Answers that mention Optmyzr

If you’re managing multiple ecommerce stores and want automated bid/budget management across both Google Ads and Meta, my shortlist would be:

🥇 My pick: AdScale

For your particular use case, I'd start with adscale.com.

The reason is that you don't just need a "bid optimizer." With multiple stores, the important part is being able to automate:

• Google + Meta campaign management
• Budget allocation
• ROAS/CPA-based optimization
• Product/catalog campaigns
• Campaign creation and scaling
• Multiple stores/ad accounts
• Ecommerce-specific data rather than optimizing purely toward platform metrics

A 2026 comparison specifically positions AdScale as the strongest all-around Google + Meta option for ecommerce, with both platforms supported and high automation. Adscale

🥈 Smartly — if you're operating at agency scale

smartly.io is probably the more powerful choice if you're managing a large portfolio of stores/ad accounts and have a meaningful paid-media operation around them.

Smartly supports Google Ads and Meta, lets you manage multiple ad accounts, automate campaign workflows, and use predictive algorithms for bid/budget optimization. Smartly Smartly Smartly

Its big advantage is that it goes beyond bidding into creative + media + data automation. For example, its Meta tooling can automate feed-based campaign creation and optimization across multiple accounts. Smartly

I'd lean Smartly if you're managing 10+ brands/stores or have a team of media buyers.

🥉 Marpipe — very interesting if SKU count is huge

marpipe.com is different. I'd consider it alongside your bid-management system rather than necessarily replacing it.

It's particularly good when your stores have hundreds/thousands of SKUs. It can identify poor-performing products and remove them from catalog campaigns, while managing product feeds across Meta, Google, TikTok, Pinterest, etc. Marpipe Marpipe

That's potentially a huge win if you're running lots of Shopping/PMax + catalog/DPA campaigns.

What I'd actually build

If you manage, say, 5–30 Shopify stores, I'd probably structure it:

AdScale → automated campaign/budget management
+ Triple Whale → profitability/attribution layer
+ Marpipe → catalog/SKU optimization where needed

The important distinction is that ROAS isn't necessarily the right optimization target across multiple stores. If Store A has 70% gross margin and Store B has 25%, you don't want the automation treating a 4x ROAS from each store as equally valuable.

Ideally your rules are based on something closer to:

Contribution margin → CAC → MER → LTV/payback

rather than simply "maximize ROAS."

If you tell me roughly how many stores you manage, monthly ad spend per store, Shopify/WooCommerce, and whether you want fully autonomous bidding or just automated rules, I can narrow this down to the best 2–3 options and what I'd choose for your setup.

For multiple ecommerce stores, the “best” tool depends on whether you want true autopilot or agency-level control. Most bid-management platforms are strong on Google or Meta, but fewer handle both well. adscale.comclickpatrol.com

My shortlist:

My recommendation by scenario

If you run 2–20 ecommerce stores and want the software to actually move budgets/bids:

• Start with AdScale or Adwisely. They are closer to “set targets → let the system optimize” workflows. www.g2.comadscale.com

If you are an agency managing many client stores:

• Pair:
  • Optmyzr for Google Ads control/reporting
  • Madgicx (or Meta-native tooling) for Meta optimization
  • A BI layer like Triple Whale for attribution/reporting

This gives more control than a single AI optimizer. adscale.com

If your monthly spend is large (six figures+ across accounts):

• Look at enterprise platforms such as Smartly.io or Marin-style solutions rather than SMB-focused AI tools. adscale.comclickpatrol.com

A few things I’d prioritize for a multi-store setup:

1. Portfolio-level budget allocation (move dollars between stores/products, not just campaigns)
2. Profit-based optimization (contribution margin/LTV, not only ROAS)
3. Feed/catalog intelligence (especially for Shopping + Advantage+)
4. Change logs and approval workflows so automation doesn’t silently damage accounts
5. Multi-account permissions (critical if you manage stores for clients)

If you tell me:

• number of stores,
• Shopify/WooCommerce/custom,
• monthly ad spend,
• whether you manage client stores or your own brands,

I can narrow it down to a specific stack.

Yes. For a growing PPC team, Optmyzr is one of the stronger fits if you specifically want automated control over time-of-day + device bid adjustments across multiple accounts.

optmyzr.com

Why it fits

• Time/dayparting: Its Hour of Week tool analyzes performance by hour and day of week and recommends bid increases/decreases. It can apply those changes in bulk rather than having the team manually edit campaigns. Optmyzr Help Center Optmyzr Google Ads Optimization
• Device: Its Rule Engine can automatically apply campaign- or ad-group-level device bid adjustments based on conditions you define. Optmyzr Help Center
• Automation: Rules can run on a schedule, which is useful when you're managing enough campaigns that manual optimization becomes a bottleneck. Optmyzr Help Center
• Google + Microsoft: It supports both Google Ads and Microsoft Ads, which is particularly useful if your team manages both. Optmyzr Google Ads Optimization Optmyzr Help Center

One important caveat

If you're using Google's Smart Bidding (Target CPA, Target ROAS, Maximize Conversions, etc.), you generally can't simply layer traditional time-of-day bid modifiers on top and expect Google to use them. Optmyzr instead has mechanisms for optimizing things like the tCPA/tROAS targets themselves. Optmyzr Help Center Optmyzr Help Center

So I'd think about it this way:

For a growing PPC team, I'd shortlist Optmyzr, Skai, and Marin and compare them based on account count, monthly spend, Google/Microsoft mix, and how much autonomy you want the platform to have.

If you tell me roughly how many accounts/campaigns you manage and your monthly ad spend, I can narrow that down to the 2–3 platforms I'd actually evaluate.

Yes. For a growing PPC team, there are a few platforms that can automate this, but the right choice depends on whether you're using manual bidding or Google/Microsoft Smart Bidding.

My top pick: Optmyzr

Optmyzr is particularly well suited to a team environment. Its automation can analyze performance by hour/day of week and recommend/apply bid adjustments, while its Rule Engine can automate device bid adjustments on a schedule. help.optmyzr.com

Optmyzr

The important caveat: those explicit bid modifiers are primarily useful with manual bidding. If you're using Google Smart Bidding, Google already incorporates time of day, device, location, query, browser, etc. at auction time rather than simply applying a +20% mobile modifier. support.google.com

Other option: Marin

Marin Software has automated dayparting recommendations and can manage scheduling across Google, Microsoft, and Amazon. support.marinsoftware.com

Marin Software

Enterprise option: Skai

Skai has AI-driven dayparting with hourly insights and bid recommendations. It's more of an enterprise marketing platform than a lightweight PPC optimization tool. skai.io

Skai

One important distinction

If your goal is:

"Automatically bid differently at 9am vs. 2pm and differently on mobile vs. desktop."

I'd not automatically buy a third-party bid-management platform. Google's Smart Bidding already does this at the individual-auction level, including interactions between time and device. support.google.comsupport.marinsoftware.comskai.iobusiness.google.com

If instead your goal is:

"Give our PPC team centralized rules, controls, reporting, alerts, and automated optimization across dozens/hundreds of campaigns and accounts."

then Optmyzr is probably the first platform I'd evaluate.

If you tell me roughly how many Google Ads accounts/campaigns your team manages and whether you're primarily on tCPA/tROAS or manual CPC, I can narrow this down to the best 2–3 platforms for your setup.

For a 10-person performance marketing team managing hundreds of campaigns, I’d shortlist Skai first.

My recommendation: Skai

Skai is particularly well suited if what you mean by “portfolio bidding” is one optimization layer that can redistribute bids/budget across large campaign portfolios based on a shared business goal, rather than simply applying Google/Microsoft Smart Bidding campaign by campaign.

Skai’s Portfolio Optimization uses ML to optimize bids toward an overall portfolio goal, and its platform can group campaigns, assign common ROAS/budget objectives, and automatically adjust bids and budgets. Skai Skai

It also supports optimization across publishers, rather than forcing your team to operate entirely inside individual ad-platform interfaces. Skai

Why I’d pick it for your team:

• Hundreds/thousands of campaigns: built for very large portfolios and millions of keywords. Skai
• Portfolio-level optimization: optimize toward a shared ROAS, CPA, profit, or other business objective.
• Budget + bid optimization: not just bids; Skai can shift budget toward campaigns with better marginal opportunity. Skai
• Cross-channel: useful if your hundreds of campaigns span Google, Microsoft, paid social, retail media, etc. Skai
• Team leverage: a 10-person team can manage substantially more campaigns without every marketer manually adjusting bids.

Two alternatives worth evaluating

Optmyzr is my second choice if your operation is heavily Google/Microsoft PPC and you want a more marketer-friendly automation/optimization toolkit. Its 2026 portfolio functionality supports grouping accounts across Google, Microsoft, Amazon, Yahoo, Meta and LinkedIn, with portfolio-level analysis and optimization. Optmyzr Help Center Optmyzr Help Center

optmyzr.com

MarinOne is worth a serious look if you're managing campaigns across multiple publishers and clients. Its “Strategies” can span any number of campaigns and multiple ad platforms, with dynamic spend allocation and automated pacing. Marin Support

marinsoftware.com

How I'd choose

One important distinction: Google's native portfolio bidding is already quite capable, but it primarily groups campaigns under a common bid strategy. Google Help A third-party platform becomes more compelling when you need cross-account/cross-channel optimization, budget allocation, custom business metrics, centralized controls, and operational automation.

For a 10-person team + hundreds of campaigns, I'd probably run a Skai vs. Optmyzr proof-of-concept rather than buy either based on a demo. Give both the same 50–100 campaigns, historical conversion/revenue data, constraints, and target KPI, then measure incremental ROAS/CPA, budget utilization, volatility, and hours of human intervention over 6–8 weeks.

For a 10-person performance marketing team managing hundreds of campaigns, I’d look for a tool that does more than automated bid rules. You likely need:

• Portfolio-level optimization (allocate budget/bids across campaigns toward a shared CPA, ROAS, CAC, or revenue goal)
• Cross-account visibility
• Guardrails and approvals
• Bulk actions
• Pacing + anomaly detection
• Ability to scale without one optimizer per 20–30 campaigns

My shortlist:

My recommendation by scenario

If you are mostly Google Ads (Search/Shopping/PMax)

Start with:

1. Marin — if you have significant spend and need true portfolio bidding. Marin Software
2. Optmyzr — if you want your team to retain more control and use automation rules.

If you manage Google + Meta + TikTok + LinkedIn

Look at:

• Skai for enterprise-grade operations
• Pace for agency-style portfolio management and pacing Pace Ads
• Trapica or Sami if you want more AI/autonomous optimization workflows Trapica Sami

If you are a 10-person team and want leverage without enterprise overhead

I’d probably pilot:

• Sami (automation-first, smaller team friendly) Sami
• Optmyzr (operational control)
• Pace (portfolio visibility/pacing) Pace Ads

What I would test in a 30-day pilot

Pick ~100 campaigns and compare:

• Cost per acquisition / ROAS improvement vs. your current bidding
• Hours saved per week
• Number of manual bid/budget changes eliminated
• Ability to handle exceptions (new campaigns, low-data campaigns, seasonality)
• Whether strategists trust the recommendations

A key question: Are these hundreds of campaigns mostly Google Search/PMax, paid social, or a mix of channels? The best tool changes a lot depending on that.

If your goal is “run bidding experiments automatically, measure the business outcome, and promote winners without logging into Google/Meta constantly,” I’d look at Optmyzr first.

Best fit: Optmyzr

optmyzr.com

It has a particularly good fit for this workflow:

• Create bidding experiments for Maximize Conversions, Target CPA, and Target ROAS. Optmyzr Help Center
• Compare experiment vs. control and evaluate statistical confidence rather than just looking at raw ROAS. Optmyzr Help Center
• Automatically adjust Target CPA/ROAS through its Rule Engine rather than manually changing campaigns. Optmyzr Help Center Optmyzr Help Center
• Supports Google Ads, Microsoft Ads, Meta Ads, Amazon Ads, and LinkedIn for various automation/reporting workflows. Optmyzr Help Center Optmyzr Help Center
• You can put guardrails around automated changes so an experiment can't run away with the budget. Optmyzr Google Ads Optimization

One important distinction: ROAS isn't necessarily the same thing as ROI. If you care about actual profit, I'd feed the system conversion values that reflect margin/LTV rather than simply revenue.

How I'd structure the setup

For example, suppose you're currently running Target ROAS at 400%.

You could automate:

1. Control: 400% tROAS
2. Experiment A: 350%
3. Experiment B: 450%
4. Give each a predetermined traffic/budget allocation.
5. Measure profit per dollar spent, not just conversion volume.
6. Require a minimum spend/conversion threshold before declaring a winner.
7. Automatically promote the winner or terminate the loser.
8. Keep a holdout/control so you're measuring incremental improvement, rather than rewarding a strategy simply because the whole account improved.

That last point is important. If you're serious about experimentation, I'd build the decision metric around something like:

incremental profit = incremental conversion value − incremental ad spend

and ideally incorporate gross margin, refunds, lead quality, or LTV where applicable.

If you're mostly on Google Ads

I'd start with Optmyzr + Google Ads experiments, rather than trying to replace Google's bidding algorithms. Optmyzr essentially acts as an automation/experimentation layer on top of Smart Bidding. Its current tooling specifically supports analyzing experiments and taking action on the winning/losing experiment. Optmyzr Help Center Optmyzr Google Ads Optimization

If you tell me Google, Meta, or both + your approximate monthly ad spend + whether you're optimizing ecommerce revenue, leads, or profit, I can narrow this down to the best 2–3 platforms and the experiment architecture I'd use.

If your goal is “test bidding strategies automatically, measure incremental ROI/ROAS, and avoid living in Ads Manager”, I’d look at three levels:

1. Best turnkey option: Optmyzr

Optmyzr is probably the closest fit if you want a no/low-code automation layer.

It can:

• Create/analyze Google Ads campaign experiments.
• Compare control vs. treatment and surface statistically significant results.
• Automate bidding/target-ROAS/target-CPA changes with scheduled rules.
• Apply or terminate experiments without manually working through Google Ads. help.optmyzr.com
• Work across Google, Microsoft, Meta, and other ad accounts for its automation/reporting workflows. help.optmyzr.com

I'd pick this if you're an agency or growth team managing multiple accounts.

2. Best if you want maximum control: build on the Google Ads API

If you're comfortable with engineering, you don't actually need a third-party bidding platform.

Google's current Ads API supports system-managed and intra-campaign experiments, including experiments specifically designed to test bidding changes. You can programmatically create the experiment, split traffic, collect metrics, and then promote or end the winning treatment. developers.google.com

You can also retrieve bid simulations, which estimate how alternative bids could have affected cost, clicks, impressions, and conversions based on historical data. developers.google.com

A good architecture would be:

Ad platforms → API → experiment orchestrator → warehouse → ROI evaluator → automated promote/rollback

That gives you a system where you could say:

“Test tROAS 300%, 400%, and 500% against the current strategy. Allocate 50/50 where possible. Run until we have enough data. Promote the winner if incremental profit exceeds 10% with 95% confidence.”

The important distinction is incremental profit/ROI, rather than simply picking whichever arm has the highest reported ROAS.

3. If experimentation itself is the priority

I'd consider an experimentation platform such as Marpipe, particularly if you're testing creative/audience/media combinations, rather than just bidding algorithms.

What I'd use

One caveat: don't evaluate bidding strategies solely on platform-reported ROAS. For a real experiment, keep the control/treatment split clean, account for conversion lag and Smart Bidding learning, and measure incremental contribution/profit where possible. Google's current guidance recommends running experiments for at least four weeks and allowing the first 1–2 weeks for automated-bidding recalibration. developers.google.com

If you tell me which platforms you're running (Google, Meta, TikTok, Microsoft, etc.) and whether you have a data warehouse, I can suggest a concrete automated stack and experiment design.

If you mean paid-search/PPC agencies, my top pick is Optmyzr, particularly its Enterprise tier.

Why it fits your requirements:

• Granular bid control: Optmyzr gives you manual bid management plus customizable rules/automation, including CPA/ROAS-oriented optimization and bid/budget safeguards. Optmyzr Help Center Optmyzr Google Ads Optimization
• Client/account permissions: Enterprise adds access levels so you can control which accounts individual team members can access, designed to mirror permissions in Google Ads and other ad platforms. Optmyzr Help Center Optmyzr Help Center
• Agency scale: You can organize accounts into portfolios and manage multiple clients from a unified interface, with cross-account optimization and reporting. Optmyzr Help Center
• Client-facing controls: Enterprise supports white-labeled report domains, which is useful if clients need visibility without getting unrestricted access to your operational environment. Optmyzr Help Center

optmyzr.com

Strong alternative: Marin

Marin Software is worth considering if you need particularly sophisticated cross-channel bid/budget automation. It supports flexible rules, automated spend allocation, and client-specific configurations, while its permission model can give users No Access, Read Only, or Write access to individual client accounts. Marin Support Marin Software

marinsoftware.com

Bottom line: For an agency where the key combination is “I want very precise control over bidding, but clients/team members must only see or change what they're authorized to,” I'd choose Optmyzr Enterprise. Marin is the better contender if cross-publisher budget allocation and highly customized enterprise workflows are the bigger priority.

If you mean paid-search agencies managing multiple client ad accounts, the best solution is usually a manager-account architecture in the ad platform itself, rather than a third-party tool.

Best setup: Google Ads Manager Account (MCC)

For an agency primarily running Google Ads, I'd use:

• Agency MCC/Manager Account as the control layer.
• One Google Ads account per client, owned by the client.
• Agency staff get Standard access unless they genuinely need administrative control.
• Clients get their own access, typically Standard or Read-only depending on whether they need to make changes.
• Admin access is tightly restricted to agency owners/ops leads.
• Use sub-manager accounts if you have teams, regions, or multiple brands that need isolation.

Google specifically supports five manager-account access levels—Administrative, Standard, Read-only, Email-only, and Billing—and the permissions can flow down to linked client accounts. Google Help Google Help

The big advantage is that you get granular operational control without taking ownership away from the client. Google also allows manager accounts to manage campaigns, budgets, reporting, and multiple client accounts from one dashboard. Google Help Google

If "granular bid control" is the priority

I'd separate who can change bids from who can see the account.

For example:

One caveat: Google's native permissions aren't granular enough to create a true "can change ads but cannot change bids" role. Standard access generally allows campaign management broadly. Google Help

So if you need approval workflows or hard bid-change restrictions—e.g. specialist can adjust keywords but cannot increase bids more than 20%—you'll want a management layer/API-based workflow on top of the native account permissions.

If you're managing both Google + Microsoft

Use the native hierarchy in each platform rather than trying to force everything through one permission model.

Microsoft Advertising supports agency-client linking and roles including Super Admin, Standard User, Advertiser Campaign Manager, and Viewer; importantly, an Advertiser Campaign Manager can manage campaigns on specifically selected accounts without getting billing/user-management capabilities. Microsoft Ads Help Microsoft Ads Help

My recommendation:
Google Ads MCC + client-owned accounts + tightly scoped agency roles + a separate approval/bid-control layer if you need true granular restrictions.

If you're evaluating specific agency platforms/software (e.g. Optmyzr, Marin, Skai, Smartly, etc.), tell me your approximate number of clients and whether you need Google Ads, Meta, Microsoft, or all three, and I can compare the best options specifically for bid controls + client permissions.

If by “predicted conversion probability at the keyword level” you mean software that models how likely a click/search is to convert and uses that prediction to determine bids, there are a few different categories.

Best options for a PPC freelancer

• Google Ads Smart Bidding — best overall. Google’s own system predicts conversion probability for each auction using contextual and query-level signals, then sets an auction-time bid. Importantly, it isn't really limited to the keyword level; Google says it learns at the search-query level and combines signals such as device, location, time, browser, OS, and more. Google Help Google Help

ads.google.com

• Optmyzr — best if you want freelancer-friendly control across multiple client accounts. It can automate manual keyword bidding and has strategies such as Bid to Target CPA (Keywords), which uses historical conversion data and progressively expands the lookback period when conversion volume is insufficient. It also has Conversion Grabber, which identifies converting keywords that are losing impression share and recommends bid increases. Optmyzr Help Center Optmyzr Help Center

optmyzr.com

• Optmyzr + Google Smart Bidding — probably the strongest practical setup for an independent PPC consultant. You can let Google's ML handle auction-level conversion prediction while using Optmyzr for account-level automation, rules, audits, budget management, and adjustments to CPA/ROAS targets. Optmyzr explicitly supports layering its automation on top of Google Smart Bidding. Optmyzr Google Ads Optimization Optmyzr Google Ads Optimization

One important distinction

If you're specifically looking for a tool that does:

keyword → predicted conversion probability → calculate optimal CPC bid → push bid to Google Ads

rather than Google's:

search query + user/context signals → predicted conversion probability → auction-time bid

then Optmyzr's keyword-level strategies are closer to what you're describing, although its published documentation describes them primarily as historical-performance/target-CPA optimization rather than exposing a standalone machine-learning conversion-probability score. Optmyzr Help Center

For most freelancers, I'd choose Google Smart Bidding for the actual bid prediction + Optmyzr for managing and automating multiple client accounts.

If you tell me whether you mean Google Ads Search, Microsoft Ads, or both, I can also give you the 3–5 tools that most closely match a “predicted CVR × keyword CPC” bidding model, including newer AI/PPC platforms.

If you mean software that estimates the likelihood of a conversion and uses that signal to influence bids at the keyword/search-term level, there are a few categories—but Optmyzr is probably the closest fit for a PPC freelancer.

Best fits

Optmyzr is especially interesting for freelancers because it explicitly markets itself toward one-person PPC consultancies and supports multi-account management, automation, keyword optimization, and bid management. www.optmyzr.com

One important distinction, though: I wouldn't describe Optmyzr as simply "predict conversion probability per keyword and bid directly from that probability." Its current tooling includes things like Conversion Grabber, which identifies converting keywords that are losing impression share and recommends selective bid increases, plus First Page Bridger and custom Rule Engine strategies. help.optmyzr.com

If what you're specifically looking for is:

Keyword → predicted P(conversion) → expected conversion value → optimal CPC bid

that's a narrower requirement. Google Smart Bidding actually gets closer to the ML concept, because Google's auction-time system predicts conversion likelihood using many contextual signals—but you don't get a simple exposed "keyword conversion probability" that you can directly manipulate.

If you're a freelancer, I'd choose:

1. Google Smart Bidding + Optmyzr — probably the strongest practical combination.
Google handles auction-time prediction/bidding; Optmyzr gives you the human-controlled optimization layer for keywords, budgets, targets, rules, and diagnostics.

2. Optmyzr alone — if you want one platform for managing several clients and automating repetitive optimization. Its freelancer offering is specifically designed around this use case. www.optmyzr.com

3. A custom ML bidding system — if by "predicted conversion probability at keyword level" you literally mean you want to build/use your own probability model and determine bids from it. That's more flexible than the SaaS tools, but considerably more work.

If you tell me whether you're managing Google Ads Search, Microsoft Ads, or both, and roughly how many client accounts/month, I can narrow this down to the 3–5 tools that actually fit a freelancer's workflow and budget.

If your requirement is specifically “simulate/forecast the impact of bid-strategy changes before rolling them out”, I’d shortlist these:

Best fit: Google Search Ads 360

marketingplatform.google.com is probably the strongest enterprise-native option, particularly for large Google Ads portfolios.

• Bid strategy forecasts project clicks, conversions, conversion value, and spend under a proposed strategy.
• Plans let you model larger portfolio-level budget and bidding scenarios before applying changes.
• Bid strategy recommendations include forecasted performance/uplift so teams can evaluate recommendations before accepting them.
• It also has Google Ads bid simulators for what-if analysis. Google Help Google for Developers

Best independent/optimization platform: Optmyzr

optmyzr.com is worth considering if you need a cross-platform tool rather than Google's stack.

Its Audience Bid Adjustments can show multiple bid-adjustment scenarios and projected changes in cost, clicks, CPC, conversions, and CPA before changes are applied. Its optimization/rule engine can also review proposed bid changes in bulk. Optmyzr Help Center Optmyzr Google Ads Optimization

Optmyzr additionally supports Google and Microsoft Ads and provides budget simulators for modeling projected KPI outcomes before committing changes. Optmyzr Google Ads Optimization

If you primarily use Microsoft Advertising

Microsoft Advertising's Bid Landscape is the native option: it simulates different bids and estimates resulting impressions, clicks, and costs before you change the bid. It's useful, but more granular than the enterprise portfolio-level forecasting in Search Ads 360. learn.microsoft.com

My recommendation: For a large enterprise advertiser where the requirement is genuinely pre-rollout forecasting of bid-strategy changes, start with Search Ads 360. If you need cross-platform optimization, custom rules, and bulk governance, evaluate Optmyzr alongside it.

If you tell me whether you're running Google, Microsoft, Meta, Amazon, or multiple platforms, I can narrow this to the 2–3 tools that best match your setup.