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Credit by Casey Carey

Picture John. He’s just become a customer of your B2B software company and agreed to buy your product, which comes with a year of support and maintenance. After 12 months, John will have to renew his contract to keep his licenses active.

Now it’s time to record the sale and move on to acquiring the next customer, right? Not quite.

You’ll record John’s initial transaction value, of course, but that’s just the beginning of John’s customer lifetime value (CLV). With fragmented audiences, expensive advertising, and fierce competition, marketers must become more strategic in how they view customers’ revenue potential.

Today, once a sale is closed, many marketers consider their job (mostly) done. They may occasionally send out a newsletter or collaborate with sales on an upsell campaign, but for the most part, it’s off to the races to find the next John.

Not so fast! The marketing landscape is changing rapidly—and buyers now expect larger-than-life experiences and personalized engagement. That’s why pairing advancements in artificial intelligence (AI) with CLV is quickly becoming a critical component of any sophisticated marketing strategy.

Calculating CLV

CLV is actually simple: It’s the present value of future cash flow attributed to the consumer throughout the entire relationship with the company. In other words, it’s the entire amount of revenue you make from a customer like John throughout their life cycle.

Additional value can come from supplemental revenue through upsells and cross-sells.  The better a marketer understands CLV, the easier it is to create strategies that attract and retain the most loyal and profitable customers.

Want to dive deeper? Watch our on-demand session about calculating CLV.

Incorporating AI

Thankfully, you don’t have to do all the calculations yourself—AI is here to help. In fact, 2019 will be the year of AI in marketing. Forbes ranks it as the top digital marketing trend to watch. 

Change is coming. Not only can AI help calculate and improve customer lifetime value, it will also compel marketers to use CLV as a primary KPI metric.

Why? Because there’s much more to be gained from a customer like John outside of initial transaction value. And now, AI gives us the power to track, analyze, and understand it all. What digital marketing channels drove John to your brand? What created the strong relationship that ultimately led to higher lifetime value?

With the ability to process and analyze massive amounts of data over a customer’s lifetime, AI helps marketers make metric-driven decisions to tailor their strategies and encourage customers to:

1. Close Faster

You know John is unique, so show him. It is possible—if tedious—to listen to a single customerand determine how to best engage with them at every touch point. But doing that at scale? Impossible.

Until now, that is. AI does the deep listening and learning for you so you can deliver relevant content that’s most likely to create strong relationships and convert customers. Armed with metrics and insights, you can now prioritize how much to invest in every customer. And if a certain spend isn’t attracting a customer, AI can tell you when it’s time to throw in the towel, saving you precious time and money.

2. Buy More

AI can change how you greet every customer and what you offer them. Leveraging the abundance of data, you can use AI to create a holistic and hyper-targeted approach that encourages customers to purchase additional products and agree to longer commitments.

Plus, with a deep understanding of personal preferences gleaned from past purchasing behavior, you can deliver offers that feel like they’re tailor-made just for John. AI equips you with the tools to build trust and turn short-term conversions into long-term loyalty.

3. Renew Quickly

When you embrace technology that helps John feel valued and understood, he becomes much more likely to stick around and grow into a loyal customer.  Better yet, as an AI-empowered marketer, your insights give you the ability to predict what he might want or need next. By incentivizing John with incremental sales and longer-term commitments, you can keep growing his CLV at a fraction of what it costs to acquire a new customer.

4. Evangelize Enthusiastically

When marketers focus on CLV as much as they focus on acquisition, brands begin to feel personal and indispensable. And with AI helping you calculate CLV, you can pinpoint and reward your best customers. That means high-value customers like John will share and recommend your products and services, and you can replicate your strategy to attract more people just like him.

Changing Metrics

As AI continues to enhance marketing strategies, the focus on discrete, or leading, metrics—like email opens, clicks, and impressions—will decrease. That’s because AI can sort through customer data and automatically adjust to optimize the results more quickly than a human ever could.

Marketers, then, are freed to shift their focus to improving aggregate performance, like CLV. However, aggregate—or lagging—metrics are reactive, meaning marketers look at end products of actions to gather data instead of the actions themselves.

The problem with lagging metrics? You won’t know what’s working until after actions or strategies have been implemented. By the time you realize a certain type of content isn’t resonating with John, for instance, it’s too late to adjust and fix it.

AI can help. By keeping data up to date, tracking it over time, and analyzing the relationship between the two types of metrics, the technology allows you to measure progress and focus on outcomes. This can help you predict what actions and inputs will achieve the desired results.

Using AI to create a detailed picture built from both leading and lagging metrics, you can see how KPIs change and interact. You can then determine an agile strategy to capitalize on what’s working, adjust what’s not, and meet—and exceed—your marketing goals.

Predicting the Future

While marketers have gotten better at connecting marketing investments to revenue impact, many aren’t taking the next step: calculating CLV.

With AI, you can predict CLV with increasing accuracy. And when you use AI to increase the value you provide customers like John, he gives it back by purchasing additional products, agreeing to longer commitments, and referring your organization to his friends and colleagues.

It’s all part of a shift toward using the power of AI to glean valuable insights, drive better decision making, and nurture and prospect more effectively.

The future is here. Are you ready?

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