E-commerce Customer Engagement

Increase revenue with fast and accurate AI-driven recommendation, personalization, and search.

The Need

Scaling e-commerce customer engagement services is complex and resource-intensive, often forcing a tradeoff between accuracy and performance and limiting revenue potential. Generative AI revolutionizes this landscape by enhancing search, recommendation, and personalization with advanced technologies like natural language processing (NLP), visual search, and hyper-personalized recommendations. With predictive personalization anticipating customer needs in real-time and seamless omnichannel integration across all platforms, businesses can deliver a more engaging, responsive, and revenue-boosting customer experience.

The Answer is Vespa

Vespa.ai is a powerful platform for developing and running real-time AI-driven search, recommendation, and personalization applications. Engage your customers with precise offers. Drive deeper engagement to increase revenue. Differentiate your brand in a crowded market.

Powering E-commerce

Vespa powers e-commerce platforms by executing complex queries across structured data, unstructured text, and high-dimensional formats like vectors and tensors—crucial for advanced AI use cases such as personalization. It runs machine learning models directly within the ranking pipeline and supports multi-phase ranking to optimize relevance while controlling infrastructure costs. With built-in vector and keyword search support, scalable data serving, and continuous model updates, Vespa delivers fast, accurate results that drive better customer experiences and higher conversion rates.

Optimized over a decade, the platform’s architecture supports real-time processing of massive datasets with minimal latency without incurring network costs or performance delays from moving data. This enables instant query responses and dynamic updates based on user interactions, enhancing the shopping experience and business outcomes.

Vespa Platform Key Capabilities

Vespa provides all the building blocks of an AI application, including vector database, hybrid search, retrieval augmented generation (RAG), natural language processing (NLP), machine learning, and support for large language models (LLM).
Vespa unifies search, recommendation, and personalization in one platform. This streamlined approach reduces complexity, accelerates development, and enables more cohesive, effective solutions—no more siloed thinking.
Build AI applications that meet your requirements precisely. Seamlessly integrate your operational systems and databases using Vespa’s APIs and SDKs, ensuring efficient integration without redundant data duplication.
Achieve precise, relevant results using Vespa’s hybrid search capabilities, which combine multiple data types—vectors, text, structured, and unstructured data. Machine learning algorithms rank and score results to ensure they meet user intent and maximize relevance.
Enhance relevance and personalization by leveraging Vespa’s real-time tensor operations. Go beyond keyword matching with support for vectors from text, images, location, and other complex data sources.
Enhance content analysis with NLP through advanced text retrieval, vector search with embeddings and integration with custom or pre-trained machine learning models. Vespa enables efficient semantic search, allowing users to match queries to documents based on meaning rather than just keywords.
Search and retrieve data using detailed contextual clues that combine images and text. By enhancing the cross-referencing of posts, images, and descriptions, Vespa makes retrieval more intelligent and visually intuitive, transforming search into a seamless, human-like experience.
Ensure seamless user experience and reduce management costs with Vespa Cloud. Applications dynamically adjust to fluctuating loads, optimizing performance and cost to eliminate the need for over-provisioning.
Deliver instant results through Vespa’s distributed architecture, efficient query processing, and advanced data management. With optimized low-latency query execution, real-time data updates, and sophisticated ranking algorithms, Vespa actions data with AI across the enterprise.
Deliver services without interruption with Vespa’s high availability and fault-tolerant architecture, which distributes data, queries, and machine learning models across multiple nodes.
Seamlessly handle increased demand with Vespa’s horizontal and vertical scaling capabilities, adding capacity on-demand to maintain peak performance during high-traffic periods.
Bring computation to the data distributed across multiple nodes. Vespa reduces network bandwidth costs, minimizes latency from data transfers, and ensures your AI applications comply with existing data residency and security policies. All internal communications between nodes are secured with mutual authentication and encryption, and data is further protected through encryption at rest.
Avoid catastrophic run-time costs with Vespa’s highly efficient and controlled resource consumption architecture. Pricing is transparent and usage-based.

Vespa at work

At Farfetch, Vespa is used to power the recommendation system for delivering personalized product suggestions to millions of users in real-time. The platform enables low-latency, high-throughput recommendations by efficiently handling large-scale data and integrating machine learning models directly into its serving layer.

Read the Farfetch blog

Vinted transitioned to Vespa to enhance the performance and scalability of their search and recommendation systems. Vespa’s ability to handle complex, large-scale data and support machine learning models natively allowed Vinted to provide faster, more personalized search results.

Read the Vinted Blog

Otto.de enhanced autosuggestions with Vespa, significantly improving relevance, performance, and scalability. With Vespa’s machine learning capabilities and flexible deployment, Otto.de personalized suggestions, reduced latency, and deliver a superior user experience.

Vespa eCommerce Stakeholders

Vespa adapts to your eCommerce needs—helping business leaders drive AI-powered growth while enabling AI teams to build and manage search, recommendation, and personalization at scale.

Business Leaders

Drive growth through better customer experiences. Vespa powers fast, accurate search, recommendation, and personalization at scale, helping customers find what they need and boosting engagement, conversions, and revenue. Its efficient architecture lowers costs and accelerates innovation for lasting competitive advantage.

Chief Revenue Officer (CRO) – Increase Average Order Value

With superior AI-driven search, recommendation, and personalization, Vespa drives higher conversion rates and enhances customer experience. Advanced search algorithms, personalized product recommendations, and tailored content allow customers to find what they are looking for quickly, discover new items they are likely to purchase, and enjoy a seamless shopping experience.

Chief Marketing Officer (CMO) – Increase Campaign Performance and Customer Satisfaction

Vespa enables real-time search, recommendation, and personalization at scale, ensuring every interaction is timely and tailored. This leads to higher engagement, increased conversion rates, and more effective campaign performance. With Vespa’s efficient infrastructure, your team can move faster, optimize spend, and continuously improve customer journeys.

eCommerce Manager – Optimize Search, Personalization and Recommendations at Speed

Vespa delivers high-performance search, recommendations, and personalization at scale—supporting fast response times even during peak traffic. Its efficient, scalable architecture enables consistent performance, reduces infrastructure costs, and simplifies operations, giving your team the flexibility to iterate quickly and deliver optimized shopping experiences that convert.

Technical Leaders

Vespa is a unified platform for powering search, recommendations, personalization, and product navigation at scale. It supports vector search, text relevance, structured data, ML ranking, tensor operations, real-time recommendations, grouping, aggregation, and faceting. With Vespa, teams avoid stitching together multiple tools and build on a modern, scalable platform proven in high-traffic, data-rich environments.

CTO/VP of Engineering – Build Advanced Personalized Search and Recommendation on a Single Platform

Deliver search, recommendations, and navigation from a single platform, enabling your AI teams to build hyper-personalized experiences that drive sales. With Vespa, teams move quickly from idea to production, whether experimenting with new ML models, adding signals, or refining business logic—all with the confidence that Vespa supports secure handling of user-generated content, fraud detection in ranking, and safe personalization. Built-in autoscaling helps manage cost and latency tradeoffs, ensuring performance at any scale.

Head of AI Engineering – Empower Your AI Team to Build Personalized, Scalable Experiences from Diverse Data

Build advanced services that integrate diverse data sources—from high-quality provider data to user-generated reviews, images, and ratings—supporting both extractive and generative features. Vespa facilitates concept-based navigation by letting your AI Team abstract from raw features to higher-level ideas like “city escape” or “family break,” enhancing discoverability and user experience. With built-in support for personalization, Vespa makes it easy to tailor recommendations and experiences to individual user preferences, powering AI-driven applications at scale.

AI Team

Develop applications that leverage data and signals to deliver the performance and quality demanded of modern e-commerce solutions without being limited and encumbered by integrating different technologies for vectors, text, signals, and ranking.

Search Engineer – Power Relevant, Real-Time Search with Geo, Personalization, and Trust Signals

Build smarter, more responsive search and recommendation experiences by combining real-time updates, geographic relevance, and personalized ranking. Vespa’s strong geo-filtering capabilities ensure users see products, offers, and content relevant to their location, while its support for real-time data keeps search results aligned with current inventory—showing only what’s truly available. Engineers can also incorporate user-generated content, ratings, and reputation signals to boost trustworthy results and detect fraudulent behavior. With built-in support for personalized ranking, Vespa enables precise, context-aware search at scale.

Resources

ESG Research Report: How Generative AI is Changing E-Commerce

Generative AI has the potential to significantly level up customer experiences, specifically for search, recommendations, and personalizing user experiences, but the market is very much in the early exploratory stage. How can generative AI transform search, recommendations, and personalization? There are roadblocks, but with the right partner, e-commerce retailers can transform their customer engagement.

Free Download

BARC Research Report: More than Vectors: How Multi-Faceted AI Databases Enable Smart Applications

This research note explores the emergence of versatile AI databases that support multi-model applications. Practitioners, data/AI leaders, and business leaders should read this report to understand this new platform option for supporting modern AI/ML initiatives.