Logistic Regression

Definition

Logistic Regression is a statistical model used in machine learning to predict binary outcomes (e.g., yes/no, open/bounce, convert/not convert). It estimates the likelihood of an event occurring by analysing relationships between input features—such as time on pageDefinition In the realm of SEO, time on page refers to the a..., click-through rate, or user demographics—and a binary response.

In content marketingDefinition Content marketing strategically creates and share..., SEO companies use logistic regression to determine whether a website visitor is likely to become a leadDefinition A Lead in the context of SEO refers to a potentia... based on on-site behaviour. A performance marketing agency might deploy it to analyse which ad impressionsDefinition Impressions track campaign effectiveness for digi... result in form submissions. Similarly, a digital marketing Auckland firm could use it to predict which email recipients will open newsletters or respond to offers.

Unlike linear regression, which predicts continuous outcomes, logistic regression provides a probability between 0 and 1. This makes it ideal for targeting, personalisationDefinition Personalisation refers to the process of tailorin..., and leadDefinition A Lead in the context of SEO refers to a potentia... qualification strategies.

Example Scenario

A performance marketing agency wants to improve leadDefinition A Lead in the context of SEO refers to a potentia... quality from paid campaigns. Using logistic regression, their data team models the probability of conversionDefinition In the realm of SEO, Conversion refers to the pro... based on input features: time spent on landing pagesDefinition Landing pages are standalone web pages specifical..., trafficDefinition In the context of SEO (Search Engine Optimisation... source, CTA clicks, and device type. The model predicts that mobile users who visit for over 60 seconds and click a CTA have a 74% probability of converting. Based on this, the agency targets similar users and increases conversionDefinition In the realm of SEO, Conversion refers to the pro... rates by 31% in two weeks.

Formula

Formula: P(Y=1)=11+e−(β0+β1X1+β2X2+⋯+βnXn)P(Y=1) = \frac{1}{1 + e^{-(\beta_0 + \beta_1 X_1 + \beta_2 X_2 + \dots + \beta_n X_n)}}P(Y=1)=1+e−(β0​+β1​X1​+β2​X2​+⋯+βn​Xn​)1​

Explanation:

• P(Y=1)P(Y=1)P(Y=1): Probability of a positive event (e.g., a conversionDefinition In the realm of SEO, Conversion refers to the pro...)
• β0\beta_0β0​: Intercept
• β1,β2\beta_1, \beta_2β1​,β2​: Coefficients for features
• X1,X2X_1, X_2X1​,X2​: Features such as time on site, clicks, etc.

Final probability: P = \frac{1}{1 + e^{-2.10}} ≈ 0.89 \text{ (89% chance of conversionDefinition In the realm of SEO, Conversion refers to the pro...)}

5 Key Takeaways

1. Logistic Regression predicts binary outcomes, such as whether a user will convert.
2. It uses behavioural and demographic inputs to produce probability scores.
3. Marketers can segment audiences based on predicted outcomes.
4. It’s ideal for campaignDefinition An SEO campaign involves focused, Organised effor... targeting, lead scoringDefinition Lead Scoring in AI Terms in Content Marketing is ..., and A/B test evaluation.
5. Results help shape personalised content flows that improve performance.

FAQs