How can you analyze customers to improve lifetime value?

in my experience to gain more LTV of our customer, for example in the Saas Industry, then you need to make them comfortable with your product and services (after sales supports). you need also to know their necessities and help them to find what are missing from their business or operations. Act as a business consultant for them, do some review about the product that their use from us, speak about their business not only sell or upsell our products, so they will feel comfortable with us, and most importantly if there is a failure or problem with our products and user experience make a fast response for support and improvements. and from commercial side we could also set a multi month contract to avoid hijacking’s from competitors.

Digital customers are looking to derive value from every transaction. Shifting brand loyalty is at the highest level. In such a scenario; not the measurement alone, but proactive measures to reduce detractors are necessary for enhancing Customer lifetime value. This can only be achieved through data-driven interventions and automation using CRM software. Behavior-based cohorts can be automatically identified, and events need to be triggered to personalize every customer interaction for higher customer lifetime value.

Segment your customers ?? Begin by dividing your customer base into distinct segments based on shared characteristics such as demographics, behavior, or purchase history. AI can help analyze vast datasets from sources like LinkedIn, revealing patterns that might not be immediately apparent. By understanding these segments, you can tailor your strategies to meet the specific needs and preferences of each group.

Here are some key strategies that I find helpful when analyzing customers and enhancing their lifetime value: Customer Behavior Analysis: Analyze customer behavior, including purchase patterns, frequency, and recency. Cross-Selling and Upselling Opportunities: Identify cross-selling and upselling opportunities. Churn Analysis: Identify common patterns and factors contributing to churn, allowing you to implement strategies to reduce it. Personalization: Personalization can enhance the customer experience By understanding your customers better, you can create targeted strategies that foster loyalty and drive long-term value for both the customer and your business.

Segmentation of customers based on their behavior and characteristics is an effective approach to enhance their lifetime value. This approach involves detailed analysis of purchase history, frequency of visits, demographics and other data to identify patterns and trends. The information obtained from this analysis can then be utilized by businesses to tailor their marketing and retention strategies, with the aim to better meet the needs of each segment and ultimately increase their lifetime value. Furthermore, obtaining regular feedback and running surveys with customers is a valuable source of information that can be used to gain insights into their preferences and pain points, which in turn inform improvements to products and services.

If you can't measure it, you cannot understand or control it. Without control, improvement is impossible. For businesses, understanding key metrics, like Customer Lifetime Value, is vital. However, in most CRM systems, even when used as intended, there doesn't seem to be an immediate way to surface these metrics and, more importantly, track their trends over time. Unlocking the full potential of your business metrics requires not just measurement but also the tools to analyse and interpret their trends for informed decision-making and continuous improvement.

Calculate CLV for each segment ?? Utilize AI algorithms to accurately calculate the Customer Lifetime Value (CLV) for each segment. This involves predicting the potential revenue a customer segment can generate throughout their entire relationship with your business. LinkedIn data can contribute valuable insights into the professional trajectories of your customers, aiding in a more precise CLV estimation.

The company's business model and the customer's purchase history are traditionally the main drivers for calculating CLV, LTV or even RFM. However, I have been warning companies that we are living in times of exponential change in people's relationships with brands and in the ways they purchase and that, therefore, data that often reflects the past of the customer's relationship with the brand may no longer be useful. guidelines on how your future behavior will be in this relationship.

By leveraging the power of CRM data, businesses can uncover valuable variables within each customer segment and make insightful comparisons across segments. This data-driven approach enables organizations to go beyond basic analysis and delve into more advanced models that factor in crucial elements such as costs, discounts, churn rates, and retention rates. By considering these variables, businesses can gain a deeper understanding of their customer base, identify opportunities for improvement, and develop effective strategies to drive growth and enhance customer loyalty. Remember, the key lies in harnessing the potential of your CRM data to make informed and impactful decisions.

Leverage advanced analytics, segment customers Gather data from various touchpoints this datafrom (CRM) system or a data analytics platform. Divide your customer base into segments based on relevant criteria Gather feedback from customers through surveys, reviews, and direct Leverage predictive analytics to forecast future customer behavior. Map the entire customer journey, from awareness to purchase and post-purchase interactions. Evaluate customer service interactions to identify areas for improvement. Based on key metrics, and implement personalized strategies to optimize customer experience, foster loyalty, and maximize lifetime value.

Once you have identified the high-value and low-value segments based on their CLV, loyalty, retention, and acquisition costs, you can take strategic actions to optimize your business outcomes. For high-value segments, you can focus on nurturing and retaining these customers by offering personalized experiences, loyalty programs, and targeted marketing campaigns. Additionally, you can allocate resources efficiently by prioritizing acquisition efforts towards potential customers who align with the characteristics of high-value segments. For low-value segments, you can reassess your marketing and sales strategies, considering options such as refining your target audience, adjusting pricing or offerings, or exploring new market opportunities.

Identify high-value and low-value segments ?? Through AI-driven analysis, pinpoint which segments contribute the most to your overall revenue and long-term success—these are your high-value segments. Conversely, identify low-value segments that may not be as lucrative. LinkedIn community data can provide professional context, shedding light on potential growth or limitations within specific segments.

Identifying high and low value segments drives everything from a company’s marketing strategy, to sales techniques, to product and service development. It is the way a business can identify target customers on which to focus. - Provides clarity on customer acquisition spending - High and Low value segments helps drive changes and introduce new features to better suit the targeted audience

Implementing personalization strategies is a key component of improving CLV. Understanding individual customer preferences enables businesses to tailor their communication and offerings, creating a more engaging and satisfying experience. This can involve sending personalized recommendations, offering exclusive deals based on past purchases, or providing targeted content that aligns with customer interests. Moreover, businesses can utilize automation and artificial intelligence to scale personalization efforts, ensuring that even as the customer base grows, individualized experiences remain a priority.

Optimize your strategies for each segment ?? Leverage AI to develop tailored marketing, communication, and product strategies for each segment. By understanding the unique characteristics and behaviors of high-value segments, you can optimize engagement and retention strategies. Simultaneously, address the pain points of low-value segments to enhance their experience and potentially convert them into higher-value customers.

optimize your CRM strategies based on CLV and potential, you can further enhance your business performance by implementing data-driven decision-making. Utilize customer analytics to gain insights into customer behavior, preferences, and patterns. This will enable you to tailor your marketing campaigns, product offerings, and customer experiences to better meet their needs. Develop a comprehensive customer journey map to understand touchpoints and interactions throughout their buying process, allowing you to identify opportunities for improvement and provide a seamless experience. Continuously monitor and measure the effectiveness of your CRM strategies through key performance indicators.

a. Feedback Loops: Integrate AI-powered feedback mechanisms to continuously refine your understanding of customer needs and sentiments. b. Dynamic Adaptation: Use AI algorithms to dynamically adjust strategies based on evolving customer behaviors and market trends. c. Personalization: Implement AI-driven personalization across customer interactions, enhancing engagement and fostering loyalty. d. Cross-Sell and Up-Sell Opportunities: Identify and leverage AI to capitalize on cross-sell and up-sell opportunities within high-value segments. e. LinkedIn Insights Integration: Stay connected with the LinkedIn community for real-time professional updates, aligning your strategies with the latest industry trends and professional developments.

Remember, it’s more cost effective to increase lifetime value from existing customers than it is to pay to acquire a new customer. 2 key metrics to focus on… Increase LTV Reduce CAC I’ve generated over $15,000,000 in sales. More like this on my profile.

Luego de tener la claridad de tus clientes ideales, es esencial también considerar qué canales de los que usan puedes realmente alcanzar y administrar como individuo o empresa, para no perder esfuerzo y recursos en medios que finalmente no podrás sostener en el tiempo (o no aún). Si concentras tu trabajo en aquellos canales que realmente puedes gestionar sostenidamente, de seguro tendrás mejores resultados. ?La perseverancia trae resultados!

One of the biggest drawbacks of any traditional customer CLV calculations is that there needs to be a large enough sample size (number of customers) in order for the CLV calculation to be meaningful. So, you have to be very thoughtful of the numbers. Because, unless the company is either doing something very right (in which case, we’d expect these numbers to increase drastically) or very wrong (decrease drastically), the results don't prove to be very helpful.