Specialty
Making marketing decisions from siloed, platform-by-platform reports is like driving while only looking in the rearview mirror. Power BI brings every data source into a single dashboard and turns scattered numbers into actionable insights for people who need to make decisions fast.
A typical digital marketing operation generates data across at least five different platforms: Google Ads, Meta Ads, GA4, Search Console, and a CRM. Each one has its own interface, export format, and attribution logic. The result is a mess of out-of-sync spreadsheets that nobody can read with confidence.
Without a single source of truth, budget decisions get made on gut feeling or on platform reports that inflate their own results. Meta says it drove 200 leads. Google says 180. The CRM shows 150. Which number is right? None of them, because every platform counts in its own way.
Power BI solves this by bringing every source into one data model, with consistently calculated metrics and automatic refreshes, so nobody has to export anything by hand.
A consolidated view of Google Ads, Meta Ads, and TikTok Ads in one dashboard: spend, impressions, clicks, leads, CPL, and ROAS by channel, campaign, and time period. Cross-platform comparisons with standardized metrics.
From the ad click to the closed deal in the CRM: every stage of the funnel with conversion rates, average time, and bottlenecks. See where leads are dropping off and which channel brings in the highest-quality leads.
Customer Acquisition Cost and Lifetime Value calculated by source channel, not just per lead. Make budget decisions based on real profitability, not on a high volume of cheap leads.
Dashboards that track progress against monthly, quarterly, and annual goals, with visual alerts when a metric falls short and end-of-period forecasts based on the current pace.
Search Console impressions, clicks, CTR, and average position combined with GA4 traffic data for a complete view of the organic channel, including keyword and landing page trends.
Revenue, average order value, conversion rate, cart abandonment, and ROAS by campaign, with drill-down by product, category, and acquisition channel. Integrates with platforms such as Shopify, WooCommerce, and VTEX.
Dashboards built for real estate: leads by development, CPL by channel, lead scoring, qualification rate, and sales velocity tracking by unit type.
Dashboards shared with clients through Power BI Service, refreshed automatically every day, with no need to send a PDF report every week.
A well-built Power BI marketing dashboard follows a three-layer architecture:
Python scripts or native connectors pull data daily from the Google Ads, Meta Ads, GA4, Search Console, and CRM APIs. The data is normalized and loaded into a central database, removing any reliance on manual exports.
Related tables in a star schema: performance fact tables linked to time, channel, campaign, and product dimensions. Measures written in DAX keep metrics consistent no matter which filter is applied: CAC, ROAS, CPL, LTV, and conversion rate.
Interactive dashboards with drill-down, date and channel filters, and automated alerts. Published to Power BI Service with scheduled refreshes and role-based access for managers, analysts, or clients.
One of the most comprehensive projects was building a unified dashboard system for multiple clients at once, integrating Google Ads, Meta Ads, TikTok Ads, GA4, and Search Console into an automated Python pipeline that fed individual Power BI reports for each client.
For real estate, custom dashboards tracked CPL by development, lead scoring by source channel, and overall project progress, so the sales team could prioritize follow-ups based on data instead of gut feeling.
For large-scale integrated media campaigns, including TV, offline, and digital, tracking maps consolidated reach, frequency, and conversion data by market and channel in real time throughout the flight.