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Customer loyalty + revenue: A new way to look at account management

Good account management comes down to building up valuable relationships with each and everyone of your customers. So having good relationship building skills is important for successful account management, but that is not the whole story.

Correctly judging when to work on which relationship is crucial to securing and expanding your accounts. However, when managing multiple accounts with typically many contacts in each account, this can become a complicated and strenuous task.

However, with the right data account managers can better understand each account relationship in order to decide who needs the most attention next.

The right data

In order to create a better account management system, companies need to take two elements into account: how loyal each customer is and the revenue of that customer. Although it simply serves as a guideline for account management, by combining the two it helps account managers gain a better understanding of the differences that exist amongst their accounts.

To get a view of your whole account base and its distribution along the revenue-loyalty spectrum, a visual diagram answers this best. Along the x-axis is plotted the customer’s loyalty, which if using NPS runs from -100 to +100, while along the y-axis is the customer’s revenue.loyalty-graph

And while this creates contention about where both the x and y-axis should intersect each other, it merely helps to group your customers into four clear quadrants by which account managers can better understand the differences that exist between their customers.

Beginning then, with the top right quadrant we have those high-paying loyal customers. These are your most valuable accounts. Next, in the top left are high-paying disloyal (or at risk of leaving) customers. These of course, should receive priority attention.

Below the x-axis, we come to the low-paying customers. In the bottom right quadrant, we have low-paying loyal customers, while in the bottom left we have those low-paying disloyal customers - these are your least valuable accounts.

What this does is take what used to be a random assortment of revenue and loyalty data, and create a value for each customer. For loyalty data is great at giving companies insights into which customers are more or less likely to remain as customers, but it gives no indication of how valuable that loyalty is to a company.

How it creates better account management

[caption id="attachment_15587" align="alignright" width="247"]pareto-effect.jpg Vilfredo Pareto was a very wise man[/caption]

As Pareto’s principal states is most often the case, 80% of your revenue comes from 20% of your customers. This clearly highlights the importance of separating the high spenders from the rest when looking at the loyalty data.

While equally as important as understanding, which accounts are high spenders, are the insights that loyalty data provides. For the way in which you manage an account that is high-paying and happy is not the same way you would want to handle an high-paying unhappy account.

By pairing revenue and loyalty, different strategies can be devised to handle each customer depending on where they are in the loyalty-revenue spectrum. For example, utmost priority should be given to unhappy/disloyal customers among the top 20%. For more important than anything else, is retaining your biggest revenue accounts.

While beyond rescuing key customers, account managers can identify opportunities for account expansion by up/cross-selling. As accounts that have enjoyed success with a product are not in need of problem resolution, but instead account management that looks to build upon this success.

A simple idea with a lot of potential

By positioning customer loyalty alongside revenue, account managers can now create strategies that more effectively use their time and resources. And by doing so, it not only benefits the company, but also satisfies the needs of each account better.

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