• Application Search
  • Retail

Dell: Powering the Search to Put the Customer First


  • 190
  • 21
  • 1.5
    million searches per day

Increased Conversions

Dell.com has experienced increases in click through rate, revenue per visit, and conversion by implementing Elasticsearch.

Reduced Server Costs by 25-30%

By migrating from FAST to Elasticsearch, Dell reduced the number of servers they needed by 25-30%.

Protect Customer-Facing Data with X-Pack

With X-Pack, Dell ensures the right people have the right access and permissions to their cluster in a live, customer-facing environment.

Receive Guidance from Elastic Support

As Dell continues to expand its use of Elasticsearch, they’re backed by Elastic Support to help them along the way – even for non-pressing issues.

Company Overview: A Global E-commerce Electronics Leader

Dell was founded in 1984 from the university dorm room of then 19-year-old Michael Dell, whose mission from day one was to service the customer first and foremost. The company has since grown to one of the leading providers of personal computers and electronics across 190 countries for consumers and organizations of all sizes.

Dell sells a variety of products that help individuals work securely from anywhere, such as computers, laptops, tablets, monitors, and thin clients, as well as servers, storage, and networking devices. Their e-commerce website, Dell.com, serves customers in 190 countries around the world, receiving 16 million unique visitors a month in the US alone.

Powering the Search to Put the Customer First

A large portion of Dell’s business takes place on its global e-commerce site, Dell.com, which first launched in 1996 and generated $1 million in sales per day just six months after going live. Beginning in 2005, the Dell e-commerce search used FAST Search engine. Between 2013 and 2014, FAST Search engine was phased out and Dell began its migration to Elasticsearch, which they rolled out to 60+ countries in 21+ languages.

They replaced the Search Engine and created a new Discover Search platform based on Elasticsearch. This new architecture is a responsive, multi-tenant, horizontally-scalable, and highly-performant stack. As a result, Dell has seen great improvements in click through rate, average order value, and conversion – and overall, a positive influence on customer satisfaction score. And, through their Elastic subscription, Dell is able to engage with Elastic consulting and support, who regularly help with architectural decisions. Like most e-commerce sites, search drives the navigation experience for these shoppers. Dell.com receives 1.5 million searches a day, which adds up to 50 million searches a month.

Dell's Journey with Elastic

The Who: Rich Claice, Jagdish Yadav, and the Search Team

The search team at Dell comprises just shy of 30 members. They are a passionate group of creative thinkers who like to face ambiguous challenges and turn them into viable solutions, not sit around and wait to be told what to do. They've seen the importance of search advance as consumer shopping expectations became more focused on instant gratification. Delivering exactly the result a consumer is looking to buy keeps them continually innovating and expanding the platform's relevancy and personalization capabilities.

If a consumer wants something, he or she is going to go to that search bar and ask for it. And they're going to expect to get the results they asked for.

Rich Claice
Sr. Principal Architect, Dell

Rich Claice and Jagdish Yadav have both been on the search team at Dell for a little over five years. They joined the company for the opportunity to work on a technology stack with a solid search platform that impacts customers in many countries and languages across the globe.

The What: Demands From Next Generation

Around 2013, the Dell search commerce platform was experiencing aging pains with a stack that was not responsive and a search engine (FAST Search Engine), that did not support multi-tenancy, cloud readiness, and more. As a result it wasn't horizontally-scalable by design from the ground up, and there were challenges creating and maintaining indices. The moment was right to modernize the search platform and meet the needs of contemporary e-commerce.

As our customers were shifting towards making purchases from their mobile phones and tablets, investing in an existing old stack that was based on FAST and wasn't responsive didn't make sense. Building or changing that would be a big investment versus building something new, lean, intuitive, and responsive.

Rich Claice & Jagdish Yadav
Search Engineering; Dell

The search team began throwing ideas around on how to come up with a single, responsive, horizontally-scalable, highly-available application that could support customers across 60+ countries, in 21+ languages, on all phone and mobile form factors. They evaluated Solr, Google Search Appliance and other search engines, but ultimately narrowed down on Elasticsearch as the search engine to drive their next generation e-commerce search platform. Multi-tenancy, ease of scalability, relevancy of results, aggregations queries and being open source were the key enablers for going with Elasticsearch.

The Why: Supporting a Revenue-Generating Piece of the Business

When they started testing out Elasticsearch, the search team at Dell had a good experience doing the linguistic processing, getting some query understanding under their belts, and figuring out the basics around how to solve for relevancy. From a customer standpoint, they received good feedback and saw even better results.

Based on this initial success, Dell engineering decided to use Elasticsearch to power their Black Friday deals site in 2014. Dell achieved its revenue target with zero downtime over the period of the Black Friday holiday event.

As Dell continued expanding their rollout of Elasticsearch in production, they contacted Elastic to explore the benefits of becoming a subscription customer. With Dell.com serving as a mission-critical piece of Dell's business, and search as a primary way visitors interact with the site, Dell was keen to partner with someone that could help them master the features and capabilities of Elasticsearch, as well as properly scale their deployment. And, as Dell was using Elasticsearch in a customer-facing application, they only thought it made sense to have a relationship with the company that is powering such a revenue-dependent part of their business.

They were also interested in the security features included in X-Pack to protect their Elasticsearch indices from accidental internal mistakes, such as role-based access control. This allows them to give specific roles privileges, providing certain permissions to folks performing administrative tasks, and read-only access to everyone else – helping to prevent their Elasticsearch instance from going down, or worse, getting mistakenly deleted. Rich jokes that it's their “fat-finger defense,” which sounds trivial, but when you look at the big picture, it's far from it – every second of Elasticsearch production impact could result in thousands of dollars in lost revenue.


The amount of revenue dependent on Dell.com is massive. If an Elastic subscription can provide the product functionality and support we need to help prevent downtime, at a fraction of the costs we'd incur handling a Sev1 outage, why wouldn't you do it?

Jagdish Yadav
Software Engineering Director, Global Online Search; Dell

The How: Search, Analytics, Linguistics, Interactivity, and Experimentation

Dell has deployed two Elasticsearch clusters on Windows servers in Dell data centers. The Dell Search Platform is based on .NET framework. One is a search cluster that powers the search experience on Dell.com, and the other is an analytics cluster used to track search-related user activity on the site. The analytics cluster provides an ability to deliver a crowd sourced and influenced search results and also provides great insight into the usage of search platform.

The Dell Search Cluster

The Dell search cluster contains an extremely comprehensive data set as it indexes everything on Dell.com, consisting of over 27 million documents which include all the products that can be purchased on the site, all the drivers for these products that can be downloaded, troubleshooting articles, knowledge-base documents, product manuals, videos and video metadata – just to name a few.

The documents themselves are also extremely rich. For example, the product documents include all the information related to that particular product: the product title, its description, the image link, keywords, meta information for the technical specifications of these products (RAM size, processor type, resolution, etc), stock status so they know how many days it will take to ship the product, pricing information, department category, and more.

The Dell Analytics Cluster

The Dell analytics cluster, which is currently more than 1 billion documents, indexes every click on Dell.com that comes from a search experience. Dell uses this data to analyze the top-performing queries, the top performing categories, and various other metrics to perform actionable, dynamic improvements to the site – whether it be the relevancy of the search results by influencing popular products higher, or serving the results from the right category based on a visitor's query.

Dell's Linguistics Pipelines

In order to deliver accurate search results in all languages, Dell created extensive linguistic pipelines for each language. The pipelines utilize Elasticsearch's language analyzers, stopword removal, spell check, synonym match, stemming, and other features to make the query more accurate. Dell also added a final step at the end of their linguistic pipelines that they call a catch-all influencer, which is essentially an offline aggregator that helps identify the entities from the query the customer entered. This aggregator runs across multiple systems, such as the content management system and their master lookup tables across various databases, and, depending on what the customer queried for in the search bar, maps the product category to the product category code, the manufacturer name to the manufacturer code, and so on and so forth. These inputs, enriched with analytics and customer identification data, are then passed to a probability engine and helps Dell re-write the final query. This context helps Dell significantly understand what the user is expecting when they perform a search.

Dell's linguistics pipelines: the backend
Dell's linguistics pipelines: the frontend.

Enhancing the User Experience

Thanks to the real-time nature of Elasticsearch, as well as its powerful aggregations, Dell introduced a new feature called virtual assistant, which gives shoppers an interactive way to refine their search before clicking the search button by giving them a preview of their results. "If I type the term 'laptop', I can see that there are refiners available to narrow down my search, one of them being screen size, another being the processor type, and so on," Rich explains. "As I click on different screen sizes or processor types, the other refiners refresh in real-time based on what's available, helping the user more easily find what they're looking for."

An Experimentation Engine

As Elasticsearch supports the creation of multiple indices, it provided a great ability for Dell Search Engineering to deliver more features based on Elasticsearch. For example, Dell was able to create an experimentation engine on their existing framework, which lets them easily test new features to a specific percentage of users and measure the impact before rolling them out to their entire deployment. This gives Dell a solid working hypothesis of the user's rate of relevant results, leading to an increase in probability of buying the searched products.

The Results: Better Experience for Customers, Better Results for Dell

As of March 2016, Elasticsearch serves as the search engine on Dell.com supporting 60+ countries in 21+ languages. And as a result of the switch from FAST to Elasticsearch, Dell has seen increases in revenue per visit, click-through rate and conversion.

Throughout their journey, they worked with Elastic support every step of the way.


We would raise questions around whether we should create a cluster per data center, whether we could create cross-data center clusters, checking what features were or were not backward-compatible before upgrading. . . if memory utilization was increasing or we saw some issues that we monitored in our logs, we would work with the Elastic support team to understand the root cause. Elastic Support has been very helpful as we continue to expand our use of Elasticsearch.

Jagdish Yadav
Director of Engineering, Global Online Search; Dell

Lastly, after seeing what Rich, Jagdish, and the rest of the search team could do with Elasticsearch, other groups in the company regularly consult them on other emerging technology projects. To date, Dell has expanded its investment in Elasticsearch to seven additional projects that are changing the way Dell understands its own business. These include using Elasticsearch to power a customer insights application, as well as a sales rep order optimization tool. With just these few examples, the company is making true its mission to service their customers first and foremost.

The Dell Search & Analytics Clusters

  • Clusters
  • Indexes
    Analytics cluster: 13 indices
    Search cluster: 53 indices (should reach 200+ indices)
  • Nodes
    26 per cluster
  • Query Rate
    Analytics cluster: 30 Queries per second
    Search cluster: 350 queries per second
  • Hosting Environment
    Windows servers in Dell data centers
  • Replicas
    1 per index
  • Documents
    Analytics cluster: 1,021,125,910
    Search cluster: 27,500,339 (should reach 100,000,000)
  • Time-based Indices
    < 5
  • Total Data Size
    Analytics cluster: 750 GB
    Search cluster: 10 GB
  • Node Specifications
    24GB RAM, 16 Core, 2TB HDD
  • Daily Ingest Rate
    Analytics cluster: 350 per second
    Search cluster: < 1 document per second