--- title: Glossary of Key Terms description: This glossary provides definitions for key terms used within Cassandra’s Marketing Mix Modeling (MMM) platform. Use this guide to better understand model outputs, budget optimization, and data integration. --- [Skip to content](https://docs.cassandra.app/migration/cassandraglossary#main-content) English Show submenu for translations [Open a Support Ticket](https://docs.cassandra.app/migration/kb-tickets/new?hsLang=en) ![64e670ef6e6ad43bbf323db2\_logo\_large-1-p-500.png\]](https://docs.cassandra.app/hs-fs/hubfs/Mktg%20Asset/64e670ef6e6ad43bbf323db2_logo_large-1-p-500.png?height=35&name=64e670ef6e6ad43bbf323db2_logo_large-1-p-500.png) Open main navigation Close main navigation - English Show submenu for translations - [Open a Support Ticket](https://docs.cassandra.app/migration/kb-tickets/new) - [Go to cassandra.app](https://www.cassandra.app/) [Go to cassandra.app](https://www.cassandra.app/?hsLang=en) Welcome. How can we help you? - There are no suggestions because the search field is empty. 1. [Knowledge base](https://docs.cassandra.app/migration?hsLang=en) 2. [Getting started with Cassandra](https://docs.cassandra.app/migration/getting-started-with-cassandra?hsLang=en) # Glossary of Key Terms ## This glossary provides definitions for key terms used within Cassandra’s Marketing Mix Modeling (MMM) platform. Use this guide to better understand model outputs, budget optimization, and data integration. ### **A** - **Adstock Effect** – The lasting impact of advertising campaigns, where exposure continues to influence consumer behavior over time. - **Algorithmic Attribution** – A data-driven approach to assigning credit to marketing channels based on statistical modeling. - **Attribution Model** – A framework for distributing credit across touchpoints in the customer journey. - **Average Error on Prediction** – A measure of how far off the model’s predictions are from actual values, indicating forecast accuracy. ### **B** - **Baseline** – Sales that would occur even without marketing spend, influenced by external factors such as seasonality and economic conditions. - **Bayesian Modeling** – A statistical method that incorporates prior knowledge and updates probabilities based on new data. - **Budget Allocator** – A feature in Cassandra that optimizes media spend based on historical performance and diminishing returns. - **Business Error** – When a model’s predictions do not align with real-world expectations, such as underestimating a highly impactful channel. ### **C** - **Calibration** – Adjusting model parameters to improve alignment with observed data and real-world performance. - **Channel Contribution** – The percentage of total revenue attributed to a specific marketing channel. - **Confidence Interval** – A statistical range estimating the likely impact of a marketing channel, indicating the certainty of attributions. - **Conversion Lift Test** – An experiment measuring the true impact of a marketing campaign by comparing exposed vs. non-exposed audiences. - **CPA (Cost per Acquisition)** – The cost incurred to acquire a new customer through marketing spend. - **CPM (Cost per Mille)** – The cost per 1,000 impressions in advertising. - **CTR (Click-Through Rate)** – The percentage of users who click on an ad after viewing it. ### **D** - **Data Integration** – The process of importing and structuring marketing data into Cassandra. - **Dataset** – The collection of structured data, including marketing spend, conversions, and external factors, used to analyze performance. - **Diminishing Returns** – The principle that increasing investment in a marketing channel eventually leads to reduced incremental gains. ### **E** - **Elasticity** – A measure of how changes in marketing spend impact conversions or revenue. - **Experimentation** – Testing marketing hypotheses through **GeoLift** or **Conversion Lift** studies. ### **G** - **GeoLift Experiment** – A test that measures the effectiveness of marketing spend by comparing regions where advertising was paused versus active. - **Granularity** – The level of detail in a dataset, such as daily vs. weekly spend data. ### **I** - **Incrementality** – The additional revenue generated by a marketing channel beyond what would have happened organically. - **Impressions** – The number of times an ad is displayed to users. ### **M** - **MMM (Marketing Mix Modeling)** – A statistical approach to measuring and optimizing the impact of marketing investments. - **Model Refresh** – Updating a Cassandra model with new data to reflect the latest business trends. - **Multicollinearity** – When multiple marketing variables are highly correlated, making it difficult to isolate their individual impact. - **Media Spending** – The total investment allocated to advertising and marketing efforts across different channels. ### **O** - **Optimization** – Finding the best way to allocate marketing budget for maximum efficiency and ROI. - **Organic Growth** – Revenue or customer acquisition that occurs without paid marketing. - **Organic Variables** – Factors influencing sales that are not directly tied to paid marketing, such as word of mouth or brand reputation. - **Output Variable** – The key performance metric (e.g., revenue, conversions) that a model predicts based on marketing inputs. ### **P** - **Paid Attribution** – Revenue attributed to paid marketing activities. - **Platform Discrepancies** – Differences between Cassandra’s model outputs and platform-reported metrics due to different attribution methodologies. - **Predictive Analytics** – Using historical data to forecast future performance. ### **R** - **ROAS (Return on Ad Spend)** – Revenue generated per dollar spent on advertising. - **ROI (Return on Investment)** – The profitability of marketing activities, calculated as revenue divided by marketing spend. ### **S** - **Saturation** – The point at which additional marketing spend no longer drives incremental sales growth. - **Saturation Curve** – A graphical representation of how marketing spend affects returns at different levels. - **Seasonality** – Recurring fluctuations in demand based on time of year (e.g., holiday sales trends). - **Sales Decomposition** – Breaking down total sales into different components, such as baseline sales, paid media impact, and seasonality effects. ### **T** - **Touchpoints** – The various interactions a customer has with marketing before conversion. - **Time Lag Effect** – The delay between marketing exposure and resulting conversions. ### **U** - **Uncertainty Measurement** – A calculation in Cassandra that indicates how confident the model is in its attribution estimates. - **User Journey** – The path a user takes from awareness to conversion across different marketing channels. --- ### **Summary & Next Steps** - Use this glossary to understand Cassandra’s key terms and improve your data analysis. - If you need further clarification, visit Cassandra’s **Help Center** This glossary will be continuously updated as new features and methodologies are introduced in Cassandra. - [Getting started with Cassandra](https://docs.cassandra.app/migration/getting-started-with-cassandra?hsLang=en) - [Data preparation & Model Calibration](https://docs.cassandra.app/migration/data-preparation-model-calibration?hsLang=en#main-content) - [Connectors - How to?](https://docs.cassandra.app/migration/data-preparation-model-calibration?hsLang=en#connectors-how-to) - [Optimization & Budgeting](https://docs.cassandra.app/migration/optimization-budgeting?hsLang=en) - [Experimentation & Validation](https://docs.cassandra.app/migration/experimentation-validation?hsLang=en) - [Forecasting & Strategic Planning](https://docs.cassandra.app/migration/forecasting-strategic-planning?hsLang=en) - 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