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AWS Retail Global

Mercado Libre

Marketing Personalization

High-quality visuals significantly shape a potential customer’s experience, yet creating compelling display ads remains a challenge for many vendors. Considering that 80% of Mercado Libre’s sellers are SMBs, they were looking for a solution tailored to empower SMBs and accelerate their growth on the platform through its ad products.

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7 countries
90,000+
The click-through rate in Hispanoamerica also witnessed a 25% increase compared to the average of non-GenAds display ads.
higher CTR compared to non-GenAds campaigns 25%

Reported impact

Business outcome

45% More Impressions and 25% Higher Click-Through Rate with GenAds After an initial expansion phase with a small batch of invited sellers and a few countries, Mercado Libre's GenAds launched unrestrictedly mid-Q2 and has already seen remarkable results. GenAds has been rolled out across seven Latin American countries, including the region’s three largest economies: Brazil, Mexico, and Argentina. Key reported metrics include today count on GenAds, including Brazil, Mexico, and Argentina 7 countries; 7 countries; increase in display impressions with GenAds 45%.

  • Revenue Growth
  • Speed to Market

Solution

Mercado Libre Reshapes Retail Media with AWS Partner Mutt Data and Stability AI in Amazon Bedrock Mercado Libre has partnered with AWS Partner Mutt Data to address the challenge of producing high-performing banner ads with generative artificial intelligence (AI), for dozens of thousands of smaller sellers. Mercado Libre developed GenAds, an innovative solution that automates the creation of compelling product images, streamlining the process for sellers and enhancing their market presence with image-generating AI. Through GenAds, Mercado Libre helped small sellers through image generation for advertising, enabling sellers of all sizes to attract customers, increase click-through rates (CTR) by an average of 25%, and boost sales effectively. GenAds: A New AI-Driven Product Imaging Service Mercado Libre selected AWS Partner Mutt Data to develop a cutting-edge solution to streamline the creation of high-quality product images for its sellers.

Data flow

Source data enters the Mercado Libre workflow through its application services, stored or indexed in Amazon S3, Amazon DynamoDB, processed with Amazon Bedrock, Stability AI, Stable Diffusion.

Solution architecture

7 components · 2 layers
  1. Compute
    • Amazon Bedrock Hosts the foundation models and inference APIs that power the generative AI features.
    • Stability AI Supplies the image generation model used to create creative assets or ads.
    • Stable Diffusion Generates images from prompts for creative or marketing workflows.
    • Claude 3 Sonnet Serves as the primary large language model for generation or analysis tasks.
    • Claude 3 Serves as the primary large language model for generation or analysis tasks.
  2. Storage
    • Amazon S3 Stores raw, intermediate, or curated files and datasets.
    • Amazon DynamoDB Stores operational application data with low-latency access.

Architecture clues

  • 45% More Impressions and 25% Higher Click-Through Rate with GenAds After an initial expansion phase with a small batch of invited sellers and a few countries, Mercado Libre's GenAds launched unrestrictedly mid-Q2 and has
  • Finally, an API allows the front end to retrieve and display these banners for ad campaign proposals.
  • GenAds has been rolled out across seven Latin American countries, including the region’s three largest economies: Brazil, Mexico, and Argentina.
  • Its infrastructure ensures high availability, enabling Mercado Libre to handle fluctuating workloads and consistently generate top-quality images, even during peak demands", Moretti explains.
  • Pablo Moretti, vice-president of Mercado Libre’s Marketplace, details that the company, along with Mutt Data, decided to use Amazon Bedrock , a fully-managed service that offers developers access to high-performing found
  • The platform also supports rapid innovation — Mercado Libre can test and implement updates like model transitions with minimal cost and effort, keeping pace with the dynamic retail environment.

Evidence from the source

7 countries
90,000+
GenAds: A New AI-Driven Product Imaging Service Mercado Libre selected AWS Partner Mutt Data to develop a cutting-edge solution to streamline the creation of high-quality product images for its sellers.
High-quality visuals significantly shape a potential customer’s experience, yet creating compelling display ads remains a challenge for many vendors. Considering that 80% of Mercado Libre’s sellers are SMBs, they were looking for a solution
Leveraging AWS’s robust infrastructure and Stability AI ’s Stable Diffusion text-to-image model in Amazon Bedrock, the companies collaborated to create GenAds, an innovative, AI-powered tool that empowers small and long-tail sellers to quic
The click-through rate in Hispanoamerica also witnessed a 25% increase compared to the average of non-GenAds display ads.
Transparency Evidence & methodology 95/100 reference value · 87% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value95/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth20/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    5 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence87%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    6 direct source quotes retained.
  • Date provenance8/10
    The publication date comes from publisher-controlled metadata.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. AWS

    Mercado Libre customer story

    First-party
    https://aws.amazon.com/solutions/case-studies/mercado-libre-mutt-data/
    Source type
    Vendor-published customer story
    Published
    Feb 6, 2025
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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