We help Google outperform Google

Yes.

Existing campaigns can be taken over by Amanda AI. Historical performance data remains in your account and continues to inform optimization decisions. You can choose this in the setup. 

Yes.

With Cross-Channel Budget Allocation enabled, the budget can be distributed between Google and Meta based on comparative performance signals.

Instead of fixed splits, allocation is evaluated based on expected marginal return across platforms.

This feature operates at the total budget level and does not increase the advertiser’s overall spend.

No.

Amanda AI works alongside Google’s Smart Bidding rather than replacing it.

Google continues to handle auction-level bid decisions through strategies such as:

• Maximize Conversions
• Maximize Conversion Value
• Target CPA (tCPA)
• Target ROAS (tROAS)

Amanda AI focuses on higher-level structural and budget decisions — determining where budget should flow and how campaigns should be organized to generate stronger signals.

Amanda AI relies on the conversion data configured in the account.

This can include:

• Native Google Ads conversion tracking
• GA4 conversions imported into Google Ads

The key requirement is that the selected conversion signal is reliable and properly configured.

Optimization decisions are made based on the data used for bidding and reporting within Google Ads. If GA4 is imported into Google Ads, it becomes part of that signal framework.

No.

You can sign up with any email address. However, we recommend using an email that is actively monitored in case we need to contact you regarding your account.

Google advertising requires balancing:

• Exploration — discovering new search queries and opportunities
• Exploitation — scaling proven high-performing segments

Amanda AI maintains this balance by allowing controlled discovery (through keyword mining and match type logic) while concentrating budget toward campaigns and segments that demonstrate strong marginal return.

Budget is not shifted aggressively based on single-period results. Instead, decisions account for signal stability and performance consistency.

Yes.

Amanda AI supports both Google Search and Google Shopping campaigns. This includes keyword-based search campaigns as well as feed-based product advertising through Google Merchant Center.

Campaigns can run independently or as part of a broader structured setup.

Yes.

If the same keyword exists across multiple ad groups with equal match type priority, Google’s Ad Rank determines which ad enters the auction.

Allowing duplicates can improve performance by letting the strongest ad group win per auction context. However, this can be turned off if structural control is preferred.

If strict keyword separation is required, Keyword Fencing is the appropriate solution.

Yes.

Amanda AI supports Performance Max campaigns and aligns them with the selected objective (such as conversion value or CPA).

Performance Max is treated as part of a broader Google strategy rather than an isolated campaign type. Budget decisions consider how PMax performs relative to Search and Shopping.

Yes.

Broad match is used strategically to discover new search queries and long-tail variations. Exact match retains priority in Google’s auction structure, but broad match allows exploration and incremental growth.

Broad match can be disabled in the portal, but if disabled, manual keyword expansion is recommended.

In new or low-data accounts, the initial focus is on structured exploration.

Without sufficient historical conversion data, early decisions rely more heavily on controlled keyword expansion, broad match discovery (if enabled), and balanced budget distribution.

As performance signals accumulate, budget allocation becomes more exploitative — scaling segments that demonstrate consistent efficiency.

The system shifts from exploration to performance concentration as data reliability increases.

Amanda AI connects to your existing Google Merchant Center and uses your product feed to structure Shopping and Performance Max campaigns.

The system evaluates product-level performance signals such as:

• Conversion value
• ROAS
• Cost efficiency
• Product segmentation

Campaign structure and budget distribution are aligned with your selected objective, ensuring product data is used strategically rather than treated as a static feed.

The Google setup is configurable.

Campaign structure, budget limits, match type usage, keyword mining, and cross-channel allocation can all be adjusted in the portal.

Amanda AI manages execution within those defined parameters, but the strategic boundaries are set by the advertiser. If structural changes are required — such as separating brand and generic campaigns or adjusting segmentation — the setup can be modified accordingly.

The system is automated, but not rigid.

Conversion lag is considered when evaluating campaign performance.

Optimization decisions are not based solely on same-day performance data. Instead, performance is evaluated over time to account for delayed conversions, especially in accounts with longer purchase cycles.

Budget and structural adjustments prioritize stability and sustained performance trends rather than reacting to incomplete short-term data.

This reduces the risk of reallocating budget prematurely due to reporting delays.

Stabilization depends on conversion volume, budget level, and objective.

Campaigns optimized for CPA or ROAS require sufficient conversion data to generate stable signals. In higher-volume accounts, stabilization can occur within weeks. In lower-volume environments, signal accumulation takes longer.

The focus is not on a fixed timeline, but on reaching consistent performance patterns rather than reacting to short-term volatility.