A gain loss analysis aims to explain the dynamics between different segments by looking at the behavior of the customers. Does a segment attract new customers, or do they churn? Are customers switching to other segments? A gain loss analysis is especially designed to answer questions like:
Before the analysis is started, we look at the scope of the research: what are the products and segments for which we want to see the switching behavior. It is important to only include substitute segments and not complementary or unrelated segments. In addition, we also determine together for which period you want the results.
Then the study is created and set up in the report. From then on, you can consult it by opening the report and clicking on the analysis on the first page.
In the filter at the top of the report, you can adjust the reference month, the length of the period (MAT, LxM,…) and the KPIs.
We calculate for every customer the evolution of the volume and revenue generated for every segment. Based on these numbers we then estimate the switching behaviour between the chosen segments.
To get a clear overview of the category dynamics, we divide the volume of every segment in 3 main groups:
The Category Overview gives an overview of the entire category. The graphpanel shows the total evolution of the category and splits this evolution in the three groups (Lost&New, Increased/Decreased Category Spending, Switching).
The Segment Overview displays a detailed view of each segment. When more than 3 segments, you can select the pages just below the graph. The bottom panel shows how much the selected segment gains from the other segments, and how much it loses to those segments.
When the bar is negative, the segment is losing turnover or volume, when it’s positive, it gains. The colors indicate to what other segments, the value or volume goes to or comes from.
In the example, the first segment is gaining turnover from all other segment, but mostly from segment 5, almost €100.000.
For all product segments and for the three groups (new-lost, increased-decreased spending, and switching), you can determine which household type or region is responsible for this change. If you notice an increase caused by new customers in the category, you can immediately identify what type of customers these are.
On the right: Here you specifically analyze the switching behavior to determine which groups switch the most and from which product to which other product they are switching.
To better understand the sales dynamics, we have provided some examples that show where the increased or decreased sales of specific customers end up. In the fictional analysis, we analyze non-alcoholic beverages and want to see the effects on Cola, Lemonade, Iced Tea, and Water.
In this example, we have 2 customers. Customer 1 did not buy soft drinks before, but has started buying them this year. Customer 2 does the opposite. The volumes of these customers will appear or disappear in the category. They will be added to the tables under ‘Lost&New’.
MAT-1 MAT Dif
Customer 1
Customer 2
LOST & NEW calculation:
In this example, we take the same customer 1, but in this example, the customer bought iced tea last year and no longer buys it now.
MAT-1 MAT Diff in-/decreased spending Switching
Since the customer has been buying non alcoholic beverages in either year, the volumes will not be considered for Lost&New.
We start with the same customer, but this time the customer also bought water.
MAT-1 MAT Diff in-/decreased spending Switching
Again, the customer has been buying non alcoholic beverages in either period, and the volumes are not eligible for Lost&New.
We start the same customer, but this time the customer bought much less water this year.
MAT-1 MAT Diff in-/decreased spending Switching
The total volumes of the customer are not increasing this time, but decreasing: