> ## Documentation Index
> Fetch the complete documentation index at: https://relevanceai-tsp-1326-docs-update.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Campaign performance analytics

> Pull cross-channel campaign reports together and surface what's working — without hours of spreadsheet wrangling.

Performance data lives in seven tools. The weekly campaign review takes someone half a day to pull together and another half day to translate into insight. A campaign analytics Agent does the pulling and the translating — so the review meeting starts with answers, not data hunting.

## When this pays off

<CardGroup cols={2}>
  <Card title="Reports take half a day" icon="hourglass-half">
    Pulling Google Ads + HubSpot + LinkedIn + GA into one slide takes the same person, the same way, every Monday.
  </Card>

  <Card title="Channel performance is opaque" icon="eye-slash">
    You know spend by channel but not what each channel is actually doing for the funnel.
  </Card>

  <Card title="Campaign comparisons are manual" icon="scale-balanced">
    Was this campaign better than the last one? Nobody can answer without an hour of cross-referencing.
  </Card>

  <Card title="Leadership wants weekly digests" icon="newspaper">
    The CMO wants a Friday "what worked, what didn't" — and it always slips because it's not anyone's job.
  </Card>
</CardGroup>

## The shape of this use case

A campaign analytics Agent takes a time window + campaign set and returns a report with reasoning.

<CardGroup cols={2}>
  <Card title="Inputs" icon="arrow-right-to-bracket">
    Time window, campaign set (specific campaigns or all), channels to include, segmentation cuts.
  </Card>

  <Card title="Sources" icon="globe">
    Marketing automation ([HubSpot](/integrations/popular-integrations/hubspot), [Marketo](/integrations/popular-integrations/marketo)), ad platforms (Google, Meta, [LinkedIn](/integrations/popular-integrations/linkedin)), web analytics, CRM, your own benchmark docs.
  </Card>

  <Card title="Output" icon="file-lines">
    A digest — top performers, underperformers, key shifts vs. last period, suggested actions — with cited data and reasoning.
  </Card>

  <Card title="Delivery" icon="paper-plane">
    Posted to [Slack](/integrations/popular-integrations/slack), written to a [Notion](/integrations/popular-integrations/notion) page for the team review, emailed to the CMO Friday morning.
  </Card>
</CardGroup>

## Where to start

Two ways in, depending on whether you want something running today or built to your exact spec.

<CardGroup cols={2}>
  <Card title="Clone a pre-built Agent" icon="copy">
    Open the **[Email Marketing Strategist](https://marketplace.relevanceai.com/listing/28783038-03f0-4aec-9c76-4b28452b6e33)**. More in the [Marketplace](/get-started/marketplace/introduction).
  </Card>

  <Card title="Build your own" icon="hammer">
    Start from scratch in the [builder](/build/introduction), or by describing it in Claude Code or Cursor with [Programmatic GTM](/get-started/core-concepts/programmatic-gtm).
  </Card>
</CardGroup>

Either way, these are prompts your team can use on day one:

* *"Pull last week's campaign performance from HubSpot and Google Ads — top 3 winners, top 3 losers, with reasons."*
* *"Compare the Q3 onboarding sequence against Q2 — what shifted in open and click rates?"*
* *"Which channels drove qualified pipeline last month? Cite the data."*

## Where to take it

Once it's running, deepen it in three moves:

<CardGroup cols={3}>
  <Card title="Give it a playbook" icon="book">
    Shape it with a [prompt](/build/agents/build-your-agent/prompt), KPI definitions in [Knowledge](/build/knowledge/create-knowledge), and [Tools](/build/agents/build-your-agent/tools) to query each platform.
  </Card>

  <Card title="Automate it on signals" icon="bolt">
    Wrap it in a [workflow](/build/workforces/create-a-workforce) that fires on a [trigger](/build/agents/build-your-agent/triggers).
  </Card>

  <Card title="Let it improve" icon="arrows-rotate">
    Weight the Agent's [evals](/build/agents/build-your-agent/evals) toward the metrics that actually predicted pipeline.
  </Card>
</CardGroup>

## Common pitfalls

<AccordionGroup>
  <Accordion title="Pulling data without interpreting it" icon="magnifying-glass">
    A wall of numbers in Slack isn't useful. Force the Agent to explain *why* metrics moved and *what to do* — not just *what they are*.
  </Accordion>

  <Accordion title="Inconsistent attribution" icon="scale-unbalanced">
    HubSpot's "campaign" and your ad platform's "campaign" probably aren't the same thing. Define attribution rules in Knowledge once and reference them every time.
  </Accordion>

  <Accordion title="No benchmark for 'good'" icon="bullseye">
    Without baselines, every CTR looks normal. Upload your historical benchmarks to Knowledge so the Agent flags actual outliers.
  </Accordion>

  <Accordion title="Stale data sources" icon="clock-rotate-left">
    Ad platforms can lag 24-48 hours. Have the Agent disclose data freshness in the report so the team knows what's preliminary.
  </Accordion>
</AccordionGroup>