300% more leads
With Elastic, Lusha is helping users triple outbound leads with AI-curated sales playlists and precision targeting.
10x higher conversions
With Elastic enhanced search and smart recommendations, Lusha helps customers boost sales conversion rates by up to 10x.
1000% ROI
Lusha customers have seen up to a 1,000% return on their Lusha investment, driven by scalable, intelligent data insights and faster prospect qualification with Elastic.
Lusha's AI-driven sales platform, supercharged by Elastic's scalable search technology, transforms prospecting with smart playlists, precision targeting, and lightning-fast data discovery.
They say the more things change, the more they stay the same — but AI is rewriting that rule in sales. Virtually every stage of the sales process is being reshaped by intelligent tools and automation. This is why Lusha is betting big on its AI-powered B2B sales intelligence platform, which enables sales teams to build trust with prospects and discover new leads faster than ever before.
Today, Elasticsearch, sits at the heart of Lusha’s technology infrastructure. This includes a GDPR- and CCPA-compliant database of over 200 million business contacts, enabling more than 1.5 million Lusha users to build accurate prospect lists and accelerate their go-to-market strategies. It uses Elasticsearch not only for scalable full-text search but also as a vector database to store and search embeddings, enabling the platform to understand user intent and deliver personalized lead recommendations based on meaning, not just keywords.
Lusha also stands out for its innovative user experience, which more closely resembles a music streaming platform than a sales dashboard. It recently launched AI Recommended Lists, a feature that surfaces customer leads in the form of playlists based on user behavior and preferences.
Sigalit Sadeh, director of product management at Lusha, says, "Prospect Playlists eliminate the need for manual lead searching by continuously surfacing high-value contacts and companies that match your targeting criteria. You can create multiple playlists for different ideal customer profiles (ICPs), industries, or sales motions, ensuring each list stays relevant and filled with the right prospects."
Ready for the future of AI-driven sales
This AI-powered sales environment is the result of a comprehensive modernization project triggered by the limitations of Lusha’s previous search platform. As the company’s user base and data complexity grew, it needed a more scalable and AI-ready search infrastructure with access to search expertise and support infrastructure that is crucial for managing production systems that serve large volumes and resolve issues quickly when they inevitably arise.
Guy Koren, data director, research and development at Lusha, says, "We wanted to move from being a static data provider to a smart assistant offering curated recommendations and sales lead playlists. That vision pushed us to update our infrastructure, building the foundations for real-time, best fit and explainable recommendations at scale."
Lusha began with a proof of concept to measure candidate platforms, including Elasticsearch, against KPIs such as cost, indexing rate, and search performance. The results were conclusive, with Elasticsearch scoring highest on almost every measure. Following the success of the trial, Lusha migrated to Elastic Cloud on AWS, deploying four large Elasticsearch clusters.
"Deploying Elasticsearch on AWS gives Lusha a highly scalable, flexible, and fully managed solution that simplifies the process of creating, upgrading, and managing Elasticsearch clusters."
Scaling search fast, keeping costs down
Lusha leverages Elastic for a range of scalable, cost-effective search capabilities. For example, structured company data filtering through Elasticsearch's domain-specific language (DSL) and free-text through named entity recognition (NER) provide users with a best-in-class experience as they query systems.
Elastic's vector search is now central to Lusha's ability to deliver custom-made prospecting recommendations at scale. By combining vector embeddings with Elastic's powerful semantic search, the system understands nuanced search intent and offers leads that match user needs, not just by keywords, but by meaning.
Elasticsearch also enables Lusha to more efficiently manage its vast data infrastructure. The platform handles approximately 200 million profiles, each represented as an event vector. These vectors capture dynamic entities including individuals changing jobs or companies relocating. This requires not only the ingestion of new data but also continual updating of records to reflect changes in company or prospect situations.
Despite the ever-growing volume of data, Elasticsearch's deployment model ensures cost efficiency at scale. This architecture supports faster, more intelligent search experiences, driving higher user engagement and creating a strategic edge in the competitive B2B data intelligence market.
"Elasticsearch organizes data in a way that supports highly specific queries, enabling fast responses and tailored results to complex questions. It is definitely the industry-leading infrastructure in the search space."
Delivering exceptional sales performance
With cleaner data, smarter recommendations, and faster search, Lusha customers can qualify leads more effectively and move through the sales cycle with greater confidence. Customers report up to a 300% increase in outbound leads and as much as a 10x boost in conversion rates.
Other Lusha customers have seen a 25% increase in closed deals and up to a 1,000% return on investment. Some report doubling the size of their pipeline, thanks to the speed and precision with which they can now target and reach decision-makers.
Looking to the future
With Elastic already powering search and vector-based recommendations, the company is now building a third use case, positioning Elasticsearch as the hub for its AI agent framework.
This initiative comprises a suite of AI agents designed to support personalized email outreach and in-depth account research. These agents help determine whether a target company aligns with the user's ICP, helping to streamline prospecting and qualification efforts.
Elasticsearch's vector search capabilities are key to this important development. By incorporating retrieval-augmented generation (RAG), the system can dynamically extract the most relevant contextual data and feed it into a large language model (LLM) to ensure the output is both precise and aligned with customer sales objectives. This includes detailed research as well as highly-personalized emails that engage with the prospect's unique goals and challenges. Koren says, "Elasticsearch is a great platform because it enables sales staff to be more human. By automating everyday activities, it frees them to spend more time nurturing valuable customers and prospects."
