Analytics & attribution you can explain in a planning meeting.
A campaign report says leads are up. Sales sees a different picture. WebXd’s marketing analytics services help you trace the records behind those reports, repair tracking gaps, and agree what the numbers mean before they shape your next decision.
The work can cover GA4, Google Tag Manager, campaign naming, CRM outcome reporting, and attribution analysis. You get a measurement approach built around a business question, with the assumptions available for anyone who needs to challenge the answer.
Start with the records that disagree.
A form event, a unique lead, and a qualified opportunity count different things. Before comparing totals, we align the date range and reporting time zone, then identify the unit each system records. That gives your team a way to explain a gap instead of treating every difference as a broken tag.
An example you can follow back to the source
Imagine a report with 48 submission events. The form log contains 42 accepted records after six repeat events are removed. Of those records, 36 match CRM contacts and six still need investigation. If sales marks 12 matched contacts as qualified, that is a later stage with its own definition.
- 48Submission eventsThe analytics event count
- −6Repeat eventsRemove repeated collection
- 42Accepted recordsThe form system's record count
- 36 + 6Matched + unresolvedKeep the unmatched records visible
- 12Qualified contactsA sales stage within the matched set
This example assumes the repeat events can be identified from supporting records. Real reconciliation may leave an unexplained difference because of consent choices, delayed updates, or missing identifiers. We record what was checked and what remains uncertain, rather than adjusting the dashboard until it appears to agree.
Check what happens when someone takes the action.
Useful conversion tracking begins with a successful action. A button click can happen before a form fails validation, and a confirmation page can be refreshed. We define the event around the intended outcome, then test the conditions that should produce it and the conditions that should leave it unchanged.
| What you notice | What we check | Evidence to retain |
|---|---|---|
| A lead appears twice | Competing tags and repeat confirmation visits | Observed event sequence |
| The booking domain becomes the source | Cross-domain setup and the actual redirect path | A recorded test journey |
| One campaign has several names | Tagging conventions and URL parameters | Campaign naming register |
| Consent choices change collection | Default consent state and later updates | Results for each tested state |
A tracking plan names each event, the useful parameters, and the person responsible for changes. For external booking tools or payment providers, we first establish which collection methods the platform supports. Google’s cross-domain guidance is a useful starting point, but the test must follow the route your visitors actually use.
Every attribution view answers a particular question.
Marketing attribution assigns credit to recorded interactions before an outcome. The right view depends on the decision, the available records, and the length of your sales cycle. We document the model and lookback window alongside the report so a change in settings does not pass unnoticed as a change in performance.
| View | Useful question | Limit to carry with it |
|---|---|---|
| Paid and organic last click | Which eligible channel received the final interaction credit? | Earlier interactions can receive no credit |
| Data-driven attribution | How does GA4 distribute credit across recorded interactions? | Credit depends on the model and available path data |
| CRM revenue attribution | Which recorded sources are associated with closed business? | Requires agreed source, join, and revenue rules |
GA4’s current attribution options include data-driven and last-click models. A CRM revenue view is separate work, with rules for source history and closed outcomes that we agree with you. Comparing these views can reveal a dependence on one assumption; it cannot reconstruct every conversation or device a buyer used.
Credit allocation alone does not prove that a campaign caused additional sales. If your decision requires incremental lift, we discuss whether a suitable experiment or another measurement study is feasible. A small or incomplete dataset is a reason to narrow the claim, not to add a more elaborate model.
Give the report a question someone needs to answer.
A useful dashboard keeps the business question in view. For a lead campaign, that might be whether a source brings inquiries that sales can accept. We connect spend and acquisition activity to the agreed outcome where records allow, while keeping unmatched leads visible and separate from confirmed results.
A review note with an owner
- Question: Is this source bringing suitable inquiries?
- Read together: spend, accepted leads, qualification status, and reporting delay
- Investigate: a source with many submissions but few matched outcomes
- Next action: check the matching rule before recommending a budget change
The handoff explains how to read the report and when the data is ready for review. An unusual change becomes an investigation with an owner, rather than an automatic instruction to move budget. If AI helps draft a summary, the underlying figures and exclusions remain available for a person to verify.
Leave the definitions with the dashboard.
The scope can combine an audit, agreed tracking fixes, a reconciliation workbook, and a reporting view. Each engagement should name the systems and outcomes it covers. You can start with one lead journey or purchase flow, then extend the work when the definitions and collection checks hold up.
- Measurement dictionary: event, outcome, source, and revenue definitions
- Tracking specification: triggers, parameters, exclusions, and test cases
- Reconciliation record: joins, duplicates, unmatched records, and known gaps
- Reporting guide: model, date basis, refresh timing, and review owner
- Change record: implemented fixes and checks to repeat after a release
A new form, campaign naming change, or CRM stage can affect reporting long after the initial setup. We identify the checks your team should repeat and who maintains each definition. Ongoing monitoring can be scoped with a review cadence and responsibilities that fit your operating needs.
This service defines and validates the measurement. If the work also requires ongoing CRM synchronization, triggered follow-up, or changes to the conversion journey, we identify those dependencies in the brief. Related CRM integration, marketing automation, and conversion rate optimization services have their own implementation scope.
Set the boundaries before connecting more data.
Can you work with the analytics tools we already have?
We begin with an inventory of your analytics, tag management, campaign platforms, and CRM reporting. Existing tools may support the question well once their settings and definitions are clear. Any new connector, warehouse, or paid reporting tool should have an agreed purpose and cost before it enters the scope.
What access should we prepare?
An initial review needs relevant reporting access and a description of how leads or purchases are recorded. Implementation may need additional permissions in tag management or the website. We agree the necessary access and use test records where possible, with collection and sharing choices reflected in the measurement plan.
Can you fix historical data?
Some existing records can be reconciled or reclassified when the source information is available. Missing historical events and lost campaign details may be impossible to recover. We distinguish a reporting correction from a collection fix and state the date from which the new setup can be relied on.
What determines cost and timing?
The main drivers are the number of systems, the quality of existing records, and the implementation needed to answer your question. Third-party platform restrictions and access can also affect the work. An agreed brief separates the initial audit from fixes, reporting, and any continuing review so the estimate is understandable.