How can you improve customer lifetime value for people with limited cognitive ability using data analytics?

Customer lifetime value (CLV) is a metric that measures how much profit a customer generates for a business over their entire relationship. It helps businesses optimize their marketing, retention, and loyalty strategies. However, some customers may have limited cognitive ability due to various factors, such as age, disability, or education. How can you use data analytics to improve CLV for these customers? Here are some tips.

1 Understand your customers

The first step is to understand who your customers are, what their needs and preferences are, and how they interact with your products or services. You can use data analytics tools, such as customer segmentation, behavioral analysis, and sentiment analysis, to create customer profiles and personas based on their demographics, psychographics, and behavioral patterns. This will help you tailor your offers, communications, and experiences to their cognitive abilities and expectations.

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2 Simplify your processes

The second step is to simplify your processes and make them easy and intuitive for your customers. You can use data analytics tools, such as usability testing, A/B testing, and conversion rate optimization, to identify and eliminate any friction points, confusion, or errors in your customer journey. For example, you can simplify your website design, checkout process, payment options, and customer service channels. You can also use data analytics to automate and personalize some of the processes, such as sending reminders, confirmations, and feedback requests.

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3 Educate your customers

The third step is to educate your customers and help them make informed decisions. You can use data analytics tools, such as content analysis, recommendation systems, and gamification, to create and deliver relevant, engaging, and helpful content to your customers. For example, you can provide product reviews, testimonials, tutorials, FAQs, and tips to your customers. You can also use data analytics to reward your customers for learning and using your products or services, such as giving them points, badges, or discounts.

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4 Engage your customers

The fourth step is to engage your customers and build a long-term relationship with them. You can use data analytics tools, such as social media analysis, email marketing, and loyalty programs, to communicate and interact with your customers regularly. For example, you can send them newsletters, surveys, invitations, and offers to keep them updated and interested in your brand. You can also use data analytics to segment and target your customers based on their loyalty level, satisfaction, and feedback.

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Venkata Sreenivas Kottapalli

Product Manager @ Oracle Netsuite | CSPO | MBA, Finance
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Agreed! Engaging by means of surveys/interviews, helps in retrieving customer needs and could be helpful in preparing single/minimal solution(s) for multiple problems!!

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5 Delight your customers

The fifth step is to delight your customers and exceed their expectations. You can use data analytics tools, such as customer satisfaction analysis, net promoter score, and customer lifetime value analysis, to measure and improve your customer satisfaction and loyalty. For example, you can use data analytics to identify and reward your most valuable customers, such as sending them thank you notes, gifts, or exclusive deals. You can also use data analytics to anticipate and solve any problems or complaints that your customers may have.

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Rachit Agarwal

Data Scientist
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Creating a loyalty program with tiers and personalized incentives, akin to programs like Delta Medallion Levels or Marriott Bonvoy, is a powerful strategy for delighting high-value customers and fostering long-term relationships. Data analytics plays a crucial role in the success of such programs by providing insights and driving informed decision-making. Through customer segmentation and machine learning, businesses can tailor rewards and incentives based on individual preferences, ensuring a more precise and effective approach to delighting high-value customers. By continuously enhancing the customer experience and offering meaningful rewards, companies can exceed expectations and keep their most valuable customers engaged and satisfied.

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6 Evaluate your results

The sixth step is to evaluate your results and adjust your strategies accordingly. You can use data analytics tools, such as dashboards, reports, and visualizations, to monitor and analyze your key performance indicators (KPIs), such as customer acquisition cost, customer retention rate, customer churn rate, and customer lifetime value. For example, you can use data analytics to compare your results with your goals, benchmarks, and competitors. You can also use data analytics to test and optimize your hypotheses, experiments, and campaigns.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can you improve customer lifetime value for people with limited cognitive ability using data analytics?

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1 Understand your customers

2 Simplify your processes

3 Educate your customers

4 Engage your customers

5 Delight your customers

6 Evaluate your results

7 Here’s what else to consider

Data Science

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How can you improve customer lifetime value for people with limited cognitive ability using data analytics?

1

2

3

4

5

6

7

1 Understand your customers

2 Simplify your processes

3 Educate your customers

4 Engage your customers

5 Delight your customers

6 Evaluate your results

7 Here’s what else to consider

Data Science

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