Hello everyone! I’m looking for advice on how to effectively track changes in user segmentation and maintain the integrity of the segmentation meaning when updating data. We currently have around 30,000 users and want to understand how their distribution within segments evolves over time.
Here are some questions I have:
Should we create a new segmentation based on updated data?
How can we establish an observation window to monitor changes in user segmentation?
How can we ensure that the meaning of segmentation remains consistent when creating a new segmentation with updated data?
Any insights or suggestions on these topics would be greatly appreciated! We want to make sure we accurately capture shifts in user behavior and characteristics without losing the essence of our segmentation.
What is the company doing? How many transactions are anticipated during a certain period of time? There are several pertinent data questions before we can respond to it.
In other words, it’s insurance industry agents, not actual customers. To comprehend the agents’ performances across many industries, we monitor their performance, which was developed by our staff. Depending on how well an agent performs in the field, these metrics/KPIs alter.
How do you go about segmenting? Examine whether there is any deviation from the anticipated feature distribution for each segment’s users. It could be necessary to recalculate the segments if there is any drift. Yet there’s no need if the drift is anticipated, such as if it’s trend- or seasonality-based.
Therefore, it’s actually agents in the insurance business rather than customers. We monitor the performance of the agents that our team developed in order to comprehend how well they work across various domains. The performance of the agent in the field determines how these metrics/KPIs evolve.