Campaigns

Campaign data covers your full email, SMS, and push programme, spanning broadcast, automation, and transactional sends. It's organised in three layers: 

1. the campaign itself, 
2. the individual nodes/messages within it, and;
3. daily performance KPIs (sends, deliveries, opens, human opens, clicks, attributed revenue and orders, bounces, unsubscribes).

✅ You can ask about

• Campaign rankings
• Send volume
• Open and click rates
• Attributed revenue
• Revenue per send
• Broadcast, automation, and transactional comparisons
• Channel breakdowns (email vs SMS vs push)
• Automation type analysis (welcome, abandoned basket, browse abandonment, birthday)
• Campaign feature usage (A/B testing, send time optimisation, product recommendations, coupons).
• Transactional sends: volume, engagement, and revenue for order confirmations, dispatch and shipping notifications, password resets, and similar messages. You can break these down by stream, the label given to each transactional use case.
• Broadcast campaign performance by the recipient's lifecycle stage at the time of send (lead, active, at-risk, or lapsed). This lets you compare the same campaign year on year.

⚠️ Watch out for

• Sends and deliveries are different: All rate metrics (open rate, CTR, unsubscribe rate) are calculated against delivered messages, not sends. This is the most common source of mismatched numbers.
• Human opens vs total opens: Total opens includes bot/automated opens. The system uses human opens by default — this matches "Emails opened (human)" in Ometria's dashboards.
• Campaign KPIs are daily: There's no hourly granularity, so timezone boundary effects can cause minor discrepancies when your timezone doesn't align with UTC.
• Transactional stream detail varies by account: some brands use many named streams, others a single default. Per-stream breakdowns are richer for some accounts than others.
• Lifecycle-at-send is for broadcast campaigns only: this mirrors the Ometria platform. It isn't available for automation campaigns.
• Product-recommendation usage is accurate for automation campaigns. For broadcasts, only the newer dynamic product recommendations are detected. Broadcasts that use the classic email-builder recommendation blocks show as not using recommendations until they move to the newer feature.

Wunderkind campaigns: are identified by titles starting with "wk_".