immediate adjustments to marketing campaigns, dynamic pricing models and on-the-spot personalised customer interactions.

  • Sentiment analysis and emotional intelligence: Analyse customer feedback, reviews and social media interactions to gauge sentiment and emotional responses. This level of analysis can result in insights into customer satisfaction and brand perception.

  • Customer lifetime value analysis: Data can help you calculate and predict the lifetime value of individual customers. This analysis can inform marketing spend, retention efforts and resource allocation, allowing you to focus on the most valuable customer segments.

  • Churn risk analysis: Analyse customer data to identify early warning signs of churn. Predictive models can help in taking proactive measures to retain at-risk customers.

  • Market trend analysis: Use external data sources to monitor market trends and customer behaviour shifts. This helps in staying ahead of the curve and adapting to changing market conditions.

  • Data visualisation for clear stakeholder communication: Use data visualisation tools to communicate complex data insights clearly and accessibly. This helps in keeping stakeholders involved and facilitating data-driven decision-making across the organisation.

  • Ethical and privacy-compliant data use: Ensure that your data utilisation practices comply with all privacy laws and ethical standards. Responsible data use is central in maintaining customer trust and avoiding legal repercussions.

Communicate with customers regularly

  • Predictive and personalised messaging: Use data not just to inform but to foresee customer needs. For instance, if a customer regularly checks out fitness gear, send them a message when there's a new arrival or a special offer in that category. It's like having a conversation in which you're always one step ahead, ready with just what they need before they ask.

  • Storytelling that connects: Turn your communications into a narrative that customers want to be part of. Share stories orientated towards your values that resonate with theirs. For a brand focusing on sustainability, share how a product was created from conception to availability, showcasing the environmental impact. This approach turns every message into a chapter of a larger story in which customers feel involved.

  • Interactive and responsive conversations: Shift from informing to connecting. After a purchase, a personalised message asking for feedback makes the customer an active participant in the conversation. Use social media for real-time, dynamic interactions. Turn every digital touch point into a two-way street, creating a sense of community and belonging.

  • Empathetic crisis communication: In challenging times, your tone and responsiveness can leave a lasting impression. Be up front about issues, empathise with those affected and be clear about resolutions. For example, during a service disruption, proactive communication outlining the problem, expected resolution time and preventive measures for the future can build trust.

Address customer problems straight away

  • Rapid response systems: Develop a system in which customer issues are quickly acknowledged. This could involve automated responses that assure customers that their concern has been logged and will be addressed promptly. For instance, a customer raising an issue through your support portal immediately receives a confirmation with an estimated time for resolution.

  • Prioritisation of issues: Set up a triage system that categorises problems based on their urgency and impact. Issues that affect many customers or major aspects of your service should be addressed with urgency. Giving the most immediate attention to the most pressing problems minimises potential fallout.

  • Well-trained frontline employees: Equip your customer-facing staff with the authority and resources to resolve common issues on the spot. When a customer contacts support, the first person they interact with should have the knowledge and permission to address the majority of standard problems without needing to escalate.

  • Real-time problem tracking: Use tools that allow you to track the status of a customer's problem in real time. This transparency enables customers to see the progress being made on their issue, reducing uncertainty and frustration.

  • Proactive problem detection: Invest in systems that can detect and flag potential issues before they become customer problems. This could involve monitoring software for your digital products or quality checks for physical goods. Addressing these issues proactively can prevent customer dissatisfaction.

  • Integrating feedback into problem resolution: After resolving a customer's problem, gather feedback on their experience. Feedback indicates how well the issue was handled and also shows the customer that you're committed to continuous improvement.

  • Clear communication throughout resolution: Keep the customer informed throughout the problem-solving process. Regular updates on the status of their issue – especially if it takes longer than expected to resolve – help to maintain trust.

  • Post-resolution follow-up: After an issue has been resolved, a follow-up to check that the customer is satisfied with the solution reinforces that you care about their experience beyond just the transactional interaction.

Be strategic – and transparent – about pricing

  • Clear pricing structure: Make your pricing as straightforward as possible. Avoid hidden fees or complex pricing tiers that can confuse and frustrate customers. A simple, easy-to-understand pricing model with well-defined features at each level helps customers make informed choices without feeling misled.

  • Market and value alignment: Your pricing should reflect the value that you provide and your position in the market. Conduct thorough market research to understand what your competitors charge and how your products or services compare. This ensures that your pricing is competitive and in line with customer expectations.

  • Value communication: It's important to communicate the value behind your pricing. Emphasise the benefits and unique aspects of your product or service that justify the cost. For instance, if your product is priced higher than that of competitors, emphasise its superior quality, unique features or exceptional customer service.

  • Dynamic pricing models: Consider implementing pricing strategies that can adapt to market conditions, customer segments or purchase behaviours. However, this should be done carefully to avoid alienating customers. Transparency is key in explaining why prices may vary.

  • Transparent changes in pricing: If prices must be adjusted, communicate these changes openly and proactively to your customers. Explain the reasons behind the price increase, focusing on how it will enable continued improvements to your product or service.

  • Customisable pricing options: Provide pricing flexibility where possible. This can include tiered pricing, discounts for longer commitments or customisable packages. Such options cater to different customer needs and budgets, so your product or service can attract the broadest possible audience.

  • Feedback loop on pricing: Actively seek and consider customer feedback regarding your pricing. Feedback that indicates how customers perceive the value they get for the price they pay can lead to applicable insights for future pricing strategies.

  • Ethical pricing practices: Always adhere to ethical pricing standards. This builds trust and safeguards your brand's reputation. Avoid practices such as price gouging or misleading promotions that can damage customer relationships.

How Stripe can help

Stripe's suite of payment solutions can be used to further analyse customers' behaviour and preferences, identify challenges or weaknesses in operations and customer experience, and give businesses the most useful types of customer data.

Stripe can contribute meaningfully to a business's proactive efforts around churn reduction. Here's a closer look at how Stripe can help in this area:

  • Stripe Billing for subscription management: Stripe Billing makes managing subscriptions easier. It allows businesses to set up varied billing models, such as tiered pricing (in which the cost changes based on usage levels) or per-seat pricing (suitable for SaaS platforms). These options enable businesses to tailor their billing to customer usage, reducing churn with more appropriate and flexible pricing structures.

  • Intelligent payment retries and dunning management: Stripe uses machine learning to optimise the retry of failed payments, determining the best times to attempt a transaction again, which increases the chances of collecting revenue without customer intervention. For dunning management, Stripe automates email notifications to customers with failed payments, gently reminding them to update their payment details, thus addressing involuntary churn.

  • Customised checkout experiences: Stripe Checkout is highly customisable, allowing businesses to design a brand-appropriate payment experience. This includes adjusting the layout, adding custom fields and embedding an entire checkout process within the product's app or website, reducing drop-offs during the payment process.

  • Stripe Sigma for customer insights: Stripe Sigma provides SQL-based querying to analyse transaction data deeply. Businesses can use this tool to track customer spending habits, subscription renewals or payment declines to identify patterns that may indicate a risk of churn. Analysing this data allows businesses to act pre-emptively.

  • Stripe Radar for fraud detection: Radar uses advanced algorithms and machine learning to detect and block fraudulent transactions. By minimising fraud, businesses can maintain a secure environment for their customers, which is important for retaining trust and reducing churn related to security concerns.

  • Global payment solutions: Stripe's global payment capabilities enable businesses to accept a wide range of currencies and payment methods. This feature is particularly beneficial for businesses with an international customer base, because it accommodates different regional preferences in payment methods, reducing barriers to successful transactions.

  • CRM and customer support integrations: The ability to integrate with popular CRM and customer support tools means that businesses can consolidate customer interaction data with payment information. This comprehensive view allows for more personalised customer service and targeted responses to issues, which can help in retaining customers.

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