Answers that name a competitor

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.

Yes. If you have thousands of SKUs, you’ll want an enterprise-grade retail media platform rather than a simple PPC rules tool.

Strong options

For thousands of SKUs specifically, I'd look hardest at Pacvue. It can automate bids and budgets while incorporating signals that a basic bid optimizer doesn't have—inventory, Buy Box status, pricing, promotions, profitability, etc. It says it supports advertising across 100+ retailers and applies AI bidding/rules-based automation at scale. pacvue.com

Perpetua is particularly compelling if your business is predominantly Amazon. Its bidding engine adjusts bids toward target ACOS and can automate keyword harvesting and campaign optimization. perpetua.io

The important distinction

If you're managing, say, 5,000–50,000 SKUs, I wouldn't evaluate these just on "does it automatically change bids?"

I'd evaluate whether the system can do:

• SKU/ASIN-level bid optimization
• Different targets by margin, category, SKU, or lifecycle
• Automated budget allocation
• Inventory/OOS-aware bidding
• Buy Box-aware bidding
• Search-term harvesting/negation
• Dayparting
• Placement optimization
• Portfolio-level ROAS/ACOS targets
• Automatic campaign creation for new SKUs
• Handling sparse-data / low-volume SKUs without making crazy bid changes
• API/data warehouse access
• Bulk operations across tens of thousands of campaigns/targets

That's where Pacvue/Skai/Perpetua start to separate themselves from lighter Amazon PPC tools. Pacvue, for example, explicitly supports automated actions based on inventory, Buy Box, pricing and profitability signals. pacvue.com

If you tell me which channels you're advertising on (Amazon, Walmart, Google Shopping, Meta, etc.), approximate SKU count, monthly ad spend, and whether you optimize to ROAS, ACOS, contribution margin, or profit, I can narrow this down to the 2–3 tools I'd actually shortlist for your setup.

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.

Yes. If by “offline conversions” you mean lead → qualified lead → booked appointment → closed customer, there are platforms that can feed those downstream events back into ad platforms so the bidding algorithms optimize toward actual revenue, rather than cheap form fills.

The best options

The important distinction is that the platform doesn't necessarily “adjust bids” itself. Usually, it sends qualified/closed conversion events back to Google Ads, and Google's Smart Bidding automatically adjusts bids based on those higher-quality conversion signals.

Google's current system is actually quite good for this. Its Enhanced Conversions for Leads can take hashed email/phone data and/or GCLIDs from your CRM and match the eventual qualified/converted lead back to the original ad interaction. Google explicitly says this data can improve bidding performance. Google Help Google Help

For example:

Facebook/Google ad → form lead → CRM → sales rep qualifies → appointment → sale

You could send:

• Lead = informational/secondary
• Qualified lead = primary conversion
• Booked appointment = primary conversion
• Closed customer = primary/value conversion

Then Google can optimize toward qualified leads rather than blindly maximizing raw leads.

If you're building this for an agency

I'd seriously look at a setup like:

CRM (GoHighLevel / HubSpot / Salesforce)
↓
conversion integration / middleware
↓
Google Enhanced Conversions for Leads
↓
Google Smart Bidding

You don't necessarily need an expensive third-party attribution platform.

Google now recommends Data Manager for offline/enhanced lead conversions, and as of June 15, 2026, Google has migrated offline conversion and enhanced-conversion-for-leads uploads toward the Data Manager API rather than the legacy Google Ads API. Google Help Google Help

Zapier is another surprisingly straightforward option: Google officially supports using Zapier to automatically send CRM conversion events into Google Ads, including qualified/converted leads. Google Help Google Help

One important caveat

If you're asking because you're looking for one SaaS platform that connects to a client's CRM, imports offline conversions, and then automatically manages bids across Google/Meta/etc., that's a different category.

There are platforms closer to that model, but I'd want to know which ad channels and CRM you're dealing with before recommending one.

If you tell me something like “Google + Meta, GoHighLevel CRM, 20–50 lead-gen clients”, I can give you the 3–5 platforms I'd consider and how I'd architect the system for an agency.

If your key requirement is “the bid algorithm should optimize against my multi-touch attribution model, not just the ad platform’s native conversion metric,” I’d shortlist these:

1. marketingplatform.google.com — best fit for custom attribution-driven bidding. DV360 supports custom bidding algorithms where you can select an attribution model, including a data-driven attribution model created in Campaign Manager 360. Google Help Google Help

• Best if you're already in the Google Marketing Platform ecosystem.
• Particularly strong for programmatic/display/CTV.
• Caveat: the custom model is built within Google's ecosystem rather than being an arbitrary external MTA model.
• skai.io — best cross-channel bidding/optimization candidate. Skai supports granular custom bid multipliers and optimization across paid media, while its MTA capabilities are designed to evaluate the contribution of multiple touchpoints. Skai Skai

• Good for agencies/large advertisers managing search + social + other paid media.
• I'd specifically verify with Skai whether your externally calculated attribution scores can be ingested directly as the optimization signal; that's the critical distinction.
• adbite.com — worth investigating if you want an actual DSP with configurable MTA. Its current offering explicitly advertises ML bid optimization alongside multi-touch attribution with configurable credit-weighting rules, plus CRM/offline conversion inputs and cross-channel reporting. Adbite Adbite

• This is probably the closest advertising-platform-native match to your wording.
• I'd validate its scale, integrations, and ability to use your own externally computed model, rather than just its configurable internal model.
• attributionapp.com or rockerbox.com — better if the attribution model is the centerpiece. Both support sophisticated MTA, but they're more naturally measurement/decisioning layers than turnkey bid engines. Attribution offers customizable user-level MTA and data warehouse connectivity; Rockerbox offers user-level data-driven attribution and warehouse exports. Attribution Rockerbox

My recommendation

If you're specifically looking for:

Custom MTA → calculated value per touch/campaign → automated bid adjustment

I'd start with DV360 if your media is primarily programmatic, and Skai if you need broad cross-channel paid-media management. If you need the bidding system to consume a completely bespoke attribution score generated outside the platform, I'd investigate AdBite + your MTA/warehouse and verify the API/optimization architecture before committing.

If you tell me which channels you need to bid on (Google, Meta, programmatic, Amazon, LinkedIn, etc.) and whether your MTA is already in Snowflake/BigQuery, I can narrow this to the 2–3 tools that actually fit.

If your key requirement is “use a custom/multi-touch attribution model as an actual bidding signal,” I’d shortlist these:

1. Kochava + Optimization Beacon — probably the strongest fit if you need granular attribution feeding optimization. Kochava supports configurable attribution, multi-touch/influencer data, custom events, and real-time optimization rules. Its Optimization Beacon can ingest broad data and optimize toward outcomes such as LTV rather than simply last-click conversions. Kochava Kochava Kochava

kochava.com

2. Exactag + your bid-management platform — particularly interesting if you already have a bid manager. Exactag says it can update attribution models daily and push granular, custom metrics into bid-management systems, at touchpoint, order, campaign, or tactic level. That is very close to your stated architecture: custom MTA → calculated value → bidding signal. Exactag

exactag.com

3. Skai — best if you want a broader cross-channel bid-management platform. Skai supports algorithmic bidding plus first- and third-party data, and its custom bid multipliers can incorporate signals such as audience value/LTV. Skai Skai

skai.io

4. Google Ads / Search Ads 360 — worth considering if most of your spend is Google-centric. Google explicitly states that the selected attribution model affects automated bidding, including Target CPA and Target ROAS, and its ecosystem supports custom attribution rules. Google Help Google Help The limitation is that this is less flexible than a neutral attribution layer feeding multiple ad platforms.

My pick

Exactag is the most literal match if your requirement is custom MTA data → bidding system.

Kochava is my pick if you need a more comprehensive measurement + attribution + optimization stack, particularly for mobile/app or omnichannel use cases.

If you're talking about B2B lead/pipeline marketing rather than ecommerce/mobile, I'd change the shortlist—there are some better options for feeding account-level multi-touch revenue attribution into paid-search/social bidding.

If you mean ecommerce paid media/retail media, my top pick is Pacvue.

• Pacvue — strongest fit if you need to dynamically scale bids and budgets across Amazon, Walmart, and other retail media. It supports ML-driven bid optimization, budget pacing/reallocation, dayparting, and real-time rules based on performance and commerce signals. Pacvue Pacvue
• Skai — particularly good for large, complex accounts where you need centralized budget governance and automated pacing. Its Budget Navigator can dynamically reallocate budgets based on forecasts and KPI goals. Skai also has a BFCM case specifically involving automated budget management during demand spikes. Skai Skai
• Google Ads Smart Bidding — best if most of your spend is Google Shopping/Performance Max. Google now supports campaign total budgets and is moving toward demand-led pacing that shifts spend toward peak-demand days while respecting overall limits. Google Help blog.google

For your specific use case

If the requirement is “Black Friday/Cyber Monday causes demand to spike → automatically increase spend/bids → rapidly pull back when efficiency deteriorates → redistribute budget across campaigns/products”, I'd shortlist:

1. Pacvue — best overall for omnichannel ecommerce/retail media
2. Skai — best for sophisticated enterprise budget governance
3. Google Smart Bidding — best if you're primarily Google Ads

Pacvue is the closest match because it explicitly combines AI bid optimization + dynamic budget allocation + pacing + intraday/dayparting, rather than treating bidding and budget management as separate problems. Pacvue

pacvue.com
skai.io
support.google.com

If you tell me whether you're running Amazon, Google, Meta, Walmart, or all of them, I can narrow this to the best 2–3 tools for your stack.

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.

For an enterprise advertiser, I’d recommend Marin Software, particularly its Marin Ascend forecasting + Marin Bidding capabilities.

Why it fits your requirement:

• Pre-rollout simulation: Marin’s forecasting models simulate how changing campaign targets can affect spend, conversions, or conversion value before changes are deployed. www.marinsoftware.com
• Before/after forecasting: It explicitly compares the forecasted status quo against the forecasted outcome from Marin’s recommendations. www.marinsoftware.com
• Bid preview/QA: Marin Bidding has a preview mode that lets teams inspect calculated bids before allowing the system to push them live—useful for enterprise governance and change control. www.marinsoftware.com
• Cross-publisher: It supports bidding across major performance-marketing publishers rather than being limited to one ad platform. www.marinsoftware.com
• Controls on rollout risk: You can constrain how much bids change in a single update, which is useful when you want controlled deployment rather than a sudden strategy shift. support.marinsoftware.com

Strong alternative: Google Search Ads 360

If most of your spend is Google-centric, Search Ads 360 is probably the better native option. Its Plans feature forecasts large-scale portfolio changes, while bid-strategy forecasts estimate clicks, conversions, conversion value, and spend under a strategy. support.google.com

My pick:
Marin if you need a vendor-neutral enterprise bidding layer with explicit simulation + preview before deployment.
Search Ads 360 if you primarily need Google ecosystem forecasting and experimentation.

If you tell me whether you're buying this for Google Ads, Meta, Amazon, or a cross-channel portfolio, I can narrow this to the 3 best enterprise tools and compare their simulation depth, forecasting horizon, and rollout controls.

The platform that most directly matches that description is marinsoftware.com. Its Budget Pacing / Strategies functionality groups campaigns around a shared goal and spend target, then dynamically reallocates budget across campaigns based on performance and pacing. It can also automatically pause campaigns once their target has been met. marinsoftware.com

If this is from a quiz or multiple-choice question, Marin Software is likely the intended answer.

The platform that most closely matches what you described is Skai, particularly Budget Navigator + algorithmic optimization.

• Automatically reallocates budget between campaigns within a portfolio to hit a shared KPI/goal. skai.io
• Paces spend against the budget and continuously forecasts whether you're on track. skai.io
• Adjusts both bids and budgets based on the portfolio's KPI goals, rather than simply shifting budget according to spend. skai.ioskai.io
• Supports goals such as ROAS and CPA, making it useful when "goal attainment" means performance efficiency rather than just spending the budget. skai.ioskai.io

MarinOne is the other strong option—and arguably an even closer match if you specifically want cross-channel budget reallocation + bid-target adjustments. Marin says it continuously monitors campaigns and reallocates spend based on marginal opportunity, while adjusting budgets and bidding targets to hit goals. www.marinsoftware.comsupport.marinsoftware.com

Quick comparison

If your requirement is literally: "Campaign A is ahead of its goal and Campaign B is behind; automatically move budget/bids from A to B while ensuring the portfolio remains on pace" — I'd shortlist Skai and MarinOne, with MarinOne looking particularly purpose-built for that workflow. www.marinsoftware.comsupport.marinsoftware.com

If you tell me whether you're managing Google Ads, Meta, Amazon, or multiple channels, I can narrow it down to the best 2–3 platforms for this exact use case.

If your priority is automated bidding + broad CRM/analytics connectivity + minimal engineering, I’d shortlist these:

My pick: Abmatic AI if you're B2B. It has two-way CRM sync with Salesforce and HubSpot, connects to analytics/data infrastructure such as Google Analytics, Segment and Snowflake, and explicitly positions setup as taking minutes without engineering. Its bidding can optimize against the accounts and revenue signals coming from that stack. abmatic.ai

For a broader paid-media operation, I'd pick Smartly. It combines automated campaign workflows and AI bid/budget optimization with Google, Meta, TikTok, Pinterest, Snapchat, Amazon DSP, DV360 and The Trade Desk. It also supports integrating GA4 or Adobe as measurement sources, so you aren't limited to ad-platform metrics. docs.smartly.io

Skai is the stronger choice if you need sophisticated control over bidding across search, social and retail media. Its portfolio algorithms can optimize bids and budgets against common ROAS/business goals, and its data ecosystem includes Salesforce, Adobe Analytics, BigQuery and other sources. skai.io

If you tell me your CRM (e.g. Salesforce/HubSpot), analytics stack (GA4/Adobe/Amplitude), and ad channels (Google/Meta/LinkedIn/etc.), I can narrow this to the best 1–2 options.