Decile Analysis in Marketing

Decile analysis is a statistical technique used to divide a data set into ten equal parts. The deciles are used to give information about the distribution of the data. Decile analysis can be used to find out where the majority of the data lies and how the data is distributed. The first decile has the smallest values and the last decile has the largest values. The deciles are then used to compare groups of data or to track changes over time. This technique is often used in market research, as it can help to identify segmentations within a target audience. Decile analysis can also be used to assess the performance of investments, or to evaluate risk levels. To carry out a decile analysis, the data set is first sorted from highest to lowest (or vice versa). The values are then divided into ten equal groups, with each group representing one decile. The first decile group will contain the values that fall at the 10th percentile, while the second decile group will contain the values that fall at the 20th percentile, and so on.

Creating Customer Spend Deciles

To create custom customer spend deciles, marketers first need to collect data on customer spending. This data can be gathered through surveys, loyalty programs, or simply by tracking sales data. Once this data is collected, it can be divided into 10 equal parts, with each part representing a different decile. Businesses can then use this information to better understand their customers' spending habits. For example, obviously, they may notice that the top-spending decile spends significantly more than the bottom-spending decile.

Estimating the sales figures from your buyers

To calculate the sales decile for your customers, first order them from highest to lowest sales. Then, take the top 10% of customers (the ones with the highest sales) and put them in the first decile. The next 10% goes in the second decile, and so on until you have all 10 deciles filled. You can then use this information to target your marketing efforts and better understand which customers are most valuable to your business. For example, you may want to focus more on acquiring new customers in the top two deciles, as they tend to be the most profitable.

Accurately segmenting customers enables effective marketing

In customer segmentation, deciles are a statistical tool that can be used to group customers based on common characteristics. By effectively utilizing deciles, marketers can more accurately target their marketing efforts and better understand the needs of their customer base. Once the data is grouped into deciles, marketers can analyze each group to identify trends and commonalities. This information can then be used to create more targeted marketing campaigns that speak directly to the needs of each customer segment.

It is common to want to know not only how each segment is doing, but also how different segments are doing in relation to each other. A useful way to compare segments is to combine two or more characteristics and then look at the deciles for the new, combined characteristic. For example, suppose you want to compare the performance of males and females. You could create a new characteristic that combines gender with some other characteristic, such as age. The resulting decile analysis would show you how different age groups perform relative to each other, for both genders. You could also combine multiple characteristics into a single analysis. For example, you could look at the deciles for a combined characteristic of income and education level. This would give you insight into which combinations of income and education are performing well relative to others.

Integrating Characteristic Information Into Segmentation Characteristics

It is common to want to know not only how each segment is doing, but also how different segments are doing in relation to each other. A useful way to compare segments is to combine two or more characteristics and then look at the deciles for the new, combined characteristic. For example, suppose you want to compare the performance of males and females. You could create a new characteristic that combines gender with some other characteristic, such as age. The resulting decile analysis would show you how different age groups perform relative to each other, for both genders. You could also combine multiple characteristics into a single analysis. For example, you could look at the deciles for a combined characteristic of income and education level. This would give you insight into which combinations of income and education are performing well relative to others.