
Not every customer impacts your bottom line the same way—and most advertisers know it. In most cases, a small portion of your audience—roughly 20–30%—can drive up to 70–80% of total sales. Identifying and reaching these high-value segments, however, is easier said than done. Standard Amazon Advertising tools offer useful but limited targeting options, such as:
While effective for broad reach, these pre-built audiences lack the precision needed to truly optimize ad spend. The result? You might be showing premium product ads to budget-conscious browsers, or missing opportunities to cross-sell to your most loyal customers. This is where Amazon Marketing Cloud (AMC) changes the game—allowing sellers to build custom, high-value audiences defined by actual spending patterns, loyalty, and cross-product engagement.
With AMC’s High Value Audiences solution, advertisers can now granularly segment their target audience by spend percentiles, new-to-brand purchases, ASIN engagement, and even cross-category purchase paths. Let’s explore how leading brands use Amazon Marketing Cloud solutions to build high-converting audiences (without coding) that power smarter media investment and stronger customer relationships.
High-value audiences (HVA) refer to a segment of customers with the highest spending potential, purchase frequency, and lifetime value to your brand. These shoppers:
By identifying such high-value audiences, you can understand which shopper segments are worth pursuing in the long term and allocate advertising budget more effectively. Instead of chasing every click, you can bid more aggressively on those likely to convert and retain, because:

Amazon Marketing Cloud (AMC) builds high-value audiences by analyzing a vast range of behavioral, transactional, and contextual signals across Amazon and beyond. It merges data from Amazon’s ecosystem, your first-party sources, and trusted third-party partners to create multidimensional audience profiles far more detailed than standard ad-platform targeting.
| Data Source | Available Insights |
|---|---|
| Amazon Ads (Sponsored Brands, Sponsored Products, Sponsored Display, and Amazon DSP) | Clicks, impressions, ASIN-level conversions, keyword interactions |
| Amazon Streaming Platforms | Ad impressions, clicks, and video views on Amazon Prime Video and Amazon Live. |
| Amazon Behavioral Insights | Product detail page views, add-to-cart actions, purchase events |
| First-Party Data | Hashed email lists, CRM data, website visitor information |
| Third-Party Providers | Higher-fidelity data from Amazon Publisher Direct partnerships. Real-time data (device type, geographic location, Website URL, etc.) from CDP platforms (Salesforce, Adobe, Tealium) |
These signals now power high-value custom audience creation across all major Amazon ad formats—a capability previously exclusive to Amazon DSP campaigns only. After the last update announced at Unboxed 2024, advertisers can create AMC audiences within Sponsored Products, Sponsored Brands, and Sponsored Display campaigns (and can integrate these AMC audiences into their active Amazon Ads campaigns for precision targeting). Additionally, Amazon Marketing Cloud solutions let advertisers set/control audience refresh frequency, ensuring that a custom list of audiences stays current and contextually relevant as buyer behaviors evolve.

Using AMC’s query builder and “code-free” high-value audience solution, advertisers can combine any mix of these signals to build custom, high-value audiences for tailored use cases. Two core audiences created by AMC for highly-targeted advertising are:
As an Amazon Marketing Cloud Consulting Partner, We Design Full-funnel Audience Strategies—Connecting AMC Insights with Sponsored Ads, DSP, and Retargeting Workflows that Drive Conversions and Lifetime Value.
Understanding which audiences to build is as important as knowing how to build them. Let’s explore the most impactful audience types that every brand should leverage with Amazon Marketing Cloud advertising solutions.
| Audience Type | Description | Why They Matter | When to Target Them Ideally |
|---|---|---|---|
| Purchaser Lookalike Audiences | New shoppers who share behavioral and demographic characteristics with your existing buyers | Delivers higher ROAS compared to generic targeting; expands reach beyond your current customer base to find high-propensity buyers at scale | Acquisition campaigns, product launches, category expansion, scaling periods (Q4, Prime Day), when rule-based audiences reach saturation |
| Subscriber Lookalike Audiences | Audiences modeled after existing Subscribe & Save customers, identifying shoppers likely to commit to recurring purchases | Subscribers have higher lifetime value than one-time purchasers; these audiences prioritize long-term revenue over single transactions | Promoting subscription-eligible products, nurturing trial-to-subscription conversions, and building predictable recurring revenue streams |
| New-to-Brand (NTB) Buyers | First-time buyers who recently made their initial purchase from your brand (typically within 30-90 days) | Fresh customer acquisition is critical for sustainable growth; these customers haven’t yet developed competing brand loyalties, thus they provide the highest opportunity for repeat purchase nurturing | Post-purchase follow-up campaigns (7-30 days after first order), complementary product recommendations, Subscribe & Save conversion campaigns, and building loyalty early in the customer journey |
| Brand Loyalists | Multi-category or multi-product purchasers who have bought across different product lines within your brand portfolio | They already trust your brand and drive higher lifetime value. Offer greater conversion rates and are more receptive to cross-sell and upsell opportunities | Cross-category promotions, brand expansion into new categories, bundle offers, referral program recruitment, limited edition/exclusive product releases |
| Cart Abandoners | Shoppers who added products to their cart but exited without completing the purchase | Represents immediate lost revenue with demonstrated high intent, higher conversion rates than cold audiences | Within 24-72 hours of abandonment for maximum intent recency; during promotional periods to provide urgency; avoid targeting if the customer subsequently purchased a substitute product |
| Add to Cart/Wishlist Targets | Users who added items to cart or saved to wishlist but haven’t purchased within a defined lookback window (for example, 7-30 days) | Strong purchase intent signal—these shoppers are actively considering your product; wishlist additions indicate future purchase planning | Product-specific promotions or discount campaigns, inventory clearance events, seasonal gift-giving periods (Mother’s Day, holidays), Lightning Deals, and limited-time offers |
| Frequent Product Page Visitors | Shoppers who viewed a specific product detail page (PDP) 2-3+ times without purchasing | Multiple views indicate serious consideration but potential objections (price, reviews, features); conversion rate increases when retargeted with social proof or incentives | After 3+ PDP views within 14 days, when new reviews/ratings are added, during price reductions or coupon availability, when launching enhanced A+ content, or new product images |
| High-Value Event Purchasers | Shoppers who bought during high-traffic events (e.g., Prime Day, Black Friday, Cyber Monday) or major promotions | They have already demonstrated a willingness to buy during peak periods, making them more receptive to new offers and more likely to become repeat buyers or brand advocates when nurtured | Retarget several weeks after their purchase. Responsive to exclusive discounts, loyalty program invitations, or early access to new products |



Let our Amazon Marketing Cloud Experts Handle Everything—From Setup to Ongoing Query Optimization, So You Can Focus on Strategy.
Custom audience creation using Amazon Marketing Cloud advertising solutions seems straightforward; however, during its implementation, advertisers make common mistakes that can waste Amazon PPC budget and dilute campaign performance. Understanding these pitfalls—and how to avoid them—is just as important as mastering the technical implementation.
Problem: Creating dozens of hyper-specific micro-segments that lack sufficient scale and complicate campaign management. Advertisers get excited by AMC’s capabilities and build 20+ audiences with overlapping criteria, making it impossible to gather statistically significant data or manage efficiently.
Solution: Don’t create too many niche audience segments. Start with 5-7 core audiences aligned to clear business objectives:
Consolidate where possible: Instead of 5 separate cart abandonment audiences by product line, start with one and segment by creative/messaging.
Graduate to complexity: Once core audiences perform consistently, then explore atomic segmentation
Problem: Multiple campaigns targeting overlapping audiences lead to internal bidding competition, inflated CPCs, and attribution confusion. For example, running separate campaigns for “cart abandoners,” “product page viewers,” and “high-intent shoppers” when 60-70% of these audiences overlap.
Solution: Run AMC overlap analysis queries before launching campaigns.
Example Query: Compare “Cart Abandoners” vs “Frequent PDP Visitors” to identify intersection percentage
Implement hierarchical audience exclusions:
Establish a clear audience hierarchy based on value: Cart abandoners > Recent purchasers > Engaged browsers > Lookalikes > Cold audiences.
Problem: Creating custom audiences in AMC once and never refreshing them, causing segments to include users who’ve already converted, are no longer in-market, or whose behavior has changed significantly. You end up retargeting customers who have already purchased, wasting budget on outdated intent signals while missing fresh high-value prospects.
Solution: Regularly refresh your audience segments depending on their type:
| Audience Type | Recommended Refresh Frequency | Rationale |
|---|---|---|
| Cart Abandoners & High-Intent shoppers | Daily to 3x/week | Intent decays rapidly; hence, target them within a few days of first interaction to increase the likelihood of conversions. |
| Recent Purchasers | Weekly | Balances recency with audience stability |
| Loyal Customers/Top Spenders | Bi-weekly to Monthly | More stable segment; less frequent refresh needed |
| Lookalike Audiences | Bi-weekly | Allows the algorithm to incorporate the latest behavioral patterns |
| Seasonal/Event Audiences | One-time or event-triggered | Prime Day shoppers are refreshed annually (prior to the event) |
Problem: Launching new audiences with new creative, new bidding strategies, and new campaign structures all at once, making it impossible to identify what’s driving results (or problems).
Solution: Adopt a single-variable testing methodology
Maintain a testing log with dates, changes, hypotheses, and results to build institutional knowledge.
Problem: Discovering a high-performing audience (e.g., cart abandoners delivering 5x ROAS) but keeping the budget capped or spread thin across too many audiences, preventing scaling of what works.
Solution: Adopt the 70-20-10 budget allocation framework:
Amazon Marketing Cloud advertising solutions offer advanced measurement and targeting capabilities; however, effectively managing them requires deep analytical expertise and operational bandwidth. For brands lacking specialized expertise or resources in-house, working with an agency is the more practical solution.
By offering targeted Amazon Marketing Cloud analytics services, we help brands unlock AMC’s full potential without the learning curve. Our Amazon Marketing Cloud solutions for agencies and brands include:
Whether you’re new to AMC or looking to scale, our tailored Amazon Marketing Cloud services are designed to support your business at every growth stage. We empower you to fully capitalize on AMC’s advanced features for smarter audience management and improved RoAS.

Ravi Kant is the Vice President of the eCommerce and Photo Editing Division at SunTec India. With over two decades of global experience, he spearheads large-scale digital commerce initiatives that drive operational excellence and measurable ROI for global businesses. His expertise spans eCommerce strategy, digital transformation, and data-driven performance optimization.