Replace search on Lenovo.com 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 Lenovo.com is a broad mandate.
Move Lenovo.com 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.
Deployed on Lenovo.com 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%.
When Global Search Lead Marc Desormeau took over the search team for Lenovo.com, 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 Lenovo.com,” 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.”
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 team launched Fusion-powered search on Lenovo.com 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.
We’re ready to get you, and your customers, to the knowledge they require. Talk to us about your unique needs, and we’ll come up with the AI search and discovery solutions that fit.