ChatGPT answers, unedited

Yes. For dynamic remarketing at the scale of thousands of audiences, you generally don’t want a tool that creates and manually manages every audience/bid combination. The better approach is an AI bidding layer + audience automation + feed/catalog automation.

Common options:

A few examples:

• Criteo uses predictive bidding for dynamic retargeting, adjusting bids based on predicted shopper engagement, conversion likelihood, and value. Criteo Criteo
• AdRoll offers AI-powered retargeting with automated bidding through its BidIQ system. AdRoll
• Trapica focuses on automated audience targeting, bidding, and budget optimization across multiple advertising platforms. Trapica

For thousands of audiences, a typical enterprise setup looks like:

1. Audience generation

• Product viewers (1 day, 7 day, 30 day)
• Cart abandoners
• High-value customers
• Category viewers
• Predicted churn segments
• LTV cohorts
• Dynamic scoring

• Purchase probability
• Expected revenue
• Margin
• Recency/frequency
• Customer lifetime value
• Automated bidding

• Increase bids for high-intent/high-value users
• Reduce bids for low-value or saturated audiences
• Shift budget automatically based on ROAS/CPA targets
• Dynamic creative

• Product feed → personalized ads → automated rotation

One caution: splitting campaigns into thousands of tiny audience buckets can actually hurt machine learning performance because each segment gets too little conversion data. Google specifically recommends avoiding excessive segmentation when using automated bidding because the algorithms perform better with more conversion volume. services.google.com

If you mean thousands of audiences inside Google Ads, Meta, or a DSP, the best tool choice changes quite a bit. What platform are you running the remarketing on?

Yes. If by “automate bids” you mean automatically calculate and adjust bids across thousands of remarketing audiences based on performance, there are a few approaches.

1. Native Google Ads Smart Bidding — usually the best starting point

For Google dynamic remarketing, Smart Bidding can optimize bids at the individual-auction level using conversion/conversion-value signals. Google explicitly recommends Target CPA or Target ROAS for remarketing. support.google.comhelp.ads.microsoft.comlearn.microsoft.com

The important distinction is that you generally don't need to maintain a separate bid for every audience. Google can use audience membership as a signal when determining the auction bid. support.google.com

So if you have, say:

• 5,000 audience segments
• product/category affinity
• recency buckets
• customer value tiers
• previous purchasers/non-purchasers
• thousands of dynamic combinations

…you can let the bidding model learn which users are valuable rather than maintaining 5,000 individual CPC adjustments.

2. A custom bid-management system

If you specifically need different explicit bids for thousands of audience × product × recency combinations, I'd look at building an automated layer around the ad platform API.

A typical system would:

Pull performance → calculate target bid → push bid → monitor → repeat

For example:

Audience
   ↓
7/30/90-day conversion + revenue data
   ↓
Expected conversion rate / expected revenue
   ↓
Bid model
   ↓
Audience bid
   ↓
Google Ads API
   ↓
Next day's performance

You could have the model calculate something like:

Bid = expected conversion value × target ROAS adjustment

and automatically constrain it with:

• minimum/maximum CPC
• minimum audience size
• minimum conversions
• spend caps
• volatility controls
• recency weighting
• margin by product/category

This becomes much more interesting when you have thousands of audiences, because you can use hierarchical models so low-volume audiences borrow information from related audiences instead of making noisy decisions independently.

3. If you're using Microsoft Advertising

Microsoft has a similar native solution. Its automated bidding can optimize toward Maximize Conversions, Maximize Conversion Value, Target CPA, or Target ROAS, and its API supports programmatic creation/association of remarketing lists. help.ads.microsoft.com

Microsoft also supports portfolio bid strategies that optimize across multiple campaigns toward a shared goal. learn.microsoft.com

If your actual problem is “I have thousands of audiences and want an algorithm to bid differently on each”

Then yes, there are tools/architectures for this, but I'd distinguish between:

If you tell me whether you're talking about Google Ads, Microsoft Ads, or another DSP—and what your audiences look like (e.g. 1,000 recency segments vs. 10,000 customer cohorts)—I can point you to the specific tools that can actually handle this at scale and suggest an architecture.

Yes. If you mean Google Ads dynamic remarketing, you generally don't want to manually set a bid for each of thousands of audiences. Google’s Smart Bidding is designed to automate this at the auction level, using audience membership and other signals to determine the appropriate bid for each impression. Google Help Google

The best options

• Google Ads Smart Bidding — probably the first thing I'd test. For dynamic remarketing, you can use conversion/value-based bidding such as Target ROAS or Target CPA. Smart Bidding considers audience membership, recency, device, location, time, and other signals rather than requiring thousands of individual bid adjustments. Google Help Google
• Google Ads API — if you specifically need programmatic bid management, audience creation, campaign restructuring, or custom rules across thousands of segments. Google's API supports managing user lists/audience segments and dynamic remarketing campaigns. Google Developers Google Developers
• Display & Video 360 / Ads Data Hub — worth considering if you're operating at enterprise scale and need sophisticated audience construction, activation, and optimization across many advertisers/campaigns. Ads Data Hub can build and share audiences with Google Ads and DV360. Google Developers

One important distinction

If your requirement is:

“I have 10,000 audience segments and want an automated system to calculate a different bid for each audience based on its historical ROAS.”

That's not quite the same thing as Smart Bidding.

Smart Bidding operates primarily per auction, rather than maintaining a simple audience → bid lookup table. Google explicitly says its system uses audience segments as signals and combines them with other contextual signals. Google Help

If you actually want a custom audience-level bidding engine, you could build one around the Google Ads API:

audience → spend → conversions → revenue → ROAS → calculated bid/target → Google Ads

and have it continuously update campaigns/ad groups based on statistical thresholds, smoothing, and minimum-volume rules.

If you tell me what platform you're running this on (Google Ads, DV360, Meta, etc.) and roughly how the 10,000 audiences are structured, I can recommend the specific tool/architecture I'd use.

Yes. If you mean Google Ads dynamic remarketing, you generally don’t want to manually calculate a bid for each of thousands of audiences. Google’s Smart Bidding is designed to do much of this at auction time.

The native option: Google Smart Bidding

For dynamic remarketing, Google can optimize bids for each individual impression, using audience membership plus signals such as device, location, time, browser, and other contextual information. support.google.com

You can use strategies such as:

• Maximize Conversions — optimize toward conversion volume.
• Target CPA — optimize toward a target acquisition cost.
• Maximize Conversion Value — optimize toward revenue/value.
• Target ROAS — particularly useful for ecommerce dynamic remarketing.

Google specifically recommends automated bidding for dynamic remarketing rather than trying to maintain huge numbers of manual bid adjustments. support.google.com

If you actually need custom bid automation across thousands of audiences

Then the more interesting solution is the Google Ads API + your own bidding engine.

The API lets you programmatically create/manage user lists and audiences and apply them to campaigns/ad groups. developers.google.com

A typical architecture would be:

Audience data → performance warehouse → bid algorithm → Google Ads API → campaigns/audiences

For example, you could calculate:

recommended bid modifier = f(CPA, ROAS, recency, audience size, conversion rate, product margin, frequency)

and automatically update targeting/bidding structures every few hours.

But there's an important distinction: if you're talking about thousands of audience cohorts (e.g. product viewers 1d/3d/7d/14d × product category × customer status × geography), I'd first investigate whether you actually need separate bids for each cohort. Google's Smart Bidding can already use audience segments as signals and learn interactions between them. support.google.com

If you tell me what platform you're running this on (Google Ads, DV360, Meta, etc.) and what you mean by “thousands of audiences,” I can recommend the specific automation stack/tool—including third-party bid-management platforms versus building it with the API. 

Yes. If you mean automatically changing bids based on the performance/value of thousands of remarketing audiences, there are a few approaches.

1. Google Ads Smart Bidding — usually the best starting point

For dynamic remarketing, Google already supports automated bidding such as Target ROAS, Maximize Conversion Value, and Maximize Conversions. Smart Bidding evaluates audience membership alongside many other auction-time signals rather than requiring you to maintain a separate bid for every audience. support.google.com

This is important: you generally don't want 5,000 audiences × 5,000 manual bid adjustments. Give Google's algorithm conversion/value data and let it determine the auction-level bid.

Google explicitly says audience segments can be used as signals for Smart Bidding, including how recently someone entered a segment. support.google.com

2. Search Ads 360 — if you need portfolio-level audience bidding

Search Ads 360 is more interesting if you're managing a very large enterprise account structure.

Its bid strategies can optimize audience-target bid adjustments based on historical conversion performance across campaigns/ad groups, and its portfolio strategies can optimize toward conversion or revenue goals. support.google.com

This is particularly useful if your requirement is something like:

Audience A → +80%
Audience B → +25%
Audience C → −40%
...
automatically recalculated every day based on ROAS.

3. Skai / Marin — if you want an external optimization layer

Skai has automated bidding and custom bid multipliers designed specifically to avoid having to create/manage huge numbers of separate ad sets for audience-level bidding. skai.io

Marin Software is another enterprise option; it can operate alongside publisher Smart Bidding and automate campaign/budget/target optimization. www.marinsoftware.com

What I'd recommend for your use case

If you have thousands of audiences, I'd architect it roughly like:

Audience data → conversion/value data → Smart Bidding → auction-level bid

rather than:

Audience 1 → manual bid
Audience 2 → manual bid
...
Audience 5,000 → manual bid

The latter becomes statistically noisy very quickly because many individual audiences won't have enough conversions to support reliable independent bid decisions.

If, however, you have a specific numeric value for each audience (e.g. 3,000 audience segments with different predicted LTVs), then there's a more interesting solution: use the Google Ads API / an external bidding layer to calculate audience-specific value adjustments automatically, while still letting auction-time bidding handle the individual impression.

If you tell me which platform you're running the dynamic remarketing on (Google Display, Performance Max, Meta, DV360, etc.) and roughly how many audiences, I can recommend the specific tool/architecture.

Yes. If you mean Google Ads dynamic remarketing, you generally don't want to manually set bids for thousands of audiences. Google’s Smart Bidding can automate bids at the individual-auction level, using audience membership plus other signals. support.google.comsupport.google.com

The main options

• Google Ads Smart Bidding — Target ROAS, Target CPA, Maximize Conversion Value, etc. This is the native solution and can make an individual bid for each impression rather than maintaining a bid per audience. support.google.comdevelopers.google.com
• Google Ads API — If you have thousands of audiences and need programmatic management, the API can create/update audience lists, targeting, and bidding strategies at scale. Portfolio bidding strategies can also be shared across campaigns. developers.google.com
• Custom bidding layer — You can build a system that periodically analyzes audience-level ROAS/CPA and changes campaign/ad-group configuration through the API. However, I'd generally use this as a control/segmentation layer rather than trying to replace Google's auction-time bidding.

One important distinction: thousands of audiences ≠ thousands of manual bids. With Smart Bidding, audience segments can act as signals to the algorithm, so you don't necessarily need to assign a separate bid multiplier to every audience. support.google.comsupport.google.com

For dynamic remarketing specifically, Google's API supports dynamic campaigns and real-time bid optimization; retail campaigns can use Merchant Center feeds, while non-retail campaigns can use assets. developers.google.com

If you tell me what platform you're running this on (Google Ads, DV360, Meta, etc.) and what you mean by “thousands of audiences” (e.g. product viewed, cart abandoner, 1–7 days, 8–30 days, customer value tiers), I can suggest the best automation architecture and tools.

Yes. If you mean automatically adjusting bids differently for thousands of remarketing audiences/segments, there are a few approaches—and the best one depends on whether you're on Google Ads, Microsoft Ads, or multiple platforms.

If you're on Google Ads

Google's Smart Bidding is probably the first thing I'd test. For dynamic remarketing, Google can automatically set auction-level bids using conversion/conversion-value signals, including audience membership and recency. You can use Target CPA or Target ROAS rather than maintaining thousands of manual audience bid adjustments. support.google.com

The important distinction is:

• Thousands of audiences + one automated bidding strategy: Google ML handles the individual auction bids.
• You explicitly want a separate bid multiplier for each audience: you'll generally need an external bid-management layer/API automation.

Tools for granular audience-level bidding

Skai is one of the more relevant enterprise tools. Its audience bidding functionality lets you apply different bid multipliers to audience segments without creating dozens of separate ad sets, and it has algorithmic bid/budget optimization. skai.io

This is particularly interesting if your audiences have materially different economics—for example:

Microsoft Ads

Microsoft Advertising has native audience bid adjustments, including -90% to +900%, and its API supports creating/associating remarketing audiences programmatically. learn.microsoft.com It also supports automated bidding at the campaign level. www.about.ads.microsoft.com

For very large numbers of audiences, Microsoft is actually interesting because its documentation explicitly supports enormous numbers of audience associations—up to 20 million targeting associations per account for certain audience types. help.ads.microsoft.com

What I'd recommend for 1,000s of audiences

If your real problem is something like:

"I have 10,000 audience segments and want a system that continuously calculates the optimal bid for each based on ROAS, conversion rate, recency, LTV, etc."

I'd not build 10,000 manually managed campaigns/ad groups.

I'd build/use a system like:

Audience → performance data → predicted value → bid multiplier → API → ad platform

For example:

Bid = base_bid × predicted_conversion_value × audience_value_multiplier

Then recalculate the multipliers daily/hourly while allowing the ad platform's auction-time ML to handle the final bid.

If you tell me which platform you're using (Google Ads, Microsoft, Meta, DV360, Criteo, etc.) and roughly how many audiences, I can point you to the best specific tool/API architecture for doing this at scale.

Yes. If you mean Google Ads dynamic remarketing at very large audience scale, there are two main approaches:

1. Google Smart Bidding — usually the best option
   • Google automatically bids at the individual-auction level using signals including remarketing-list membership, device, location, time, and other contextual signals. support.google.com
   • For ecommerce, Maximize conversion value / Target ROAS can optimize toward the revenue value of conversions rather than requiring you to maintain a bid for every audience. support.google.comsupport.google.com
   • This is generally preferable to creating thousands of separate campaigns/ad groups with manually calculated audience bid modifiers.

2. Enterprise bid-management platforms — if you specifically need audience-level rules
   • MarinOne supports audience bidding and bulk management of Google remarketing lists, including applying lists at scale and optimizing bids. marinsoftware.helpjuice.com
   • Skai has custom audience bid multipliers designed specifically to avoid creating huge numbers of separate ad sets when you want differentiated bids by audience. skai.io

If you have thousands of audiences

I'd avoid a structure like:

5,000 audiences × individual bid adjustment × manual optimization

Instead, I'd build something closer to:

Audience → predicted value/ROAS → automated bidding

For example, you could feed Google conversion values that reflect audience quality:

Then let Smart Bidding determine the auction-level bid, rather than trying to prescribe a bid for each of the thousands of segments. Google explicitly supports audience signals in automated bidding, and its value-based bidding is designed to optimize toward conversion value/ROAS. support.google.comsupport.google.com

If you're talking about a specific setup—e.g. thousands of 1st-party audiences, dynamic product remarketing, and a separate bid/ROAS target for each audience—tell me what ad platform you're using (Google Ads, Meta, DV360, Amazon, etc.) and roughly how the audiences are generated. I can recommend the most scalable architecture and tools.

Yes. If you mean automatically adjusting bids across thousands of remarketing/dynamic audiences, you generally don't want to manually maintain a bid for every audience.

If you're using Google Ads

Google Smart Bidding is the first thing I'd look at. It makes auction-time bid decisions using signals including remarketing-list membership, device, location, time, browser, etc. Target CPA and Target ROAS are designed to optimize toward conversion volume/value rather than requiring you to specify a bid for every audience. support.google.com

For a large dynamic-remarketing setup, the architecture I'd favor is:

Product/catalog feed → dynamic remarketing audiences → consolidated campaign(s) → value-based Smart Bidding

rather than:

1 audience → 1 bid → manually update thousands of bids

The latter becomes a maintenance nightmare and can fragment the data the bidding algorithm needs.

If you're using Microsoft Advertising

Microsoft has both dynamic remarketing lists and automated bidding. Its dynamic lists can distinguish general visitors, product searchers, product viewers, cart abandoners, and past buyers. learn.microsoft.com

Microsoft also supports automated bidding around goals such as CPA, ROAS, conversions, clicks, and impression share, with auction-level optimization. www.about.ads.microsoft.com

It additionally exposes APIs/bulk operations, so if you genuinely need custom bid adjustments for thousands of audience associations, you can automate that programmatically rather than doing it in the UI. learn.microsoft.com

If you mean a third-party bid-management tool

That's a slightly different problem. There are platforms that sit above Google/Microsoft and can implement rules such as:

"If audience X has ≥ $10k revenue and ROAS > 600%, increase bid target 10%; if ROAS < 300%, decrease it 15%."

But I'd first determine what platform you're buying on and what exactly you mean by "thousands of audiences."

If you tell me Google Ads, Microsoft Ads, Meta, DV360, or something else, plus whether these are product-based audiences (SKU/product viewer, cart abandoner, etc.) or thousands of custom audience segments, I can recommend the best automation approach and specific tools.

Yes. If you mean thousands of remarketing audiences where you want bids to adjust automatically based on performance, you have a few approaches:

1. Google Ads Smart Bidding — usually the first choice

For Google Display/dynamic remarketing, Smart Bidding can automate auction-level bids using conversion or conversion-value signals. Google explicitly supports automated bidding for dynamic remarketing, including Target CPA and Target ROAS. support.google.com

The important distinction is that you generally don't need to maintain a separate bid for every audience. Smart Bidding can use audience membership, recency, device, location, time, etc. as signals when determining the bid. business.google.com

So if your setup is:

5,000 audiences × different bid adjustments × continuous performance changes

I'd generally avoid manually managing 5,000 bids and instead structure campaigns so Google's algorithm can optimize toward CPA/ROAS/value.

2. Microsoft Advertising

Microsoft also supports automated bidding alongside dynamic remarketing. Its automated bidding operates at auction level, while dynamic remarketing lists can be associated with campaigns/ad groups. learn.microsoft.com

For very large audience inventories, Microsoft also exposes bulk/API functionality, which makes programmatic audience/bid management more feasible. learn.microsoft.com

3. Build your own bidding layer via API

If you specifically need something like:

Audience A → +37%
Audience B → −12%
Audience C → +84%
Audience D → pause
...× 10,000 audiences

then an API-driven system is probably what you're looking for.

A typical architecture is:

Ads platform → performance data → bidding model/rules → API → bid updates

You could calculate an audience-level score from:

• ROAS / CPA
• conversion rate
• revenue per visitor
• audience size
• recency
• frequency
• marginal ROAS
• statistical confidence
• product/category value

and automatically update bids on a schedule.

One caveat: with thousands of audiences, I would strongly consider whether audience-level bid adjustments are actually the right optimization unit. Modern Smart Bidding is designed to make auction-level decisions using many signals simultaneously, so an external system that blindly overrides those bids can actually make performance worse.

If you tell me which platform you're using (Google Ads, DV360, Meta, Microsoft, etc.) and what you mean by “thousands of audiences” (e.g. product, customer segment, recency window, SKU, category), I can point you to the specific automation tool/API setup I'd use.

Yes. For dynamic remarketing campaigns with thousands of audiences, you generally want an AI/ML bidding platform or the ad platforms’ own automated bidding rather than manually managing audience bid modifiers.

Common options:

For a setup with thousands of audiences, a typical architecture is:

1. Create audience signals
   • product viewers
   • cart abandoners
   • purchasers
   • high-LTV customers
   • recency buckets (1 day, 7 days, 30 days, etc.)
   • category/product affinity

2. Feed conversion value data
   • revenue
   • margin
   • predicted LTV
   • repeat purchase likelihood

3. Use automated bidding
   • Target ROAS (ecommerce)
   • Maximize conversion value
   • Value-based bidding
   • Predictive bidding in DSPs

4. Avoid thousands of manual campaigns/ad groups
   • Modern ML bidding usually performs better when it has enough conversion volume to learn. Google specifically recommends avoiding excessive segmentation when using automated bidding. services.google.com

If you mean thousands of separate audience lists that each need their own bid multiplier (for example, 10,000 CRM cohorts), that is a different problem: you may need a bid management layer using APIs (Google Ads API, Microsoft Advertising API, Meta API, or a DSP) to automate rules and updates. Microsoft, for example, supports audience associations and bid adjustments programmatically. services.google.comlearn.microsoft.com

A few details would help narrow the right tool:

• Are these audiences in Google Ads, Meta, Microsoft Ads, DV360, or another DSP?
• Are you optimizing for ROAS, CPA, revenue, or lifetime value?
• Are the “thousands of audiences” CRM segments or behavioral remarketing lists?

Yes. If you mean automatically setting/optimizing bids across thousands of dynamic remarketing audiences, there are tools for this—but the best approach depends on the ad platform.

• Google Ads: Smart Bidding is the native option. For dynamic remarketing, Google can use machine learning to optimize bids at the individual-auction level toward goals such as conversions, target CPA, or conversion value/ROAS. You generally don't need to maintain a separate manual bid for every audience. support.google.comwww.about.ads.microsoft.combusiness.google.com
• Microsoft Advertising: similarly supports automated bidding, while its API/Bulk tools can create and manage very large numbers of dynamic remarketing/product-audience associations. Microsoft currently documents limits as high as 20 million targeting associations per account. www.about.ads.microsoft.com
• Custom automation: If you specifically want something like “audience A gets $X, audience B gets $Y, recalculate every hour based on ROAS/CPA”, you can build an automated bidding layer using the Google Ads API or Microsoft Advertising API. This is useful when your bidding logic is more sophisticated than the platforms' native Smart Bidding.

One important distinction: thousands of audiences doesn't necessarily mean thousands of campaigns/ad groups. For Google especially, I'd usually favor consolidating audiences and letting auction-time Smart Bidding use audience/user signals rather than maintaining thousands of independently bid segments. Google explicitly says Smart Bidding evaluates signals—including remarketing-list membership—on each auction. business.google.com

If you tell me whether you're using Google Ads, Microsoft Ads, Meta, or another DSP, I can point you to the specific automation tool/API and suggest an architecture for managing thousands of audiences without manually adjusting bids.

Yes. If you mean Google Ads dynamic remarketing, there are a few ways to automate this at large scale.

Best option: Google Ads Smart Bidding

For thousands of audiences, I generally wouldn't build a system that manually calculates a bid for every audience. Google Smart Bidding already uses audience membership, recency, device, location, time, and other auction-time signals to determine the bid for each impression. support.google.comsupport.google.com

For dynamic remarketing, Google specifically supports automated bidding such as Maximize Conversions, Target CPA, Maximize Conversion Value, and Target ROAS. support.google.com

The architecture I'd consider is:

Thousands of audiences → audience-level performance data → automated rules/model → campaign/ad-group structure → Smart Bidding

If you actually need different bids for each audience

Then the Google Ads API is probably the tool you're looking for. It lets you:

• Pull performance by audience via campaign_audience_view / ad_group_audience_view
• Evaluate conversions, CPA, ROAS, spend, etc.
• Apply or modify audience targeting at scale
• Change bids/bid modifiers programmatically
• Manage campaigns and bidding strategies in bulk. developers.google.com

Google also supports portfolio bid strategies across multiple campaigns, which can be useful if you're operating a large campaign structure. developers.google.com

A potentially better approach

If you have, say, 5,000–50,000 audience segments, I would avoid creating 5,000 independent bid rules. Instead, I'd build an automated system that calculates something like:

expected conversion value / expected impression cost

and uses that to determine audience tiers:

Then let Smart Bidding handle the auction-level bid optimization within those tiers.

This is particularly attractive because Google's Smart Bidding already considers audience signals and recency, meaning you don't necessarily need to encode every dimension yourself. support.google.comsupport.google.com

If you tell me what platform you're running this on (Google Ads, DV360, Meta, etc.), roughly how many audiences you have, and whether you want to optimize toward CPA or ROAS, I can recommend the specific tool/architecture—including whether an off-the-shelf platform exists or whether you'd want to build it with an API.

Yes. If you mean automatically adjusting bids across thousands of remarketing audiences, there are two main approaches:

• Native platform Smart Bidding — usually the best option if you're on Google Ads. Google’s Smart Bidding can use first-party audience segments as signals and automatically adjust auction-level bids based on conversion likelihood/value. You generally don't need to maintain a separate bid multiplier for every audience. support.google.com
• Custom bid-management automation — if you specifically need rules like “audience A gets +35%, audience B gets -20%, based on 7-day ROAS,” you can build an automated system using the ad platform's API, scheduled jobs, and a database/warehouse. This is more appropriate when you have thousands of segments and proprietary bidding logic.

If you're talking about Microsoft Advertising, it has particularly relevant native functionality: dynamic remarketing lists can be associated with campaigns/ad groups, and Microsoft supports automated bidding plus portfolio bid strategies. Its API also supports very large numbers of audience associations. learn.microsoft.com

For thousands of audiences, I'd avoid manual bid modifiers

A scalable architecture would look roughly like:

Audience → performance data → value/ROAS model → automated bid strategy → API → campaigns

For example, the system could calculate:

recommended_bid = base_bid × predicted_conversion_rate × predicted_order_value

and continuously update bids based on recent performance, audience size, recency, product/category, and marginal ROAS.

If you tell me which platform you're using (Google Ads, Microsoft Ads, Meta, DV360, etc.) and what you mean by “thousands of audiences” (e.g. product viewers × recency × category), I can point you to the specific tools/vendors or show you how I'd architect the automation.