Improve Contact Center Metrics and
Customer Satisfaction with Rosette
Gain customer insight and track trends across channels with fuzzy name matching and analytics from Rosette.
Proactively address quality, risk, and compliance gaps for improved satisfaction and experience.
Spend less time finding and
more time helping.
Improve customer satisfaction and agent productivity
Find who you’re looking for the first time
Language and script agnostic
Reduce duplicate records
12 Ways Rosette Matches Customers to Their History
Jesus ↔ Heyzeus ↔ Haezoos
Abdul Rasheed ↔ Abd al-Rashid
William ↔ Will ↔ Bill ↔ Billy
MaryEllen ↔ Mary Ellen ↔ Mary-Ellen
Dr. ↔ Mr. ↔ Ph.D.
McDonalds ↔ McDonald ↔ McD
Phillip Charles Carr ↔ Phillip Carr
Diaz, Carlos Alfonzo ↔ Carlos Alfonzo Diaz
J. E. Smith ↔ James Earl Smith
Dick . Van Dyke ↔ Dick Van . Dyke
Mao Zedong ↔ Мао Цзэдун ↔ 毛泽东 ↔ 毛澤東
Dec 15, 1984 ↔ 12/15/84
Never lose another customer over a mis-typed name
Name matching is hard.
Spelling variations, initials, nicknames, and titles can all slow down the process. While many software tools use a rich thesaurus of name variations for matching, this approach still stalls if a name is not listed.
To address this problem, Rosette uses a statistical, machine learning-based approach that can resolve names against external references to find the right person, the first time.
Search for “Richard Johnson” and see
how Rosette picks up “Dick Johnson,” a nickname.
Rosette uses advanced semantic and machine learning techniques to quickly and accurately locate customer records. Misspellings, non-Latin scripts, missing accent markings? Rosette is unfazed.
Try our demo today and see how Rosette can improve metrics
and satisfaction on both ends of the line.