Cohort segmentation

Cohort segmentation is a method used to segment the market for the greatest strategic implications.


Cohort analysis is the behavioral analysis of a given segment of users who share a common characteristic over a period of time.

Cohort analysis works as a segmentation of users whose historical behavior is taken into account to detect patterns or changes in behaviors throughout the user’s life cycle. It is especially interesting for discovering trends and taking action.

For example, a cohort could be all users who have signed up on a given day. On this segment, an analysis would be carried out on how these users behave, what actions they perform and how their behavior differs from other groups of users.

Please help me find a healthcare related service, product, or organization on one of a multitude of social networking sites. Which cohort segmentation section is the service, product, or organization geared for on the site? Why would this type of marketing be successful?

Select one other cohort segmentation category. From a management perspective, what recommendations would you make to the marketing department to broaden the marketing efforts to include another cohort segmentation not currently being targeted.

Analysis of cohorts in ecommerce

Some of the cohort analyses can be applied to e-commerce to gain efficiency in digital strategy.

Transformation of Leads into Customers

Through Analytics you can generate a report that defines the leads that have finally become customers. To do this, you have to select a period of time of at least a few months. Select cohorts by date of first visit to the web to cross it with the metric number of customers. So you can check if you are managing to convert more customers on the first visit with the web

Revenue by geographic location

The cohort can be defined according to the location of the client. In this way you can check the difference in user habits in Andalusia or Galicia.

Define the best traffic channels

With cohort analysis you can check which channels work best. After grouping in cohorts by means of first visit, it is possible to study which channel has more user retention, which has a higher average cart value or from which medium the customers with the highest LTV are generated.

Behavior of registered users

With the cohort of registered customers you can check if they have a greater commitment than the rest of the clients with the web.

Cohort Analysis in Google Analytics

Google Analytics has a report called cohort analysis in which you can do web analytics studies such as user retention: which ones return two days after registering, a week later, or 30 days later.

What is Sentiment analysis

Sentiment Analytics


Sentiment analysis is a type of natural language processing to track the public’s mood about a particular product.

Sentiment analysis involves building a system for collecting and categorizing opinions about a product. Also known as opinion mining, it can be automated using machine learning, a type of artificial intelligence (AI), to extract sentiment from text.

Applications of sentiment analysis

With this system, you can help marketers evaluate the success of an advertising campaign or new product launch or analyze whether versions of a product or service are popular.

For example, a review from a website might be quite positive about a digital camera, but at the same time it is specifically negative about how heavy this camera is. Being able to identify this type of information in a systematic way gives the provider a much clearer picture about public opinion than surveys or focus groups, because the data is provided by the customer directly.

How sentiment analysis works

  • We analyze the exact intent of a phrase to know if it speaks of a brand or a product.
    We value the phrase through polarity, which classifies the message according to the author’s intention, and can be positive, negative or neutral. With this you control the feeling of the users.
  • Processing of the information of the previous points. This process is divided into:
    • Manual: if the word or expression can have different meanings depending on the field, that word will have to be classified manually where appropriate.
    • Automatic analysis: different keywords are established that frame the expressions depending on what words or set of similar words you have. An example of this could be that any phrase that carried “good”, “beautiful”, “beautiful” was included in the positive feeling section.

Limitations of Automatic Sentiment Analysis

The main one is that it is not as effective in ranking as manual sentiment analysis can be.

In addition, the programs that are responsible for the automation of these tasks are not able to differentiate exactly if a sentence contains sarcasm or irony and, therefore, could confuse a sarcastic phrase of the style “yes, yes, that product (x) is very good but on the other end”. Therefore, the vast majority of software are not able to know the real intention of a sentence and, consequently, catalog it as positive or negative.

There are certain programs that are able to differentiate a sincere phrase from a more ironic one but they are somewhat more complex to configure.

What is cohort segmentation?

In the context of business analytics, a cohort usually refers to a subset of users specifically segmented by acquisition date (i.e. the first time a user visits your website). A “cohort analysis,” then, simply allows you to compare the behavior and metrics of different cohorts over time.

What is the difference between cohort and segment?

A segment is not time or event-based but a cohort is a group of people that is observed over a period of time.

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Solution Preview

The Women’s Health Screening chart, accessible on Facebook, targets women in various age cohorts. The chart is broken down into age categories for adult women: 18-39; 40-49; 50-64; and 65 and older (U.S. Department of Health and Human Services Office on Women’s Health, 2013). This type of marketing can be successful for many reasons. First, women tend to share all kinds of information through social networking, like jokes, poems, recipes, shopping updates, and any information they believe will benefit the members of their social network. Even though there are fewer women in the 65 and older cohort using social networking sites routinely, their daughters, nieces, sisters, and granddaughters will be able to quickly scan the appropriate box for the age cohort and inquire among female relatives about whether they have had the necessary health screening tests. The chart is easy to use and quickly …

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