Developing Paradata Tools to
Maximize Call Center Conversion
Maximize Call Center Conversion
Rates
Todd Heinrich (presenter), Jeff Pittman, and Kuttan Abu
International Field Directors and Technologies Conference May 16, 2011
Overview
• Define various types of survey paradata.yp y p
• Examine an RTI project that needed to update its call center
performance reports.
• Demonstrate some of the graphical tools created to utilize paradata to
better track recruiter activities.
What is Survey Paradata?
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• Survey Paradata – additional data that is ancillary to the primary y y p y
activities of the data collection.
• Some Types
– Recruitment
• Phone logs
• Timestamps to track a recruiter’s progress
• Information about the recruiter like where they grew up, educational background, and employment history
– Collection
• Length of time from initial contact to completion
• On a web survey you might have number of sessions required to complete a survey
– FrameFrame
• Linking Geographical Information System(GIS) with various demographic data such as average income, education levels and racial mix.
The need for better metrics
• About the RTI project p j
– 8+ year project for a confidential client
– Large mixed mode (web/paper) establishment survey
– Sampled just under 200k establishments
– 160k surveys completed
– 160k surveys completed
– Dedicated call center for the collection with ≈ 15 full time interviewers
– Focus on establishments in specific industries and occupations
• Over time, our traditional recruiter performance indicators where
showing trends that didn’t correspond to the actual case outcomes
– Lower talk times
– Large variance of time between the initial contact to final completion
– Large variance of time between the initial contact to final completion
The impact of the Internet
p
• The way our recruiters interact with establishments has changed y g
dramatically over the life of the project.
From phone to a mixed-mode recruitment protocol
– Provide URLS to recruitment materials over the phone.
– Active recruitment via email.
– Provided recruitment documents as attachments over email during the initial call.
I t i ld id i t t b d d
– Interviews could provide instant web usernames and passwords.
• Call center performance reports needed to be updated to reflect the
Identifying variables that impact performance
• Metrics based around talk time & phone contacts have a much smaller p
correlation with conversion in a mixed-mode recruitment.
• The industry (SIC code) of the establishment has a large impact on the
overall recruitment protocol.
– Example : ‘White Collar’ vs. ‘Blue Collar’ establishments see differences in:
Mode of Response (Web vs. Paper) Utilization of email for recruitment Telephone talk time
Number of phone contacts Speed of conversion
Evaluating performance with Paradata
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• When reporting on trends, its important to compare ‘like’ data. p g , p p
• Comparing recruiters with similar case mixes.
• Comparing current performance vs. past performance.
• Analyzing performance based on paradata allows call center managers
to better identify strengths and weaknesses of staff.
- Rural vs. Urban establishments
- White Collar vs. Blue Collar establishments
- State where the interviewer grew up vs. all other States
- Small vs. larger establishments
Tools used to compare similar
establisments
Type of technology used
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gy
• Adobe’s ColdFusion Web Application Serverpp • Adobe’s ColdFusion Graphing Engine
Automating Case Assignment based on
Paradata
Paradata
• In theory, if you can quantify strengths and weaknesses of the call y, y q y g
center staff and then anticipate the attributes of the sample, you could model a case assignment algorithm to maximize response rate.
• We have a problem with T.M.I. - (Too Much Information)
– Where do you stop?
A t t d t d th l ith t tl d t d
– Automated systems need the algorithms constantly updated
– Staff turnover
Real World Case Assignment
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• The poor performers often have more variance.p p
• The good interviewers are usually good no matter how you slice the
paradata.
Manually work case assignment from the bottom up
• Provide tools to allow Call Center Mangers to easily evaluate and assign staff to the
new cases.
• Identify poor performers strengths and assign new cases to bolster response rate. • Isolate cases that may be harder to convert and assign staff with that better success in
