Optimizing Customer Support

Post on 07-Jan-2017

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Optimizing Customer Support

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Correlation between support usage and user transactions

Identify at-risk, high LTV customers

Products that create support volume

What you’re going to learn

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1

Case Study

Harris Farm Markets

Harris Farm Markets

Harris Farm Markets

Resolving individual customer issue

Making ongoing operational improvements

The Results

RJMetrics Demo

Number of tickets

Number of tickets

Number of tickets

Tickets by status

Average time to resolution

Average time to resolution

Peak ticket days and hours

Who is filing tickets?

Correlation between support usage and LTV

Identify at-risk, high LTV customers

Products that create support volume

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