Unified marketing dashboard: Google, Meta, LinkedIn

What is a unified marketing dashboard?

It is one reporting view that joins ad spend and results from every platform with web analytics and CRM outcomes, on shared definitions. Where a channel report stops at clicks or platform conversions, a unified view follows the same campaigns to qualified opportunities and closed revenue.

It rests on three parts:

• Normalized cost data from Google, Meta, LinkedIn and any offline spend, in one currency and one date scheme.

• One conversion taxonomy, so a lead, a marketing qualified lead and an opportunity mean the same thing to marketing and sales.

• A join to the CRM, so each opportunity can be traced back to the campaigns that touched it.

What does fragmented reporting cost?

Fragmented reporting costs time and trust more than it costs any single line of spend. When each team reads its own platform, the numbers disagree and budget meetings turn into arguments about whose report is right.

The manual version is fragile too. Monthly CSV exports joined in a spreadsheet break on a changed column, a currency mix or a missed filter, and a lead from last quarter that closes today is hard to tie back to the ad that started it.

Which metrics belong on it?

Lead with the measures that tie spend to revenue, and keep platform metrics one level down.

• Spend by channel and campaign, from every platform.

• Cost per qualified opportunity by channel, not only cost per lead.

• Lead to opportunity conversion by channel, to see which sources bring buyers.

• Pipeline and closed revenue linked to campaigns, sourced and influenced shown separately.

• Time from first touch to opportunity, for long sales cycles.

Clicks, impressions and click-through rates stay available in drill-downs for the people who tune campaigns. They explain why a number moved; they should not decide where the next budget goes.

How do you connect the data?

Connect each source on a schedule into one store, then apply your definitions in that store, not in each chart.

1. Fix names and UTMs first. Google recommends always setting source, medium and campaign, and treats values as case sensitive.^[1] A shared naming convention is the join key across platforms.

2. Bring in cost data. GA4's campaign data import adds cost, clicks and impressions from non-Google platforms, joined on source and medium with exact matches.^[2] Teams with a warehouse can pull each platform's API directly instead.

3. Export analytics to a warehouse when you outgrow the interface. GA4's BigQuery export sends raw event data daily, with a near real-time streaming option, and is available to standard properties.^[3]

4. Join the CRM. Store click IDs and UTM values with each lead, then join opportunities and revenue to campaigns. LinkedIn can add campaign names and IDs to landing page URLs automatically through dynamic tracking parameters.^[4]

5. Send outcomes back. Google Ads offline conversion import uses the stored click ID to report sales that happen after the click, so bidding learns from pipeline.^[5] Closed-loop reporting covers this step for each platform.

Why do the numbers still disagree?

They disagree because each platform counts conversions with its own attribution rules, windows and time zones, and B2B deals close long after the click. That is expected.

Decide which system is the record for each stage. Platforms report their own delivery and spend. Analytics reports site behavior. The CRM reports pipeline and revenue. Show platform conversions as signals, and judge channels on CRM stages. When you need to weigh channels against each other over time, read MTA vs MMM for the trade-offs.

How do you get the team to use it?

Make it the view the weekly meeting runs on, and keep it small.

• One page first. Spend, cost per qualified opportunity and pipeline by channel. Add pages only when someone asks a question the first page cannot answer.

• Named owners. One person owns definitions, one owns data freshness.

• Access by role. Partners can see channel cost without seeing margin or deal data.

• A change log. Every change to a definition gets a date and a reason, so trends stay comparable.

A dashboard earns trust when finance and sales recognize their own numbers in it. Our marketing analytics and attribution service builds the naming, tracking, CRM join and reporting as one piece of work, within our digital marketing services. For the ad platforms alone, Ads Analyzer is the cross-channel ad reporting product DGo built.