Editing AI for Marketing Analytics (section)

== <span style="color: #FFFFFF;">Remembering</span> ==
* '''Customer Lifetime Value (CLV/LTV)''' — The predicted total revenue a business can expect from a customer over their entire relationship.
* '''Churn prediction''' — Forecasting which customers are likely to stop purchasing or subscribing.
* '''Propensity modeling''' — Predicting the likelihood a customer will take a specific action (purchase, churn, upgrade).
* '''Attribution modeling''' — Assigning credit for conversions to the various marketing touchpoints that preceded it.
* '''Multi-touch attribution (MTA)''' — Distributing conversion credit across multiple touchpoints using data-driven models.
* '''Marketing Mix Modeling (MMM)''' — Econometric regression models measuring the ROI of each marketing channel.
* '''A/B testing''' — Controlled experiment comparing two variants; the gold standard for measuring marketing interventions.
* '''Bayesian A/B testing''' — Uses Bayesian inference to make earlier decisions with quantified uncertainty.
* '''Lookalike modeling''' — Finding potential new customers who resemble existing best customers; used in digital advertising targeting.
* '''Audience segmentation''' — Clustering customers into groups for targeted campaigns.
* '''Real-time bidding (RTB)''' — Automated auction for ad impressions; ML models bid in milliseconds.
* '''Click-through rate (CTR) prediction''' — Core ML task in digital advertising: predicting which users will click on which ads.
* '''Conversion rate optimization (CRO)''' — Using data and experiments to improve the fraction of visitors who convert.
* '''Personalization''' — Tailoring content, offers, and messaging to individual users based on their predicted preferences.
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