In this page you will find the definition of frequently used terms on the MadKudu platform.
Note: Record in this document is used to include both Person (Lead, Contact) and Companies (Accounts)
- Account Fit: model predicting the Fit of an Account, based on firmographic and technographic data. Requires a website or domain field.
- Attribute: firmographic, demographic, or technographic data point coming from your CRM to use in a Fit model or segmentation. Configured in the Attribute mapping in the app.
- Audience: population of leads/contacts or accounts defined to train a model or look at the performance of a model. Configured in the Audience mapping in the app.
- Batch: processing and scoring of records by batch, as opposed to real-time scoring. Learn more.
- Behavioral data: data relative to a visitor behavior on a website, app or any marketing/sales interaction.
- Data Studio: MadKudu's platform to create scoring models, computations and segmentations. Learn more.
- Decay: lifespan of an event. The weight of an event in the behavioral score gradually decays overtime to ensure that the score accurately depicts a customer’s behavior at that point in time.
- Demographic data: data points on a Person (title, role, seniority, Twitter handle ...)
- Closed Won: Standard conversion definition of an Opportunity Closed Won (probability = 100%). Configured in the Conversion mapping in the app.
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Computations: enrichment traits used in Fit models or segmentations (e.g. industry, company_size, tag_is_b2b, has_dbms_tech, is_hiring...). Learn more.
- Standard Computations: enrichment available out of the box, provided by MadKudu
- Custom Computations: enrichment based on attributes and standard computations MadKudu is mapping from your system to create computations specific to your business / need. (e.g. has_designer_title, is_using_kafka, zoominfo_industry...)
- Conversion: prospect converting into an opportunity from Open Opp to Closed Won. The prospect can be a Lead, Contact or Account. Configured in the Conversion mapping in the app.
- Customer Fit: model predicting the Fit of a Person, based on firmographic and technographic data
- Enrichment: firmographic, demographic, technographic data points collected on users and account from your systems or MadKudu's 3rd party providers (Clearbit, PredictLeads). Learn more.
- Firmographic data: data points on a Company (industry, company size, country ...)
- Event: action performed by a user, used in their behavioral scoring. Events from your systems are mapped into more 'user-friendly' names in the Event mapping, which is called a 'meta-event'
- False-positive: result incorrectly predicting to convert: records scored very good/good but didn't convert
- False-negative: result incorrectly predicting to not convert: records scored low/medium who converted
- Intent data: information collected about visitor behavior on 3rd party website showing a level of interest in a solution. Examples of providers: G2Crowd, Bombora...
- Lead Grade: model combining the Customer Fit and Likelihood to Buy
- Likelihood to Buy: refers to the output of a behavioral model (or engagement model) predicting the level of engagement of a person or account.
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Lift (Conversion lift): impact on conversion compared to the average population.
- A positive lift shows a positive impact on conversion of having this trait, or performing this action
- A negative life shows a negative impact on conversion of having this trait or performing this action
- MadML: scripted versions of Mappings when SQL in needed to create more advanced configurations than the App allows. Learn more.
- Mapping: process of data preparation and standardization of your system data into the MadKudu standard format to be used across the platform. Different mappings need to be configured before starting to create a model. Learn more.
- MQA: model predicting the Likelihood to Buy of an Account. It shows the level of engagement of the account, based on behavioral and intent data. If MQA means Marketing Qualified Account, this acronym in the context of MadKudu is used as a proxy for any type of behavioral model at the Account level, whether it includes marketing activity or not.
- Open Opp: Standard conversion definition of an Open Opportunity (probability = 0%). Configured in the Conversion mapping in the app.
- Override: rule added in the Customer Fit model which overrides what the historical data say to force the segment of a lead/contact to very good, good, medium or low. Example: "If industry is Education Services then segment should be low"
- Precision: in the context of MadKudu, the ratio of conversion rate between the highest segment (very good or very high) and the lowest segment (low).
- PQL: in the context of MadKudu, model predicting the Likelihood to Buy of a Person. It shows the level of engagement of the lead/contact, based on behavioral data. If PQL means Product Qualified Lead, this acronym in the context of MadKudu is used as a proxy for any type of behavioral model at the Person level, whether it includes product usage or not.
- Real-time: processing and scoring of records in realtime, as opposed to batch scoring. Learn more.
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Recall: percentage of all your conversions correctly scored by the model: the percentage of converters scored very good and good, or very high and high.
True Positive divided by (True Positive + False Negative). - Score: numeric output of the model, allowing to rank records from 0 to 100
- Segment: classification output of the model, allowing to segment population into different segments (e.g. very good, good, medium, low)
- Signals: information output of the model, providing intelligence on the record enrichment or behavior.
- Springbok: nickname of the Data Studio. Learn more.
- SQO: in the context of MadKudu, Standard conversion definition of a Sales Qualified Opportunities, or any custom definition. Configured in the Conversion mapping in the app.
- Technographic data: data points on a Company tech stack (before or behind the firewall)
- True-positive: result correctly predicted to convert: records scored very good/good who converted
- True-negative: result correctly predicted to not convert: records scored low/medium who didn't convert
Can't wrap your head around one of them or one not listed? Shoot us an email at product@madkudu.com