# How To Calculate SMAC (Stage Monthly Active Clusters) in TeamSupport | Arithmix

Learn how to accurately calculate SMAC (Stage Monthly Active Clusters) in TeamSupport with our step-by-step guide. Improve your team's performance and gain valuable insights into your customer support metrics.

Calculating SMAC (Stage Monthly Active Clusters) is a valuable tool for businesses to measure the engagement and activity of their customers. It provides insight into how often customers are interacting with your product or service, and can help identify trends and patterns in customer behavior. In this article, we will discuss what SMAC is, when it is valuable to calculate, and how to calculate it.

## What Is SMAC (Stage Monthly Active Clusters)?

SMAC is a metric used to measure the engagement and activity of customers within a specific stage of the customer journey. It is calculated by counting the number of unique customers who have interacted with your product or service within a given month, and grouping them into clusters based on the number of interactions they have had.

For example, if a customer has interacted with your product or service once in a month, they would be placed in the "1 cluster". If they have interacted twice, they would be placed in the "2 cluster", and so on. The total number of clusters represents the total number of unique customers who have interacted with your product or service within that month.

## When Is It Valuable To Calculate SMAC (Stage Monthly Active Clusters)?

SMAC is valuable to calculate when you want to measure the engagement and activity of customers within a specific stage of the customer journey. It can help identify trends and patterns in customer behavior, and provide insight into how often customers are interacting with your product or service.

For example, if you are a software company and you want to measure the engagement and activity of customers within the onboarding stage, you can calculate SMAC for that stage. This will give you insight into how often customers are interacting with your product during the onboarding process, and can help identify areas where improvements can be made.

## How To Calculate SMAC (Stage Monthly Active Clusters)

To calculate SMAC, follow these steps:

1. Identify the stage of the customer journey you want to measure.
2. Determine the time period you want to measure (e.g. one month).
3. Count the number of unique customers who have interacted with your product or service within that time period.
4. Group the customers into clusters based on the number of interactions they have had.
5. Calculate the total number of clusters.

For example, if you want to calculate SMAC for the onboarding stage of your software product for the month of January, you would:

1. Identify the onboarding stage.
2. Determine the time period (January).
3. Count the number of unique customers who have interacted with your product during onboarding in January.
4. Group the customers into clusters based on the number of interactions they have had.
5. Calculate the total number of clusters.

By following these steps, you can calculate SMAC for any stage of the customer journey and gain valuable insights into customer engagement and activity.

## How Do You Calculate SMAC (Stage Monthly Active Clusters) in TeamSupport

TeamSupport itself isn�t naturally geared towards letting you calculate complex metrics like SMAC (Stage Monthly Active Clusters). As an alternative, teams typically use products like Arithmix to import data from TeamSupport and build out dashboards.

## What is Arithmix?

Arithmix is the next generation spreadsheet - a collaborative, web-based platform for working with numbers that�s powerful yet easy to use. With Arithmix you can import data from systems like TeamSupport, combine it with data from other systems, and create calculations like SMAC (Stage Monthly Active Clusters).

In Arithmix, data is organized into Tables and referenced by name, not by cell location like a spreadsheet, simplifying calculation creation. Data and calculations can be shared with others and re-used like building blocks, vastly streamlining analysis, model building, and reporting in a highly scalable and easy to maintain platform. Data can be edited, categorized (by dimensions) and freely pivoted. Calculations are automatically copied across a dimension - eliminating copy and paste of formulas.