Glossary

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Glossary / Evaluation and implementation guide

Audience Scoring

Audience scoring assigns numeric or tiered values to contacts or segments based on behavior (email clicks, page visits, event attendance) and profile fit (role, company size, industry).

Scores drive segmentation and nurture decisions, such as moving high scorers into a sales-ready track, and differ from lead scoring by often operating at list or segment level rather than per individual deal.

A practical example

Example: contacts who attended two webinars and opened three consecutive newsletters reach a 'warm' tier and enter a product-education sequence, while low scorers stay in general content streams.

What to evaluate before investing

  • Check whether scores update in real time or on a batch schedule, and whether decay applies to stale activity.
  • Confirm you can build score models from both behavioral and profile attributes without custom code.
  • Verify score changes can trigger workflow actions, such as segment moves or alerts.

Limitations and tradeoffs

Scores reflect modeled engagement, not purchase intent; recalibrate weights periodically or tiers drift as campaigns and audience behavior change.

Plan your next step with MeshLine

Connect this decision to your automation, organic marketing and customer lifecycle management. In a MeshLine demo, discuss your existing tools, the scope you need and how to measure the result.