Data analysis for call centers

Posted by: Yellowfin Team

In part one of our mini blog series exploring cross-industry uses and benefits of data analysis – Data analysis for the Retail Industry – we explored how the retail industry was harnessing the insights of Business Intelligence (BI) software.

Now, we’ll take a look at the ability to apply BI to call centers to enhance operations, and better leverage customer information collected via call center interaction.

A new research report by the Aberdeen Group – unlocking Business Intelligence in the Contact Center – outlines how BI can be applied to call center operations to improve performance by collating and analyzing both structured and unstructured data.

The report was compiled from information gathered from over 70 respondents.

Top concerns

The leading concerns that led survey participants to investigate methods for improving call/contact center performance were:

  • Dissatisfied customers (55%)
  • Lack of customer knowledge regarding customers (customer trends unknown) (53%)
  • Underutilized data resources (36%)
  • Low call center staff performance rates (35%)

Divide and conquer

Respondents were divided into three distinct categories:

  • Best-in-Class (20%) Those who engage in “practices that are the best currently being employed and are significantly superior to the Industry Average, and result in the top industry performance.”
  • Industry Average (50%) Those who engage in “practices that represent the average or norm, and result in average industry performance.”
  • Laggards (30%) Those who engage in “practices that are significantly behind the average of the industry, and result in below average performance.”

BI provides insight into customer-base, business processes and a pathway to better call center management

The report found that better performing organizations analyze customer communications and apply that analysis to improve customer service. The report said that this enabled leading organizations to:

  • Improve first call resolution rates
  • Improve daily closure rates
  • Reduce average cost of calls (by reducing length of calls, repeat calls and increasing customer satisfaction ratings)

Aberdeen analyzed call center performance of survey participants, based on those three criteria, over a 12 month period.

Results

The results clearly demonstrated that those organizations that invested in data analysis technology and procedures achieved improved business performance across key indicators as well as significant Return on Investment.

Best-in-Class (top 20% of survey respondents based on aggregate performance scores)
• 84% improvement with first call resolution rates
• 13% increase in change in daily closure rate by call center staff over the past 12 months
• $17.78 average cost of call over past 12 months

Industry Average (middle 50% of survey respondents based on aggregate performance scores)
• 66% improvement with first call resolution rates
• 7% increase in change in daily closure rate by call center staff over the past 12 months
• $32.11 average cost of call over past 12 months

Laggard (bottom 30% of survey respondents based on aggregate performance scores)
• 36% improvement with first call resolution rates
• 3% decrease in change in daily closure rate by call center staff over the past 12 months
• $46.31 average cost of call over past 12 months

Best-in-Class were also able to achieve significantly higher average customer satisfaction ratings on a scale of 1-5, where 1 represents ‘extremely unsatisfied’, and 5 represents ‘excellent’:

Best-in-Class
• 3.9
Industry Average
• 3.7
Laggard
• 3.5

Best-in-class analyze their data

The best performing survey respondents shared the following commonalities, they:

  • Established policies for data governance (recording/monitoring calls)
  • Integrated call center data into a central database
  • Utilized operational BI

Best practice for BI usage: pairing data analysis with business goals

Unsurprisingly, the survey results indicated that firms who performed best, and were rated as ‘Best-in-Class’, shared common factors regarding how they used data analysis, with:

  • 82% measuring customer satisfaction against corporate goals
  • 75% using analytics and reporting tools to assess both inbound and outbound dialogue

Conclusion

The Aberdeen research concludes that to achieve ‘Best-in-Class’ performance, call centers must “implement a dedicated operational business intelligence platform” which will support:

  • Faster decisions
  • More accurate decisions
  • Better business insight and identification of trends for strategic planning
  • Faster dissemination of actionable information to key operational decision-makers

The use of operational BI gives call centers and operators a clearer picture of customer wants and needs by tracking key metrics such as customer satisfaction and retention. Aberdeen’s research indicated that 50 percent of Best-in-Class organizations use operational BI to manage customer support needs, compared to 28 percent of averagely performing companies, and 18 percent of poorer performers.

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