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RCS Analytics: Measuring Engagement Beyond Clicks and Delivery

RCS Analytics: Measuring Engagement Beyond Clicks and Delivery
29 January 2026

As customer communication shifts from plain text toward richer messaging, many businesses are re-evaluating how they measure engagement. Traditional SMS reporting has long focused on delivery and clicks, but these metrics often provide limited insight into how messages are actually consumed. Rich Communication Services (RCS) introduces additional interaction signals that allow businesses to observe user behavior in more nuanced ways.

 

Rather than positioning RCS analytics as performance guarantees, it is more accurate to view them as additional visibility layers. These signals help teams better understand how customers interact with messages, especially in journeys where visual content and structured actions are involved.

 

 

Moving Beyond Delivery-Centric Metrics

 

In conventional SMS reporting, success is typically assessed using a small set of indicators:

 

 

While useful, these metrics primarily answer whether a message arrived or was clicked, not how it was engaged with. RCS analytics expands this view by exposing interaction-related signals that can support more informed evaluation.

 

 

Key Engagement Signals Accessible to Business Users

 

From a business perspective, RCS analytics can surface several observable indicators without requiring technical interpretation:

 

 

These signals allow teams to assess engagement patterns across campaigns rather than relying solely on final conversion outcomes.

 

 

Understanding Interaction Quality Through Structured Actions

 

One practical advantage of RCS is its support for predefined user actions. From a measurement standpoint, this enables clearer interpretation of user intent.

 

Key observations may include:

 

 

These insights can support improvements in message clarity and flow design over time.

 

 

Observing Visual Content Engagement

 

RCS allows messages to include images, cards, and carousels. While these elements do not guarantee better outcomes, analytics can help teams observe how visual formats perform relative to text-only messages.

 

Business-relevant observations may include:

 

 

Such observations can inform content strategy decisions without making assumptions about causality.

 

 

Timing and Responsiveness as Contextual Signals

 

Beyond raw interaction counts, timing data can provide useful context. For example:

 

 

These patterns can support scheduling, segmentation, and expectation-setting discussions within marketing or operations teams.

 

 

Using RCS Analytics Responsibly in Business Decisions

 

It is important to note that RCS analytics should be interpreted as directional signals, not absolute performance indicators. External factors such as audience behavior, message relevance, and campaign context continue to play a major role.

 

For business users, the value lies in:

 

 

When framed this way, RCS analytics becomes a decision-support tool rather than a promise of improved results.

 

 

Expanding Visibility Without Overstating Outcomes

 

RCS analytics provides businesses with a broader view of customer engagement beyond delivery and clicks. By observing read behavior, interaction patterns, and timing signals, teams can gain more contextual understanding of how messages are experienced. When used carefully and conservatively, these insights can support better communication design while remaining aligned with compliance and governance expectations.

Irsan Buniardi