How to Read MARC Engagement Data: A Practical Guide for Marketers

Marketers love dashboards—but only when the data inside them is actionable. One of the biggest advantages of MARC is that its engagement analytics aren’t vanity metrics. Every data point maps to a real behavioral signal that helps teams understand how prospects absorb, share, and respond to physical video storytelling.

Yet many teams new to MARC ask the same question: “What should we actually be looking for?” This guide breaks down each major MARC metric, how to interpret the behavior behind it, and how to use that insight to make better marketing and sales decisions.

Why MARC Engagement Data Matters

Traditional direct mail has always been a black box. Once a mailer lands, marketers can’t see who opened it, whether anyone shared it internally, or how long someone spent with the content. MARC closes that gap by giving teams the same visibility they expect from digital—view time, replays, multi-viewer sessions, and more.

Understanding how to interpret this data is the key to transforming direct mail from a cost center into a measurable performance channel.

The Core Metrics and What They Mean

1. Total Engagements

This tells you how many times the brochure has been opened and interacted with. High engagement count typically indicates:

• Active interest from the lead or account
• Internal sharing among colleagues
• Revisiting the narrative for clarification or advocacy

Rule of thumb: Anything above 4–5 engagements per brochure is a strong buying signal; MARC’s average is over six. When an account crosses that threshold, outreach should become more targeted and timely.

2. Average View Duration

View duration is one of the most important behavioral indicators. MARC’s typical campaigns see over a minute of engagement per view—far stronger than standard digital benchmarks.

Short views (under 15 seconds) often mean the messaging didn’t resonate or the recipient wasn’t the right target. Long views (60+ seconds) suggest deep attention and emotional connection to the story.

3. Video Completion Rate

Completion rates show how well the narrative holds attention. A high completion rate means the message structure, pacing, and content are landing effectively.

When completion rate is low but view duration is high, the video may be too long or overloaded with detail. In future creative iterations, tightening the story can improve retention.

4. Replays

Replays are among the strongest intent signals in MARC’s analytics ecosystem. Prospects replay videos when they:

• Want to revisit a value point
• Want to share the story internally
• Are preparing for a budget or planning conversation

In ABM programs, replays often correlate with buying committee activation. In late-stage cycles, replays correlate with deal velocity.

5. Multi-Viewer Behavior

MARC detects multi-viewer sessions—one of the most critical indicators in B2B selling. When several viewers engage together, it means internal collaboration is underway.

Interpretation:

• Early-stage → interest is spreading
• Mid-stage → stakeholders are evaluating fit
• Late-stage → validation is taking place before a decision

6. Multi-Day Engagement

When a brochure gets engagement across several days, it signals persistent interest and an active evaluation cycle. Digital channels rarely produce this level of longevity—MARC regularly does.

How to Use MARC Data in Real Campaigns

Optimize Targeting

Analyze which accounts have the strongest engagement metrics and cluster them by vertical, persona, and messaging type. These patterns influence future segment-building and creative strategy.

Refine Creative

Low completion rates? Simplify the narrative. High replay counts? Highlight the section being replayed more prominently. Multi-viewer sessions? Add team-focused messaging.

Support Sales Timing

Sales should treat MARC metrics like intent data:

• Replays → outreach within 24 hours
• Multi-viewers → send supplementary resources
• Long duration → propose a deeper discussion

Recommended Internal Links

• The Direct Mail Engagement Curve
• Direct Mail Optimization Framework
• The New Attribution Layer