Understanding Behavioral Segmentation: Data Science Algorithms and Visualization
Learn about behavioral segmentation, data science algorithms, and visualization. See a demo on experiencedatascience.com to create and interpret customer segments.
File
Behavioral Segmentation - From Data to Market Strategy
Added on 09/28/2024
Speakers
add Add new speaker

Speaker 1: 74% of customers feel frustrated when your product offerings are not personalized and behavioral segmentation is a way to solve the problem. So in this video you will see on what is behavioral segmentation, related data science algorithms as well as visualization. You can also access a demo on behavioral segmentation on my website experiencedatascience.com. So let's jump in. Simply said behavioral segmentation is about understanding customer behavior, how they interact with your product or website, how often they use it, how much they spend and what products they buy. It requests collecting data from various sources such as website navigation data, billing data, product purchase data and lots of other sources. More data you have better you'll be able to understand the behavior. Once you have collected the data you can start the behavioral segmentation process which involves feature creation, segment creation using clustering algorithm, segment interpretation and then creating a marketing strategy. In order to illustrate the process let me take an example of a telecommunication company who has collected data on customer demographics, what services the customer has as well as the billing information. Now we can create segments using a clustering algorithm and assign each customer to a segment. Shown here is a result of clustering algorithm and there are three segments which are shown here in blue, red and green color. Each dot corresponds to a customer and we can hover over the dots to see the customer details. So what does the segments mean? A radar chart can help us interpret them. For example the green cluster is one with the customers with the highest tenure and who use all services such as internet services, online backup, tech support and streaming movies. The blue cluster is the one with the lowest tenure and moderate usage of all services and the red cluster corresponds to the customers who have only phone services and do not have digital internet services. Now we know the customer behavior we can develop market strategy. The green cluster is digitally engaged customers. A market strategy could be to create a digital loyalty card and reward them based on use of digital services. This in turn will also increase the revenue for the company. The blue cluster are moderately engaged customers with low tenure and a market strategy could be to offer discounts and convert them into long-term contracts. The red clusters are basically customers with only phone service and a market strategy could be to educate them about the advantages of digital services and then upsell digital products. You can try out the demo on behavioral segmentation on my platform experiencedatascience.com. The demo is located over here. You'll be able to see the data, make the clustering as well as interpret the clusters. No coding is required and you can hover over the tip button to see on how to use the demo. So friends thank you for watching. Please do subscribe to the channel, like and comment on the video.

ai AI Insights
Summary

Generate a brief summary highlighting the main points of the transcript.

Generate
Title

Generate a concise and relevant title for the transcript based on the main themes and content discussed.

Generate
Keywords

Identify and highlight the key words or phrases most relevant to the content of the transcript.

Generate
Enter your query
Sentiments

Analyze the emotional tone of the transcript to determine whether the sentiment is positive, negative, or neutral.

Generate
Quizzes

Create interactive quizzes based on the content of the transcript to test comprehension or engage users.

Generate
{{ secondsToHumanTime(time) }}
Back
Forward
{{ Math.round(speed * 100) / 100 }}x
{{ secondsToHumanTime(duration) }}
close
New speaker
Add speaker
close
Edit speaker
Save changes
close
Share Transcript