Predictive CLV Overview

Important: This feature is available as part of the Advanced Intelligence Package add-on that must be ordered for your account. Please contact your account manager or Oracle sales.

CLV (Customer Lifetime Value) is the projection of revenue a customer will generate over his or her lifetime. Predictive CLV is commonly used to allocate marketing budgets where they have the most impact, on those customers where marketing makes a difference. Top customers are easy to identify. But what about customers that have the potential to become top customers but have only just begun their customer lifecycle? And what about good customers that are about to walk away? Predictive CLV is used to act early in cases like these. See Steps to understanding Predictive CLV.

Note: At the moment, Predictive CLV only applies to the email channel and SMS channel.

An image of the CLV dashboard

At the heart of this feature is a blend of machine learning algorithms and artificial intelligence that understands where a customer relationship is headed. As soon as the Predictive Engine is connected to your database, it will provide the CLVs of your customers based on the latest information available. Of course, it can do so in real-time.

To navigate to the Predictive CLV page:

  1. Click Insight An image of the global navigation with the Search icon selected. on the side navigation bar.
  2. Select Predictive CLV.

How Predictive CLV helps marketers

With Predictive CLV, marketers can:

  • Determine customer acquisition costs based on future predictions.
  • Inform customer support based on CLV.
  • Identify future high frequency users that currently have below average spend per transaction.
  • Identify users who may churn in the long-term but are currently high frequency users.
  • Identify high value customers from the 'mid-level' RFM segments.

Example: A marketer uses the Predictive CLV dashboard to analyze her profile list's predictive CLV trend. She sees that the Avg. Predictive CLV chart presents only a modest upward trend. To improve the trend line, she uses the personas in the Predictive CLV PET for personalization in her email campaigns. For example, to encourage the Short term spenders to continue making purchases, she uses dynamic content rules to send them a higher value discount coupon than the one she sends to Long term spenders.

Steps to understanding Predictive CLV

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