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Google Ads — Budget, Bidding & Optimization Review

I compared Google Ads planning scenarios, relevance signals and optimization options while documenting the decision logic needed for disciplined campaign governance.

Google AdsBudget plannerBiddingKeyword review
Google Ads — Budget, Bidding & Optimization Review presentation mockup
ClientBetter Gas Energy Services Limited
SectorLPG retail, cylinder exchange & distribution
GeographyNigeria · Abuja/FCT & surrounding distribution areas
RoleStrategy, implementation, management & analysis where supported
Evidence window2026 screenshots with several distinct budgeting scenarios
Engagement datesNot independently established
What the client needed

Forecasts are decision-support inputs. They become performance evidence only after actual spend, traffic quality and downstream outcomes are reconciled.

Budget and bidding decisions were reviewed as scenarios rather than treated as guaranteed outcomes, with platform estimates separated from actual spend and achieved performance.

Delivery architecture

How the work was structured.

A case-specific operating model rather than a generic service checklist.

01Objective
02Budget scenario
03Bid logic
04Review loop
What I delivered

Implementation translated into operational value.

01

Assessed conversion objectives and economic constraints

Configured and reviewed within the relevant platform context, with QA and evidence boundaries documented.

02

Compared platform-estimated budget scenarios

Configured and reviewed within the relevant platform context, with QA and evidence boundaries documented.

03

Reviewed keywords, relevance and quality signals

Configured and reviewed within the relevant platform context, with QA and evidence boundaries documented.

04

Prioritized optimization edits and rationale

Configured and reviewed within the relevant platform context, with QA and evidence boundaries documented.

05

Separated forecast values from actual results

Configured and reviewed within the relevant platform context, with QA and evidence boundaries documented.

06

Set an ongoing campaign-learning and review plan

Configured and reviewed within the relevant platform context, with QA and evidence boundaries documented.

Measurable evidence

What the available reporting actually proves.

₦9,000/day

Example custom budget

Source: Google Ads planning screen

Period: 2026 capture

This is a planning scenario, not necessarily the final running budget.
73

Estimated weekly clicks

Source: Google Ads forecast

Period: ₦9,000/day scenario

Forecast clicks are estimates, not achieved traffic.
₦863.02

Estimated average CPC

Source: Google Ads forecast

Period: ₦9,000/day scenario

Estimated CPC is not actual realized CPC.
338

Estimated weekly clicks

Source: Separate Google Ads scenario

Period: Separate planning capture

Do not combine this scenario with the ₦9,000/day scenario.
How it worked

Decision logic, implementation and QA.

  1. 01

    Define economic constraints

    Review the platform state, implement the relevant configuration, test the customer/measurement path and document the operational handoff.

  2. 02

    Compare forecast scenarios

    Review the platform state, implement the relevant configuration, test the customer/measurement path and document the operational handoff.

  3. 03

    Review relevance and quality signals

    Review the platform state, implement the relevant configuration, test the customer/measurement path and document the operational handoff.

  4. 04

    Prioritize optimization actions

    Review the platform state, implement the relevant configuration, test the customer/measurement path and document the operational handoff.

  5. 05

    Document learning plan

    Review the platform state, implement the relevant configuration, test the customer/measurement path and document the operational handoff.

Results & interpretation

Commercial significance without overstating causality.

Observed / configuredMarket demand / audience
Observed / configuredDiscovery or click
Configured / measurableBetter Gas web / messaging experience
Configured / measurableMeasurable enquiry
Configured / measurableHuman / automated follow-up
Only where independently evidencedOrder or visit where independently evidenced

The evidence on this page distinguishes observed platform state, configured journeys, forecasts and future measurement requirements. Where purchase attribution is absent, no ROAS or ROI claim is made.

Source evidence gallery

Original evidence is tracked separately from presentation mockups.

Privacy review required

Search campaign - Better Gas Energy Services Google Ads account - Google Ads (26.05.2026 22_01).png

What this proves: this source is part of the documented evidence set for the case study.

What remains unverified: any metric, identity or operational claim not explicitly described in the evidence panel above.

Raw admin screenshots are not rendered publicly until sensitive data is redacted and approved.
Privacy review required

Search campaign - Better Gas Energy Services Google Ads account - Google Ads (14.05.2026 22_05).png

What this proves: this source is part of the documented evidence set for the case study.

What remains unverified: any metric, identity or operational claim not explicitly described in the evidence panel above.

Raw admin screenshots are not rendered publicly until sensitive data is redacted and approved.
Future optimization

Recommended next measurement and operating improvements.

Recommendation 1

Reconcile forecasts against actual spend weekly

Recommendation 2

Measure conversion quality by query and landing page

Recommendation 3

Record optimization changes and outcomes

Next project

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