Marketing Analytics Consulting: Connect Every Channel's Spend to the Revenue It Brings In

Marketing analytics consulting answers one question for the owner or marketing lead who signs off the budget: which channels bring in customers who pay, and at what cost? Lightray Solutions answers it by joining your ad platforms, Google Analytics 4 and your CRM into one Power BI model, so a closed deal can be traced back to the campaign that started it.

Edward Pinela, MBA, builds the model himself, remotely, and the first step is a free 30-minute strategy call about your channels and systems. Most clients then start with a fixed-price build quoted in writing, or with a Power BI Flex Support block from $2,500 for 20 senior hours at $100–$125/hr, with hours that never expire.

“Amazing! Lightray Solutions built us a Power BI dashboard based on my busy restaurant’s quickbooks data that allows me to see my entire business on a daily basis which has been a game-changer! Excellent communication and service!”

— Quinn R., Google review

Why don't the numbers from Google Ads, Meta and GA4 agree?

Because each platform counts conversions by its own rules. Ad networks credit themselves for any conversion inside their own click or view window, so one sale can be claimed by two networks at once. GA4 applies a single attribution model across channels, and the CRM records only the leads a salesperson actually saw.

None of those numbers is wrong; they answer different questions. Marketing analytics settles which question the budget depends on, usually cost per acquired customer and revenue by channel, then builds that answer from the CRM outward. Platform figures stay in the model for campaign tuning, but the spending decision rests on closed business, not on clicks.

What does marketing analytics consulting deliver?

A working model and a short set of reports, not a slide deck of recommendations. The model holds daily spend by campaign, sessions and conversions from GA4, and leads, opportunities and closed revenue from the CRM, all keyed so a deal can be matched to its first and latest marketing touch. The table shows the questions it is usually built to answer.

• Tracking audit: UTM conventions, click IDs and form fields checked, so leads arrive in the CRM with their source intact.
• One data model joining spend, web behaviour and pipeline, refreshed on a schedule instead of exported by hand.
• Channel economics: cost per lead, cost per acquired customer and revenue by channel and campaign.
• Funnel view: how many leads from each source become qualified, proposals and customers, and how long each step takes.
• Written definitions for every measure, so marketing and finance read the same number the same way.

How is spend tied to closed revenue?

Through identifiers captured at the moment a lead converts. The landing page records UTM parameters and the ad click ID in hidden form fields; the CRM stores them on the lead record; and the model joins that record to the campaign's spend for the same day. When the deal closes weeks later, its revenue is already linked to the campaign.

Most gaps appear at the handoff points: a form that drops the parameters, a phone lead entered without a source, a salesperson who creates a duplicate contact. Part of the work is closing those gaps and showing the share of revenue that still has no known source, so nobody mistakes an incomplete picture for a complete one.

Which attribution model should a smaller business use?

Usually two side by side: the first touch that created the lead and the last touch before it converted. GA4 itself now offers only data-driven and last-click models; Google removed first click, linear, time decay and position-based in November 2023. Rebuilding first touch from your own CRM data restores the view that shows which channels open new conversations.

Data-driven attribution needs volume to mean anything, and a company closing a few dozen deals a month rarely has it. Comparing first and last touch is easier to explain, easy to check against the CRM, and enough to see whether a channel opens deals, closes them, or does neither.

Can the model show what makes a lead turn into a customer?

Partly. Power BI's key influencers visual runs a regression across lead attributes such as source, industry, company size or first page visited, and ranks the ones linked to a won deal. Microsoft advises at least 100 observations of the outcome you analyze and 10 of the comparison, so it suits companies with a steady flow of closed leads.

Treat the result as a lead for investigation, not proof of cause. If webinar leads close at twice the rate of paid-search leads, the next step is to ask sales why before moving budget. Turning that pattern into a score inside the CRM is a separate project, covered on lead scoring system implementation.

How does the engagement run, and how is it different from GA4 work?

Four stages, all by video and screen share: a tracking and data review, the model build, a reconciliation week where report totals are checked against the CRM and the ad accounts, then a handover with recorded walkthroughs. A first version typically covers your two or three biggest channels; others follow once those totals tie out.

If your question is narrower, such as GA4 events that stopped firing or a property that was never set up properly, a Google Analytics consultant engagement is the right size. For reports built on GA4 alone, see Google Analytics dashboard creation; agencies reporting to many clients should read Power BI for marketing agencies. The wider practice sits under business intelligence consulting.

Edward has 20+ years and 200+ projects behind him, and Lightray holds a 4.9 Google rating. Because the deliverable is a Power BI build, the Power BI guarantee applies: if you don't like working with us within the first 4 hours, you get your money back.

Further reading: Microsoft Learn — key influencers visual in Power BI.