By the end of this module, participants will be able to:
- understand the difference between descriptive segmentation and behavioral segmentation
- identify segments based on frequency, affinity, or consumption intensity
- understand the editorial and business value of working with dynamic segments
- recognize how this information can be used in newsletters, recommendations, or registration strategies
From demographic segmentation to behavioral segmentation
At an initial level, a newsroom may segment audiences by country, device, or language. At a more advanced level, teams also begin to analyze how users behave:
- how frequently they return
- how much content they consume
- which types of content they prefer
- whether they recirculate or leave quickly
- whether they show signals of greater propensity to register or subscribe
Behavioral segmentation is often more useful for editorial decision-making than purely descriptive segmentation.
Types of useful segments
Some common and useful segments include:
- new users
- returning users
- high-consumption users
- single-article readers
- users with affinity for a specific topic or section
- users with high conversion propensity
- users at risk of churn
The goal is not to build segments for their own sake, but to create groups that help teams make better decisions.
These categories only become useful once they are operationally defined. A “high-consumption user” might mean someone who visits at least five times per week or reads more than three articles per session — the threshold depends on the organisation’s audience patterns. “Affinity for a topic” can be identified through repeated visits to a section or consistent engagement with a specific content type. “At risk of churn” typically describes a subscriber whose visit frequency has dropped significantly over a defined window, such as two consecutive weeks. Without these definitions, segments remain labels rather than tools.
Affinity and intensity of consumption
Affinity refers to a user’s preference for certain topics, formats, or products.
Intensity refers to how much and how frequently a user consumes content.
Combining these two dimensions allows teams to build very useful segments. For example:
- very frequent users with affinity for politics
- occasional users highly interested in sports
- newsletter readers with deep reading but low recirculation
In practice, affinity is usually derived from a user’s visit history across sections, topics, or content formats. Intensity is measured through visit frequency and consumption depth — how often someone returns, and how much they read when they do. The combination of both dimensions creates segments that are genuinely useful for editorial and audience decisions. A user with high affinity but low intensity might respond well to a personalised newsletter that brings the content to them directly. A user with high intensity and broad affinity is likely already close to a conversion moment and may respond to a well-timed registration prompt.
Dynamic segments and activation
A dynamic segment is not a fixed category but a group that changes as user behavior changes. In practice, this means that users move between segments automatically as their behaviour evolves. A reader who visits twice in a week may fall into a “new user” segment; if they return consistently over the following month, they shift into “returning user”; if their visits then drop sharply, they may enter an “at-risk” segment — all without any manual reclassification. This automatic updating is what makes dynamic segments useful for activation: a retention message or registration prompt fires at the right moment, based on actual behaviour, rather than a scheduled campaign that treats all users the same.This logic is particularly useful in activation strategies:
- which users should see a registration message
- which users should receive a thematic recommendation
- which readers appear ready for a subscription offer
- which groups should be reactivated with a specific format or product
From observation to action
The real difference between superficial segmentation and mature segmentation lies in the ability to connect observation with action.
Segmentation only provides value when it is used to:
- personalize experiences
- prioritize editorial or product strategies
- improve decision-making
Consider a simple example. A team observes that users who read three or more articles from the investigations section within a seven-day period convert to registered users at four times the average rate. That is an observation. The activation version of that observation is: set up a targeted registration prompt that appears for users who hit that threshold. The prompt does not go to everyone — only to readers who have already shown the specific behaviour that predicts conversion. That is the difference between segmentation as a description and segmentation as a decision.
Try it yourself
Your analytics platform has identified four user profiles based purely on recent behaviour. No demographic data — only behavioural signals:
User A — Visits 5–6 days per week · Reads almost exclusively Politics and Europe · Avg. 4 articles per session · Never registered · Has received your newsletter for 8 months
User B — First visit this week · Arrived via Google · Read one article · Spent 7 minutes on it · Did not visit a second page
User C — Visits 2–3 times per week · Strong affinity for Culture and Books · Short sessions (1–2 articles) · Registered 3 months ago · Has hit the paywall 6 times — never converted
User D — Was visiting daily six weeks ago · Consumption has dropped sharply · Last visit was 12 days ago · Previously high affinity for Local News
Consider:
- Describe each user in one sentence using behavioural vocabulary — frequency, intensity, affinity, stage in the journey.
- Propose one concrete editorial or audience action for each profile. What would you do differently for each?
- User C has seen the paywall 6 times without converting. What does that pattern suggest — and what would you test first?
- User D hasn’t officially churned yet. What behavioural threshold would you set to trigger a re-engagement action — and what would that action look like?
Descriptive segmentation tells you who your readers are. Behavioural segmentation tells you what to do next.