The concept of CLV has been around for a long time. The exponential growth towards the use of AI has brought a whole new breath of fresh air to this complex and yet imperative concept that impacts all forms of businesses. The question we need to address is the relation of AI to CLV. Like many other metrics, AI helps analyze CLV more efficiently. This doesn’t necessarily mean that AI-powered analysis does something entirely different. Instead, it does the same thing humans do – just better. With humans, there is always a chance of error in calculation or biased forecasts. But with AI, the whole process is much more reliable. As a result, AI eliminates human error and effort from CLV insights enhancing speed and efficiency along the way.
While acquisition strategies are essential, businesses are beginning to realize that their real competitive advantage lies in nurturing long-standing relationships with existing customers. CLV is a metric that dives deep into the revenue stream generated throughout the customer journey by way of their association with a brand. Coupled with AI, CLV modeling can offer predictive insights that can strategically steer marketing efforts for sustained growth. The key is nurturing relationships with existing customers and expanding their lifetime value. CLV modeling using AI provides powerful predictive insights to optimize marketing strategies for growth.
Benefits of Using AI-powered CLV Modeling
1. Increased Customer Retention
By using AI to analyze customer data, businesses can identify specific areas where they can address service gaps, improve the customer experience and boost loyalty, leading to higher retention and profits over time.
2. Improved Customer Acquisition
AI-powered systems are able to use existing consumer data, identify new potential customers and target them with personalized messages and offers. These businesses are able to acquire new customers at a higher rate than their competitors.
With the assistance of AI, a business can achieve an optimal blend of diverse products, discover the best approaches, tailor specific preferences for individual customers or specific groups, and determine the most suitable channels for acquiring new customers at a cost-efficient rate. This streamlines marketing budgets and acquisitions, preventing excessive expansion.
3. Reduced Marketing Costs
Acquiring new customers is more expensive than retaining existing ones. AI can help businesses reduce marketing costs while still acquiring new customers, providing businesses with detailed insights into the consumer behavior of their target audience. This allows businesses to create cost-effective, targeted marketing campaigns that are more likely to convert potential customers into paying ones.
4. Increased Efficiency
Businesses that use AI to manage CLV reap the benefits of increased efficiency. This is because AI-powered systems automate many of the tasks associated with managing customers, freeing up human employees to work on high-touch, high-impact tasks that further enhance the customer experience.
How to Make AI Work in Optimizing and Increasing Your Profits
In order to make AI work in optimizing CLV and increasing your profits, you will need to take advantage of existing, relevant customer data. Here are a few ways that you can use AI to enhance CLV management:
Conclusion
By operationalizing AI-powered CLV models across the organization, brands can optimize every touchpoint to maximize customer value over their entire lifecycle. The ultimate competitive advantage will come from retaining and enriching relationships with core customer segments over the long term and at the same time maximizing business profitability.
Aboitiz Data Innovation (ADI) is a forward-thinking data science and AI firm that has provided data-driven, transformative AI consulting to businesses across diverse sectors, including banking & financial services, power, and smart cities (real estate, airports, construction, land and food) industries.
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