First-touch and last-touch reports can disagree while both are internally correct. They assign credit to different points in a journey. The useful question is what decision the report supports: discovering demand, closing demand or budgeting across stages.
How to make the decision
Use the following sequence for a UAE English-language business. Keep a copy of the inputs and the reason for each decision so a later reviewer can reproduce it. The right answer depends on the actual offer, audience and data available; the example is a planning exercise, not a claimed Megvi client outcome.
| Step | What to do |
|---|---|
| Write the journey | Record the sequence of eligible interactions, dates and conversion window. Identify what the system could not observe, such as an offline recommendation or a device switch. |
| Apply the rules consistently | First touch credits the earliest eligible interaction; last touch credits the latest eligible one before conversion. A platform may use additional exclusions or model rules, so confirm its settings. |
| Compare by decision | Use first-touch patterns to inspect discovery channels and last-touch patterns to inspect closing routes. Neither alone proves a channel caused the purchase. |
| Add business outcomes | Join the attribution view with revenue, lead quality and margins where those records are trustworthy. Keep a separate label for unattributed conversions. |
Worked example
Illustrative path: a buyer finds an SEO guide, later clicks a branded search ad and finally returns directly to purchase. A first-touch report credits the guide; a last-touch report may credit the ad or the last eligible non-direct interaction depending on configuration. One sale has not become two sales.
Where this approach can fail
Do not sum credit across competing attribution models. Google Analytics currently lists data-driven and two last-click models in its attribution reports; a first-touch view here is a conceptual comparison or a separately built analysis, not a native GA4 model. Also avoid concluding that direct or branded activity has no value because a model excludes it.
Review checklist
Record model, lookback window, channel grouping, timezone and conversion definition next to every comparison. If Google Ads and GA4 disagree, audit event collection and attribution settings before changing spend.
Ask an owner to confirm the inputs and assumptions before using this method to change a live campaign, customer record or product recommendation. Keep the original version of any measurement or creative asset so the next review can separate what changed from what only appears to have changed.
What to do next
For a separate check of purchase-count differences between platforms, read internal linking for ecommerce. If you need help applying the method to a live account or store, explore Megvi’s Google Ads service and bring the current page, campaign or data flow plus the result you want to improve.
Reference: Google Analytics: attribution settings (checked 21 October 2026). The worked example above is editorial and should be verified against the current platform or product setup.
Ahmed Elneil
https://megvidigital.comAhmed Elneil is a certified digital marketer and entrepreneur with over 5 years of experience helping brands grow through Search Engine Optimization (SEO), paid advertising, and CRM automation.