CyberFreezeDev
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Ad spend, traffic and CRM sales joined daily, showing what each rupee became.
Not more charts. Fewer, joined-up numbers.
Each platform counts differently. The dashboard joins them on dates, campaigns and UTM tags to show spend, leads, customers and cost per customer.
Meta tells you it drove a set of conversions. Google Ads claims some of the same people. GA4 shows sessions by source. The CRM shows which leads actually paid. Each platform is right on its own terms and none of them agree, because each one counts differently and none can see the others.
A marketing intelligence dashboard pulls all of these into one place every day, matches them on dates, campaigns and UTM tags, and shows the numbers an owner actually asks for: what we spent, how many leads came in by channel, how many became customers, and what each customer cost.
It is the reporting half of our marketing work. If you also want the campaigns run, see growth marketing. If the leads arrive on WhatsApp, the WhatsApp CRM automation service tags each one with its source so the dashboard can follow it to revenue.
Scheduled pulls from Meta, Google Ads, LinkedIn, GA4 and your CRM, with failure alerts.
Scheduled pulls from the Meta Marketing API, Google Ads API, LinkedIn Ads and your CRM, plus GA4's native BigQuery export. We usually run these on n8n so failures raise an alert instead of leaving a silent gap.
Campaign names, UTM tags and currencies normalised so every table agrees.
Campaign names, UTM tags and currencies are normalised in the warehouse so a campaign means the same thing in every table. Lead and order records are matched back to the source that brought them where the tracking allows.
Looker Studio for most teams, or a custom web dashboard for per-client logins.
Looker Studio for most teams because it is free and easy to share, or a custom web dashboard when you need logins per client, white-labelling for an agency, or charts Looker Studio cannot draw.
UTMs, GA4 events and conversions audited, with a naming convention everyone follows.
Most dashboards fail because tracking was never set up consistently. We audit UTM use, GA4 events and conversion definitions, and write a naming convention your team and agencies can follow.
Alerts on spend jumps or zero leads, plus a written weekly summary by email.
A message when spend jumps, leads drop to zero, or a campaign runs past its budget. A short weekly summary, written by a language model from the actual numbers, emailed to the people who do not open dashboards.
The monthly questions, and the exact definitions of lead, customer and revenue.
We start from the five to ten questions the owner or marketing head asks every month, and the definitions behind them: what counts as a lead, a qualified lead, a customer, revenue.
GA4, ad conversions, UTM habits and CRM lead source checked, with gaps ranked.
We check GA4 events, conversion setups in each ad account, UTM habits and how the CRM records lead source. Gaps are listed with fixes, in order of how much they distort the numbers.
Scheduled loads into BigQuery or Postgres, joined tables and history backfilled where available.
Read access to each platform, scheduled loads into BigQuery or Postgres, and the joined tables. We backfill history where the platforms still hold it.
A first version on real data, reviewed with users, with unused charts removed.
A first version on real data, reviewed with the people who will use it. Pages and charts that nobody reads are removed.
Every source and metric documented, and the Google Cloud project in your name.
Documentation of every source, table and metric definition, ownership of the Google Cloud project in your name, and a check-in after the first month of use.
Described without the client's name, as agreed.
Meta Ads, Google Ads, GA4 and CRM data joined in BigQuery and shown in Looker Studio. A single small channel does not need it.
We built a cross-channel marketing dashboard that brings Meta Ads, Google Ads, GA4 and CRM data together. n8n workflows load the ad and CRM data into BigQuery alongside GA4's own export, scheduled queries join them, and Looker Studio shows spend, leads and customers by channel and campaign on one page.
Where it does not fit: if you run one channel with a small budget, the platform's own reports are enough. And a dashboard cannot fix attribution that the tracking never captured; if leads arrive by phone with no source recorded, we will fix that first or tell you which numbers to treat as estimates.
Each platform reports only its own results and counts conversions its own way, so their totals usually add up to more customers than you actually got. A joined dashboard checks spend against what your CRM or store says really happened.
Not always. For a few sources and modest data, Looker Studio connectors and a Google Sheet can be enough. Once you want GA4 event-level data, history beyond the platforms' limits, or joins with CRM records, a warehouse like BigQuery is the reliable route.
Looker Studio is free. BigQuery charges for storage and queries, which stays small for most small and mid-size businesses at the data volumes involved; we design queries to keep it that way and show you the billing page. We do not publish project prices; the contact form asks for your budget range.
Yes. Marketing agencies are one of the sectors we work with. We can build one pipeline that serves many client accounts, with each client seeing only their own data.
You do. The Google Cloud project, the warehouse and the dashboard are created under your account, and we work with access you can revoke.
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