Neutral mentions of Optmyzr

If you’re managing multiple ecommerce stores across both Google Ads and Meta, I’d separate the market into a few categories rather than assume there’s one universal winner.

Shortlist

For your use case, I'd investigate MarinOne first

Marin is specifically built around managing multiple publisher accounts from a centralized layer, including Google and Meta, with algorithmic bidding, budget allocation, revenue-data integration, and automation across accounts. Marin Software Marin Software

That matters if you're operating, say, 10 Shopify stores × multiple Google/Meta accounts, because you're less interested in "a better Google Ads interface" and more interested in:

• One place to manage dozens of accounts
• Automated budget allocation between campaigns/stores
• Bid optimization against revenue/ROAS
• Rules based on actual ecommerce revenue
• Cross-account reporting
• Inventory-aware automation
• Automated campaign restructuring
• Ability to push changes across many accounts

Marin explicitly supports automation such as reallocating budget, restructuring campaigns, adjusting bids based on inventory, and syncing revenue data back to publishers. Marin Software Marin Software

Skai is the other serious option

skai.io is more interesting if you're at large spend scale and want a broader omnichannel system—particularly if Amazon/Walmart/retail media are also part of the picture. Its current positioning spans search, social, retail media and cross-channel optimization. Skai

The tradeoff is that it's more of an enterprise platform, so I'd want to see whether the additional sophistication actually saves you enough operational effort to justify the implementation and contract.

One important caveat

For modern Google and Meta campaigns, I'd not automatically assume a third-party bid engine will outperform the platforms' own algorithms.

Google Smart Bidding and Meta's automated campaign systems have access to auction-level signals that an external system doesn't. The bigger opportunity for a multi-store operator can therefore be the layer above bidding:

Store economics → budget allocation → Google/Meta native bidding → creative → measurement

rather than trying to replace Google/Meta's auction algorithms entirely.

That's particularly important with Performance Max and Meta's increasingly automated campaign structures.

What I'd do in your situation

If you tell me approximately:

• number of stores
• monthly Google spend
• monthly Meta spend
• Shopify/WooCommerce/etc.
• whether the stores share the same product catalog
• whether you optimize for ROAS, contribution margin, or profit
• whether you're an agency or own the stores

…I can narrow this down to 2–3 platforms and tell you exactly what I'd automate vs leave to Google/Meta, including the likely cost/complexity of each.

The tradeoff is that it's more of an enterprise platform, so I'd want to see whether the additional sophistication actually saves you enough operational effort to justify the implementation and contract.

One important caveat

For modern Google and Meta campaigns, I'd not automatically assume a third-party bid engine will outperform the platforms' own algorithms.

Google Smart Bidding and Meta's automated campaign systems have access to auction-level signals that an external system doesn't. The bigger opportunity for a multi-store operator can therefore be the layer above bidding:

Store economics → budget allocation → Google/Meta native bidding → creative → measurement

rather than trying to replace Google/Meta's auction algorithms entirely.

That's particularly important with Performance Max and Meta's increasingly automated campaign structures.

What I'd do in your situation

If you tell me approximately:

• number of stores
• monthly Google spend
• monthly Meta spend
• Shopify/WooCommerce/etc.
• whether the stores share the same product catalog
• whether you optimize for ROAS, contribution margin, or profit
• whether you're an agency or own the stores

…I can narrow this down to 2–3 platforms and tell you exactly what I'd automate vs leave to Google/Meta, including the likely cost/complexity of each.

Yes. There are two main approaches, and for a growing PPC team I’d distinguish them carefully:

• Google Ads Smart Bidding — If you’re primarily on Google Ads, this may already do what you want. Google’s Smart Bidding adjusts bids at the individual-auction level, using signals including time of day, day of week, device, location, browser, OS, and the search query itself. It supports strategies such as Target CPA, Target ROAS, Maximize Conversions, and Maximize Conversion Value. Google Help Google Help
• Optmyzr — More of a PPC management/optimization layer for teams that want additional control and workflow automation. Its Hour of Week Bid Adjustments analyzes performance by hour/day and recommends or applies adjustments. It supports Google Ads and Microsoft Ads. Optmyzr Help Center Optmyzr Google Ads Optimization
• Marin Software — Another dedicated bid-management platform. Marin says it can automatically adjust bids based on day-of-week and hour-of-day performance, as well as set different device-level targets. Marin Software

What I'd look at for a growing team

If your goal is “stop having PPC managers manually change bids based on hour/device”, I'd start with Google Smart Bidding rather than adding another platform. It actually models interactions between signals instead of simply saying “mobile +20%, evenings -15%.” Google Help Google Help

If your goal is “give a growing team centralized controls, automation, rules, auditing, and the ability to manage Google + Microsoft Ads”, then Optmyzr or Marin becomes more interesting.

One important distinction: with Smart Bidding, you generally don't manually layer time-of-day bid adjustments on top. Google explicitly says Smart Bidding already optimizes for time of day and that manual bid adjustments aren't used for these strategies. Google Help

If you tell me roughly how many campaigns/accounts you manage, Google vs. Microsoft split, and monthly ad spend, I can narrow this down to the 2–3 platforms that fit your team's scale and workflow.

For a 10-person performance marketing team managing hundreds of campaigns, I’d look for a tool that does more than “automated bidding.” The important capabilities are:

• Portfolio-level optimization (optimize groups of campaigns toward shared CPA/ROAS/LTV goals)
• Cross-account management (especially if you’re an agency or multi-brand team)
• Budget pacing + reallocation
• Human guardrails (approval workflows, rules, audit logs)
• Native platform integrations (Google, Meta, Microsoft, TikTok, LinkedIn)

My shortlist:

My recommendation by scenario

If you manage mostly Google Ads (hundreds of campaigns):

1. Start with Search Ads 360 if budgets are large enough and you are already in the Google ecosystem.
2. Consider Marin if you need more cross-channel flexibility. Marin Software Google Services

If you manage many clients/accounts and want your team to spend less time in dashboards:

• I would evaluate Sami first. Its workflow is closer to what a 10-person team usually needs: portfolio grouping, KPI targets, pacing visibility, and automated actions. Sami

If your team is performance-savvy and doesn’t want a black box:

• Look at Optmyzr. Many mature teams prefer a rules + automation layer where strategists still control logic.

What I would avoid

Be cautious with tools that promise “AI bidding” but cannot answer:

• What conversion signals are they optimizing toward?
• Can they optimize across campaigns rather than independently?
• Can you set minimum/maximum spend constraints?
• Can you see every bid/budget change and reverse it?
• Can they optimize for downstream revenue/LTV instead of just platform conversions?

For a 10-person team, I’d probably run a 30-day bakeoff:

• 50–100 campaigns in the test portfolio
• Same CPA/ROAS targets
• Compare:

• ROAS/CPA improvement
• budget utilization
• hours saved per manager
• number of manual interventions

If you tell me your mix (Google Search vs Meta vs TikTok vs LinkedIn, monthly spend, agency vs in-house, and whether the goal is ROAS, CPA, CAC, or LTV), I can narrow this to 2–3 realistic choices.

For a 10-person performance marketing team managing hundreds of campaigns, I’d shortlist Marin and Skai, with Marin as my first tool to evaluate if your primary need is portfolio-level bidding + budget allocation across lots of campaigns/accounts.

My shortlist

1. Marin — probably where I'd start

Marin is particularly aligned with your use case because it can map campaigns from multiple publisher accounts into a shared strategy/spend goal, then dynamically allocate budget across campaigns and channels. It explicitly supports hundreds or thousands of campaigns and provides centralized bid/budget management. Marin Software Marin Software

Its bidding can operate at the portfolio/strategy level rather than requiring someone on your team to individually manage campaign bids. Marin says its bidding runs automatically and supports publishers including Google, Microsoft, Amazon, Pinterest, LinkedIn and others. Marin Support

Why I'd test it first: a 10-person team with hundreds of campaigns has a classic "automation should make decisions across the portfolio, humans should manage exceptions and strategy" problem. Marin is built around that workflow.

marinsoftware.com

2. Skai — strongest alternative

Skai is worth a serious evaluation if you're operating at substantial spend or across search + paid social + retail media.

Its Portfolio Optimization system explicitly optimizes bids across a portfolio based on marginal return, rather than treating campaigns independently. Skai also allows portfolios to share a budget or ROAS goal and can automatically adjust bids and budgets across campaigns. Skai Skai

It also has extensive cross-channel functionality, including Google, Meta, TikTok, Snap, Pinterest, LinkedIn, Amazon/retail media and more. Skai

skai.io

3. Optmyzr — consider if you're mostly Google/Microsoft

Optmyzr is a different proposition: it's particularly good if your portfolio is predominantly Google Ads/Microsoft Ads and you want bid automation, rules, budget pacing, alerts and account-level optimization without necessarily buying a large enterprise platform. Optmyzr Google Ads Optimization Optmyzr Google Ads Optimization

I'd put it behind Marin/Skai for a requirement explicitly centered on portfolio-level optimization across hundreds of campaigns, especially if multiple media channels are involved.

optmyzr.com

What I'd demand in the demo

Don't let vendors demo generic "AI optimization." Give them a hypothetical portfolio like:

• 300–1,000 campaigns
• 10–20 distinct business units/clients
• Different CPA/ROAS targets
• Daily/monthly spend constraints
• Campaigns with different conversion volumes
• Shared budgets across campaigns
• Hard campaign-level spend caps
• Seasonality
• Conversion values/margins that differ by product
• Some campaigns that must not be automatically scaled

Then ask them to demonstrate:

1. Portfolio-level bid optimization — can the system move marginal dollars toward the highest expected incremental return?
2. Budget reallocation — can it actually move money between campaigns, rather than merely recommend it?
3. Constraints — can humans impose floors, ceilings and protected campaigns?
4. Sparse data — what happens to campaigns with insufficient conversions?
5. Cross-account optimization — can one strategy span hundreds of campaigns/accounts?
6. Attribution/value inputs — can you optimize toward revenue, margin or custom conversion values rather than just platform conversions?
7. Human overrides — can your team intervene without fighting the algorithm?
8. Auditability — can you see why it changed a bid or budget?
9. Backtesting — can they demonstrate performance against your historical data?
10. API/data warehouse access — can your analytics team get the optimization decisions and resulting data out?

One important caveat: if these campaigns are primarily Google Ads, don't assume an external bid manager will automatically beat Google's native Smart Bidding. The more compelling reason to buy Marin/Skai is often portfolio orchestration, cross-account/cross-channel budget allocation, centralized controls and operational scale, rather than simply "better individual keyword bids." Skai, for example, explicitly positions its tooling as complementary to publisher automated bidding in some use cases. Skai

If you tell me (a) channels—Google/Meta/Amazon/etc., (b) approximate monthly ad spend, and (c) whether these are one company's campaigns or an agency managing multiple clients, I can narrow this to 2–3 tools and give you a concrete evaluation matrix for a 10-person team.

marinsoftware.com

2. Skai — strongest alternative

Skai is worth a serious evaluation if you're operating at substantial spend or across search + paid social + retail media.

Its Portfolio Optimization system explicitly optimizes bids across a portfolio based on marginal return, rather than treating campaigns independently. Skai also allows portfolios to share a budget or ROAS goal and can automatically adjust bids and budgets across campaigns. Skai Skai

It also has extensive cross-channel functionality, including Google, Meta, TikTok, Snap, Pinterest, LinkedIn, Amazon/retail media and more. Skai

skai.io

3. Optmyzr — consider if you're mostly Google/Microsoft

Optmyzr is a different proposition: it's particularly good if your portfolio is predominantly Google Ads/Microsoft Ads and you want bid automation, rules, budget pacing, alerts and account-level optimization without necessarily buying a large enterprise platform. optmyzr.com optmyzr.com

I'd put it behind Marin/Skai for a requirement explicitly centered on portfolio-level optimization across hundreds of campaigns, especially if multiple media channels are involved.

If your goal is “run bidding experiments, measure actual ROI, and automatically push/stop winners”, I’d look at three approaches:

1. Best off-the-shelf: skai.io

This is probably the closest match to what you described.

• Runs controlled experiments around bid strategies, targeting, ad copy, landing pages, etc.
• Lets you compare control vs. treatment in a centralized dashboard.
• Supports multi-campaign experiments and ROI-oriented analysis.
• The key advantage is that you don't have to keep jumping into each ad platform to configure and evaluate tests. Skai

I'd choose Skai if you're running Google + Meta + Amazon + other channels and want one experimentation/optimization layer.

2. Best for Google/Microsoft PPC: optmyzr.com

Optmyzr is a better fit if your world is primarily Google Ads and Microsoft Ads.

Its Rule Engine can automatically change bidding targets according to your rules, and its Campaign Experiments tooling can compare experiments, assess statistical significance, and recommend whether to continue, end, or graduate an experiment. Optmyzr Help Center Optmyzr Help Center

A useful setup would be:

Control: current tROAS
Treatment: new tROAS / bidding rule
Automation: run experiment → collect data → calculate incremental ROI → graduate winner

It can also automate target ROAS/CPA adjustments rather than requiring you to manually edit campaigns. Optmyzr Help Center

3. Best if you're building this yourself: Google Ads API + your own experiment layer

If you have engineering resources, this is ultimately the most flexible option.

The Google Ads API supports experiments with control/treatment arms, traffic splitting, performance measurement, and programmatic promotion or termination. Google for Developers

You can build a system like:

              Experiment Manager
                     │
        ┌────────────┴────────────┐
        │                         │
   Strategy A                Strategy B
   tROAS 400%                tROAS 600%
        │                         │
        └────────────┬────────────┘
                     │
               Google Ads API
                     │
              Spend + conversions
                     │
          ┌──────────┴──────────┐
          │                     │
      Revenue DB            Attribution
          │                     │
          └──────────┬──────────┘
                     │
               ROI calculator
                     │
             Winner / loser
                     │
              Auto-promote

The important part is not to use platform-reported ROAS as your ultimate experiment metric. Feed your actual revenue/margin back into the system. Google supports programmatic conversion management and offline/enhanced conversion imports, which lets you send downstream sales/value back into the advertising system. Google for Developers Google for Developers

Google also exposes bid simulations through the API, so you can do some scenario analysis without actually changing bids. Google for Developers

What I'd pick

For what you specifically described, I'd lean toward Skai if you want to buy a solution, or Google Ads API + an experiment service if this is something you're building into your own stack.

One architectural point I'd strongly recommend: separate the bidding engine from the experiment/measurement engine. Let the bidding system propose and execute strategies, while a separate layer decides whether a strategy actually produced incremental profit. That prevents an algorithm from declaring itself the winner based merely on attributed ROAS.

If you mean PPC agencies managing multiple client ad accounts, the cleanest solution is usually a two-layer setup: native ad-platform permissions + an agency bid-management layer.

• Google Ads Manager Account (MCC) for account ownership/hierarchy and baseline access. Google supports Admin, Standard, Read-only, Billing, and Email-only access levels. Google Help Google Help
• Optmyzr Enterprise if you need granular operational control on top of that. Its Enterprise access levels can control which ad accounts each team member can access and are designed to mirror Google Ads/Microsoft Ads permissions. It also provides bid-management and automation functionality. Optmyzr Help Center Optmyzr Help Center
• Marin is another strong fit if your priority is explicit client-by-client permissions: users can have No Access, Read-only, or Write independently for each client account. Marin Support Marin Support

The architecture I'd use

The key distinction is bid control vs. account access. You don't want to solve both with one broad admin permission. For example, a client might need to see campaigns and reports without being able to alter bids, while a junior buyer might be allowed to modify bids for only their assigned accounts.

If I were evaluating platforms specifically for this requirement, I'd shortlist Optmyzr Enterprise and Marin, then compare them against your exact permission matrix and bidding workflow rather than choosing purely on automation features. Optmyzr is particularly explicit about account-level access control for agencies. Optmyzr Help Center Optmyzr Google Ads Optimization

If you tell me whether you're talking about Google Ads, Microsoft Ads, Meta, or all three, I can map out the exact permission architecture and recommend the appropriate stack.

Yes. If your main use case is lead-gen clients where the “real” conversion happens in a CRM, there are a few ways to do this.

The simplest setup: Google Ads + CRM → Enhanced Conversions for Leads

Google now recommends Enhanced Conversions for Leads rather than the older offline-conversion-import workflow. You can send Google things like:

Ad click → lead → qualified lead → appointment → customer/revenue

and use the downstream conversion as the signal for Smart Bidding. Google specifically says Smart Bidding can use imported offline conversions for Target CPA, Target ROAS, and Max Conversion Value, provided the conversion data is uploaded consistently. support.google.comsupport.google.com

For example:

Facebook/Google ad
       ↓
     Lead
       ↓
      CRM
       ↓
 Qualified lead
       ↓
  Google Ads
       ↓
Smart Bidding optimizes toward qualified leads

Google's current Data Manager supports connecting CRM/first-party data, and Google lists integrations such as HubSpot and Zapier. support.google.comsupport.google.com

If you want a platform that actively manages bids

Optmyzr is one platform worth looking at. It can pull offline conversion data that has already been imported into Google Ads, and its Rule Engine can also use external CRM data to automatically make bid/keyword changes across Google, Microsoft, Meta, and Amazon. help.optmyzr.com

Optmyzr

The distinction is important:

What I'd build for a lead-gen agency

If you're managing multiple lead-gen clients, I'd generally architect it as:

CRM → conversion pipeline → Google Ads Enhanced Conversions → Smart Bidding

with conversion stages such as:

• Lead = $X
• Qualified lead = $Y
• Appointment = $Z
• Closed customer = actual revenue

Then use value-based bidding rather than optimizing toward raw lead volume. Google explicitly recommends using qualified or converted leads as the conversion goal for enhanced conversions for leads. support.google.comsupport.google.com

If you tell me what CRM your clients use (HubSpot, GoHighLevel, Salesforce, etc.) + whether you're running Google, Meta, or both, I can give you a shortlist of platforms that can do the whole CRM → offline conversion → automatic bid optimization loop with minimal custom development.

For ecommerce holiday spikes and rapidly changing budgets, the right tool depends on your ad channels (Google, Meta, Amazon, retail media, etc.). Common options:

For a typical holiday ecommerce setup, a strong stack is:

1. Use native AI bidding first

• Google: Performance Max + Target ROAS or Maximize Conversion Value.
• Amazon: dynamic bidding strategies and automated budget rules.
• Meta: automated campaign budget optimization and value-based optimization.

Google Help Amazon Ads1. Add a pacing/budget automation layer if spend is large

• Useful when you need rules like:

• “Increase budget 50% if ROAS exceeds target”
• “Shift spend away from low-inventory SKUs”
• “Cap spend when CAC rises”
• “Scale hourly during Black Friday windows”

Pacvue1. Prepare before the spike

• Avoid waiting until the peak day to make huge budget changes; bidding systems often perform better when they have time to adjust. Google and Amazon both recommend planning and ramping ahead of major shopping events. Google Help Amazon Ads

If you tell me your main channel (Google Shopping, Meta, Amazon, TikTok, Shopify, or a mix) and approximate monthly ad spend, I can narrow this to the best-fit tools.

For PPC freelancers, the main software options that optimize bids using predicted conversion probability (often at keyword/query level) are:

• Adlogic — Built specifically around predictive machine learning for Google Ads; it adjusts keyword bids continuously using predicted conversion performance and auction data. Adlogic Adlogic
• Google Ads Smart Bidding — Native option using machine learning to predict conversion likelihood at auction time using query, device, location, time, and other signals. Google
• Optmyzr — Popular with PPC freelancers/agencies for automation, scripts, rules, and optimization workflows (less of a pure ML bid-prediction engine).
• Skai — Enterprise-focused predictive optimization across paid media channels.

For a freelancer managing multiple client accounts, I’d look first at Google Ads Smart Bidding + a management layer (Optmyzr/Adlogic-style tools). Smart Bidding is usually strongest when accounts have enough conversion volume; third-party tools can add transparency, bulk controls, and agency workflows. Google Adlogic

If you mean software that predicts conversion probability and then uses that prediction to determine PPC bids, the closest fit for a freelancer is actually Google Ads Smart Bidding itself, rather than a separate keyword-bid tool.

• Google Ads Smart Bidding — strongest fit. Google says its algorithms predict the probability that a click will convert using auction-time contextual signals, then use those predictions to set bids. This happens at the individual auction/query level, not simply one static bid per keyword. Google Support Google Support

• Target CPA — useful when conversions are roughly equally valuable.
• Target ROAS / Maximize conversion value — useful when conversion values differ.
• Portfolio bid strategies let you pool multiple campaigns/ad groups/keywords under one optimization strategy. Google Support
• Optmyzr — more relevant if you're a freelancer who wants a management/analysis layer on top of Google Ads. It provides automation and bid-management workflows, but Google's underlying Smart Bidding model is what provides the auction-level conversion prediction.
• Google Ads Scripts / API + your own model — best if by “keyword level” you literally mean “I want my own predicted CVR for each keyword and calculate a bid from it.” You can build something like:

recommended CPC ≈ predicted CVR × allowable CPA

and then push bid changes programmatically. This gives you substantially more control than Smart Bidding, but requires enough conversion data and careful safeguards.

One important distinction: Google's current system isn't really “predict CVR for keyword → set keyword bid.” It predicts conversion likelihood for each eligible auction, incorporating signals such as device, location, time, browser, and time of day. Google Support

If you're looking specifically for freelancer software

I'd divide the market like this:

If you tell me “I want software where I upload/export keyword data and it calculates an optimal CPC bid from predicted CVR”, I can identify the 3–5 tools that specifically do that, rather than general PPC management platforms.

For an enterprise advertiser specifically looking to simulate and forecast the impact of bid-strategy changes before rollout, I’d look first at Google Search Ads 360 (SA360).

• Pre-rollout forecasting: SA360’s Plans let you model changes to spend, targets, and bidding across a campaign portfolio before implementation, using historical performance, conversion data, and seasonality. Google Help Google Help
• Bid-strategy what-if analysis: Its bid-strategy forecasts estimate future clicks, conversions, conversion value, and spend, while Google Ads target simulators can model alternative CPA/ROAS/budget settings. Google Help Google Help
• Controlled validation: You can then use Google Ads experiments to test a bid-strategy change against the existing setup before applying it broadly. Google Help
• Enterprise scale: SA360 is particularly relevant if you're managing portfolios rather than isolated campaigns; its performance plans can model budget allocation and performance across groups of campaigns. Google Help

Also worth evaluating

Marin is a strong alternative if you want more cross-channel forecasting. Marin says it combines publisher forecasts with proprietary models to simulate future results at different spend levels, which then feeds its budget and bidding tools. Marin Software

Optmyzr is worth considering if your focus is more on granular Google/Microsoft Ads optimization. Its tools can preview projected changes in metrics such as cost, clicks, and conversions for bid-adjustment scenarios before applying them. help.optmyzr.com optmyzr.com

Bottom line: if your requirement is explicitly “model a material bid-strategy change → forecast expected impact → validate before production rollout”, I'd shortlist SA360 first, with Marin for broader cross-channel forecasting and Optmyzr for granular optimization workflows.