Contact Center Name Search
Find your customers faster and improve customer satisfaction with intelligent name matching
11.4 seconds saved per search*
An individual record lookup may not seem to take long, but each second spent searching for customers adds up. Fuzzy name matching mitigates the three most common errors that lead to missed searches for customer records:
- Misspelling/Phonetic Misunderstanding
- Nicknames, non-English names
- Incomplete / inaccurate records
*Average observed in customer proof-of-concept. Customer experience varies depending upon their database.
Intelligent Name Matching
Rosette finds potential matches in the database regardless common record errors like nicknames, misspellings, names split inconsistently across database fields, solving thirteen name phenomena across fifteen languages.
Rosette names search presents all likely matches for each search query based on a predetermined match score threshold. Possible matches are ranked from most to least likely, allowing call center staff to review the results and ask the appropriate follow-up questions to find the right record faster.
A hybrid solution, Rosette’s trusted blend of machine learning and traditional name matching techniques has improved name search for the world’s thorniest name matching challenges for over 15 years.
- Increase productivity: With Rosette, you can find who you’re looking for the first time without asking for clarification so that your call center agents can spend more time on helping and less time on searching.
- Improve customer satisfaction: Make your customers happy by focusing on their problems rather than wasting their time with identification questions.
- Reduce the average handle time: Rosette’s greater accuracy can help you decrease your average handle time up to 11 seconds.
- Reduce duplicate records: Rosette’s fuzzy matching decreases the likelihood that human errors like misspellings, linguistic and cultural differences, and inverted name fields will lead staff to create duplicate records.
- No language boundaries: Rosette has a fluency across 15 languages and a deep understanding of the linguistic complexities of names and indeed is the first choice for name matching.
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Frequently Asked Questions
How much can Rosette improve the average handle time?
In our experiments with more than 700,000 calls, we saw an average decrease of 11 seconds per call to find the correct record.
Why is Rosette better than my current database solution?
Rosette uses machine learning rather than name lists for its name matching logic. This means new names are found the first time. It also avoids the problem of an exponentially growing list, especially with names that have multiple elements. A 3-element names (first, middle, last), for example, with 12 variations for each element would add 12x12x12 = 1,728 variations to a list.
Unlike expensive and less accurate legacy solutions driven by thousands of spelling variants from known names, Rosette analyzes the intrinsic structure of each name component and performs an intelligent comparison using advanced linguistic algorithms. Under the hood, Rosette name matching utilizes the cutting edge of NLP techniques including neural networks, hidden Markov models, transliteration rules, and word embedding vectors.
How does Rosette improve the call center customer satisfaction?
66% of customers are frustrated before they even start talking with a customer service representative (source). Why take even more of their time with identification questions? Rosette helps your contact center agents decrease the time they spend on customer identification, therefore, they can spend more time on solving your customers' problems and making them happy.
Do I need to change my database system to use Rosette?
No. You can integrate it into your current CRM system, ask our engineering team for more details.