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Artificial Intelligence: The key to Customer Lifetime Value
Fri, 1st Mar 2024

Every business, no matter the category or industry, is in a relationship with its customers. It's the extent of that relationship that's important. It's the long-term partners you want, not the non-committal fling. And the former should get the most attention from you. How do you know which customers are in it for the long haul? The gold standard of metrics is customer Lifetime Value (CLV). 

A CLV model predicts how much your relationships will be worth over their lifetime and is essential for marketers who want to know if they're creating sustainable value for their business as well as to make informed decisions about resource allocation and customer retention strategies. 

How to calculate CLV?
The approach to CLV varies by industry. For retail and eCommerce, CLV is a factor in the average number of purchases a customer makes over a certain period. Subscription-based businesses use the Monthly Recurring Revenue (MRR) generated from each customer each month as a core metric alongside Churn Rate and Upgrade/ Downgrade Rate to determine CLV. Brands in financial services look at product holding, which is the different types of products like accounts or policies held by each individual customer, which is then measured against the risk profile to assess overall CLV. 

The point is that there are countless different industry versions, but ultimately, all roads lead to Rome. Despite varying approaches and metrics, overall, each business has similar considerations. These include looking at revenue, cost, lifespan and engagement. 

If you're skilled at seeing patterns, the common denominator among all tactics may already be clear. All require integrating data across multiple dimensions to build a holistic view of customer value. If you didn't spot it, don't worry. Ultimately, this is the crux of the issue. Humans can stare at data all day and never see complex patterns. AI, on the other hand, can spot them in seconds.

AI to maximise CLV
It's fortunate that we now have so much information about our customers. Don't let this go to waste by not taking advantage of it. AI can bridge the gap. By leveraging AI and machine learning to digest complex data, brands can predict future behaviour and calculate CLV more accurately. Moreover, these insights can tailor strategies, optimise customer experiences, and prioritise high-value customer segments for growth. 

It's the predictive capacity that makes AI come into its own regarding CLV. Using Machine Learning algorithms, AI can forecast future customer behaviours based on historical data, which can't be done manually or using traditional models. With predictions in hand, brands can shape marketing campaigns, messaging and optimisation on the fly to nurture high-value customers with personalisation at scale. In other words, you're not waiting weeks (or even months!) to see which customers become high-value because you know beforehand who is likely to become one and can then act accordingly to ensure that happens and the relationship is secured. 
It's also possible to link CLV to pricing. Price-sensitive businesses, like subscription services, require AI-enhanced CLV to understand the value of different customer segments to inform more nuanced pricing strategies that align with customers' long-term value. 

Prepare now to reap the benefits later
Using an agency partner, brands have multiple options to compute their CLV, such as building their own AI model or using open-source models. It should be noted, however, that purpose-built AI models that integrate seamlessly with the core product offer a clear competitive advantage over default general-purpose solutions. If you're going to focus on personalisation, why not go the whole hog and personalise the tools used to enable it? The long-term efficiency and performance gains are undebatable, allowing decision-makers to have timely information in a readily accessible format. 

However, no matter which route a brand chooses, incorporating AI into CLV computation and prediction is now necessary. It enables brands to operate more intelligently and efficiently, tailoring strategies to their customer base's nuanced needs and potential. By leveraging AI, brands can enhance profitability, foster customer loyalty, and adapt faster to changing market dynamics. This will secure a competitive advantage for businesses in every industry.