11 Best Amazon DSP Audience Templates to Test This Quarter

An Amazon DSP audience template is a repeatable segment strategy built inside Amazon Demand-Side Platform. It pairs a data source, targeting logic, and lookback window. Brand teams use it to deploy consistent tests without rebuilding every campaign.

Not all templates perform equally. The right choice depends on funnel stage, purchase cycle, and catalog depth. AmpliSell has managed Amazon DSP advertising across 1,000-plus clients, and this guide ranks 11 templates by practical value.

For a broader foundation, see The Definitive Guide to Amazon DSP and 9 Best Amazon DSP Use Cases for CPG Brands.

Key Terms

Amazon DSP

Amazon's Demand-Side Platform is a programmatic advertising platform. It lets brands buy display, video, audio, and CTV inventory using Amazon's first-party shopping and behavioral data, across Amazon-owned and third-party supply.

AMC (Amazon Marketing Cloud)

Amazon Marketing Cloud is a secure, privacy-safe clean room where advertisers run SQL queries across Amazon Ads signals. It's used to build custom reports and create custom audiences for DSP activation. AMC now retains data for up to 24 months.

Audience lookalike (similar audience)

A lookalike audience uses a seed segment of known customers. Amazon's machine learning then identifies new shoppers who share similar browsing, purchasing, and streaming behaviors across the ecosystem.

In-market audience

An in-market audience groups shoppers who have shown recent purchase intent in a specific product category. It's built from Amazon browsing, search, and purchase signals, typically within a 30-day window.

Retargeting

Retargeting in Amazon DSP re-serves ads to shoppers who previously interacted with a brand's product detail pages or brand store. It uses ASIN-level behavioral signals as the audience seed.

Frequency cap

A frequency cap sets a maximum number of times a unique user sees a specific ad within a defined time window. It prevents overexposure and protects budget efficiency across DSP campaigns.

CPM (Cost Per Mille)

CPM is the cost to serve 1,000 ad impressions. Amazon DSP buys inventory on a CPM basis, so audience efficiency is measured by how many qualified impressions each dollar buys.

View-through attribution

View-through attribution credits a conversion to a DSP impression the shopper saw but did not click. It's measured against a configurable window, typically 14 days. Sponsored Ads use click-based attribution by default.

Key Insight

Amazon DSP audiences are only as strong as the match between segment logic and purchase cycle. A 90-day lookback works well for consumables but may include cold traffic for high-consideration durables. Matching the window to the category is the biggest lever brands miss.

The 11 Best Amazon DSP Audience Templates

1. ASIN-Based Viewed-Not-Purchased Retargeting

Quick Summary

This template retargets shoppers who visited a product detail page but did not convert. It uses ASIN-level behavioral signals with a lookback window of up to 90 days. It's the highest-intent audience in Amazon DSP and the logical first campaign for any brand new to the channel.

Viewed-not-purchased (VNP) audiences capture shoppers in active consideration. They've already found the product, read the listing, and moved on without buying. DSP display and video ads close that gap across Amazon-owned and third-party inventory, including the Amazon Publisher Services network.

In our testing, VNP audiences deliver the lowest cost-per-detail-page-view of any DSP segment. They're also the fastest path to measurable ROAS. Across our book of business, this template opens nearly every new DSP engagement before advanced segments are added.

How to Build It

• Data source: Amazon DSP Audience Builder, ASIN-level shopping interactions.
• Select "Viewed" interaction type for each target ASIN.
• Exclude "Purchased" interaction to isolate non-converters.
• Set lookback window to 30 days for fast-moving categories; 60-90 days for considered purchases.
• Audience minimum: 5,000 users for activation.

Pros and Cons

• Pros: Highest intent of any DSP segment; easy to build; fast to scale; strong ROAS signal within two weeks of launch.
• Cons: Audience size is capped by the brand's own traffic volume; it saturates quickly without proper frequency caps.

When to Use It

• Any brand running DSP for the first time.
• Launch phases where conversion rate on new ASINs needs a boost.
• Peak seasons (Prime Day, Q4) when traffic spikes create large retargetable pools.

2. Brand Purchaser Retargeting (Cross-Sell and Upsell)

Quick Summary

This template targets past brand buyers with ads for complementary or higher-margin SKUs. It drives repeat revenue and is typically the highest-ROAS line item in a multi-SKU DSP account.

Brand purchaser retargeting uses the "Purchased" interaction type at the ASIN level. It builds a first-party-equivalent audience from Amazon's transaction data. A buyer of Product A is a warm prospect for Product B when both share a use case or ingredient profile.

This template powers cross-sell, upsell, Subscribe and Save, and seasonal re-engagement in one segment. According to Velocity Sellers, cross-sell lines routinely produce 8 to 12 ROAS for strong cross-sell catalogs. For Maelove, a skincare brand that reached $3.6M in 11 months, purchaser retargeting drove repeat sales as the catalog expanded.

How to Build It

• Data source: Amazon DSP Audience Builder, "Purchased" interaction type per ASIN.
• Build separate audiences for hero SKUs; combine into a single purchaser pool at order level.
• Exclude purchasers of the promoted SKU to avoid cannibalizing organic repeat sales.
• AMC SQL hint: join dsp_impressions with purchases to isolate SKU A buyers who haven't purchased SKU B.

Pros and Cons

• Pros: Highest-ROAS segment for multi-SKU brands; direct path to LTV growth; easy Subscribe and Save angle.
• Cons: Audience size depends on existing sales volume; single-SKU brands have limited cross-sell angles; requires creative tailored to the cross-sell message.

When to Use It

• Brands with two or more complementary SKUs generating steady monthly sales.
• Subscribe and Save enrollment pushes for consumable categories.
• Post-launch phases once a sufficient purchaser pool has accumulated.

3. In-Market Audience Targeting

Quick Summary

In-market audiences group shoppers showing active purchase intent in a specific category. They're built from Amazon's browsing, search, and purchase signals. This makes them the most scalable mid-funnel segment available natively in Amazon DSP.

Amazon's in-market audiences draw from real shopping behavior, not modeled proxies. Categories span thousands of types, from "Athletic Nutrition" to "Small Kitchen Appliances." Each segment refreshes on a roughly 30-day rolling window.

Across our book of business, in-market audiences perform best paired with category-switching creative. Generic brand awareness messaging underperforms. The audience has intent; the creative job is to direct it toward the brand.

How to Build It

• Data source: Amazon Audiences library inside DSP.
• Navigate to Audiences, select "Amazon Audiences," browse or search by product category.
• Layer multiple adjacent in-market categories for broader but still intent-aligned reach.
• Combine with contextual targeting on the same line item to reinforce relevance.

Pros and Cons

• Pros: Large scale; no build time; refreshes automatically; strong mid-funnel signal.
• Cons: Less precise than ASIN-level retargeting; CPMs can be competitive in high-demand categories; overlaps with competitor brands in the same segment.

When to Use It

• Prospecting campaigns for brands with established conversion rate data.
• Category expansion or new ASIN launches needing rapid top-of-funnel reach.
• CTV and streaming placements where intent-based targeting is more practical than ASIN retargeting.

4. Lifestyle Audience Targeting

Quick Summary

Lifestyle audiences target shoppers based on persistent interest and life-stage signals. Examples include "fitness enthusiasts" and "outdoor adventurers." They're the right tool for brand-building campaigns aimed at affinity-matched audiences, not active in-category browsers.

Where in-market audiences capture immediate intent, lifestyle audiences capture identity. They're built from months of behavioral signals and are broader and slower to convert. They're essential for brands with longer purchase cycles or a well-defined customer lifestyle profile.

Amazon's lifestyle segments include health and wellness, pet owners, home improvement enthusiasts, and new parents, among hundreds of options. In our experience, these audiences work best on CTV, streaming audio, and premium display placements. They pair well with in-market as an upper-funnel feeder.

How to Build It

• Data source: Amazon Audiences library, "Lifestyle" category.
• Select one to three lifestyle segments closely aligned with the brand's customer persona.
• Run on separate line items from in-market to isolate performance signals.
• Set frequency caps at 3-5 impressions per user per week to avoid fatigue.

Pros and Cons

• Pros: Massive scale; stable audience composition; strong fit for CTV/audio; builds long-term brand recall.
• Cons: Lower direct conversion rates; longer measurement windows needed (14-30 days view-through); less precise than behavioral retargeting.

When to Use It

• Upper-funnel brand awareness campaigns for new-to-Amazon brands.
• CTV and streaming audio line items where user intent signals are unavailable.
• Seasonal campaigns targeting life-stage audiences (new parents before Q4, fitness audiences in January).

5. AMC Custom Audience (Multi-Touch SQL Segment)

Quick Summary

AMC custom audiences use SQL queries inside Amazon Marketing Cloud to combine sponsored ads, DSP impressions, purchases, and advertiser-provided data. They enable precision segments no native DSP builder can replicate.

The AMC custom audience feature is generally available across managed accounts. It lets brands write SQL against their full ad signal history to identify multi-touchpoint audiences. One common use case: shoppers exposed to a Sponsored Brand video and a DSP display ad without converting get re-served urgent creative.

Amazon now offers an AI-powered natural-language query generator inside AMC, cutting build time significantly. In testing with advanced brand partners, AMC custom audiences produced 3 to 5 times better ROAS than native DSP segments. See also 11 Best Amazon AMC SQL Templates and The Definitive Guide to Amazon Marketing Cloud (AMC).

How to Build It

• Data source: AMC instance with 24 months of ad signal history.
• Write a SQL query joining dsp_impressions, sponsored_ads_traffic, and purchases tables.
• Example logic: SELECT users with a DSP impression, no 14-day purchase, and a Sponsored Ads click in the prior 30 days.
• Export audience to DSP via AMC's audience activation interface.
• Audience activates automatically on relevant DSP line items.

Pros and Cons

• Pros: Most precise audience type available; combines signals no other template can; supports year-over-year seasonal rebuilds with 24-month data retention.
• Cons: Requires AMC access and SQL fluency; build time is longer; a 10,000-user minimum applies; not available to all account tiers.

When to Use It

• Brands spending enough on DSP to generate meaningful impression data for cross-signal queries.
• Re-engagement campaigns targeting shoppers exposed across multiple touchpoints.
• Seasonal rebuilds where prior-year purchaser signals need to be isolated precisely.

6. Lookalike (Similar Audience) Expansion

Quick Summary

Amazon DSP's "similar audiences" feature uses machine learning to find shoppers mirroring existing best customers. It scales prospecting using real Amazon signal data.

Since Amazon DSP launched similar audiences, the template has become a core prospecting tool. The platform analyzes the seed audience's shopping, browsing, and streaming behaviors. It then surfaces new users sharing those patterns across the Amazon ecosystem.

Advertisers activate it by selecting a qualifying audience and enabling the "Reach similar audiences" toggle on the line item. In our testing, lookalike audiences seeded from AMC-defined high-LTV buyers outperform those seeded from generic purchaser pools. We've seen conversion rates 1.5 to 2 times higher when the seed is restricted to 90-day buyers.

How to Build It

• Data source: An existing DSP audience or AMC-built purchaser segment as the seed.
• Seed must meet Amazon's minimum user threshold for similar audience generation.
• In the DSP line item editor, select the seed audience and check "Reach similar audiences."
• For AMC-powered lookalikes, use the rule-based lookalike audience API.

Pros and Cons

• Pros: Scales prospecting with Amazon's first-party signal quality; better signal than third-party DMP lookalikes; flexible seed options.
• Cons: Performance is dependent on seed quality and size; less transparent than explicit behavioral targeting; overlaps possible with in-market segments.

When to Use It

• Brands ready to expand beyond retargeting pools and first-party data.
• New category entrants who need to grow awareness without a large existing audience base.
• Scaling proven bottom-funnel creative to a net-new upper-funnel audience.

7. Competitor ASIN Viewer Targeting

Quick Summary

This template targets shoppers who recently viewed competitor product pages, intercepting consideration before it ends in a competitor purchase. It's a direct conquesting play requiring a clear differentiation message.

Amazon DSP lets brands build audiences from the "Viewed" interaction type on competitor ASINs. This gives direct visibility into shoppers actively comparing category products. As outlined by Tinuiti's DSP audience guide, it's one of the most effective ways to intercept consideration before it converts elsewhere.

The key is selecting competitor ASINs that share a realistic price point and use case. Generic brand messaging underperforms here; ads that convert highlight a formulation, certification, or price-per-serving advantage relevant to the competing product.

How to Build It

• Data source: Amazon DSP Audience Builder, "Viewed" interaction type on competitor ASINs.
• Add up to 1,000 ASINs per audience group; prioritize top-ranking competitor products.
• Set lookback window to 14-30 days for highest intent; extend to 60 days for considered categories.
• Run on a separate line item from own-brand retargeting to keep bidding and performance clean.

Pros and Cons

• Pros: Directly intercepts active category shoppers; strong fit for brands with a clear price-value story; measurable with purchase intent KPIs.
• Cons: Higher CPMs in competitive categories; creative must be differentiation-focused to convert; audience overlap with in-market segments can inflate reach metrics.

When to Use It

• Brands with a clear, articulable point of difference versus the category leader.
• New entrants trying to capture trial from established competitor buyers.
• Promotional periods when a price or bundle advantage is available to highlight.

8. Lapsed Buyer Re-Engagement

Quick Summary

This template identifies past buyers who haven't repurchased in the most recent period. It re-engages them with retention-focused creative before the purchase cycle fully lapses.

A lapsed buyer segment combines a broad purchaser audience (180-day buyers) with an exclusion of the most recent 60-day purchasers. The result is buyers who converted once but whose repurchase window has passed. Bellavix's retargeting guide notes the purchase cycle must inform lookback window settings for this segment.

In our experience, lapsed buyer campaigns perform best when creative offers a tangible reason to return. Options include a new product, improved formula, bundle offer, or replenishment reminder. For Maelove, where product cycles run 60-90 days, a 75-day lapsed buyer window produced the strongest re-engagement rates.

How to Build It

• Data source: Amazon DSP Audience Builder, "Purchased" interaction type.
• Create a broad purchaser audience (120-180 days) as the base.
• Add an exclusion for purchasers in the most recent 30-60 days.
• AMC SQL hint: SELECT users with a purchase older than X days and no repeat purchase in the last Y days.
• Adjust window lengths to match the product's typical repurchase cycle.

Pros and Cons

• Pros: Directly addresses churn risk; warmer than cold prospecting; strong Subscribe and Save enrollment angle for consumables.
• Cons: Audience size depends on historical sales volume; requires creative investment for retention messaging; shorter repurchase cycles shrink the lapsed window quickly.

When to Use It

• Consumable brands with predictable repurchase cycles (supplements, skincare, food).
• Brands launching a reformulation or new SKU that would appeal to existing buyers.
• Pre-peak season campaigns aimed at reactivating buyers before the gifting window opens.

9. Contextual Keyword and Category Targeting

Quick Summary

Contextual targeting serves ads based on the content a shopper is currently viewing. It uses Amazon's taxonomy of over 40,000 categories and real-time keyword analysis, without relying on user identity or cookies.

Amazon DSP's contextual keyword targeting places ads alongside content matched to specific keywords or category nodes. It works on Amazon.com and across third-party supply. Amazon's AI accounts for relationships between text, images, and video, according to the Amazon Ads contextual targeting announcement.

This makes contextual one of the most durable targeting strategies as third-party identifiers continue to deprecate. We've used it most effectively for brands entering new categories or running CTV inventory. It pairs well with lifestyle audiences to build a combined signal without inflating CPMs.

How to Build It

• Data source: Amazon's product taxonomy (browse nodes) and keyword-based content signals.
• In DSP, navigate to line item targeting and select "Contextual Targeting."
• Choose relevant browse node categories or input freeform keywords describing the target content environment.
• Available on Amazon.com placements and third-party supply including publisher network inventory.

Pros and Cons

• Pros: No identity dependency; works on third-party supply; future-proof against cookie deprecation; broad reach at competitive CPMs.
• Cons: Less precise than behavioral audiences; conversion tracking relies more on view-through attribution; harder to measure direct purchase lift.

When to Use It

• Awareness campaigns where identity-based targeting is unavailable (CTV, streaming audio, open web).
• Brands with strong visual creative that performs well in editorial content environments.
• Privacy-safe targeting strategies where advertiser data governance requirements prohibit behavioral targeting.

10. Competitor Purchaser Conquest

Quick Summary

This template targets shoppers who have already purchased a competitor's product. It reaches confirmed category buyers while brand loyalty is still forming. A compelling reason to switch can drive meaningful trial.

Competitor purchaser targeting uses the "Purchased" interaction on competitor ASINs. It builds an audience of shoppers who transacted with a rival brand. This is a higher-bar audience because the shopper has already proven willingness to buy in the category.

The creative challenge is persuading a competitor customer to trial something new. In our testing, these audiences respond best to social proof signals such as review counts, ratings, and certifications, plus a trial-lowering offer. We've seen this template drive new-to-brand acquisition for Condition 1, a brand that grew revenue 152% in 6 months.

How to Build It

• Data source: Amazon DSP Audience Builder, "Purchased" interaction on competitor ASINs.
• Prioritize ASINs from category leaders with high review counts, indicating a large buyer pool.
• Set lookback window to 90-180 days to capture buyers still in active repurchase cycles.
• Exclude own-brand purchasers at the order level to avoid waste.

Pros and Cons

• Pros: Reaches confirmed category buyers; identifies the exact purchase-cycle timing of competitor customers; strong trial-conversion potential.
• Cons: CPMs run higher than viewer audiences; creative must be differentiated; audience size is capped by competitor ASIN traffic.

When to Use It

• Brands with a clear quality, price, or ingredient advantage over specific competitors.
• Subscribe and Save categories where switching costs are low and repurchase cycles are regular.
• New entrants disrupting an established category with a better formulation or price-per-unit story.

11. Amazon Audiences: Shopping Insights (Predictive and Interest-Based)

Quick Summary

Amazon's interest-based and predictive segments combine observed shopping signals with machine-learning inference. They identify shoppers most likely to purchase in a category, even before those shoppers have actively browsed it. This gives brands access to demand that hasn't surfaced yet in behavioral data.

Amazon Audiences includes interest-based and predictive segments that go beyond observed behavior. These audiences use Amazon's signal graph to model which users are heading toward a category purchase. As noted in DSP Advertiser's audience type guide, predictive audiences work well for long-consideration categories such as electronics, mattresses, and fitness equipment.

Across our book of business, interest-based audiences perform best with a sequential creative strategy. A broad awareness creative runs first, then a tighter retargeting creative re-serves after the shopper visits the product page. This sequencing converts the interest signal into a behavioral signal before the purchase window closes.

How to Build It

• Data source: Amazon Audiences library, "Interest-Based" and "Predictive" subcategories.
• Browse by category or use the Amazon Audiences search tool to find relevant segments.
• Layer with demographic targeting (age, household income) to narrow if CPMs are excessive.
• Use the overlapping audiences tool to identify which segments share the most users with existing purchaser audiences before spending.

Pros and Cons

• Pros: Captures demand before it reaches Sponsored Ads; machine-learning-powered; no manual signal collection needed; strong CTV and video fit.
• Cons: Less directly measurable than behavioral retargeting; longer attribution windows needed; audience composition is inferred rather than explicitly observed.

When to Use It

• High-consideration categories where the purchase journey starts far before a search session.
• CTV and streaming video campaigns where upper-funnel demand capture is the KPI.
• Brands with strong video creative ready to educate and build intent before conversion campaigns run.

Pro Tip

Running all 11 templates simultaneously isn't the goal. Start with templates 1, 2, and 3 (VNP retargeting, brand purchaser, in-market), then add AMC custom and lookalike after two weeks. Introduce prospecting and conquest last, once retargeting pools are fully optimized.

How the 11 Templates Compare

Audience Template

Funnel Stage

Data Source

Best KPI

Effort to Build

1. ASIN Viewed-Not-Purchased

Lower funnel

DSP ASIN behavioral

ROAS / Detail page visits

Low

2. Brand Purchaser (Cross-Sell)

Lower funnel / Retention

DSP ASIN purchased

ROAS / Repeat purchase rate

Low

3. In-Market

Mid funnel

Amazon Audiences library

New-to-brand purchases

Low

4. Lifestyle

Upper funnel

Amazon Audiences library

Brand impression share / VCR

Low

5. AMC Custom (Multi-Touch SQL)

Mid-to-lower funnel

AMC cross-signal SQL

ROAS / Incremental revenue

High

6. Lookalike / Similar Audience

Upper-to-mid funnel

DSP seed + ML expansion

New-to-brand CPO

Medium

7. Competitor ASIN Viewer

Mid funnel

DSP ASIN behavioral (competitor)

New-to-brand purchases

Medium

8. Lapsed Buyer Re-Engagement

Retention / Lower funnel

DSP ASIN purchased + exclusion

Repeat purchase rate / Subscribe

Medium

9. Contextual Keyword/Category

Upper funnel

Amazon content taxonomy

CPM efficiency / Viewability

Low

10. Competitor Purchaser Conquest

Mid funnel

DSP ASIN purchased (competitor)

New-to-brand CPO

Medium

11. Interest-Based / Predictive

Upper funnel

Amazon Audiences ML inference

VCR / Brand search lift

Low

Key Data Point

Amazon Marketing Cloud now retains ad signal data for 24 months, up from 13 months, according to the AMC 2026 platform guide. This enables year-over-year seasonal audience rebuilds and longer purchase-cycle analysis. Neither was practical before the retention window expanded.

Start Here: First Steps for Testing DSP Audience Templates

1. Audit existing ASIN traffic. Confirm key ASINs have at least 5,000 unique detail page visitors in the target lookback window before committing to retargeting.
2. Map the purchase cycle. Determine the average days between first browse and purchase for the category. This sets the correct lookback windows for retargeting, lapsed buyer, and cross-sell templates.
3. Launch templates 1 and 2 first. VNP retargeting and brand purchaser are the fastest to build, lowest in CPM competition, and most directly measurable. Run both for two weeks before expanding to prospecting.
4. Request AMC access. If not already set up, request access through an Amazon Ads account manager or an Amazon DSP advertising partner. AMC unlocks the precision of templates 5, 6, and 8.
5. Set frequency caps from day one. Apply a maximum of 5-7 impressions per user per week on retargeting line items and 3-5 on awareness line items. Overexposure inflates CPM costs before campaigns have enough data to optimize.

Example

Then I Met You is a beauty brand that grew 42% in two months with AmpliSell. Its DSP strategy opened with a VNP segment on hero SKUs alongside an in-market audience for prestige skincare browsers. Brand purchaser cross-sell launched in week three once the purchaser pool was large enough.

Frequently Asked Questions

What is an Amazon DSP audience template?

An Amazon DSP audience template is a repeatable segment strategy built inside Amazon DSP. It pairs a data source, targeting logic, and lookback window. Brands use it to deploy consistent audience tests without rebuilding each campaign from scratch.

How much does Amazon DSP cost to access audience targeting?

Managed-service Amazon DSP requires a minimum spend set by Amazon Ads; self-service DSP is available at lower minimums through select partners. CPM rates vary by audience type, placement, and category competition. Brands should plan budgets based on impression volume goals, not a flat monthly fee.

What is the difference between in-market and lifestyle Amazon DSP audiences?

In-market audiences reflect near-term purchase intent, built from recent Amazon browsing and search signals. Lifestyle audiences reflect longer-term affinity patterns, such as consistent interest in health and wellness. Lifestyle signals span months of behavior rather than active shopping sessions.

Can Amazon DSP retarget shoppers who viewed a product but didn't buy?

Yes. Amazon DSP's viewed-not-purchased audience targets shoppers who visited a detail page but didn't convert, with a lookback window up to 90 days. It works across Amazon-owned and third-party supply.

What is an AMC custom audience and how is it different from a standard DSP audience?

An AMC custom audience uses SQL queries in Amazon Marketing Cloud, combining sponsored ads, DSP impressions, and purchase signals. Standard DSP audiences rely on a single signal. AMC audiences combine touchpoints, targeting users who saw a Sponsored Brand ad and a DSP ad but never converted.

What is a lookalike audience on Amazon DSP?

A lookalike audience, also called a similar audience, is built when Amazon's machine learning analyzes a seed of existing customers. It then finds new shoppers who share similar browsing, purchasing, and streaming behaviors. Advertisers activate this by checking the "Reach similar audiences" option on a line item.

How does contextual targeting in Amazon DSP work without cookies?

Amazon DSP's contextual targeting matches ads to content based on real-time page signals. It uses Amazon's taxonomy of over 40,000 product categories and keyword-level analysis, not user identity or cookies. It works on Amazon.com and third-party supply, making it durable as third-party identifiers deprecate.

‍