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  2. Lead scoring - Wikipedia

    en.wikipedia.org/wiki/Lead_scoring

    Predictive Lead Scoring: predictive lead scoring models use machine learning to generate a predictive model based on historical customer data augmented by third party data sources. The approach is to analyze past lead behavior, or past interactions between a company and leads, and find positive correlations of such data to a positive business ...

  3. Lead generation - Wikipedia

    en.wikipedia.org/wiki/Lead_generation

    The introduction of marketing automation has made lead scoring easier to implement. [1] The score assigned to each lead is assigned based on their level of interest, fit with the company's target market, and likelihood of becoming a paying customer. It is not static and can change based on the demographic or behavioral criteria set by the company.

  4. Lead management - Wikipedia

    en.wikipedia.org/wiki/Lead_management

    Lead management is a set of methodologies, systems, and practices designed to generate new potential business clientele, generally operated through a variety of marketing campaigns or programs. Lead management facilitates a business's connection between its outgoing consumer advertising and the responses to that advertising.

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  6. DICE framework - Wikipedia

    en.wikipedia.org/wiki/DICE_framework

    The DICE framework, or Duration, Integrity, Commitment, and Effort framework is a tool for evaluating projects, [1] predicting project outcomes, and allocating resources strategically to maximize delivery of a program or portfolio of initiatives, aiming for consistency in evaluating projects with subjective inputs.

  7. Weighted sum model - Wikipedia

    en.wikipedia.org/wiki/Weighted_Sum_Model

    In decision theory, the weighted sum model (WSM), [1] [2] also called weighted linear combination (WLC) [3] or simple additive weighting (SAW), [4] is the best known and simplest multi-criteria decision analysis (MCDA) / multi-criteria decision making method for evaluating a number of alternatives in terms of a number of decision criteria.

  8. Data envelopment analysis - Wikipedia

    en.wikipedia.org/wiki/Data_envelopment_analysis

    Data envelopment analysis (DEA) is a nonparametric method in operations research and economics for the estimation of production frontiers. [1] DEA has been applied in a large range of fields including international banking, economic sustainability, police department operations, and logistical applications [2] [3] [4] Additionally, DEA has been used to assess the performance of natural language ...

  9. Normalization (statistics) - Wikipedia

    en.wikipedia.org/wiki/Normalization_(statistics)

    In theoretical statistics, parametric normalization can often lead to pivotal quantities – functions whose sampling distribution does not depend on the parameters – and to ancillary statistics – pivotal quantities that can be computed from observations, without knowing parameters.