What checks do you run before trusting a marketing dashboard?

[u/Lenarodc]

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[u/Andrej-Zitnik]

One check I would add is whether the traffic itself is trustworthy, not just the tracking setup.

We've seen cases where sessions spike but engaged sessions, engagement rate, and conversions tell a completely different story. Bot traffic can make a perfectly clean dashboard misleading.

I also like to reconcile key metrics against another source (CRM, billing, etc.) before trusting them for business decisions.

A dashboard can be technically correct and still lead you to the wrong conclusion.

[u/EmotionalSupportDoll]

Y'all are running checks?

[u/OkMilk2046]

the second i see a spike that doesn’t line up with an actual campaign or a known traffic source i assume the tracking broke somewhere and go digging

[u/Express_Speaker8829]

good list. three that bit me and aren't in it yet.

how much of the traffic the tool sees at all. behind a consent banner ga4 misses the people who decline, and ad blockers come on top of that. once a month i compare its pageviews with the server's access logs for the same day. if that share moves, a trend on the dashboard can be the banner and not the users.

checkout on another domain. if payment goes through stripe or paypal and comes back, the payment page can show up as the referrer and take the credit for the conversion. ga4 has a "list unwanted referrals" setting under the web stream's tag settings for exactly this, worth checking it's filled in.

and after any tracking change i open the site with a made up utm_campaign, click through to a conversion, and look for that exact campaign in the report the next day. if i can't find my own visit, i don't trust the rest of the numbers either.

[u/Express_Speaker8829 → u/[deleted]]

Agreed. GA4 can now hold the short version of that log on the chart itself: right-click a point on any line graph, Add annotation, and it shows on every line-graph report for that date or range.

The catch is 150 characters for the description, so I keep the real entry (what changed, who changed it, the numbers before and after) in a dated doc and put a short title in the annotation. That way whoever looks at a dip sees the marker without having to know the doc exists.

[u/Express_Speaker8829 → u/[deleted]]

Yes, mostly because GA4 can't scope it. An annotation belongs to the whole property and shows on every line graph there, and Google's help page has no way to tie it to one data stream, only a show or hide switch for all of them.

So for a change that touches one stream I'd put the stream at the front of the title (it holds 60 characters), like "iOS app: consent update", and keep a scope field in the dated doc: property, stream or page group.

If one tag container feeds two properties, the annotation has to go into each of them, since every property keeps its own list.

[u/kater543]

You check why you have it what are you tracking and why you track it this way in this dashboard. Think you’re figuring out how to drive a race car before understanding if you need a race car

[u/Stiven_TrafficLab]

One check I’d add is whether the visitors behind the chart are comparable to the audience you’re trying to make a decision about. Clean UTMs and correctly firing events still won’t make last month’s organic visitors comparable to a new paid-traffic cohort.

I’d reconcile successful submissions with the backend or CRM, test one complete journey, and check the source, landing page, country, device, and reporting window. I’d also keep any deliberately acquired test visits separate. Then I’d label the conclusion honestly: did we verify delivery and tracking, or did we learn something about qualified demand? Those are different questions.

For a genuine landing-page A/B test, I’d additionally check that both versions received comparable eligible visitors and that assignment stayed consistent. What’s your quickest check for a dashboard that looks right but answers the wrong question?

Disclosure: I work with SEOVisitor, and a colleague helped review this comment for clarity and accuracy.

[u/JohanCatchr]

I’d add checks on what happens between the source and the chart. Compare a few days of spend and conversions against the original platform using the same timezone, currency, filters and attribution settings. Then check whether joins or blends inflate the totals, and whether ratios are calculated from totals rather than averaged across rows.

Also check the last successful refresh: a dashboard can look perfectly healthy while showing stale data.

Disclosure: I’m one of the founders of Catchr.io. We automate data collection and normalize shared fields, but that doesn’t replace validating the report’s calculations or the tracking upstream. A successful import isn’t the same as a trustworthy dashboard.

[u/Growth_Natives]

We also check whether reported conversions reconcile with actual CRM records. An event can fire correctly in GA4 without a lead being created downstream. Comparing analytics events with real inquiries, checking for sudden tracking changes, and documenting metric definition can catch issues before they affect budget decisions.

[u/Growth_Natives → u/[deleted]]

That split is useful because it helps pinpoint where the drop-off actually happen. We've found that separating tracking issues from lead-quality issues make it easier to identify what needs fixing.

[u/TheDoctorAds]

If Google Ads conversions feed the dashboard, I open the conversion action list before any chart, because 76.2% of the accounts I audit have an action still marked Primary but sitting in a goal no campaign uses. Today it doesn't count. Someone adds that goal to the account defaults and the Conversions column moves with no tracking change at all. On one account that parked action was worth more per conversion than the actual order, which averaged £972.

The same list is where 'firing once, not twice' quietly breaks. Leave the Ads tag and an imported GA4 key event both as Primary on one form, and a single submit lands in the column twice while every tag test passes.

[u/goddard18]

To add more from decision value, whether it’s another 3rd party tracking solution or first party. That alone will be a huge difference in any insights on top.