The challenge

No one likes to queue. A research agency had collected extensive data for their client, a national bank, on precisely this issue. They had data on the length of time customers spent waiting, the number of staff at the tills and other relevant information. Data was available for many different branches of the bank for countless hours.

The agency outsourced the statistical analysis of the data to us.

Objectives

To identify the factors influencing queuing time so that queues could be kept to a minimum by allocating an appropriate number of staff to serve on the till.

Our approach

We created a statistical model using the data provided by the research agency. This included tens of thousands of observations, showing queuing time and the circumstances at the time.

Outcomes

Our analysis explained a large part of the variation in queuing time. Local factors such as pay-days, market days, levels of income and number of staff servicing the tills had a huge influence. More general factors such as day of week, time of day, seasonality and the state of the economy also affected queuing time.

We made recommendations as to the best number of till staff at any particular time. These varied depending on
different assumptions as to what was an “acceptable” time for a customer to queue.

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The challenge

Our client, a national bank, had installed over 300 free-to-use ATM cash machines in isolated or deprived areas. They were located in local supermarkets and post offices. But were they being used? Were there any benefits in doing this? Was it worth extending the service to other similar areas?

Objectives

• To assess how many customers used the new machines and how often they used them
• To identify customers’ attitudes to the ATMs
• To estimate the time and money customers saved because of the new machines
• To assess the extent to which the stores with the machine, and the neighbourhood as a whole, were benefiting from the installations.

Our approach

We carefully selected a sample of 40 locations which had a new ATM. We carried out face-to-face interviews with customers. These checked levels of use and compared behaviours before and after the installations.

As with all market research, it was vital to get a representative sample of the relevant sector of the population. To achieve this, we conducted interviews on two different days of the week, approximately one week apart. We asked store managers to encourage customers to fill in a questionnaire when an interviewer wasn’t there.

Outcomes

Our report included customer attitudes towards the new ATM machines and the estimated time and money saved by their installation. We quantified the benefits according to factors such as area of the country, level of deprivation of the region and distance to the nearest free-to-use ATM.

The savings were considerable. When this was reported to the regional and national press, the client gained a lot of positive publicity

The post Face to face with ATM cash machines appeared first on PCP Market Research.