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CRM in Programmatic: Part Four

The fourth and final post in a series aimed at helping marketers put their first-party customer data to use in digital display advertising

In the previous parts of our CRM series (parts one, two and three), we discussed how a CLV-driven CRM strategy can help to foster the right long-term customer relationships. Now, for this last installment, we’ll dig deeper into CLV and face one of marketers’ biggest challenges: how to actually measure CLV.

Like most measurement, there’s not one-size-fits-all answer.

Different Customers, Different Values

In many cases, it can be months or years before a new customer begins to deliver profitability for a business. On top of this, some customers will never be profitable ones. In today’s economic climate particularly, there is a growing segment of customers who are “deal hunters,” who may engage with costly advertising only when significant, margin-busting discounts are offered. Of course, the ideal would be a customer who comes to the company after minimal marketing investment and who is happy to make repeat purchases as well as buy into brand extensions with little further interaction. But the reality is that this is rarely possible.

So the best option for most companies is to identify customer segments by potential value and target each of them in the most effective, cost-efficient ways. It’s this realization that makes CRM according to CLV so important, with CLV informing CRM strategy.

Data, Data, Data

Getting your CRM data in order can improve your ability to affect CLV measures. According to Econsultancy’s Customer Lifetime Value Report 2014, more than a quarter (26%) of company respondents attributed their success in CLV to date to a more effective use of data, while customer segmentation came in at 24%. More than a third (34%) of company respondents also cited more personalized interactions, including onsite communications and email, as being effective in increasing their CLV.

Furthermore, as businesses strive to integrate all customer data sources and silos in order to build a single, joined-up view of the customer, this is ultimately going to benefit their CLV. In the above mentioned report, it is unsurprising that companies rate the single customer view as the most effective tool for enhanced customer lifetime value (32%). More than a quarter (27%) also cited a strong interaction between online and offline channels as positively benefitting CLV. Additionally, 52% say better use of data will increase CLV in the future.

This leads to the question: how is CLV being measured?

No Single Answer, But Don’t Forget Attribution

There’s no straightforward answer. Whichever measurement is used, the basic equation looks something like this: customer revenue minus the cost to acquire and then serve the customer.

A wide variety of economic models and calculations exist to help marketers arrive at a definitive figure, but these depend on variables that are not just specific to a sector, but an organisation. There is not really a one-size-fits-all system of measurement, and so knowledge tends to come with time and experience. That said, the most common model used is the recency-frequency-monetization calculation, or RFM dimensions, which we explained in a previous post.

CLV and advanced marketing attribution are deeply intertwined in building sustainable customer relationships. In the end, the attribution model you choose will impact which customer segments you value the most – and that will impact how you decide to spend your marketing budgets now in the future. Ultimately, this will all impact the relationship you’ll have with each customer.

That’s why it’s also important to have the right attribution model for your business. As we found out in a recent webinar, marketers still have a lot of doubts regarding attribution in the digital age. And there’s really no one answer, no one model to rule them all. In the end, the closest answer we have for both CLV measurement and attribution models is: know your data, know your business, and let one help the other. From there, you’ll know your customers, and how to better forge lasting relationships with them.

CRM needs CLV, CLV needs attribution, and in the end they all need each other. Improving CRM, however, might just be the starting point to all of this – and programmatic, allowing personalization like never before, one method to deepen customer relationships at a cost relative to their lifetime value.