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  • Kuba Płonka

Preventing Problems, Winning Hearts: The Art of Proactive Care

We live in an ever-changing landscape of customer support… and that is a marvellous thing! New ventures arise, offering a revolutionary way to amaze us with not only their offering but also the experience they offer both in the pre-sale and post-sale phases.

Bigger and smaller companies must adapt and invest time and resources into more sophisticated customer success and customer experience. Thanks to that transformation, we can all now benefit from having high-standard support that was just a dream a few years ago. That shift wouldn’t happen if we wouldn’t advance in technology, how we can use it, and the best things yet to come.

How it started and what we have right now

"56% of people surveyed would rather message a business than call customer service, and 67% expect to message businesses even more over the next two years."

In the past, obtaining customer support was often a frustrating experience due to long wait times and repetitive phone calls to call centres. Nevertheless, more efficient and personalised customer service has become increasingly necessary with business expansion and technological advancements.

The emergence of data analytics and machine learning has revolutionised how companies approach customer support. Businesses can gain valuable insights into customer behaviour, preferences, and pain points by collecting and analysing vast amounts of customer data. This wealth of information allows companies to understand their customers deeper and tailor their services to meet their needs. But one of the most significant recent breakthroughs in the CS and CX area comes from the power of AI.

"AI technologies could potentially deliver up to $1 trillion of additional value each year."

One of the most essential benefits of AI-powered customer service is the ability to provide personalised support at scale. By analysing data from various sources, AI systems can gain a holistic understanding of each customer's unique needs and preferences. This allows businesses to offer tailored recommendations, products, and services relevant to each customer, resulting in a more engaging and satisfying experience.

Another advantage of AI-powered customer service is the ability to automate repetitive tasks and processes. By automating routine inquiries and issues, businesses can free up the CS team to focus on more complex cases and provide personalised support when needed. This not only improves the efficiency of the customer service team but also allows for a higher level of service overall.

"Happy customers want to support the businesses they love. 90% of consumers are more likely to purchase more, and 93% are more likely to be repeat customers at companies with excellent customer service."

It's worth noting that chatbot solutions powered by AI are becoming increasingly popular in both B2B and B2C channels as they enhance the customer experience. With chatbots, customers can receive immediate assistance 24/7 without being put on hold. These bots are programmed to handle various inquiries and issues, from simple questions to complex technical problems. This not only improves the overall customer experience but also frees up customer service agents to focus on more complex cases and provide personalised support when required.

Finally, AI-powered solutions enable businesses to predict potential issues before they arise. By analysing patterns and trends in customer data, AI systems can alert companies to potential problems and offer solutions before they become significant issues. This proactive approach not only improves the customer experience but also helps businesses avoid costly mistakes and maintain customer satisfaction.

"Machine learning is at the heart of everything we do at Spotify."

Spotify, a well-known music streaming service, employs proactive support to improve customer satisfaction. They use machine learning algorithms to analyse users' preferences and listening habits, which informs Spotify's Discover Weekly feature. Every Monday, users receive personalised music recommendations which cater to their unique tastes. By creating individualised playlists, Spotify provides customers with new and exciting music discoveries, eliminating the need for them to search for new songs. This proactive approach not only enhances the overall user experience but also fosters more robust user engagement and loyalty. If you want to know more about how Spotify uses machine learning, here is a fantastic article.

Creating a Proactive CS Strategy

To create an effective proactive customer service strategy, consider the following tips and guidelines:

Embrace data-driven insights Collect and evaluate customer information from various channels, such as purchase records, feedback, and social media engagements. This data offers a robust understanding of customer inclinations, empowering you to provide personalised solutions.

Leverage AI and automation Efficiently analyse customer data by utilising AI-powered tools. Machine learning algorithms can detect patterns, anticipate customer behaviour, and automate personalised interactions, ultimately saving time and effort while providing exceptional service.

Anticipate and resolve issues proactively One practical approach to improving customer experience is identifying common pain points and proactively developing solutions to address them. Creating self-service resources like knowledge bases, tutorials, and troubleshooting guides can empower customers to resolve issues independently.

Personalise interactions Utilise customer data to personalise interactions and recommendations, showcasing a profound comprehension of their preferences. Tailor communication, offers, and suggestions based on their needs and preferences to establish a stronger connection with them.

Measuring the Success of Proactive Customer Service

As always, there are as many metrics as teams and use cases, so keep that in mind and tailor them to YOUR specific need and specifications of your customers and their journey with your product or service.

  1. Customer Satisfaction Score (CSAT): Conduct regular surveys to gauge customer satisfaction with proactive support initiatives. A higher CSAT score indicates that proactive measures are positively impacting customer experiences.

  2. First Contact Resolution (FCR) Rate: Measure the percentage of customer inquiries resolved during the initial interaction. A high FCR rate signifies that proactive customer service efforts effectively address customer needs, reducing the need for multiple contacts.

  3. Customer Retention Rate: Track the percentage of customers who continue doing business with your company over time. A higher retention rate indicates that proactive support initiatives foster customer loyalty and satisfaction.

  4. Response Time: Monitor the time it takes for your support team to respond to customer inquiries or proactive outreach. Decreasing response times ensures timely assistance and enhances customer satisfaction.

Finish line

"83% of consumers want companies to contact them proactively to provide customer service."

In today's competitive business environment, providing exceptional customer experiences requires being proactive in customer service. Leveraging data analytics, machine learning, and AI enables businesses to anticipate customer needs, address potential issues proactively and exceed customer expectations. Essential steps to enhance customer satisfaction include implementing personalised outreach, creating self-service resources, and providing proactive assistance.

Measuring success through KPIs and tools like OKRs allows businesses to continuously improve their proactive customer service approach continuously, fostering long-term customer loyalty and business growth. With a customer-centric mindset and the power of technology, companies can revolutionise how they serve their customers.


Here are some additional resources for those who want to dive deeper into the topic:

  • The article "Customer Experience in the Age of AI" by Harvard Business Review provides real-world examples and guides leveraging AI to drive customer-centricity and business growth.


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