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Understanding Engagement & Intent

Ekphrastic uses Engagement Time and Intent to help you understand the level and type of activity associated with your tracked links.

These metrics provide different signals:

  • Engagement Time indicates how much tracked engagement activity was recorded.

  • Intent reflects selected interactions that occurred through the tracked link.

Neither metric identifies why someone engaged with your content or predicts what they will do next. They are best used alongside Sessions and Interactions to build a broader picture of engagement.

Understanding Engagement Time

Engagement Time represents measured engagement activity during tracked Sessions.

Ekphrastic records engagement in 15-second activity intervals. As active tracking continues, these intervals accumulate to produce the Engagement Time shown in Buyer Engagement.

For example, if four active tracking intervals are recorded, Ekphrastic records approximately 60 seconds of Engagement Time.

What Engagement Time means

Engagement Time can help you compare the level of activity generated by different tracked links and Sessions.

A higher Engagement Time indicates that more tracked engagement activity was recorded.

However, Engagement Time is not an exact measurement of how long someone:

  • Read a document

  • Watched a video

  • Studied an ROI Model

  • Considered your proposal

  • Remained continuously focused on the content

For this reason, treat Engagement Time as an engagement indicator, rather than an exact measure of attention.

Example: It is more accurate to say "Ekphrastic recorded approximately 8 minutes of engagement activity" than "the buyer read the content for 8 minutes."

Understanding Intent

Intent is an interaction-based engagement signal.

Ekphrastic calculates Intent using selected interactions recorded through a tracked link. Different interaction types contribute different amounts to the overall signal.

Intent is deterministic. It is not generated by AI and is not a prediction of purchasing behaviour.

How interactions contribute to Intent

Supported interactions contribute to Intent using the following weighting:

Interaction
Intent contribution

Report

+25

Link

+10

Author

+8

Save / Load

+5

As qualifying interactions occur, their contributions are combined to build the Intent score associated with the tracked activity.

This means that the type of interaction matters, not simply the total number of interactions.

For example, one interaction worth 25 points contributes more to Intent than several lower-weight interactions with a combined value below 25.

Intent classifications

Ekphrastic translates the accumulated Intent score into classifications to make the signal easier to interpret.

Intent score
Classification

Below 30

Passive

30–49

Engaged

50–79

High Intent

80 or above

Very High Intent

These classifications describe different levels of measured interaction with your shared content.

They should not be interpreted as probabilities or stages in a buying process.

What "High Intent" means

The term High Intent indicates that the tracked activity has accumulated enough qualifying interactions to reach Ekphrastic's High Intent threshold.

It does not mean that Ekphrastic has determined that the person:

  • Intends to purchase

  • Is ready to buy

  • Has approved a business case

  • Is a qualified opportunity

  • Has reached a particular sales stage

Similarly, Very High Intent indicates a higher level of qualifying interaction activity. It is not a prediction that a purchase will occur.

Intent is most useful as a signal that helps you identify tracked shares that may deserve closer attention.

Why two Sessions can produce different Intent

Two Sessions with similar Engagement Time can produce different Intent signals.

For example, one Session may contain mostly passive engagement activity, while another includes several qualifying interactions.

Likewise, a longer Session does not automatically mean higher Intent.

This is because:

Engagement Time measures recorded engagement activity.

Intent measures selected interactions.

Looking at both provides more context than either metric alone.

Using Intent with Session Interactions

When an Intent classification catches your attention, review the underlying Session activity where available.

This lets you see the Interactions behind the overall signal rather than relying only on the classification.

A useful review might consider:

  1. How many Sessions have occurred.

  2. How much Engagement Time was recorded.

  3. Which Interactions occurred.

  4. Which content generated activity.

  5. What Intent classification resulted.

This provides a more complete picture of the engagement associated with the tracked link.

Intent and buyer identity

Intent is calculated from activity associated with a tracked link.

It does not independently establish who performed those interactions.

If a tracked link is forwarded, subsequent qualifying activity continues to contribute to the analytics associated with that tracked link.

For this reason, Intent should be interpreted in the context of the shared link or opportunity, rather than as independently verified behaviour from a specific individual.

Using engagement signals effectively

Buyer Engagement works best as additional context for your sales process.

For example, engagement information may help you identify:

  • Shared content generating repeated activity

  • Tracked links accumulating meaningful interactions

  • Opportunities where engagement has increased

  • Content that appears to be attracting greater attention

You can then use your knowledge of the opportunity, customer and sales process to decide whether that activity warrants follow-up.

Ekphrastic provides the engagement signals. The commercial interpretation remains yours.

Remember

When reviewing Buyer Engagement:

  • Sessions show tracked visits.

  • Engagement Time shows accumulated tracked engagement activity.

  • Interactions show supported actions recorded during Sessions.

  • Intent summarises selected interactions into an engagement classification.

Use these signals together rather than treating any single metric as definitive evidence of buyer behaviour.

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