Disconnected channel metrics often make it difficult to understand how customers are truly engaging overall. These siloed signals are rarely linked to strategy or action, leaving commercial teams to optimize individual channels rather than the customer experience. As a result, organizations struggle to align priorities, detect changes early and act with confidence.

A unified customer engagement metric would allow organizations to serve individual customers a true omnichannel experience. Instead of evaluating touch points in isolation, teams can assess engagement at the customer level and understand how it accumulates and evolves over time. This makes it possible to distinguish fleeting activity from sustained engagement and respond accordingly.

What is the Customer Engagement Index?

ZS’s Customer Engagement Index (CEI) turns fragmented engagement signals into a single, governed measure of a customer’s omnichannel engagement. CEI measures customer engagement across three complementary dimensions:

• Breadth: The span of channels a customer meaningfully touches
• Depth: How far they progress in engaging with each channel (e.g., open → click → download)
• Consistency: Whether activity is sustained over time

CEI is a consistent metric that can fit seamlessly into the tools teams already use and can be deconstructed to identify drivers of engagement.

FIGURE 1: Illustration of the components of CEI

What CEI can tell companies about customer engagement

CEI plugs directly into day-to-day planning and execution. It can sharpen customer segmentation, help set “unified customer engagement goals” and can power next best actions—personalizing the channel, content and cadence of engagement at n=1 level. Actioning on CEI-based recommendations can optimize customer experience and drive up to 2%-5% lift in brand performance.

CEI is a feature of the ZAIDYN^® Affinity Monitor report tool, which, along with the Access Monitor tool, gives teams insights on over a million HCPs across specialties and is informed by a billion touch points. Industry-level and client-level CEI are available to subscribers at no additional cost, giving teams a straightforward decision-ready signal alongside channel engagement and performance views they already trust.

CEI benchmarks customers against the industry by showing how proportions are performing based on where they are located in the relevant CEI quintile across brands and industry.

FIGURE 2: Benchmarking of company CEI vs. industry

FIGURE 3: CEI contribution across channels

Figure 3 shows how CEI contribution is split across digital, rep and other channels at each brand life cycle stage. This split gives users the ability to understand the channel composition of engagement that is driving CEI for a given stage quickly and to communicate these stats in a simple, executive-friendly way.

Teams can use it to align channel strategy by stage, deciding whether to lean more on rep-led engagement or digital touch points—while also tracking how that mix shifts over time as brands move from launch to post-loss of exclusivity.

How companies apply CEI to marketing strategy

Tracking CEI at the national, regional, segment and individual customer levels can provide insights to build engagement-based customer personas. CEI enables companies to measure changes in overall engagement campaign performance and quantify ROI. These signals further support smarter resource allocation and power dynamic next-best-action recommendations, optimized to maximize individual customer engagement.

While the sections above illustrate CEI applications in context, the primary practical use cases of CEI can be summarized as follows:

Measurement and insight

• Tracking engagement behavior: Monitoring how HCP engagement changes over time across channels (national to HCP level).
• Leading indicator of sales: Using CEI as an early signal to adjust channel, content and cadence before sales shifts show up.

Personalization and activation

• Creating customer personas: Building engagement-based personas to track questions beyond just what they value, like how and where HCPs engage.
• Formulating next best action: Personalizing and orchestrating actions specific to the HCP to maximize CEI uplift

Planning and optimization

• Setting goals: Defining segment-level engagement “north stars” using historical CEI and optimal frequency benchmarks.
• Optimization omnichannel: Using CEI as a common currency to diagnose gaps and optimize mix and cadence across channels.

Performance and investment

• Measuring campaigns: Quantifying engagement uplift and ROI impact from campaigns and initiatives.
• Allocating resources: Prioritizing investment using a combined view of potential, engagement and responsiveness.

Start tracking customer engagement index scores now: Practical next steps

By leveraging the CEI scores currently available in the Affinity Monitor HCP report, companies can establish clear near-term engagement benchmarks, concentrating proactive outreach on high-CEI, high-value customers. In parallel, these CEI segments can power downstream applications such as next-best-action recommendations, customer prioritization within the field suggestion pipeline and intelligent suppression or deprioritize lower-CEI HCPs who are less likely to respond.

For deeper diagnostic, especially where HCPs look strong at the industry level but lag on the contributor view, companies can leverage CEI Plus. It provides a more granular analysis at the HCP and account, segment, channel and time-window level. This view shows what’s working, where momentum is breaking down and how to reach those HCPs more effectively. The output is a focused narrative that’s immediately actionable: a prioritized list with reason codes, guidance on message and channel sequencing, and a concise test plan that plugs straight into your CRM or campaign tools.

Having the data at your fingertips is one part of the equation. Executing on that data is another. Pairing these insights with ZAIDYN Customer Engagement allows you to orchestrate personalized materials across channels that these customers know and trust using agentic AI to interpret signals, recommend next best actions and more. Ready to put it all together? Let’s go.