Coveo Relevance Cloud vs. Luigi's Box

Coveo Relevance Cloud is a great solution to implement into Salesforce to provide Knowledge-Centered Support, Enhancements to a Customer Community, to provide sales aids, or to complement your customized app in Salesforce.

Incentivized

Luigi's Box is very good in analysing the customers behaviours. Based on the algorithms in the background it is capable to predict and suggest to the customer suggestions of the products that the customer does not even think of. When you want to set up more complicated ways to increase a conversion, it is harder to set up and then there is a big need to be a skilled person in order to set it all up in a correct way.

• Coveo is fast, search results come up quick (though it's not always great).
• Not much complexity to run.
• Coveo is implemented within our portal and doesn't require extra steps to use it.

Incentivized

• search merchandizing
• analytics - data for searches with no/low conversions
• synonym suggestions
• custom keyword enrichment for specific products
• boosting of specific brands/categories
• query reqrites

• It would be great if Coveo 6 allowed you to rebuild indexes from a certain subtree instead of needing to rebuild the entire tree to see changes. This functionality was added in Coveo 7 and is very useful.
• In Coveo 6, integration with Sitecore is more difficult than one would expect. This integration is much improved in Coveo 7.
• I have seen cases where an exception thrown when crawling a specific document will cause the indexing to stop completely. I believe this only happens in implementations using custom faceting but it could be handled more efficiently if the trouble document was skipped and the indexing could continue.
• Relevancy ranking editor is good but not as powerful as GSA. GSA offers a self-learning scorer which automatically analyzes user behavior and the specific links that users click on for specific queries to fine tune relevance and scoring.
• We've ran into issues on multiple clients with Sitecore items being indexed multiple times in Sitecore 7 and Coveo 7. The fix Coveo suggested was to upgrade our Sitecore version and Coveo but unfortunately this didn't resolve our issue. After months of testing we were finally able to resolve this by implementing our own CoveoItemCrawler to get around the issue (based on https://developers.coveo.com/display/public/SC201404/Items+in+the+Same+Language+Gets+Indexed+Multiple+Times;jsessionid=3C1A2AE33540E0A0B8BB52BA3A64AF70).
• Integration with RabbitMQ in Coveo 7 seems error prone. We often see the error "The AMQP operation was interrupted" and on occasion, need to restart the Coveo service to get this operating again. In some extreme cases, we have also had to restart the server because of issues when attempting to restart the Coveo service.

Incentivized

• integrating the feed with Channable (feed management tool) was a bit complex at first, but once that was done, it was much simpler.
• more personalised product recommendations

Incentivized

This question is not applicable to me

Incentivized

The admin of Luigis Box is very easy to learn, provides functionality as well as data for decision making. Other then that, Luigi's Box is also user-friendly for customers. So, while there is a learning curve for the initial setup in the back-end, our users are happy and converting well.

Their support is excellent. Quick and helpful.

We had really good references for Luigi's Box so we barely considered any other option or alternative. I must say that we do not regret so far. Mostly because the implementation was fast and easy and thanks to self learning algorithm, Luigi's Box needs minimum maintenance. The product seemed a bit pricy at the beginning but it paid of.

• Quick to find things in a massive database when needed.
• Results need to be more concise - sometimes we spend more time looking for the right file than if we were to just search amongst our own networks instead.
• Coveo is not always the most useful but does its job when general information is needed.

Incentivized

• We have zero complaints about how internal search works
• If there is any suggestion to improve the search results from our colleagues, we can solve it out in a few minutes