Sep. 28, 2016 | InBrief

Breaking down and generating accurate customer service time

Breaking down and generating accurate customer service time

With increasing competition from online retailers and delivery services, many brick and mortar retailers are facing challenges growing the physical and store portion of their business. Their challenges include:

  • Limited merchandise

  • Convenience of having product delivered

  • Lower prices available online

In order to maximize value from stores, retailers need to focus on customer service. Customer service, when executed correctly, will result in repeat business. But one negative experience and a customer may be lost forever!

Most retailers seek to achieve an optimal level of service that will satisfy customers but is also fiscally responsible. How do you strike the right balance and operationalize the customer experience? There are three methods to collecting/evaluating customer service data (contingent on the availability of system data and the level of detail in the scheduling software):

  1. Work sampling/direct study
  2. System data

  3. Strategy based approach

Work Sampling or Direct Study

Work sampling or direct study involves engineers observing associates or customers and analyzing the activities occurring throughout a shift or store visit. Three types of studies can be conducted:

  • Associate direct study - An engineer observes one associate, documenting his or her activities throughout a shift

  • Associate work sampling - An engineer follows a pre-defined path and documents the activities of all associates

  • Customer direct study - An engineer observes one customer documenting his or her activities throughout a visit

Below are the advantages and disadvantages associated with each type of study:



Associate Direct Study

  • Detailed data about associate activities

  • Multiple studies can be completed in unison

  • 1:1 ratio between associate and engineers

    • Manpower required for sampling of associates

    • Slow implementation across stores

    • Study a select number of stores

  • One-sided view of store experience

Associate Work Sampling

  • Multiple studies can be completed in unison

  • More stores can be studied because less manpower is required

  • Faster implementation across all stores

  • Less detail than an associate direct study regarding associate activities

  • One-sided view of store experience

Customer Direct Study

  • Multiple studies can be completed in unison

  • Understand and evaluate each customers complete store visit

  • 1:1 ratio between customers and engineers

    • Manpower required for sampling of customers

    • Slow rollout across stores

    • Study a select number of stores

  • One-sided view of store experience

  • Depending on number of customers visiting a store, as well average length of a customer visit, there exists potential for an extended study period

System Data

System data is information stored in a database or server. System data, when captured correctly, is critical to measuring customer service. However, system data is often incomplete and does not include key pieces of information such as duration of interaction and unique interactions with associates. If interactions and duration are captured, the data needs to be closely examined to determine if the interaction is all value added time.  If the data is not thoroughly examined, the amount of time required to complete customer service activities can be underestimated or exaggerated.

Although there are some limitations in regards to capturing customer service data, information such as unique transactions, items sold, or distinct customers can be utilized in combination with work sampling data or strategy based decisions to generate the required service time for each customer entering the store or unique transaction completed.

Strategy Based

A strategy based approach involves being aware that associates in the store are the face of the company. Customer service can be lost in the mix when a disproportionate amount of energy is focused on reducing operating costs by process improvement and cost saving initiatives versus revenue generating activities. Informing associates how much time they should spend on customer service reminds front line associates that the customer comes first. Additionally, it reminds engineers and project managers that training and the appropriate roll-out schedules are critical steps in all process improvement and cost saving initiatives.

When determining how much customer service time is needed, a company has several options:

  • Focus groups – a demographically diverse group of customers or associates discuss the customer experience in a store

  • Store analysis – change customer service amount in same store(s) and document how sales are affected. The same group of stores should be used for all studies; major holidays and/or events should be avoided to accurately assess how customer service affects sales.

  • Customer journey mapping – a diagram that illustrates the steps your customer(s) go through when engaging with your company. For a more detailed look into the customer journey mapping process, read this article from Harvard Business Review, and check out some West Monroe insight for more information.

  • Industry benchmarking – comparing the customer service at your company with industry best practices.

Each of the techniques analyzed above -- work sampling, system data, and a strategy based approach -- used alone will provide a great foundation for providing optimal customer service.  The most successful approach, however, is a combination of the three techniques. A sample approach may look like this:

  1. Choose a store(s) to serve as pilot/test store(s)
    • Can be only one department
  2. Determine a range of customer service goals (i.e., percentage of time spent on customer service)
    • A variety of approaches were discussed in the strategy based section
  3. Inform the stores how much time they should allocate to customer service
  4. Use work sampling to verify that customer service time is being utilized effectively
    • Work with the stores to make the necessary adjustments (if applicable)
  5. Use system data to understand sales during the trial period
  6. Repeat steps 3-5 for several different customer service percentages
  7. Compare the sales results between each different customer service percent to determine the optimal level of customer service for your business
    • Remove any outlier sales data that may skew the results

Following the outlined approach will provide your customers with the appropriate amount of attention, maximize sales, and demonstrate to your associates that you are invested in a customer-centric culture with a hands-on approach.

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