Global delivery logistics service 

Our client wanted to understand the driver for high volumes of tracking calls in to the contact centre to determine root cause and identify improvement strategies in agent behaviour, process, and / or technology in pursuit of reducing in these contacts.

The challenge

Delivery service identified that “tracking call” volume was high and continuing to increase. They asked us to research the various reasons for these tracking calls using speech analytics technology, and to utilise expert quality evaluators to further determine root causes.

We proposed a deep-dive evaluator listening study coupled with qualification and call filtering using Speech Analytics technology to determine root causes for tracking calls, with the goal of proposing changes to people, process, and / or technology in pursuit of the reduction goals above.

Approach

Global Delivery Service recently identified tracking calls as the driver of a majority of their calls. Using Speech Analytics and expert human listening, we conducted a study focused on identifying specific sub-drivers along with root causes and recommendations for mitigation.

After conducting a baseline listening session discussing with both the client and evaluator SMEs, three disparate areas worthy of further investigation came to the fore:

  • Delivery drivers deviating from door-tag procedure in 5% of tracking calls
  • Agents providing incorrect estimated delivery dates in 3% of tracking calls
  • Agents proactively recommending future callbacks in 8% of tracking calls

Based on collaboration with the Client, future callback offers were of greatest interest and made up the largest volume, representing over 157,000 interactions per month.

Findings

After creating several Speech Analytics categories to quantify the volume and frequency of proactive callback offers, a bespoke evaluation form was crafted focusing on adherence to procedure, appropriateness of callback recommendations, alternative resolution paths, and other indicators of customer satisfaction and FCR.

Key findings included:

38% of proactive callback recommendations were erroneous or not supported by procedure, representing over 60,000 calls per month

57% of unnecessary callback recommendations should have been diverted to self-service channels instead of offering repeat contacts

10% of unnecessary callback recommendations were made as part of a “polite call closing” and not tied to any procedure – for example, “please feel free to call us back if you have any further questions”

Recommendations

Upon conclusion of the deep-dive listening exercise, the following mitigation steps were agreed:

  • Re-train agents to better understand customer-facing self-service options and encourage them to deflect future contracts to self-help channels
  • More accurately and honestly set expectations, while avoiding definitive dates or providing a buffer for timely delivery.
  • Additional areas requiring further measurement in subsequent project iterations:
    • How often do customers actually call back when agents recommend they do so?
    • How effectively are agents explaining the relevant features of self-service tools and aps?
    • Are they offering to assist customers in launching self-service options?

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