12 real-life Business Process Automation examples for Marketing

12 real-life Business Process Automation examples for Marketing

Automation in marketing is valuable because it can produce personalised, timely communication at scale without losing brand consistency, compliance, or relevance.

The examples below show the pattern clearly: the best automations turn fragmented lead signals, campaign data, and content inputs into faster follow-up, tailored messaging, and cleaner execution, while leaving positioning, creative judgment, and audience strategy in human hands.

Industry

Sector

Poshmark's AI-Powered Product Listings

Poshmark has significantly lowered the barrier to entry for its sellers by launching Smart List AI, a proprietary tool that automates the creation of product listings. Leveraging advanced image recognition and generative AI powered by Naver, the system analyzes seller-uploaded photos to automatically generate accurate titles, descriptions, and categories, allowing even inexperienced users to produce high-quality listings with minimal effort.

Use Case
AI-automated product listing creation
Tools
Naver AI
Input
Seller-uploaded product photos, product category signals, top-performing listing templates, and pricing benchmarks
Process
The AI analyzes uploaded images to identify product type, brand signals, and condition; it then automatically generates a title, description, and suggested category for the seller to review and publish
Output
Significant reduction in listing friction for casual sellers and an increase in the overall volume of high-quality listings on the platform
Outcome
48% reduction in listing creation time during beta testing
Pure Play Ecommerce
Marketing

Leonardo AI's Character Re-generation and Visual Refinement

Springbok Agency utilised Leonardo.ai to transform the brand mascots of Ethias, a leading Belgian insurer, from flat 2D cartoons into emotionally resonant, Pixar-style 3D characters. By integrating AI into their creative pipeline, the agency moved production in-house, enabling the rapid generation of high-fidelity assets that would have traditionally required expensive external 3D modelling and rendering.

Use Case
Character Re-generation and Visual Refinement
Tools
Leonoardo AI
Input
Original brand-specific character designs (the "Ethi" mascots), existing brand assets, and custom-curated databases of high-quality training images.
Process
Springbok built a specialised five-tool AI pipeline with Leonardo.ai at the core. The team uploaded original characters and used a high-fidelity blending engine to regenerate them with enhanced textures and emotional depth. They employed an iterative feedback loop, using successful outputs to further train the model, and utilised Leonardo’s Motion features to animate the static assets. This "NextGen Studio" approach allowed for seamless style matching and scene transfers between Photoshop and the AI model.
Output
A diverse library of 3D-style, emotionally expressive assets and animated content, including variations in character poses, wardrobe, and accessories (such as the addition of an "Ethi" family dog for pet insurance promotions).
Outcome
Production time for complex campaigns was reduced from one month to just one week. By eliminating the need for external 3D contractors, the agency cut production costs by 70% while maintaining absolute brand integrity and scaling creative output across B2C, B2B, and corporate channels.
Insurance and Pensions
Marketing

Marketing Automation in Law

Submitted by Frederic Kalinke

This AI Automation helps law firms streamline their marketing efforts by auto-generating personalized emails and brochures based on website lead inquiries, delivering tailored client communication that saves one hour of manual administrative work per lead.

Use Case
Marketing Automation
Tools
Google Gemini + Workspace
Input
Website lead
Process
Auto-generate personalised email based on user input or inquiry
Output
Tailored client email and brochure
Outcome
1 hour saved per lead
Legal Services
Marketing
Read blog

Unilever's Streamlined Marketing Content

Unilever utilises advanced AI models to automate the generation of marketing content resulting in a 90% reduction in response drafting time and ensuring global brand consistency across all digital touch points.

Use Case
Marketing Content Automation
Tools
Internal Tools & Persado AI Platform
Input
Vast datasets aggregated from various consumer sources, customer queries, and existing product specifications.
Process
The system automates the creation of marketing copy and customer emails while generating informative product descriptions for e-commerce platforms. Simultaneously, AI models analyse data to predict emerging customer trends and preferences. The Persado AI platform is further utilised to personalise digital advertisements for individual consumer segments.
Output
Automated marketing copy, customer emails, AI-generated product descriptions, and predictive reports on consumer trends.
Outcome
Drafting time reduced by over 90%, maintaining a consistent brand voice. Personalised ads have seen a 15% increase in conversion rates, while AI-generated descriptions have achieved up to a 70% improvement in product visibility and sales performance.
Grocery and FMCG Retail
Marketing

Tesco's Personalised Loyalty Gamification

Tesco utilises an advanced AI-driven personalisation engine, developed by Eagle Eye (EagleAI), to deliver "Clubcard Challenges" to millions of members. The system transforms routine grocery shopping into a gamified experience by setting bespoke spending targets across specific product categories, significantly increasing incremental spend and customer engagement.

Use Case
Personalised Loyalty Gamification
Tools
Internal Tools & EagleEye
Input
Granular first-party consumer data from the Clubcard loyalty scheme, including transaction history, product preferences, and "index versus average" buying patterns. It also integrates Tesco’s product catalogue and participation metrics from previous loyalty campaigns.
Process
The EagleAI platform executes over 190 individual data-driven decisions per customer to construct a unique set of 20 challenges. The AI utilises deep machine learning to determine the optimal spend thresholds and reward levels for each individual, ensuring the tasks are challenging enough to drive incremental behaviour yet attainable enough to maintain engagement. Members then select 10 of these 20 personalised "quests" to complete over a six-week period.
Output
A highly customised digital dashboard within the Tesco app featuring 20 bespoke challenges (e.g., "Spend £10 on plant-based meals"), real-time progress tracking, and automated point issuance upon completion.
Outcome
Successfully reached 10 million Clubcard members, achieving a 76% conversion rate from page visitors to active players. Of those, 62% reached their first reward threshold. The initiative won "Best Global Loyalty Launch" at the 2025 International Loyalty Awards and allows customers to earn up to £50 in bonus points, which can be doubled in value through Tesco’s reward partners.
Grocery and FMCG Retail
Marketing

Heineken's Mercury Marketing Spend Optimiser

Heineken deploy Mercury, an AI-driven marketing budget allocation engine that uses Bayesian analysis and linear programming to determine the optimal distribution of above- and below-the-line spend across all brands. The system is complemented by Promo Advisor, which enables brand managers to simulate promotional campaign outcomes before committing budget.

Use Case
AI-Driven Marketing Budget Allocation and Promotion Simulation
Tools
Internal Tools
Input
Historical campaign performance data; brand spend allocations; market data; promotional calendars across all Heineken brands
Process
Mercury applies Bayesian analysis to decompose campaign effectiveness, then uses a linear programming model to recommend the most profitable allocation of marketing investment; Promo Advisor runs what-if simulations for promotional scenarios before execution
Output
Optimised marketing spend allocations per brand per market; promotional ROI forecasts; scenario simulation outputs for brand managers
Outcome
Incremental gross profit delivered across key markets
Food and Beverage Manufacturing
Marketing

Diageo's Foresight System Consumer Trend Intelligence

Diageo use a proprietary AI-powered listening tool, the Foresight System, built in partnership with Share Creative and Kantar, that continuously scans over 160 million online conversations to identify emerging consumer trends across global beverage alcohol markets. Insights feed directly into brand strategy, campaign planning, and product innovation.

Use Case
AI-Powered Consumer Trend Monitoring and Insight Generation
Tools
Codec AI
Input
160 million+ online conversations from social media, forums, YouTube, and digital media in English, Mandarin, and Spanish
Process
Codec AI algorithms classify conversations by shared interests, values, and behaviours; NLP and topic modelling identify net-new micro-trends and track macro-trend evolution year-on-year; outputs are synthesised into dashboards and the annual Distilled trends report
Output
Actionable consumer trend intelligence by macro-trend, region, and brand; real-time foresight dashboard for campaign and product teams; annual Distilled report published globally
Outcome
Five macro-trends tracked continuously and used to inform brand activations and channel strategy; Distilled 2025 identified the zebra striping non-alcoholic consumption trend, directly influencing Diageo's portfolio and campaign decisions
Food and Beverage Manufacturing
Marketing

Sephora's Virtual Artist AI Try-On and Personalised Recommendations

Sephora deploy an AI-powered Virtual Artist that enables customers to try on makeup products via augmented reality and receive personalised product recommendations based on skin tone, purchase history, and browsing behaviour. The system has facilitated over 200 million virtual try-ons and contributed to a 4x increase in e-commerce sales over six years.

Use Case
AI-Powered Virtual Try-On and Product Recommendation
Tools
Optimove
Input
Customer selfies, skin tone analysis, browsing history, and purchase history from 25+ million Beauty Insider programme members
Process
Computer vision analyses facial features and skin tone to match customers with suitable products; ML models generate personalised recommendations; Optimove orchestrates CRM campaigns and automated re-engagement triggers for at-risk loyalty members
Output
Real-time virtual makeup try-on visualisations; personalised product recommendations; automated re-engagement campaigns for declining loyalty members
Outcome
40% increase in customer engagement; 11% uplift in conversion rates; e-commerce net sales grew from $580 million to over $3 billion
Non Food Retail
Marketing

Coca-Cola's Fizzion Brand Compliance Automation

Coca-Cola deploy Fizzion, a co-developed AI design intelligence system with Adobe, that encodes brand guidelines into a machine-readable StyleID. Creative teams and agency partners generate hundreds of localised campaign variations at up to ten times the speed of traditional production, without compromising brand integrity.

Use Case
Automated Brand-Compliant Content Localisation
Tools
Adobe Firefly
Input
Designer workflows within Adobe Creative Cloud; existing brand guidelines; campaign briefs across 200+ markets
Process
Fizzion observes designer decisions in real-time, encodes creative intent as a StyleID, and uses Adobe Firefly generative AI to apply brand rules automatically across formats, platforms, and markets
Output
Hundreds of on-brand, locally adapted campaign variants ready for deployment across 200+ markets
Outcome
Content production speed increases by up to 10x; brand consistency maintained at scale; creative teams freed to focus on storytelling rather than formatting
Food and Beverage Manufacturing
Marketing

Spotify's Wrapped Automated Personalisation Campaign

Spotify automate the production and delivery of Wrapped, an annual personalised year-end recap campaign distributed to over 574 million users globally. The system aggregates a full year of per-user listening data into shareable visual stories, driving mass organic social amplification and measurable platform re-engagement at scale.

Use Case
Automated Personalised Year-End User Data Campaign
Tools
Internal Tools
Input
Full-year individual streaming data including track plays, skips, saves, genre interactions, and listening timestamps across all 574 million users
Process
Scalable data pipelines process billions of data points using distributed computing; ML clustering algorithms generate personalised listening personas and insights; NLP categorises songs by genre and mood; generative AI produces personalised AI-narrated podcasts summarising each user's listening year
Output
Fully personalised shareable visual Wrapped stories per user; AI-generated personalised audio podcasts; artist and creator Wrapped performance dashboards
Outcome
Wrapped reached 200 million engaged users within 24 hours, a 19% year-on-year increase; 500 million shares, up 41% year-on-year; 2.2 million social conversations generated before launch week
Consumer Internet Platforms
Marketing

Marks & Spencer's AI Product Description Generation

Marks & Spencer deploy generative AI to write 80% of product descriptions across clothing and home categories, enabling faster product listings and scaled content personalisation. The initiative forms part of a broader digital growth strategy, with M&S reaching 9.4 million active online customers and its app now accounting for 44% of online orders.

Use Case
Automated Product Description Generation at Scale
Tools
mParticle
Input
Product attributes, imagery metadata, category briefs, and brand tone-of-voice guidelines for clothing and home ranges
Process
Generative AI models ingest product data and M&S brand guidelines to produce on-brand product descriptions at scale; mParticle unifies customer data from app, web, and in-store POS to power personalised homepages and targeted content delivery
Output
AI-generated product descriptions for online listings; personalised homepage experiences and content recommendations per customer
Outcome
80% of product descriptions now AI-generated, accelerating time-to-market for new ranges; app share of online orders grows from 37% to 44% year-on-year; active online customer base reaches 9.4 million
Non Food Retail
Marketing

Uber's Content Localisation Engine

Uber is building an automated "Dynamic Language Tiering" and localisation system to accelerate entry into new markets, leveraging AI to manage the cultural and linguistic adaptation of its platform across 70+ countries.

Use Case
Geographic Market Entry
Tools
Input
Product content, marketing materials, and regulatory documentation for new regions.
Process
An AI orchestrator selects the best machine translation models for specific content types, while automated "Quality Assurance" agents (Dragon Crawler) test the localised experience for errors.
Output
Automated translation and validation of 85% of all global content.
Outcome
Dramatically reduced time-to-market for new regions and the ability to scale language support based on real-time market demand.
SaaS and Software Products
Marketing
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