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dc.contributor.authorZaki, Mohameden
dc.contributor.authorMcColl-Kennedy, R., Janeten
dc.contributor.authorNeely, Andyen
dc.date.accessioned2021-05-25T08:49:25Z
dc.date.available2021-05-25T08:49:25Z
dc.identifier.issn0017-8012
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/322932
dc.description.abstractThe most common methods of tracking customer sentiments has a big blind spot: They can’t pick up on important emotional responses. As a result, qualitative surveys, like Net Promoter Score, end up missing critically important feedback. Even if they provide a positive score, customers often reveal their true thoughts and feelings in the open-ended comment boxes typically provided at the end of surveys, and AI can help companies make use of this valuable data to better predict customer behavior. Specifically, there are six benefits for adopting AI to analyze this feedback: It can 1) show you what you’re missing in your qualitative surveys, 2) help train your employees based on what’s actually important to customers, 3) determine root causes of problems, 4) capture customers’ responses in real time, 5) spot and prevent declines in sales, and 6) prioritize actions to improve customer experience.
dc.publisherHarvard Business School Publishing
dc.rightsAll rights reserved
dc.titleUsing AI to Track How Customers Feel — In Real Timeen
dc.typeArticle
prism.publicationNameHarvard Business Reviewen
dc.identifier.doi10.17863/CAM.70387
dcterms.dateAccepted2021-05-04en
rioxxterms.versionAM
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2021-05-04en
dc.contributor.orcidZaki, Mohamed [0000-0003-0264-2691]
rioxxterms.typeJournal Article/Reviewen
cam.issuedOnline2021-05-04en
cam.orpheus.successIndefinite embargo applied due to journal policy
cam.orpheus.counter4*
rioxxterms.freetoread.startdate2100-01-01


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