Data Analysis in Mystery Shopping

Data analysis is the process of inspecting and modelling data, usually with the goal of discovering useful information that can support decision making. Data analysis has multiple approaches for each industry and sector.

While data analysis can include statistical procedures, it usually becomes an ongoing process where data is continuously collected, and analysed almost simultaneously. An essential part of guaranteeing data reliability is the accurate analysis of the data analysis’ findings. Improper analysis can lead to incorrect fact and figures, and may negatively influence the perception of a business through their own findings.

But how can data analysis be used in mystery shopping? Well, by collecting the data used in mystery shopping in an unbias way, particularly when using computer programs that are made for the purpose of data collection, the data regarding your business can be shown in a way that is easy to understand, and show the facts about the statistics for your business.

Mystery shopping is a service used by external market research companies and watchdog organisations, though it can be used internally by companies to measure their own quality of service, regulation compliance, or to gather information about their own products and services, without the full knowledge of their own employees. It’s a sneaky but smart way to ensure a company is performing their job adequately. A mystery shopper’s identity isn’t usually known while they complete their task, though if a company gets word of a potential visit, they usually inform their workers. This warning doesn’t happen if it’s an internal visit, because companies want real results for their data analysis.

A mystery shopper is set specific tasks to perform to gain the data that a company needs. They will usually enter a premises, and make notes on every transaction that they do and don’t have with the employees of the company. They may purchase a product, ask a lot of specific questions, be told to behave a certain way, and even come back later on to try and return the product they brought. The actions they take are later recorded, and the feedback sent to the company that hired the mystery shopper to complete these tasks.

This data, when it reaches the company, is usually collected among other mystery shopping visitor statistics. These analytics refers to the gathering and interpretation of data in order to make better, more informed business decisions, and optimise business processes. In mystery shopping, the most common use of analytics revolves around understanding how various social interaction experiences can influence customer loyalty.

The analytics of mystery shopping should always contain three specific features: An appropriate survey design, a sample of the product that is large enough to get a feel for the company’s products and services, and a skilled analyst who can understand the business and research on behalf of the client.

Douglas Stafford is a foremost provider of mystery shopping in the UK, who boast their own in-house information technology team to provide you with the best online reporting tools.

Post Author: Owen Jamie