ChatGPT answers, unedited

Yes. For Google Ads, Smart Bidding can automate auction-level bids while using remarketing/audience segments as signals. For thousands of audiences, the Google Ads API + portfolio bid strategies is the scalable route. support.google.com developers.google.com

If you mean Microsoft Advertising, portfolio bid strategies similarly automate bidding across campaigns. github.com

Yes. If you mean Google Ads dynamic remarketing, there are two ways to automate this at scale:

• Google Smart Bidding — usually the simplest approach. Dynamic remarketing supports Smart Bidding, including conversion/value-based strategies, which set bids at auction time using signals such as audience membership, device, location, time, etc. Google Help Google Help
• Google Ads API + your own bidding engine — if you literally have thousands of audience segments and want different rules/bids for each, you can programmatically create/manage audiences and targeting and modify bids. Google's API supports user lists, audience targeting, and bid modifications. Google for Developers Google for Developers

If you have thousands of audiences

I would not normally create a separate manually managed bid for every audience. Smart Bidding is designed to incorporate audience signals into auction-time decisions, and Google specifically says that with automated bidding, audience segments are used as signals to improve bidding. Google Help Google Help

A scalable architecture would look something like:

Audience/event data → segmentation → Google Ads audiences → Dynamic Remarketing → Smart Bidding

Then, if you have business-specific rules such as:

• high-value customers → higher value weighting
• cart abandoners → aggressive bids
• product viewers → lower bids
• long-lapsed visitors → lower bids
• different ROAS targets by product/category

you can build an API-driven layer that periodically analyzes performance and changes campaign/ad-group targeting or bidding parameters. Google provides API operations specifically for managing remarketing user lists and bid modifiers. Google for Developers Google for Developers

One important distinction: Smart Bidding optimizes individual auction bids; it isn't the same thing as maintaining a separate fixed bid for each of thousands of audiences. In many cases, letting the algorithm learn across the audience signals will scale better than trying to manually calculate thousands of independent bids. Google Help

If you tell me what platform you're using (Google Ads, DV360, Meta, Amazon, etc.) and what "thousands of audiences" means in your setup, I can lay out a concrete automation architecture, including the API/algorithm and where the bid decisions should happen.

Yes. If you mean Google Ads dynamic remarketing, you generally don’t want a separate bid manually calculated for each of thousands of audiences.

Google’s Smart Bidding is designed to do this at auction time: it evaluates audience membership and other signals and sets a bid for each impression opportunity. It can optimize toward conversions or conversion value/ROAS. Google Help Google Help Google Help

For a setup with thousands of audience segments, I’d look at three approaches:

• Google Ads Smart Bidding — best default. Put your first-party/data audiences into the campaign and let Smart Bidding use them as signals. Google specifically says Smart Bidding can account for audience-segment membership and segment duration. Google Help
• Value-based bidding / Target ROAS — best if audiences have materially different customer values. Feed Google meaningful conversion values rather than trying to maintain thousands of audience-specific bid multipliers. Google Help
• Custom bid automation via the Google Ads API — best if you actually need audience-level rules. For example, you could build a system that reads performance by audience × product × recency window and adjusts campaign/ad-group settings or budgets automatically. But I'd avoid trying to override auction-time bids at the individual-audience level unless you have a strong reason; Google recommends keeping Smart Bidding exposed to as much traffic as possible rather than heavily fragmenting campaigns/ad groups. Google Help

For dynamic remarketing specifically, Google supports it in Display, Performance Max, and App campaigns, with Smart Bidding available for Display; the dynamic component uses users' prior product/service interactions to tailor ads. Google Help Google Help

If your real problem is “I have 10,000+ audiences and want software to automatically determine the right bid/budget for each audience based on ROAS/CPA”, that's a slightly different problem—and there are platforms/API architectures specifically suited to it. I can lay out the best tools/vendors and an architecture for automating this at 10K–100K audience scale.

Yes. For thousands of audiences, you typically need an AI/algorithmic bid management platform or the ad platform’s own automated bidding rather than manually setting audience bids.

Common options:

• Google Ads Smart Bidding — Target CPA, Target ROAS, Maximize Conversions, and value-based bidding can optimize remarketing bids using auction-time signals. Google specifically recommends automated bidding for dynamic remarketing campaigns. Google Help
• Criteo Dynamic Retargeting — built for large-scale product remarketing, using predictive bidding to adjust bids per impression/user/product combination. Criteo Criteo
• The Trade Desk / DSPs — useful if your audiences span many segments and channels; DSPs can automate bid decisions across large audience pools.
• RevX Intellibid — provides ML-based audience segmentation and automated bid optimization across platforms. revx.io
• Custom bidding stack — for enterprise setups, companies often combine a CDP (audience engine) + ad APIs + a bidding model that adjusts bids based on recency, LTV, intent, product affinity, and conversion probability.

For thousands of remarketing audiences, the usual architecture is:

1. Feed audience signals (viewed product, cart, purchase history, LTV, recency).
2. Score users/segments by predicted value.
3. Pass value signals into Google/Meta/DSP bidding systems.
4. Let auction-time algorithms optimize impressions.

If you mean Google Ads dynamic remarketing specifically, Meta Advantage+ catalog ads, or programmatic display, the best tool choice differs.

Yes. If you mean Google Ads dynamic remarketing, there are a few ways to automate this at very large scale—but the best approach depends on whether you want Google’s AI to determine bids or you want an external system to calculate audience-specific bid multipliers.

Best options

• Google Smart Bidding — usually the first choice. Google’s bidding system evaluates audience membership along with device, location, time, recency, and other auction-time signals and sets a bid for each auction. This avoids maintaining thousands of individual bid rules. Google Help Google
• Google Ads API — best if you specifically want to programmatically manage thousands of audiences/campaigns. The API supports creating/managing user lists and targeting, as well as dynamic remarketing campaigns. Google for Developers Google for Developers
• Search Ads 360 — interesting if you have a very large enterprise setup and specifically need automated audience-level bid adjustments. Its bid strategies can use historical audience performance to optimize audience-target bid adjustments across portfolios of campaigns/ad groups. Google Help
• Your own bidding engine + Google Ads API — useful if you have a proprietary scoring model, e.g. audience × product × recency × customer value → bid multiplier. The API can automate the deployment, while your system determines the strategy. Google explicitly supports using third-party/in-house solutions alongside its automated bidding. Google

For thousands of audiences, I'd avoid this architecture

1 audience → 1 campaign → manually calculated CPC bid

It becomes extremely fragmented and each audience may not have enough conversion data to make statistically reliable decisions.

Instead, I'd generally use:

Thousands of audience signals → centralized Smart Bidding / portfolio strategy → auction-time bid

Google specifically notes that Smart Bidding can use first-party audience segments as signals and also accounts for how long someone has been in the segment. Google Help

If you have a requirement like “I have 20,000 dynamic remarketing audiences and want the system to automatically calculate a different bid/ROAS target for each based on revenue, margin, recency and conversion rate”, that's a different problem—and I can sketch an architecture for that, including Google Ads API + data warehouse + bidding algorithm + safeguards.

Yes. If you mean Microsoft Advertising/Bing dynamic remarketing, there are two layers you can automate:

• Platform-native automated bidding: Microsoft Advertising has automated bid strategies that optimize bids at the auction level toward goals such as CPA, ROAS, conversions, or clicks. Microsoft Advertising
• Audience-level bid automation: Microsoft lets you associate remarketing/dynamic remarketing audiences with campaigns or ad groups and apply bid adjustments, including up to +900% / −90%. Microsoft Ads Help Microsoft Learn
• API/bulk automation: Microsoft Advertising's API supports creating and associating remarketing/product audiences, so you can build an external rules engine that manages thousands of audience associations rather than manually editing them. Microsoft Learn Microsoft Learn

For thousands of audiences, I'd use an automated bid-management layer

For example:

Audience → conversion/ROAS data → scoring model → bid adjustment → Microsoft Ads API

You could have rules such as:

• 30-day ROAS > 8 → +50%
• ROAS 5–8 → +25%
• ROAS 3–5 → 0%
• ROAS < 3 → −30%
• <50 conversions → don't adjust yet
• High-value cart abandoners → separate multiplier
• Recent purchasers → suppress or bid down
• Automatically recalculate every 6–24 hours

The important distinction is that you probably don't want to create thousands of campaigns or manually set thousands of bids. Let Microsoft's auction-level Smart/automated bidding handle the individual auction, while your automation controls the audience-level strategy/segmentation.

If you're talking about Google Ads rather than Microsoft Ads, I can also outline the best architecture there—e.g. Google Ads API + portfolio/Smart Bidding + audience-value rules, which is somewhat different.

Yes. If you mean Google Ads dynamic remarketing, you generally don't need a separate tool to manually bid across thousands of audiences.

Best option: Google Ads Smart Bidding

Google's Smart Bidding automatically calculates bids at the individual-auction level using signals such as:

• Remarketing-list membership
• Recency of the user
• Device
• Location
• Time/day
• Browser/OS
• Predicted conversion probability

It can optimize toward Target CPA, Target ROAS, Maximize Conversions, or Maximize Conversion Value. Google Help Google Help

For dynamic remarketing specifically, Google supports Smart Bidding on Display campaigns and recommends automated targeting/bidding when appropriate. Google Help Google Help

So if you have thousands of audience segments, I'd usually avoid creating a separate manual bid for each one. Instead, I'd structure the audiences around meaningful differences in expected value/intent, feed conversion or revenue data into Google, and let Smart Bidding differentiate bids at auction time.

If you need explicit audience-level bid automation

That's a different problem. For example:

Audience A → $0.40
Audience B → $0.85
Cart abandoners → $2.10
Product viewers → $0.70
Purchasers → $0.05
Recalculate all 5,000 bids every 6 hours based on CPA/ROAS.

For that, you can build an automation layer using the Google Ads API or a third-party bid-management platform. Google explicitly supports using APIs/third-party management solutions alongside its automated bidding infrastructure. Google Help

The interesting architecture is actually to combine the two:

Audience data → performance/value model → bid constraints/targets → Google Smart Bidding → auction-level optimization

That tends to scale much better than a giant rules engine assigning a bid to every audience.

If you tell me whether you're talking about Google Ads, Meta, DV360, The Trade Desk, or another platform, and roughly how many audiences/campaigns you have, I can recommend the specific automation stack and architecture.

Yes. If you mean automatically determining and updating bids across thousands of dynamic remarketing audiences, there are a few approaches—but the best one depends on whether you're on Google Ads, Microsoft Advertising, or both.

The easiest option: let the ad platform bid at auction time

For Google Ads, Smart Bidding can use audience membership, recency, device, location, time, and other signals to calculate a bid for each auction. That means you generally don't need to maintain a separate manual bid for every audience. Google explicitly says audience segments can be used as signals by Smart Bidding. Google Support Google

For Microsoft Advertising, automated bidding similarly optimizes bids in real time toward goals such as CPA, ROAS, conversions, or conversion value. Microsoft Advertising Microsoft also supports dynamic remarketing based on the specific products users interacted with. Microsoft Advertising

If you specifically need audience-level bid control

You can build an automated bidding layer using the ad platform's API:

1. Pull performance for every audience/product segment.
2. Calculate metrics such as: - ROAS
3. CPA
4. conversion rate
5. revenue per click
6. audience size
7. recency
8. Assign a bid multiplier based on those metrics.
9. Push the changes through the API in bulk.
10. Recalculate daily/hourly, with safeguards against volatility.

Microsoft, for example, exposes API/bulk functionality for dynamic/product audiences and allows audience associations with campaign/ad-group bid adjustments. Microsoft Learn Microsoft Advertising Help

The important architectural point is that I wouldn't create thousands of independent campaigns just to get thousands of bids. A better setup is usually:

Dynamic remarketing → audience/product signals → automated bidding model → campaign-level Smart Bidding

rather than:

10,000 audiences → 10,000 manually maintained bids

If you're talking about a specific use case

If you have something like 5,000–100,000 audiences/product segments and want an algorithm to say "bid +40% on audience A, -20% on B, +150% on C" automatically, that's very doable.

I can map out a specific automated bidding architecture, including the API/tooling options and the bidding formula, if you tell me whether this is Google Ads, Microsoft Ads, or both and roughly how many audiences you're dealing with.

Yes. If you mean automatically adjusting bids across thousands of dynamic remarketing audiences, there are a few approaches—and the best one depends on whether you're using Google Ads, Microsoft Ads, or another DSP.

If you're on Google Ads

Google Smart Bidding is probably the first thing I'd look at. It can use audience/remarketing segments as signals and adjust auction-level bids automatically rather than requiring you to maintain a separate bid for every audience. Google explicitly says Smart Bidding uses audience-segment signals and can account for factors such as how long someone has been in a segment. Google Help

For a very large audience taxonomy, the architecture I'd generally recommend is:

• Audience → signal, rather than manually assigning a bid to every audience.
• Conversion value / ROAS → optimization objective.
• Let the platform determine the auction-level bid.
• Maintain your audience definitions and exclusions programmatically.
• Use a custom layer only if you need different economic values for thousands of audience cohorts.

If you need explicit audience-level bid control

Search Ads 360 is interesting. Its bid strategies can optimize remarketing-target bid adjustments based on the historical performance of the remarketing targets across a portfolio. In other words, it can actually automate the remarketing-target adjustment rather than simply using the audiences as signals. Google Help

That becomes attractive if your setup looks something like:

10,000 audiences × different recency/product/value cohorts → different effective bids

rather than:

10,000 audiences → one Smart Bidding system.

Microsoft Advertising

Microsoft also has automated bidding and portfolio strategies. Its Audience campaigns support automated strategies such as Maximize Conversions and Target CPA, while portfolio bidding can pool campaigns toward a common objective. Microsoft Ads Help Microsoft Ads Help

Microsoft also allows remarketing audiences to have bid adjustments, with adjustments ranging from -90% to +900% when managed manually. Microsoft Ads Help

If you're talking about thousands of audiences

At that scale, I'd probably not build a simple rules engine that says "audience X = $1.20 bid, audience Y = $2.10." It tends to become brittle and creates sparse-data problems.

A better system is something like:

Audience/cohort
      ↓
Historical conversion rate
      ↓
Expected conversion value
      ↓
Expected ROAS / CPA
      ↓
Bid multiplier or target
      ↓
Platform Smart Bidding

You can then have an automated service periodically calculate cohort-level recommendations and push only the appropriate controls into the ad platform.

If you tell me which platform you're using (Google Ads, Microsoft Ads, DV360, Meta, etc.) and roughly how the audiences are structured, I can recommend the specific tool/API stack—including whether there's an off-the-shelf product that can handle the thousands-of-audiences problem without you building it yourself.

Yes. If you mean Google Ads dynamic remarketing, there are a few ways to automate this at very large scale—but the right architecture depends on what you mean by “across thousands of audiences.”

The simplest option: Google Smart Bidding

Google's own Smart Bidding can automatically adjust the bid at auction time using audience membership and other signals. For Display/dynamic remarketing, Google supports strategies such as Target CPA, Maximize Conversions, and Target ROAS. Google Help Google

So you generally don't need a separate bid for every audience. You can feed thousands of audiences into campaigns/ad groups and let Google's model determine the auction-level bid.

This is particularly useful when audiences overlap heavily: Google says Smart Bidding can use audience segments as signals and account for factors such as how long someone has been on a segment. Google Help

If you specifically want rules like "Audience A = +40%, Audience B = -20%"

Then you're looking at an automation layer on top of Google Ads, typically using the Google Ads API.

You can programmatically:

• Create/manage thousands of audience lists.
• Attach audiences to campaigns/ad groups.
• Pull spend, conversions, revenue, CPA/ROAS, etc.
• Calculate an optimal bid/bid modifier based on each audience.
• Automatically update campaigns on a schedule.
• Apply different targets or budgets to audience cohorts.

Google's API explicitly supports creating and targeting audience segments, while Google Ads Scripts can automate campaign targeting changes. Google for Developers Google for Developers

For thousands of audiences, I'd usually build this differently

Rather than:

10,000 audiences → 10,000 manually maintained bids

I'd build:

Audience data → performance aggregation → bid/targeting model → Google Ads API → automated feedback loop

For example:

The important distinction is that Google's Smart Bidding is already doing much more sophisticated auction-level optimization than simply assigning a percentage bid adjustment to each audience. Google describes Smart Bidding as evaluating combinations of signals rather than independently stacking bid adjustments. Google

So if you're talking about thousands of audience segments, my first choice would be:

Dynamic remarketing + Smart Bidding/Target ROAS + audience segments as signals, rather than trying to maintain thousands of independent bids.

If, however, you have a proprietary scoring system—e.g. 10,000 audiences × customer LTV × recency × product margin × predicted conversion rate—then Google Ads API + your own bidding engine becomes very interesting.

If you tell me whether this is Google Ads, Meta, DV360, or another platform, and roughly how many audiences/campaigns/ad groups you're managing, I can recommend the specific tool/architecture (including existing SaaS tools vs. building it with an API).

Yes. If you mean thousands of dynamic remarketing audiences/segments, you generally don't want to manually set a bid for each audience. The major ad platforms now have automated bidding that can optimize at the auction level.

Google Ads

For dynamic remarketing, Google Smart Bidding is probably the closest native solution. Google says Dynamic Remarketing supports real-time bid optimization, and Smart Bidding uses audience membership plus other signals when determining bids. Google for Developers Google Help

For a large setup, you can use the Google Ads API to automate the infrastructure around it:

• Create/update thousands of audience segments.
• Associate audiences with campaigns/ad groups.
• Apply shared portfolio bidding strategies across campaigns.
• Change targets such as CPA/ROAS programmatically.
• Pull performance data and adjust your strategy based on conversion value.

Google explicitly supports portfolio bidding strategies shared across multiple campaigns through the API. Google for Developers Google for Developers

developers.google.com

Microsoft Advertising

Microsoft has a similar setup: automated bidding + dynamic remarketing lists. Its automated bidding operates at the auction level, while dynamic remarketing lists can be associated with campaigns/ad groups. Microsoft Advertising Microsoft Learn

Microsoft also exposes the functionality through its API, so you can programmatically create/manage remarketing lists and their campaign associations. Microsoft Learn

learn.microsoft.com

If you're talking about a custom bidding engine

If your actual use case is something like:

10,000 audiences × thousands of products × different recency/frequency/value cohorts → automatically calculate the optimal bid for each combination

then yes, you can build a bid-management layer on top of Google/Microsoft rather than maintaining individual bids manually.

A common architecture is:

Audience → Performance data → Expected conversion rate/value → Bid model → API → Campaign/bidding strategy

For example, you could calculate:

bid = expected_conversion_value × target_ROAS adjustment × audience/value multiplier

and have the system periodically update campaign targets or audience-level settings.

The important distinction is that Google's Smart Bidding already does much of the auction-level optimization. Your custom system is most useful when you have a proprietary segmentation/value model that Google doesn't know about—for example, customer LTV, margin, inventory value, churn probability, or thousands of business-specific audience scores.

If you tell me which platform (Google Ads, Microsoft, Meta, DV360, etc.) and what you mean by “thousands of audiences”, I can recommend the specific tool/API architecture—and whether you should use native Smart Bidding, a third-party bid-management platform, or build your own.

Yes. If you mean Google Ads dynamic remarketing, there are tools that can automate bidding across thousands of audiences—but in many cases you shouldn't actually create/manage a separate bid for every audience.

Best option: Google Ads Smart Bidding

Google's Smart Bidding is designed to handle this at scale. It sets bids at auction time and can incorporate remarketing-list membership along with device, location, time, browser, OS, creative, and other signals. Google Help Google Help

For a dynamic remarketing setup, I'd generally look at:

• Target ROAS — best when you pass purchase/revenue values and care about ROAS.
• Maximize conversion value — useful when you want Google to maximize revenue/value within budget.
• Target CPA / Maximize conversions — if conversions are relatively uniform in value. Google Help Google Help

Google can use first-party audience segments as signals to Smart Bidding, so you don't necessarily need to calculate a manual bid multiplier for each audience. Google Help

If you specifically need custom audience-level bid automation

Then I'd look at building an automation layer using the Google Ads API. You can programmatically retrieve performance and update campaigns/ad groups/bid modifiers at scale. Google supports bid-modifier management through its API. Google for Developers

A typical architecture would be:

Thousands of audiences → performance data → scoring/model → bid recommendation → Google Ads API → automated updates

For example:

The important distinction is that Smart Bidding already performs much finer-grained optimization than an audience-level rule system—it can make unique bids for individual auctions rather than simply saying "Audience A = +30%." Google Help

If you tell me what platform you're running the remarketing on (Google Display, Demand Gen, DV360, Meta, Criteo, etc.) and what you mean by "thousands of audiences", I can recommend the specific automation tool/stack I'd use and how I'd structure it.

Yes. For dynamic remarketing campaigns with thousands of audiences, you generally don’t want a tool that creates a separate manual bid for every audience. The scalable approach is usually a combination of:

1. Platform-native automated bidding
2. Audience/value signals
3. Bid management platforms or APIs for custom rules

Here are the main options:

1. Google Ads Smart Bidding (most common)

For Google Display dynamic remarketing, Performance Max, and other remarketing setups, Google’s own bidding algorithms can optimize bids at impression time using audience signals, conversion likelihood, product data, and user behavior. Strategies like Target CPA and Target ROAS are designed for this kind of scale. Google Help Google Help

Typical setup:

• Build audiences: - Viewed product, no purchase
• Added to cart
• Started checkout
• Past purchasers
• High-value customers
• Category/product viewers
• Time since last visit
• Feed those signals into campaigns
• Let Smart Bidding adjust bids dynamically

Google specifically recommends automated bidding for large-scale advertisers because it can optimize across many signals rather than requiring thousands of manual bid changes. Google Help

2. Google Ads API + custom bidding engine

If you have thousands of audience segments and need your own rules, you can build a layer on top of Google Ads:

Examples:

• Increase bids 40% for: - cart abandoners <7 days
• customers with predicted LTV >$500
• Decrease bids for: - low-margin products
• frequent non-buyers
• Change ROAS targets by segment

The Google Ads API supports dynamic remarketing campaign management and can be used to automate campaign/feed/bidding workflows. Google for Developers

3. Enterprise bid management platforms

For very large accounts (millions of users, many campaigns), tools in this category include:

• skai.io
• marinsoftware.com
• smartly.io

They typically provide:

• automated bid rules
• budget allocation
• portfolio optimization
• reporting across many campaigns/accounts

4. Feed-driven dynamic remarketing tools

If your challenge is thousands of products × audiences × creatives, look at tools that automate catalog/feed-based ads rather than audience-level bidding.

Google dynamic remarketing already avoids creating thousands of ad groups by using product feeds and automated selection of relevant products. Google Services

Recommended architecture for thousands of audiences

A common enterprise setup:

CRM/CDP
  ↓
Audience scoring model
  ↓
Google Customer Match / remarketing lists
  ↓
Google Ads Smart Bidding
  ↓
Automated ROAS/CPA optimization

+
Optional:
API layer for exceptions and business rules

The key question is what kind of audiences you mean:

• Thousands of Google Ads audience lists (remarketing segments)?
• Thousands of product/user combinations (e.g., "viewed SKU X but not purchased")?
• Thousands of campaign/ad groups with separate bids?
• Are you optimizing for ROAS, CPA, margin, or lifetime value?

The best tool choice changes a lot depending on that.

A common enterprise setup:

Yes. If you mean Google Ads dynamic remarketing, there are several ways to automate this at scale—but the best approach depends on whether you want Google to learn the bid itself or you want an external system to calculate and push bids by audience.

Best option: Google Smart Bidding

For thousands of audiences, I would generally not create a separate manual bid for every audience. Google Smart Bidding can adjust bids at auction time using signals including remarketing-list membership, recency, device, location, time of day, and other contextual signals. Google Help Google Help

For dynamic remarketing specifically, Google supports Smart Bidding for Display campaigns, and dynamic remarketing can also run through Performance Max. Google Help Google Help

A typical setup would be:

Thousands of audience segments
        ↓
Audience / product / behavioral signals
        ↓
Google Smart Bidding
        ↓
Auction-time bid
        ↓
Dynamic product creative
        ↓
Conversion / revenue feedback

You can use Target CPA or Target ROAS if you have enough conversion/value data. Google also supports portfolio bid strategies across multiple campaigns, although portfolios aren't available for Performance Max. Google Help Google Help

If you specifically want "bid X for audience A, Y for audience B..."

Then you'd want an external bidding automation layer, typically using the Google Ads API.

For example, you could have a rules/model like:

Your system could pull performance data daily/hourly, calculate the desired adjustments, and push campaign/ad-group changes through the API.

However, there's an important distinction: Google Smart Bidding already makes auction-time decisions using audience membership as one of its signals. So trying to maintain thousands of explicit audience-level bids can actually fight against the ML system rather than improve it. Google Help

If you have thousands of audiences

I'd consider a hybrid architecture:

1. Audience generation — CRM/CDP/Google audience lists.
2. Audience scoring — calculate expected conversion rate or revenue per user.
3. Audience clustering — group thousands of audiences into perhaps 20–100 economically meaningful tiers.
4. Campaign structure — map those tiers to campaigns/ad groups where necessary.
5. Smart Bidding — let Google's auction-time model handle the final bid.
6. External controller — periodically adjust targets/budgets based on marginal ROAS/CPA.

That is much more scalable than trying to manage 10,000 individual CPC bids.

If you're dealing with Google Ads specifically, I can also lay out an architecture for an automated bidder that handles 10K+ audiences, including the API, data warehouse, bidding algorithm, safeguards, and how I'd structure the campaigns.

Thousands of audience segments
        ↓
Audience / product / behavioral signals
        ↓
Google Smart Bidding
        ↓
Auction-time bid
        ↓
Dynamic product creative
        ↓
Conversion / revenue feedback

You can use Target CPA or Target ROAS if you have enough conversion/value data. Google also supports portfolio bid strategies across multiple campaigns, although portfolios aren't available for Performance Max. Google Help Google Help

If you specifically want "bid X for audience A, Y for audience B..."

Then you'd want an external bidding automation layer, typically using the Google Ads API.

For example, you could have a rules/model like:

Your system could pull performance data daily/hourly, calculate the desired adjustments, and push campaign/ad-group changes through the API.

However, there's an important distinction: Google Smart Bidding already makes auction-time decisions using audience membership as one of its signals. So trying to maintain thousands of explicit audience-level bids can actually fight against the ML system rather than improve it.

If you have thousands of audiences

I'd consider a hybrid architecture:

Yes. If you're talking about Google Ads dynamic remarketing, there are a few ways to automate this at very large scale.

Best options

• Google Ads Smart Bidding — Usually the best first choice. Google’s automated bidding can use audience-segment signals and conversion/value data to adjust bids auction-by-auction. For dynamic remarketing, Google specifically recommends Target CPA, Maximize Conversions, and Target ROAS. Google Help Google Help
• Google Ads API — Best if you have thousands of audience/campaign combinations and want your own rules engine. The API supports both campaign-level and portfolio bidding strategies, with portfolio strategies shared across multiple campaigns. Google for Developers Google for Developers
• Google Ads Scripts — A lighter-weight option for automatically changing bidding settings based on performance data without building a full application. Google for Developers
• Microsoft Advertising has a similar setup: automated bidding plus audience-level bid adjustments, and its API supports dynamic remarketing/product audiences. Microsoft Advertising Microsoft Learn

If you mean "I have 10,000+ audiences and want each to get its own bid"

That's a slightly different problem.

I'd generally not create a separate manual bid for every audience. Instead, build a bid-optimization layer that calculates something like:

Bid = base_bid × audience_value × recency × product_value × conversion_probability

Then have the system push those changes through the Google Ads API on a schedule.

For example:

The important distinction is that Smart Bidding already does much of this at auction level. If you have enough conversion volume, Google's algorithm may outperform a system trying to micromanage thousands of audience bids.

If, however, you have a very large catalog + thousands of audience segments + different economics by product/customer lifecycle, a custom bid-management system can make sense.

If you tell me Google Ads vs. Microsoft, roughly how many audiences, and whether you're optimizing for CPA or ROAS, I can recommend the specific tool/architecture I'd use.

Yes. If you mean Google Ads dynamic remarketing, you generally don't want a separate manual bid for each of thousands of audiences. Google’s own Smart Bidding is designed to use audience membership and other auction-time signals to calculate bids automatically. Google Google Help

The scalable options

• Google Ads Smart Bidding — probably the first thing I'd test. Strategies such as Maximize Conversions or Maximize Conversion Value / tROAS can adjust bids at auction time based on audience membership, recency, device, location, etc. Google Google Help
• Google Ads API — if you actually need programmatic bid management across thousands of audiences, you can build an automation layer around the API. It can retrieve audience performance and manage audience targeting, user lists, campaigns and criteria. Google Developers Google Developers
• Custom bidding engine — for sophisticated setups, you can pull audience-level spend/conversion/revenue data, calculate target bids or multipliers, and push changes through the Google Ads API. This is useful if you have your own model for determining audience value.

The important distinction is that Smart Bidding doesn't necessarily require you to calculate a bid for every audience yourself. Google explicitly says audience segments can be used as signals by automated bidding, including recency within the segment. Google Help

For dynamic remarketing specifically, Google's system already performs real-time bid optimization, while dynamic ads select products/services based on the user's previous activity and the feed. Google Developers

If you have thousands of audience cohorts

A good architecture would be:

Audience data → performance/value model → Google Ads API → campaigns/audience targeting → Smart Bidding

For example, if you have cohorts like:

• Viewed product, 0–3 days
• Viewed product, 4–7 days
• Viewed product, 8–30 days
• Added to cart, 0–3 days
• Added to cart, 4–14 days
• Purchased category A
• Purchased category B
• High-LTV customers
• etc.

I'd generally avoid creating thousands of independent campaigns just to give each cohort a different bid. Instead, consolidate where possible and let Smart Bidding use the audiences as signals. Google's current API documentation specifically recommends audience segments for direct targeting and audiences for layered/persona-based targeting. Google Developers

If your real requirement is "I have 5,000+ audiences and I want an algorithm to automatically calculate a bid multiplier for each based on ROAS/CPA/LTV", that's a different problem—and yes, you can build a fairly robust automated bidding system around the Google Ads API.

If you tell me Google Ads vs. Meta, what your audiences represent, and whether you want CPA, ROAS, or profit/LTV optimization, I can suggest the specific tool/architecture I'd use.

Yes. If you mean Google Ads dynamic remarketing, there are a few ways to automate this at very large scale—but the best approach depends on whether you want Google to optimize bids itself or you want to impose different bid logic for thousands of audiences.

Best options

• Google Ads Smart Bidding — usually the first choice. Google’s auction-time bidding already incorporates signals such as whether someone is on a remarketing list, device, location, etc., and can optimize toward conversions or conversion value. Google Help Google Help
• Google Ads API — best if you actually need to programmatically manage thousands of audiences, campaigns/ad groups, bid modifiers, and optimization rules. The API supports audience targeting and modifying bids at campaign/ad-group level. Google for Developers Google for Developers
• Custom bidding engine — you can pull audience-level performance from the API, calculate a desired bid/bid modifier based on CPA, ROAS, margin, recency, LTV, etc., and push changes back automatically. Google exposes campaign-audience performance data through campaign_audience_view. Google for Developers

For example, you could have something like:

Audience                  7d ROAS    Target ROAS    Bid action
----------------------------------------------------------------
Cart abandoners 0-1d       9.2x        6.0x         +25%
Cart abandoners 2-7d       7.1x        6.0x         +10%
Product viewers 0-3d       5.8x        6.0x          0%
Product viewers 4-14d      3.9x        6.0x         -20%
Past purchasers 30-90d     2.1x        6.0x         -40%

The important architectural question is whether you really want 5,000 independently managed bids. In many cases, that's counterproductive because Google Smart Bidding can make auction-level decisions using hundreds of signals that a simple audience-level rule can't capture. Google itself recommends Smart Bidding for dynamic remarketing and supports Target CPA/Target ROAS and conversion-value optimization. Google Help Google Help

A more sophisticated setup is:

Thousands of audiences → aggregate performance → calculate audience value/LTV → feed conversion values into Google → let tROAS/Max Conversion Value handle the individual auction bids.

That gives you automation without having to constantly micromanage thousands of bid adjustments.

If you tell me Google Ads vs. Meta, roughly how many audiences (1K/10K/100K+), and whether you're optimizing for CPA, ROAS, revenue, or profit, I can recommend the specific tool/architecture—including existing platforms versus building it with the Ads API. Google for Developers

Yes. If you mean Google Ads dynamic remarketing, there are tools that can automate this at very large scale—but the best approach depends on whether you want Google to determine the bid at auction time or you want an external system to assign different bid targets to thousands of audience cohorts.

Best option: Google Ads Smart Bidding

For most cases, you don't need to manually bid on each audience. Google Smart Bidding can optimize bids auction-by-auction using signals including remarketing-list membership, device, location, time, browser, OS, and other contextual signals. Google Help Google Help

For dynamic remarketing specifically, Display campaigns support Smart Bidding, including Target CPA, Maximize Conversions, Maximize Conversion Value/Target ROAS, etc. Google Help

So a setup like:

5,000 audiences × 20 products × millions of auctions

doesn't require you to calculate 100,000 individual bids. Google's bidder is effectively doing the auction-level optimization for you. Google says Smart Bidding can set millions of unique bids per second. Google Help

If you specifically want audience-level bid automation

Then I'd look at a Google Ads API + custom bidding engine architecture.

The Google Ads API supports programmatic management of audience segments and dynamic remarketing. Google for Developers You can build a system that:

1. Pulls performance by audience/cohort.
2. Calculates expected CPA, ROAS, LTV, margin, etc.
3. Groups thousands of audiences into bid tiers.
4. Updates campaign/ad-group/bidding parameters automatically.
5. Feeds conversion/value data back into Google.
6. Lets Smart Bidding handle the actual auction-level bid.

This is generally preferable to trying to maintain thousands of literal manual CPC bids.

Third-party platforms

If you don't want to build the API layer yourself, platforms such as Search Ads 360 or enterprise PPC-management platforms can provide rules, portfolio bidding, reporting, and automation across large account structures. Google also explicitly supports using Smart Bidding alongside third-party search-management systems or an in-house API. Google Help

One important distinction: Google's Smart Bidding is not the same thing as "set a separate bid for every audience." It uses audience membership as one of many predictive signals. That is usually more scalable and statistically robust than isolating every audience and bidding independently.

If you tell me what the 5,000 audiences actually represent (e.g. product viewed, days since visit, customer value, geography, CRM segment) and whether you're using Display, Performance Max, or DV360, I can recommend the specific automation stack and architecture I'd use.

Then I'd look at a Google Ads API + custom bidding engine architecture.

Yes. If you mean Google Ads dynamic remarketing, you generally don’t need a separate bid-management tool for thousands of audiences.

Best option: Google Ads Smart Bidding

Google’s Smart Bidding can automatically set bids at auction time based on conversion/conversion-value probability, including remarketing-list membership and other contextual signals. It supports Target CPA, Target ROAS, Maximize Conversions, and Maximize Conversion Value. Google Help Google Help

For dynamic remarketing specifically, Google recommends Smart Bidding and supports Target CPA/Target ROAS approaches. Google Help

So instead of doing:

Audience 1 → bid $0.80
Audience 2 → bid $1.20
…
Audience 5,000 → bid $2.10

you can have the algorithm effectively determine the bid for each auction/user opportunity.

If you need different bids for thousands of audience segments

That's where I'd consider a bid-management/optimization layer on top of Google Ads. The architecture would be:

Audience/CRM data → segment scoring → Google Ads → Smart Bidding → auction-level bid

You could feed in signals such as:

• Recency: viewed product 1 day ago vs. 30 days ago
• Product/category
• Customer value
• Cart vs. product viewer
• Predicted conversion probability
• Predicted order value
• Lifetime value
• Geography/device
• Audience size and historical performance

Then optimize toward ROAS or profit, rather than maintaining thousands of manually calculated CPC bids.

Google also supports portfolio bid strategies, which let one Smart Bidding strategy operate across multiple campaigns/ad groups rather than managing each independently. Google Help Google Help

If you're asking about a third-party tool

There are enterprise platforms such as Skai, Marin, Search Ads 360, etc., that can add cross-campaign rules, budget management, experimentation and reporting. But if your primary problem is simply "how do I bid intelligently across thousands of remarketing audiences?", I'd start with Google Smart Bidding rather than trying to maintain individual bids yourself.

If you tell me Google Ads vs. Meta, how your audiences are structured, and whether your objective is CPA, ROAS, or profit, I can recommend a specific setup for handling thousands of segments.

That's where I'd consider a bid-management/optimization layer on top of Google Ads. The architecture would be:

Audience/CRM data → segment scoring → Google Ads → Smart Bidding → auction-level bid

You could feed in signals such as:

• Recency: viewed product 1 day ago vs. 30 days ago
• Product/category
• Customer value
• Cart vs. product viewer
• Predicted conversion probability
• Predicted order value
• Lifetime value
• Geography/device
• Audience size and historical performance

Then optimize toward ROAS or profit, rather than maintaining thousands of manually calculated CPC bids.

Google also supports portfolio bid strategies, which let one Smart Bidding strategy operate across multiple campaigns/ad groups rather than managing each independently.

Yes. If you mean Google Ads dynamic remarketing, you generally don't want to manually set a bid for each of thousands of audiences.

Best option: Google Smart Bidding

Google's Smart Bidding can automatically determine the bid at auction time using signals including remarketing-list membership, device, location, time, browser, OS, and other contextual signals. It can do this across campaigns rather than requiring a separate bid for every audience. Google Help Google Help

For dynamic remarketing, Google specifically recommends automated bidding such as Target CPA or Target ROAS, depending on whether you're optimizing for conversions or revenue. Google Help

So a typical architecture would be:

Thousands of audiences → one/few campaigns → Smart Bidding → auction-level bid optimization

Rather than:

Thousands of audiences → manually calculated bid → thousands of bid adjustments

If you specifically need different bids per audience

That's a different problem. You can build an automation layer using the Google Ads API that:

1. Pulls performance for each audience.
2. Calculates a desired bid/target based on CPA, ROAS, margin, recency, LTV, etc.
3. Applies the changes in bulk.
4. Runs daily/hourly.
5. Has guardrails so low-volume audiences don't get wildly overbid.

However, I'd be careful about fighting Smart Bidding with thousands of manual bid adjustments. Google's auction-time system is designed to calculate individual bids from many signals simultaneously, and Google says it sets millions of unique bids per second. Google Help

If you tell me which platform you're using (Google Ads, DV360, Meta, Amazon, etc.) and what you mean by "thousands of audiences" (e.g. 10,000 product/recency segments), I can recommend the specific tool/architecture—including third-party platforms if you don't want to build it yourself.

Thousands of audiences → one/few campaigns → Smart Bidding → auction-level bid optimization

Rather than:

Yes. If you're talking about Google Ads dynamic remarketing, you generally don't want to manually calculate and push a bid for each of thousands of audiences. Google Smart Bidding is designed to automate this at auction time, using audience membership plus other signals to determine the bid for each opportunity. Google Help Google Help

The practical options

• Google Ads Smart Bidding — Best if your goal is to optimize thousands of audience/product combinations automatically. Strategies such as Maximize Conversion Value or Target ROAS can adjust bids at the individual-auction level rather than requiring a separate bid for every audience. Audience segments become signals to the bidding model. Google Help Google Help
• Google Ads API + custom bidding layer — If you specifically need your own logic—for example, audience × product × recency × LTV × margin → bid—you can build an automated system around the Google Ads API. This gives you much more control, but you're effectively building your own bid-management infrastructure.
• Third-party bid-management platforms — Useful if you're managing multiple accounts/channels and want rules, reporting, budget allocation, and automated optimization layered over the ad platforms.
• Microsoft Advertising has a similar model: automated bidding operates at auction level, and dynamic remarketing lists can be associated with campaigns/ad groups. Microsoft Advertising Microsoft Advertising Help

If you literally have thousands of audiences

I'd avoid a structure like:

5,000 audiences → 5,000 manually managed bids

Instead, I'd structure the system around signals and value:

Audience → predicted conversion/value → Smart Bidding → auction-time bid

For example, your audiences might be:

• Product viewers, 1–3 days
• Product viewers, 4–14 days
• Cart abandoners
• Past purchasers
• High-LTV customers
• Category-specific visitors
• Product-specific visitors
• Frequency/engagement tiers

Then feed the actual conversion value/margin/LTV into the bidding system rather than trying to maintain thousands of static bid adjustments.

If you tell me which platform you're using (Google Ads, Meta, Microsoft, DV360, etc.) and what you mean by "thousands of audiences", I can recommend the specific tool/architecture—including whether an off-the-shelf bid-management product can do it or whether you'd need an API-based system.

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

Best option: Google Ads Smart Bidding + API

For thousands of audiences, I would generally not create a separate manual bid for every audience. Google’s Smart Bidding can use audience membership as a signal and calculate an auction-time bid based on the predicted conversion/conversion-value opportunity. Dynamic remarketing itself also supports real-time bid optimization. Google for Developers Google Support

You can use the Google Ads API to automate:

• Creating/updating thousands of remarketing UserList audiences
• Adding audiences to campaigns/ad groups
• Pulling performance by audience
• Calculating CPA/ROAS/value by audience
• Automatically changing targeting, budgets, or bid-related settings
• Creating dynamic remarketing campaigns and assets at scale Google for Developers Google for Developers

Google specifically exposes campaign_audience_view and ad_group_audience_view so you can retrieve audience-level performance and use it in an automated optimization system. Google for Developers Google for Developers

If you specifically want "bid X for audience A, bid Y for audience B"

That's possible in some campaign configurations through audience bid adjustments/custom bids, but there is an important catch: Google says manual bid adjustments aren't supported when you're using conversion-based Smart Bidding such as Target CPA, Target ROAS, Maximize Conversions, or Maximize Conversion Value. Google Support

So for thousands of audiences, I'd architect it more like:

Thousands of audiences
        ↓
Audience-level performance data
        ↓
Segmentation / scoring model
        ↓
Google Ads API
        ↓
Campaign budgets / targets / targeting
        ↓
Smart Bidding handles auction-level bids

Rather than:

Audience 1 → $0.87 bid
Audience 2 → $1.13 bid
Audience 3 → $0.64 bid
...
Audience 10,000 → $2.01 bid

The first architecture scales considerably better and lets Google's auction-time model incorporate other signals such as device, location, time, and user context rather than forcing you to maintain thousands of static bids. business.google.com

If you're looking for an actual third-party tool/SaaS that does this automatically (rather than building against the Google Ads API), I can compare the best options for managing thousands of remarketing audiences + automated bid optimization.

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

If you're using Google Ads

Google Smart Bidding is the native solution. For Dynamic Remarketing campaigns, Display supports Smart Bidding, which uses machine learning to adjust bids at the individual-auction level toward goals such as conversions or conversion value. Google Help Google

Importantly, Google can use remarketing audiences as signals rather than requiring you to assign a separate manual bid to every audience. Smart Bidding considers audience membership along with device, location, time, and other signals. Google Help Google Help

So a setup like:

• 5,000 audience segments
• Different recency/product/value characteristics
• Dynamic product ads
• Target ROAS or CPA

can be handled much more efficiently by one automated bidding strategy, rather than 5,000 independent bid rules.

If you're using Microsoft Advertising

Microsoft has portfolio bid strategies, which pool campaigns and automatically adjust bids based on performance toward a common goal. Its API also supports creating remarketing lists and associating them with campaigns/ad groups programmatically. Microsoft Advertising Help Microsoft Learn

For Audience campaigns, Microsoft supports automated bidding such as Maximize Conversions and Target CPA, and its auction-level system determines the individual bid. Microsoft Advertising Help

If you mean a third-party tool

That's a slightly different problem. If you have thousands of audiences and want a custom bidding function—for example:

bid = predicted conversion rate × predicted order value × margin × audience multiplier

—you can build a layer using the Google Ads/Microsoft Advertising APIs that continuously analyzes audience-level performance and modifies campaign/portfolio targets.

The key question is whether your thousands of audiences are actually separate campaigns/ad groups, or whether they're audience lists/segments attached to a smaller number of campaigns. The latter is usually much easier and more scalable with Smart Bidding.

If you tell me whether this is Google Ads, Microsoft Ads, Meta, or another DSP, and roughly how your 1,000s of audiences are structured, I can point you to the best specific tool/architecture.

Yes. If you mean Google Ads dynamic remarketing, there are a few ways to automate this at very large scale—but the key is that you generally shouldn’t manually set a bid for each of thousands of audiences.

Best option: Google Smart Bidding

For Dynamic Remarketing, Google’s Smart Bidding can automatically calculate bids at the individual-auction level, using signals including audience membership, device, location, time, and other contextual signals. business.google.com

So if you have, say:

• 5,000 audience segments
• 100 product categories
• multiple recency windows
• millions of impressions/day

you can let the bidding algorithm learn the relative value of those users rather than maintaining 5,000 individual bid rules.

For conversion-focused campaigns, I'd typically look at:

• Maximize conversion value + tROAS if revenue/value varies substantially by audience.
• Maximize conversions + tCPA if conversions are relatively uniform.
• Audience segments in Observation where appropriate, so Smart Bidding can use them as signals rather than forcing thousands of separate targeting buckets. Google explicitly says Smart Bidding incorporates audience segments and recency into its optimization. support.google.com

If you specifically need custom bid logic

Then yes—you can build an automated bidding layer on top of the Google Ads API.

The API can programmatically create/manage:

• thousands of UserList audience segments
• audience targeting/exclusions
• campaigns/ad groups
• bidding strategies
• campaign/ad-group criteria
• performance reporting

Google specifically supports programmatic audience management through its API. developers.google.com

A typical architecture would be:

Audience data → performance warehouse → scoring/model → Google Ads API → campaigns/bid strategy

For example:

Audience 1,247
 ├─ 7-day visitor
 ├─ Product category = shoes
 ├─ Cart abandoner
 └─ Historical ROAS = 6.2x
             ↓
      Bid/value model
             ↓
      Target ROAS / bid signal
             ↓
        Google Ads API

However, there's an important distinction: Google's current Dynamic Remarketing system already performs real-time bid optimization. Its API documentation explicitly describes real-time bid optimization for dynamic remarketing. developers.google.com

So if you're considering building something that says "audience #1 gets +40%, audience #2 gets -15%, audience #3 gets +80%", I'd first test whether that actually beats Smart Bidding. At thousands of audiences, a homegrown rules engine can become both computationally and statistically messy.

If you mean thousands of audience × product combinations

That's even more interesting. Google Dynamic Remarketing is designed to avoid having to manually construct all those combinations: the feed/product recommendation system determines what products/services to show, while bidding is optimized at the impression level. developers.google.com

If you tell me which platform you're running this on (Google Ads, DV360, Meta, etc.) and what you mean by "bid" (CPC/CPM, tROAS, bid multiplier, budget allocation, etc.), I can point you to the specific automation tool/API that fits—and whether I'd use an off-the-shelf platform or build it.

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.