Data Processing & Reporting Checklist for Digital Marketing

Create a documented taxonomy for utm_source, utm_medium, and utm_campaign, then validate links with regex and GA4 debug views. Consistent UTMs prevent misattributed traffic and broken channel rules.

Ensure gclid, dclid, fbclid, and ttclid persist from landing pages into GA4 and your CRM or warehouse. This preserves ad platform attribution despite privacy changes and cross-device journeys.

Convert all timestamps to UTC and normalize spend to a base currency using daily FX rates from Open Exchange Rates or XE. Misaligned zones and currencies distort ROAS and pacing.

Use composite keys like platform-campaign_id-ad_id and latest updated_at logic to drop duplicates in SQL. Agency CSVs often include repeated rows that double count spend and conversions.

Create slowly changing dimension tables for account, campaign, ad set, and ad identifiers with names and statuses. Renames or deletions will otherwise break historical reporting and cohort analysis.

Use updated_at cursors, high watermarks, or hash-based change detection with Fivetran, Supermetrics, or Airbyte. Pulling deltas reduces costs and avoids overwriting newer data.

Capture consent_mode, gbraid, and anonymization flags to segment traffic by compliance in GA4 and downstream models. This prevents biased blends of incomplete and complete data.

Map platform-specific columns to unified fields for spend, impressions, clicks, and conversions, then compute CTR, CPC, and CPM in dbt. Canonical schemas eliminate metric drift across channels.

Link ad data to Shopify, WooCommerce, or CRM conversions with order_id, email hash, or click_id to calculate CAC and ROAS. Start with deterministic links before adding model-based attribution.

Translate utm_source and utm_medium into standard channels like Paid Search, Paid Social, Organic Search, Email, and Referral. Consistent channels enable blended metrics such as MER for executives.

Classify conversions as primary, secondary, or micro across platforms, and standardize value fields. This avoids mixed baselines when comparing ROAS and CPA between networks.

Winsorize extreme CPC or CVR values and backfill missing dates with zero rows for stable time series. Document all manual patches to maintain auditability.

Compute revenue by cohort week and channel using SQL window functions or R, then derive CAC payback and long-term ROAS. Cohorts turn short-term metrics into strategic budget guidance.

Parse naming conventions via regex or pull fields from platform APIs to tag audience, placement, and creative attributes. Tagging enables fatigue analysis and creative-level ROAS.

Use Tabula or Camelot for digital PDFs and AWS Textract or Tesseract for scans, then parse vendor, period, and totals into a structured table. Many niche publishers still deliver finance data via PDF.

Cross-check PDF totals against Stripe, QuickBooks, or Netsuite exports and enforce tolerance thresholds. Automated reconciliations catch OCR errors before they hit reporting.

Turn PDF performance reports from smaller networks into CSV, standardize fields, and append to your canonical tables. This ensures long-tail channels are included in blended KPIs.

Apply regex and mapping rules to harmonize campaign and placement names found in agency PDFs. Store raw and cleaned values for traceability and to prevent duplicate entities.

Save original files to S3 or GCS, record SHA-256 hashes, source mailbox or portal URL, and ingest timestamps. Strong lineage makes audits and troubleshooting faster.

Use Gmail API or IMAP filters to capture monthly invoices, or fetch from portals with Playwright, then enqueue for extraction on a schedule. This removes manual download bottlenecks.

Build first-touch, last-touch, linear, and time-decay models in dbt or warehouse SQL, and expose model selection as a parameter. Multiple lenses reduce decision bias.

Create a centralized metrics dictionary that specifies which costs are included and how revenue is measured by window and channel. Consistency prevents KPI debates and rework.

Calculate delay distributions between click and conversion and present 7-day vs 28-day metrics side by side. This avoids premature optimization and undercounting recent spend.

Use user_id, device_id, and hashed emails from GA4, Segment, or RudderStack to reduce duplicates across channels and devices. Better identity increases attribution accuracy.

Run geo or audience holdouts with traffic separation and record test metadata like start, end, and targeting. Report lift, cost per incremental, and confidence intervals, not just raw deltas.

Analyze brand search and direct traffic changes during paid pauses to quantify cannibalization and halo effects. Use time series controls instead of anecdotal comparisons.

Aggregate channel-level spend, impressions, clicks, and conversions by week and add holiday and promo flags for Robyn or LightweightMMM. Clean inputs are essential for stable models.

Create executive views with MER, CAC, and ROAS trends, and separate deep dives for channel managers in Looker Studio, Tableau, Mode, or Power BI. Reuse filters to maintain consistency.

Generate text that highlights significant shifts, budget pacing, and top creative using templated logic and thresholds, then send to Slack or email. This cuts prep time for weekly standups.

Check for nulls, negative spend, CPC spikes, zero-conversion days, and missing UTMs, and post alerts to Slack with a link to a triage playbook. Rapid detection prevents wasted budgets.

Keep SQL and dbt models in git with not null, unique, and accepted_values tests, and run CI on every merge. This avoids silent metric shifts from schema changes.

Use Airflow, Dagster, or Prefect for scheduling with dependency graphs, retries, and SLAs that escalate on missed deadlines. Predictable refreshes keep the business in sync.

Export curated CSVs or Google Sheets for finance and ops with refresh timestamps and validation, separate from analytical tables. Prevent ad hoc edits from contaminating your source of truth.

Host metric definitions, lineage, and naming conventions in dbt docs, Notion, or Atlan, and log changes with effective dates. Documentation reduces rework and accelerates onboarding.