Customer Stories

Records Indexed Every 12 Hours
Increase in Annual Revenue Through Search
Increase in Relevancy

The Challenge

Replace search on with an engine that can take Lenovo into the future. With products that span B2C, SMB, and B2B businesses and serve customers in 180 countries speaking 88 different languages, supporting is a broad mandate.

Our Plan

Move search out of the black box and onto Fusion’s open source technology. With Fusion’s machine learning capabilities and out-of-the-box tools like rules editor, personalize Lenovo customers’ search results and improve relevancy.

The Results

Deployed on for the last 6 months of 2017, annual revenue contribution through search increased 175%. In 2018, revenue increased again, by 95%. With Fusion signals turned on for just a few months, relevancy improved by 55%.


Search Is the Universal Language of Lenovo Customers

With diverse products and customers, personalization is the key to making – and keeping – a connection.

Lenovo is the number one PC manufacturer in the world, but that’s just the beginning of its product offerings. It’s also the number one provider of supercomputers, it sells phones (as Motorola), it provides large data center solutions, and sells widgets down to the little red track point nub on a laptop. With B2C and B2B business spanning over 180 countries in 88 different languages, Lenovo’s customer base is as diverse as the products.

So what leads a graphic designer in Beijing to the exact ThinkPad she needs? How does a business in North Carolina find the right infrastructure to support its internal systems? No matter what language the customer is using or what they’re saying, search is the universal language.

Make It Do What We Need It to Do

When Global Search Lead Marc Desormeau took over the search team for, he was confronted with a question, “Why is search not doing what we need it to do?”

“We index half a million records every 12 hours. Everything from data feed and product information, pricing, catalogs, things we sell. We also index information about jobs at Lenovo, about our green policy, our technologies, and customer use cases so it’s quite the range. It’s a pretty broad mandate to support,” said Desormeau.

Just prior to Desormeau joining the team, it had set out to replace the current search engine, a FAST-based solution that was quickly sunsetting. Reaching out to Gartner and Forrester for vetted possibilities, the search team learned about Lucidworks Fusion as an option. During an 18-month extended RFP process, multiple vendors were assessed. Meanwhile, the mandate of the desired search engine shifted from simple transactional support to enacting a full digital transformation at Lenovo.

“Ultimately based on Lucidworks’ vision around AI, their future plans for machine learning and more sophisticated search implementations, and really looking for a search platform that can take us into the future, the decision was made to move to Lucidworks Fusion.”

From Black Box to Open Source

Before Fusion, search at Lenovo was a mysterious black box. Keywords went in, some Great and Powerful Oz pulled levers behind a curtain, and search results came out. Fusion, built with open source Apache Solr and Apache Spark, changed that. Fusion’s out-of-the-box tools allow flexibility and customization so results can be tailored specifically to a product line, location, language, user, and more.

As the new, flexible search platform proved it could be leveraged to help meet different departments’ goals, the Lenovo community became more engaged with search.

Fusion tools like a business rules editor and query pipelines pulled back the curtain and helped the three-person search team get more buy-in from the greater company.

“We’re using data captured from our search engagements to inform some of our investments in SEM by looking at customers who are coming to us organically. How are they then engaging with our own site search? How can we start joining some of that data to ultimately present a better experience? So both in terms of attention, and awareness that the search platform is more than just a little box on the screen, it’s actually providing a lot of insights into our customers,” says Desormeau. “People are starting to understand there’s some real data here that’s valuable, and we can use that to present our customers with a better experience.”

The Results

The team launched Fusion-powered search on mid-year 2017. After just six months, Lenovo’s revenue contribution through search increased 175%. For 2018, when all search traffic passed through Fusion, the revenue increased again by 95%. On Lenovo’s customer support site, clickthrough rates and bounce rates have shown dramatic improvement with Fusion, proving that customers are more quickly finding the content they’re looking for.

More recently, Lenovo has implemented Fusion signals to track user behaviors like click, add to cart, and purchase. Combining these user signals with machine learning, the search tem was able to automate search result ranking for the vast amount of data in their knowledge base. Relevancy, measured by how often customers click on the first result versus any subsequent result, has improved by over 55% in the span of just a few months since launching signals.

“We don’t have to go in and validate that results are good, our customers are telling us the results are good. We’ve had some dramatic growth. The results that we’ve had with Fusion are nothing short of astounding,” says Desormeau.

“People are starting to understand there’s some real data here that’s valuable, and we can use that to present our customers with a better experience.”

-Marc Desormeau, Global Search Lead, Lenovo


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