Coveo Qubit vs Coveo Relevance Cloud

• Qubit platform uses solid testing algorithms and delivers reliable reporting and analytics of testing campaigns. The dashboard section is easy to use and provides a good high level overview of the core campaign metric performances.
• On-boarding and implementation of Qubit technology was painless and well handed throughout the entire process even with more complicated platforms.
• Turn-around time for development and testing of campaigns is extremely fast. This enables the business to have a much higher throughput of tests and allows for quick validation of ideas rather than having to wait for months before a test is ready to go live on production site.

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• 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.

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• While they do work very closely with us, especially our success manager, more involvement on a technical level or a dedicated engineer, would be a great advantage. We develop a lot of experiences in house and, like all companies that dev in house, we have our own way of working. A dedicated engineer that got to know us better as well and understood how we work could only help. Sometimes, a few errors can get through QA due to this.

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• 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.

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• Faster recognition of customer needs - finding out exactly what customers are doing when they come on site.
• Assessment of online assets for effectiveness and improvements - facilitated the analysis of 500 online feedback questionnaires for a campaign.
• Mapping out lead conversion and helping identify opportunities to improve it.

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• 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.

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