Marketing attribution agency in Mumbai, India
Search Savvy connects your ad platforms, GA4, SEO, AI referrals and CRM to show which channels and campaigns produce leads, sales and profit. We clean up campaign tagging, compare attribution models honestly, test what truly drives growth, and give you a budget view you can act on.
What marketers ask before trusting channel numbers with real budgets.
From clean source data to confident budget decisions.
How each platform and GA4 currently assign credit, and where they disagree.
A naming standard and builder so every link is tagged correctly and consistently.
Custom GA4 channel groups, including AI referrals from ChatGPT, Perplexity, Gemini and Copilot.
Conversion paths, model comparison and lag time reports interpreted for your business.
Leads and closed sales tied back to source and campaign for true return on spend.
"How did you hear about us?" captured to reveal dark social, word of mouth and AI influence.
Geo and audience experiments that show what spend actually adds.
Spend, seasonality and outcomes modelled across channels for planning budgets.
Blended cost per lead, revenue per channel and clear reallocation recommendations.
Fix the inputs, compare the views, test the big claims, then move the budget.
The budget decisions you face and the outcomes that count are agreed first.
UTMs, channel groups and conversions standardised so sources are readable.
Ad platform, GA4 and CRM data joined to the sales that matter.
Credit under platform, last-click and data-driven views set side by side.
Holdouts, geo tests and self-reported data challenge the biggest claims.
Budget moves proposed, results tracked and the analysis refreshed regularly.
Every platform wants credit for the same sale. A neutral view shows what each really adds.
| Feature | Platform self-reporting | Search Savvy attribution analysis |
|---|---|---|
| Perspective | Each platform credits itself | Neutral view across all channels |
| Double counting | Same sale claimed by several platforms | Reconciled against actual orders and CRM revenue |
| Hard-to-track channels | Direct, dark social and AI traffic hidden | Channel groups and self-reported data reveal them |
| Proof of impact | Correlation inside the platform | Incrementality tests where possible |
| Metrics | Platform ROAS | Blended return, CAC and payback |
| Decisions | Shift budget to whoever reports best | Shift budget to what adds revenue |
Acting on the wrong credit is more costly than having no report at all.
Brand search and retargeting look brilliant while the channels that created demand look weak.
Typos and mixed naming split one campaign into many and hide results.
Untagged links, apps and AI answers all collapse into direct or referral.
Totals across ad platforms exceed actual sales, and nobody checks.
Optimising for leads when only a small share ever become customers.
Assuming spend causes sales without a holdout to prove it.
AI answers influence buyers in ways that rarely show up as a click. See AI search optimization
A custom GA4 channel group separates visits from ChatGPT, Perplexity, Gemini and Copilot, so you can compare their conversion and revenue.
Many AI-influenced buyers arrive later through branded search or direct, so we add a self-reported source field to forms and checkout.
Performance Max and Advantage+ report their own results, so we compare them against blended revenue and run holdout tests.
Related services that feed attribution with data or act on its findings.
Straight answers about credit, models and measuring marketing impact.
Still have a question? Ask usSearch Savvy's attribution and marketing analysis service includes an attribution audit, UTM and campaign governance, GA4 channel group design including AI referrals, attribution model comparison, CRM and revenue joins, self-reported attribution, incrementality tests, marketing mix analysis, dashboards and budget recommendations.
GA4's default model is data-driven attribution, which distributes credit using your account's conversion data, alongside last-click options. Google retired several older rule-based models, such as first-click, linear and time decay, in 2023, so comparing views often needs reports outside GA4 as well.
They use different attribution settings, conversion windows and counting methods, and Google Ads credits its own clicks while GA4 considers all channels. Consent, time zones and import delays add further gaps. Differences are normal, but large or unexplained ones usually point to tracking errors.
Incrementality testing measures what your marketing adds beyond what would have happened anyway. You hold back ads from a group, such as a region or audience, and compare results with a group that sees them. It is the most reliable way to check a platform's claims.
Marketing mix modelling uses statistical analysis of spend, sales, seasonality and other factors over time to estimate each channel's contribution. It does not need individual tracking, so it works with privacy limits, but it needs enough history and is best used for budget planning.
Create a custom GA4 channel group that matches referrers such as chatgpt.com, perplexity.ai, gemini.google.com and copilot.microsoft.com. Many AI-influenced visits still arrive as direct or branded search, so adding a "how did you hear about us" field helps capture the rest.
Yes, but we start by fixing the foundation, because attribution built on bad data misleads. We audit tagging, conversions and channel definitions first, and recommend GA4 or conversion tracking fixes where needed before drawing conclusions about channels.
A monthly review suits most businesses, with a deeper quarterly look at budget allocation. Review sooner after changing channels, launching big campaigns, redesigning the site or altering consent settings, because each of these can shift how credit is assigned.
Tell us which channels you run and how you track sales. Our analytics team will review your data and reply with a first view of where credit may be misplaced within 48 hours.
Talk to our team about attribution built on clean tagging, real revenue data and tests that separate causes from coincidences.
