Marketing KPI best practices

Marketing KPI best practices#

This guide explains how to translate your marketing objectives into KPIs that are traceable inside Adverity. It combines industry-standard KPI definitions with concrete platform guidance so you can position Adverity as the governance layer for dimensions, metrics, and calculated KPIs across every workspace.

Prerequisites#

End-to-end KPI workflow#

Follow these stages to keep KPIs consistent from ingestion to reporting:

  1. Collect and normalize inputs. Create dedicated datastreams for each paid channel (for example, Google Ads, Meta Ads, TikTok Ads) and apply the recommended segments listed in the connector-specific guides. Bundle CRM or commerce exports if revenue or customer metrics live outside media platforms.

  2. Harmonize fields. Use the Data Mapping feature to align spend, impressions, conversions, and revenue fields. When a KPI needs a derived metric (for example, potential impressions), apply standard or custom transformations to produce the required columns before mapping.

  3. Monitor quality. Configure universal or custom monitors (such as volume, timeliness, or column consistency) and review their output so you can catch anomalies before they impact dashboards.

  4. Explore and validate. In Explore create calculated fields and pivot tables to test KPI definitions with campaign managers.

  5. Publish dashboards and alerts. Use Present dashboards plus distribution options to share KPI packs. Schedule email exports or provide periodic snapshots for leadership reporting.

Managing KPI metadata in Adverity#

Use Manage KPIs & Dimensions (available from the Explore & Present navigation) to standardize every building block before it reaches your dashboards.

  • Search and filter. Use the search box or the Filter by Datasource drop-down to focus on a connector or schema when auditing fields for a KPI category (for example, search for retention before configuring the retention tables below).

  • The table columns show the following information:

    • Schema name is the technical field from the connector or warehouse.

    • Explore & Present name is the business-friendly label seen by dashboard consumers.

    • Visible toggles whether the field appears in Explore.

    • Fractional digits controls numeric precision and inherits to child workspaces unless overridden.

For detailed instructions on configuring dimensions, metrics, and calculated KPIs in the administration interface, see Viewing and configuring dimensions, metrics, and calculated KPIs.

Note

Keep these properties in sync with your KPI definitions to avoid rework in Explore and ensure Adverity remains your single source of truth.

Creating calculated KPIs#

For step-by-step instructions on building calculated KPIs, see Using Calculated KPIs and adding them to widgets.

Engagement KPIs#

Apply engagement KPIs to verify that creative and audience combinations prompt valuable interactions.

The field names referenced below are examples (for example, clicks or impressions); equivalent fields exist in other connectors with similar semantics.

KPI

Formula and fields

Recommended Adverity components

Interpretation and tips

Click-through rate (CTR)

Divide clicks by impressions and multiply by 100; requires both metrics.

For example, paid-media connectors expose clicks and impressions fields; map them and create a Explore calculated field.

Segment by device, placement, or audience to isolate creative fatigue.

Engagement rate

engagements divided by impressions (or use the platform-provided engagement rate).

For example, Facebook Ads exposes actions.* fields and LinkedIn Ads exposes engagements; create a transformation to aggregate likes, comments, and shares.

Track pre-click signals for awareness campaigns; correlate with reach to validate upper-funnel activity.

Video completion rate (VCR)

Video plays to 100% divided by video starts.

For example, YouTube Analytics or TikTok Ads connectors expose the necessary video metrics; visualize them in a widget KPI box.

Low VCR suggests creative length or relevance issues; pair with cost-per-completed-view.

Cost per engagement (CPE)

Harmonized spend divided by total engagements.

Ensure both fields live in the same datastream (or transformation) before creating the KPI.

Set guardrails per objective; high CPE is acceptable for premium audiences but should be justified by downstream conversion value.

Conversion KPIs#

Conversion KPIs indicate whether campaigns drive leads or sales events. Keep the funnel stage consistent when comparing channels.

Each field reference in the table (for example, actions.lead or conversions) is illustrative; similar metrics exist in other paid and owned connectors.

KPI

Formula and fields

Recommended Adverity components

Interpretation and tips

Leads / Conversions

Sum the relevant conversion metric (for example, actions.lead) from each connector.

For example, Facebook Ads provides results_by_adverity and Google Ads exposes conversions; similar fields exist in other sources, so harmonize them into a single conversions field.

Align attribution windows across connectors before comparing totals.

Conversion rate (CVR)

conversions divided by clicks, multiplied by 100, at campaign or ad-group level.

Map conversions and clicks at the same grain and create a Explore calculated field or transformation.

Diagnose landing-page or offer issues. Pair with device or keyword breakdown for paid search.

Cost per acquisition (CPA) / cost per lead (CPL)

Harmonized spend divided by conversions or leads.

Spend (cost) target field plus conversion count; KPI widget with alert.

Compare against bids or target CPA to manage pacing.

Form completion rate

marketing_qualified_leads divided by landing page sessions using web analytics sessions and CRM-qualified lead counts.

Blend a web analytics source with CRM data and join them in a transformation.

Highlights hand-off issues between media and onsite experience.

Revenue and efficiency KPIs#

These KPIs connect marketing investment to revenue outcomes.

Field names such as order_value or spend are examples; substitute the equivalent fields from your connectors or warehouse tables.

KPI

Formula and fields

Recommended Adverity components

Interpretation and tips

Revenue

Sum the order or purchase value fields (for example, order_value).

Use e-commerce connectors (Shopify, Google Analytics 4) or warehouse tables that store the revenue fields.

Validate currency conversion and tax handling before aggregation.

Return on ad spend (ROAS)

revenue divided by spend (express as a ratio or percentage).

Harmonize both fields and trend them in Present.

Track both blended (MER) and channel ROAS to allocate budget.

Marketing efficiency ratio (MER)

Total revenue divided by total marketing spend across paid and owned/earned investment.

Combine paid media cost with CRM-opportunity cost; use bundle datastream or Explore data view.

Useful for executive reporting; set minimum viable MER thresholds.

Customer acquisition cost (CAC)

Total spend divided by count of new_customers.

Blend ad spend datastreams with CRM or commerce new-customer feed.

Monitor versus customer lifetime value to ensure payback targets are met.

Retention and lifetime KPIs#

Use these KPIs when marketing owns lifecycle or CRM programs.

Field references (for example, returning_customers) are examples; use their equivalents from your commerce or CRM data.

KPI

Formula and fields

Recommended Adverity components

Interpretation and tips

Repeat purchase rate

returning_customers divided by total_customers over a period.

Destination feed from warehouse or Shopify connector; use a transformation to tag returning users.

Tie to lifecycle campaigns to gauge nurture program health.

Customer lifetime value (LTV)

average_order_value multiplied by purchase frequency and gross margin (or use a modeled warehouse output).

Load modeled LTV from your warehouse (for example, a Snowflake table) and join with campaign spend in Explore.

Compare against CAC to prioritize retention versus acquisition spend.

Churn rate

lost_customers divided by starting_customers; requires a lifecycle status field.

CRM export with status, combined with marketing touchpoints.

Build alerts when churn spikes for cohorts targeted by a specific program.

Diagnostic data-quality KPIs#

Operational KPIs protect your dashboards by highlighting data gaps or delays.

Monitors expose status columns (for example, monitor_status or issue_count) that you can add to data extracts for downstream widgets; the examples below illustrate how to use those outputs.

KPI

Formula and fields

Recommended Adverity components

Interpretation and tips

Monitor success rate

Percentage of monitor evaluations where monitor_status = success.

Append monitor status columns to the data extract or export them from Data Quality and visualize the pass rate in Present.

Sudden drops highlight new anomalies; investigate before dashboards show stale data.

Issue backlog

Sum of issue_count for open monitor issues in the current workspace.

Use the Data Quality issues table or a dataset enriched with issue_count to track unresolved problems.

Trending backlog upward indicates operational risk and should be prioritized with the data engineering team.

SLA gap

Hours since the last successful fetch (derived from Activity logs or last_successful_fetch timestamps) per datastream.

Combine Activity export data with monitor status columns and plot the elapsed time.

Surface gaps early so channel owners can rerun fetches before SLA breaches propagate to reports.

What’s next?#

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