The fight for the customer

In the age of online trade, it is more important than ever for retailers with a fixed location to know how to attract customers themselves and maintain their custom.

To find out what makes the customer happy, customer satisfaction is ascertained on the whole with individual aspects influencing the decisions to buy, such as, the range and diversity of goods offered, the shop layout, the price/performance ratio etc.  The data is generally evaluated descriptively.

Limits of traditional analysis – Facts without context

This analysis does, however, have its limits as it provides only facts: how satisfied is my customer currently? How does their satisfaction change over time?

As a rule, it is recommended to first and foremost optimise the factors with the lowest ratings. This does not always lead to an increase in the total satisfaction as there are further questions that need to be taken into account:

What exactly do I need to optimise that will most likely lead to a significant increase in my customer’s satisfaction?

This is an extremely important question, especially in regard to the trader’s limited budget. If an aspect does not have a significant influence on satisfaction, the investment in its optimisation can prove to be a bad decision.

Are all aspects equally important for my customer?

The areas of satisfaction raised in the survey can influence the overall satisfaction in varying degrees. For example, the freshness of fruit and vegetables may be more important than the freshness of meat.

How do the aspects influence each other? 

In descriptive analysis, the different aspects are viewed in isolation against reality. For example, satisfaction with the freshness of goods may actually influence price satisfaction.

Illuminating the context made easy – Driver analysis in trade

To answer these questions, IWD market research GmbH uses the PLS structural equation modelling, which is known as driver analysis. The drivers, i.e. influential factors on the overall satisfaction, are checked within the context of their significant meaning.

In the last few years this method has gained more and more currency in science, but has nevertheless been deemed too elaborate in practice. Therefore, it has more insights and clearer guidance for the decision maker when used as a management tool.

A real-world example

As part of a study, customers of a retailer were questioned directly at the point of sale. In doing so, it was important to evaluate not only the overall satisfaction but also individual satisfaction with, for example, the price, the availability of goods, the range of goods offered and the freshness of various product groups (bread and baked goods, fruit and vegetables, meat) as well as the shopping environment (value of employee friendliness, waiting times at the till, the cleanliness).

Using a driver analysis with SmartPLS, factors with a significant influence and their influence strength can be identified.  Additionally, the question could be answered as to how these drivers are characterised by individual product groups as well as the shopping environment.

Excerpt of model structure in SmartPLS

Specific recommendations for action

A representation in an importance-performance-matrix makes it clear where the retailer should start. In this matrix, the average overall valuation in the satisfaction model (performance) is uniformly scaled on a point system from 0 to 100 and compared with the influence on the overall satisfaction (importance). The importance is presented on a scale from 0 to the highest reached influence value.

The analysis of the driver shows that the retailer should first put the freshness of the product groups, followed by the valuation of prices, under the microscope. In relation to satisfaction with the shopping environment, it must be made sure, due to the highest influence, that the performance does not sink below the middle value.

A detailed consideration further shows that the most urgent need for action is to be found with the freshness of meat as well as fruit and vegetables, followed by the price perception of meat and the waiting times at the till. The valuation of cleanliness should not sink below the average.

Take a look at the exact results and recommendations in the dashboard “Driver of customer satisfaction in a food retail store”. Select “Overall Performance” to see how the aspects of freshness, price, range of offered goods, availability and shopping environment perform and influence customer satisfaction. Move the cursor to the aspects in the chart you are interested in to see the exact values. In the next step, for example, select “Freshness in detail” and see the exact value for performance and importance in the product groups.“

Tangible analysis for sustainable optimisation at POS

If shyness with the driver analysis is discarded, more information and concrete guidance can be retrieved from the survey data with minimal effort. These can be checked and adjusted afterwards using tracking via the time series.

The driver analysis can also be conducted for open-ended statements in combination with an overall satisfaction measure. Therefore, more and more insights can be gained from short surveys.

By applying the PLS structure equation modelling, the way is free for tangible analyses of contexts and predictive guidance on precisely controlling valuable optimisations in trade.

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