SEGMENTS COMPARATOR

Segments Comparator is the module for comparing two segments with each other and analysing the results.

1. Introduction

This module is used to select two different segments and compare them to each other. It is very useful to see which aspects of every campaign have worked better and to differentiate which features obtained more results.

2. How to create a new comparison

Select two segments to compare them with each other. If you want to compare a segment with the control group, we recommend selecting the main segment first and the control group second. Remember that in order to use segmentation based on Customer Lifetime Value or a buyer-people cluster you must first create the segment. If no segment appears in the dropdown, it must be previously created in the segmentation module.

Time scheduling

In this module, the amount of time used to compare the segments it’s a key aspect, depending on this, the values obtained and the assumptions about the success of the campaigns will get very different results.

3. Data Visualization

This section allows for a more visual understanding of the results of two segments for comparative analysis. It is important to select the main segment first and the control group second. Remember that in order to use segmentation based on Customer Lifetime Value or some buyer-person cluster, you must first create the segment.

1. Data Overview

It shows an initial comparison of the segments selected. The graphic compares the level of loyalty, where X is the number of tickets per customer, Y is the average cost per customer and the size of the circle is the volume of customers in each segment. The table presents a comparison of the main KPIs to compare.

2. Executive Summary

This section shows several summaries crucial for the comparison of the segments, they are classified into:

• Segment A overview: General information about the main KPIs of the first segment chosen.

• Segment B overview: General information about the main KPIs of the second segment chosen.

• Global insights: A general overview of the ticket percentages and money received for each segment.

• Performance insights: A general comparison of the performance evolution of each segment, analyzing the numbers by itself and by every 1000 customers.

• RFM insights: An analysis of the recency, frequency, and monetary value of each segment.

• Life cycle insights: It shows the difference of each value obtained in the Customer Life Cycle by the different customers in the segments.

3. Commercial communications (GDPR)

It shows a comparison of the volume of customers who have agreed to receive commercial communications in both segments. This information must be ingested in the subscribed field of the client. Remember that you can only send commercial communications with those customers and registries that have agreed to receive commercial communications.

4. Revenue evolution

The evolution of the main consumption indicators of the two segments is shown in this table: the information shows the number of active customers during the period, the total segment spending, the number of tickets made, and the average of consumption tickets made.

Using the different time options you can see and compare the evolution of both segments. Remember that at this point absolute values are being compared.

5. Revenue uplift

This field shows the customer activation based on the difference between the global uplift and the uplift evolution, all compared in every 1000 customers:

• Uplift evolution per 1.000 customers: We use the KPIs of Tickets per 1,000 clients and Revenue per 1,000 clients to compare the results of very different volumes. The uplift is calculated by subtracting the value of segment 2 from segment 1.

• Global uplift per 1.000 customers: Global difference of the entire selected period of the number of tickets and total revenue. Remember that the calculation is done by first calculating the KPI per 1,000 customers (all customers from the segment) and then making the difference of segment 1 minus segment 2.

6. Repetition rate

The repetition rate allows us to compare both segments using the metrics of tickets per customer and revenue per customer throughout its evolution in the period.

7. CLV Distribution

This graphic shows the distribution of the number of active clients during the analyzed period of the two analyzed client segments. The longer the period analyzed, the more profiles at risk or hibernation will appear.

8. Global data comparison

Comparison of the most important KPIs in absolute values of the two selected segments: the number of active clients, the total cost of the clients, the number of tickets made, and their average ticket.

9. RFM average comparison

The average of the RFM values for the two compared segments is shown below. The recency refers to the number of days since the last purchase, the frequency represents the number of tickets per customer and the money represents the total expense.

10. Life Cycle

The following graphic shows the Lifetime Value average (LTV) and the time between purchases calculated in days (TBP).