ML-powered brand intelligence that generated 4.8 million designs
Digital Scientists built an AI-driven content ecosystem for Mailchimp's Creative Assistant, enabling small businesses to produce professional branded campaigns in under 10 seconds.
4.8M+
Designs Created
<10s
Per Campaign
4
ML Microservices
14+
Content Categories
Building the AI backbone behind Mailchimp's Creative Assistant
Mailchimp engaged Digital Scientists to build the machine learning infrastructure powering their Creative Assistant design tool. The engagement spanned multiple interconnected projects, codenamed Magpie, Raven, and Rhesus, each responsible for a critical layer of the content intelligence pipeline.
Magpie is a website scraper service that uses advanced scoring mechanisms to capture brand and campaign assets from any URL. Raven is the content intelligence engine that analyzes, categorizes, and pairs captured content for specific campaign intents. Rhesus provides image analysis using ML models for logo detection, saliency mapping, and marketing image classification.
Together, these services enable Mailchimp users to generate professional, branded multichannel campaigns with the click of a button, eliminating the manual effort of uploading brand assets and selecting campaign content.
Small businesses struggle to create professional marketing content
Mailchimp's small business users needed professional-quality branded designs for email, social media, and ads, but lacked the design skills, time, and tools to produce them. The biggest barrier to adoption of Mailchimp's Creative Assistant was the manual setup process: users had to upload logos, pick colors, choose fonts, and source campaign imagery before they could generate a single design.
Manual Brand Setup
Users had to manually upload logos, colors, and fonts before generating any designs, creating friction that killed adoption.
No Content Intelligence
Campaign content had to be scraped each time with no understanding of context, intent, or relevance to specific marketing goals.
Disconnected Channels
Generating campaign content across email, social media, and ads required separate workflows with no unified brand intelligence layer.
What Mailchimp's small business users needed to accomplish
Seamlessly integrate their existing website brand into Mailchimp without manual uploads
Generate professional branded designs for multichannel campaigns in seconds
Receive intelligently paired campaign content recommendations based on marketing intent
Produce ready-to-send email, social media, and ad campaigns from a single content source
Accurately abstract a user's brand from existing digital assets without any user input
Get campaign content recommendations that improve over time based on engagement data
Intelligent website scraping that captures brand DNA instantly
Magpie started as an effort to increase adoption of Mailchimp's ecommerce solution by helping users migrate their existing product data. It quickly grew into a comprehensive website scraper service that uses advanced scoring mechanisms to capture brand and campaign assets from any URL.
A user simply enters their website URL into Mailchimp's Content Studio, and Magpie along with its companion services automatically detects, analyzes, and classifies all discoverable brand elements. The service captures logos, brand colors, background/text color pairings, fonts and font styles, brand images, and a complete website style guide including button styles, navigation patterns, and background treatments.
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What Magpie captures
AI-powered content intelligence that understands marketing intent
Raven is the content intelligence engine that analyzes data acquired through Magpie to provide intelligent campaign content pairings. Its mission: accelerate a marketer's efforts by intelligently recommending content for their next campaign.
The system operates in four stages: User Identification classifies the business by industry and website type. Collection & Analysis uses text and image ML models to collect, store, and categorize content elements. Content Curation groups categorized elements into content pairings based on intent, channel, and campaign type. Performance Analysis feeds engagement data back to refine future recommendations.
How Raven analyzes a website
When a user enters their website URL, Raven identifies marketing triggers such as popup offers, promotional banners, and calls to action. It then extracts and categorizes content elements across multiple dimensions.
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Raven identifies marketing triggers like signup popups to determine campaign intent
Content element categories
Raven searches for specific content elements based on context, enabling accurate categorization and intelligent pairing for campaign use.
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Content pairings with ML confidence scores for campaign relevance
From website to multichannel campaigns in seconds
Raven's content pairings feed directly into Mailchimp's Creative Assistant (SAWA), which transforms brand elements and campaign content into professionally designed assets for email, social media, and ads. Each channel receives optimized content with platform-specific formatting, imagery, and copy.
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Email Campaign
Auto-generated with hero image, brand colors, about copy, and current promotion
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Facebook Ad
Contextual imagery with human figures, optimized for engagement
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Twitter Post
Product imagery with stylistic backgrounds and auto-generated hashtags
Creative Assistant demo
From website analysis to branded designs
The brand elements are instantly assembled into a brand profile and sent to Creative Assistant, which transforms them into beautiful, professionally branded designs.
These designs, in PNG or JPEG format, can be used as ads, heroes, or resized for social media. The entire process generates a multi-channel marketing campaign in less than 10 seconds.
Through the AI-driven pipeline, Mailchimp customers can import a full range of content features to generate custom multichannel designs with the click of a button.
A microservices ecosystem for content intelligence
Digital Scientists designed and built four interconnected microservices that form the content intelligence backbone of Mailchimp's Creative Assistant platform.
Magpie
Website scraper service using advanced scoring mechanisms to capture brand assets, product data, and campaign content from any URL.
Raven
Content intelligence engine that analyzes, categorizes, and pairs campaign content based on marketing intent and channel requirements.
Rhesus
Image analysis service providing logo detection, saliency mapping, and marketing image classification using computer vision ML models.
Hummingbird
Data adapter service that bridges Magpie's output to Creative Assistant (SAWA), translating scraped assets into the design generation format.
Workstream 1
Website Classification
Ecom, Content, Portfolio, Business Card
Workstream 2
Structure Analysis
Pinpoint content to capture and analyze
Workstream 3
Content Analysis
Context identification, parsing, quality
Workstream 4
Content Pairing
Intent-based campaign content assembly
Deep analysis of every brand touchpoint
When Magpie scrapes a webpage, it breaks the site into identified structures using parsing and scoring logic. These structures are sent to Raven, where they are prioritized and analyzed to yield the most valuable and relevant campaign content. The top content pairings, including images, header text, subheader text, CTAs, and more, are sent to Creative Assistant for design generation.
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Measurable impact at scale
Within eight months of the beta launch in April 2020, Mailchimp users created nearly five million instant designs, a testament to the power of removing friction from the creative process.
By combining machine learning with thoughtful product design, Digital Scientists helped Mailchimp make professional-quality branded design accessible to millions of small businesses. Site Analyzer eliminated the biggest barrier to adoption, manual asset uploading, and Creative Assistant turned brand intelligence into beautiful, ready-to-use marketing content.
Increased adoption of Creative Assistant by eliminating manual brand setup
Enabled Brand Playground concept for new user acquisition
Achieved 90%+ accuracy for scraped brand elements across content sources
Expanded Rhesus image analysis to serve multiple Mailchimp platform services
4,849,372
designs created
within 8 months of beta launch
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