Integrating Customer Insights into Your Customer Success Strategy

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    More About Customer Intelligence

    Understanding and responding to customer needs is crucial for any Customer Success strategy to be effective. Many organizations have a very surface-level view of customer insights. It’s much more than simply asking your customer for feedback and planning to implement it. Customer insights are deep understandings of your customers’ behaviors, preferences, and feedback, which allow Customer Success Managers to make more informed, customer-focused decisions. It’s time for organizations, especially within the SaaS space, to think bigger and be more intentional with how they implement customer insights. 

    Let’s talk more about what this means for you and your organization.  

    What Are Customer Insights?

    First off, let’s define what it is. Customer insights are what you get when you heavily utilize customer data to discover the behaviors, preferences, and needs of your customers. It’s how companies can build a more personalized customer experience. 

    Data is the foundation of customer insights. The good news is that there are a lot of tools coming out of the woodwork that make gathering customer data much easier for any organization. 

    This is part of a series of articles about customer intelligence.

    The Importance of Customer Insight for Customer Success

    Gathering customer data is the foundation for generating customer insight. There’s no way around this. 

    The modern customer wants a personalized approach. Salesforce research found that 66% of consumers expect companies to understand their unique needs and expectations, and 52% expect all offers to be personalized.

    In Customer Success, those insights are pivotal in delivering value, anticipating customer needs, and creating long-term loyalty. The power that customer insights bring can be found mainly in its diversity. Knowing the different types of behavior, attitudes, and demographics within your customer base can help tailor your strategies effectively.

    Types and Examples of Customer Insight

    Behavioral Insight

    To derive behavioral insights, you can leverage analytics platforms that track and analyze customer interactions with your product or service. Tools like Google Analytics, Mixpanel, and Amplitude are excellent for understanding the behavior of your customers. You can track metrics like page views, session duration, and bounce rates. These insights give you a clear view of how users navigate and engage with your platform. 

    For a more in-depth analysis of product usage, tools like Pendo or Hotjar offer heatmaps, session recordings, and in-app surveys to understand feature usage and identify usage gaps.

    Attitudinal Insight

    For attitudinal insights, sentiment analysis tools are key. AI-powered platforms like Qualtrics, SurveyMonkey, and Zendesk offer amazing sentiment analysis capabilities. These tools help CSMs gauge customer satisfaction, understand feedback, and identify trends in customer sentiment. These tools can analyze data from surveys, social media, support tickets, and online reviews, providing a comprehensive and holistic view of customer attitudes toward your brand.

    Demographic Insight

    Gathering demographic insight often starts with collecting data through your CRM, like Salesforce or HubSpot. These platforms can store and manage customer data, including job function, location, job title, and industry. Both can integrate with many other data tools like Clearbit or LeadGenius. All of this data allows for better customer segmentation which leads to more personalized marketing campaigns and tailored customer experiences.

    Drawing Insight From Customer Data

    Drawing practical insight requires more than just collecting data. The following steps are key to discerning what data is necessary for long-term customer relationships:  

    • Utilizing Customer Feedback: Consider implementing tools like Typeform or Google Forms to collect direct feedback. NLP (Natural Language Processing) technologies can help analyze open-ended responses, providing deeper insights into customer sentiment.
    • Analyzing User Behavior: Utilize advanced data analytics platforms like Tableau or Looker to see user behavior data and determine patterns or trends. These tools can integrate data from various sources, offering a holistic view of customer interactions.
    • Leveraging Customer Interactions: CRM platforms, when integrated with communication tools like Slack or Microsoft Teams, can turn customer interactions into actionable insights. Customer service platforms like Zendesk or Freshdesk capture every customer touchpoint, providing the perfect dataset for analysis and insight generation.

    Integrating Customer Insight into Your CS Strategy

    Now that you know how to gather the right data, it’s time to apply it. The true test of customer insight is its application. Here’s how these insights can play a pivotal role in shaping your CS strategies.

    Customizing Customer Success Plans Based on Customer Insight

    • Personalized Onboarding Processes: Onboarding is the foundation of almost every CS engagement. Use customer insights to create tailored onboarding experiences that address specific customer pain points, job titles, and goals of your customers. This will help mitigate churn, build better customer relationships from the get-go, and position your CSM team as subject matter experts to all your new clients. 
    • Tailored Communication Strategies: This is simply the process of developing communication plans that resonate with different customer segments based on their behavior and preferences. A combination of analytics and direct client feedback can help you find the right channels and frequency to improve your customer interactions; whether it be slack, emails or meetings. 

    Proactive Issue Resolution with Predictive Customer Insight

    • Anticipating Customer Needs and Challenges: Predicting future behavior can help you proactively offer solutions before issues arise. With the help of AI, it’s now much easier to analyze all sorts of customer interactions and product or service usage at scale to generate accurate customer health scores and sentiment analysis.  Both of these data sources are extremely valuable to Customer Success leaders since they serve as early indicators of customer satisfaction and loyalty. All of this important data can live in one place for full account visibility.   
    • Preventing Potential Issues: Utilizing these insights can also mitigate churn and improve overall customer satisfaction. Data driven insights mean more accurate and unbiased customer risks are being reported on in real-time. As mentioned earlier in the article, feedback is a big part of customer insights. Having accurate, up-to-date feedback from your customers can help Customer Success teams be more proactive in their approach to each customer situation. Whether it’s identifying an issue before it becomes an escalation or providing an exciting update on a feature request your customer just submitted, all forms of customer feedback are opportunities for CSMs to provide value. 

    Continuous Improvement through Feedback Loops

    • Collecting Ongoing Customer Feedback: Consider implementing tools that provide real-time analysis and alerts when there are changes with your customers. Whether their health score changed, a new support ticket was logged, or an angry tone was detected in a communication; it’s important to understand a holistic and up-to-date view of your customers. 
    • Iterative Adjustments to CS Strategy Based on Insights: Continuously refining customer success initiatives to align with evolving customer expectations is key for long-term success. Over time you can collect data and draw insights on what customer success strategies work and which don’t. For example, are your customers more likely to renew their contract when regular business reviews happen? Or when more people from your clients’ organization are involved with the deal?
    • Encouraging Customer Advocacy through Positive Experiences: You turn satisfied customers into brand advocates by consistently exceeding expectations based on their feedback. An effective customer insights platform can help your team easily identify which customers fit this profile. It can help you actively target them for testimonials, case studies, and referrals. 

    Common Challenges to Integrating Customer Insight

    Even with the best intentions, firms encounter blocks like outdated data, biased information, and an overreliance on human memory or limited CRM data. These challenges often result in strategies that are out of sync with the current customer scenario and don’t accurately represent the current customer experience. 

    Strategies to Overcome Challenges

    One of the most effective ways to overcome these obstacles is through advanced technologies like AI. Modern solutions can provide accurate, objective, and real-time data collection directly from the source. AI-powered tools like go beyond traditional customer insights to predict consequential business outcomes such as churn, account expansion, and revenue opportunities. Plus, this data collection is continuous so it’s always up to date with accurate information. 

    Evolving Customer Insight and CS Strategies

    With the advent of AI and machine learning, the future of customer insights looks towards predictive analytics—turning engagement and sentiment data into predictive insights for churn and growth.

    Staircase AI is a tool that makes the gathering of customer insights easy and effective. Our AI-driven metrics draw on meaningful insights by analyzing all your customer interactions with your company through all your communication channels to determine their overall sentiment and health. When you use Staicase’s AI analysis, you can accomplish the following: 

    • Drive Real Business Insights and Action Items: Identifying behaviors, attitudes, and demographic data is important. Now you can expand on that data and drive insights that lead to real business outcomes based on the data gathered through Staircase.  
    • Turn Engagement and Sentiment Insights into Real-Time Predictions: churn, expansion, revenue, and more can now be more accurately measured thanks to AI-driven insights. It also makes it easier to identify customers who are likely and least likely to renew. 
    • Forecast Growth and Expansion Opportunities: It’s been proven time and time again that expansion revenue generates more long-term business growth than new revenue. AI-driven insights provided by Staircase are what make it possible for any organization to identify expansion opportunities in real time by making it much easier for Customer Success teams to bring in more revenue for their organizations. 


    Customer Success strategies must be adaptable. Industries, especially SaaS, are always evolving. The needs of our customers are always changing. Having a mindset of adaptability will be a key to continued success even in the more stable markets. 

    Key Takeaways:

    • AI is not just for show but a strategic tool to turn data into real-time insights.
    • Utilizing current, unbiased insights aligns CS strategies with actual customer narratives.
    • The integration of predictive analytics stands to improve Customer Success frameworks, giving CS leaders visibility into more growth and expansion opportunities.

    Using the strategies and steps talked about in this article will position your organization and customers for long-term success.