Abstract: A computer-implemented system and method model customer responsiveness to marketing initiatives using an optical wave-based simulation framework. Campaigns are encoded as incident light waves characterized by color (C), angle of incidence (?), and intensity/weight (W), while customers are represented as optical media with per-entity vectors including refractive index (RIi), reflection polarity (RPi), response latency (RLi), and absorption/reflection coefficients (?i, ?i). A simulation engine propagates campaign waves through a virtual medium, generates reflective/refractive/interference patterns under induced and involuntary noise, and captures resultant patterns on a virtual film as measurable effects. An analysis module infers sensitivity and reciprocity, classifies cohorts (e.g., aligned absorbers, inverted reflectors, delayed responders), and predicts drift likelihoods. Reinforcement learning adaptively refines campaign parameters and orchestration to minimize marketing noise and improve effectiveness.

Abstract: A system and method for collecting, organizing, and curating customer engagements across multiple interactions and touch points. The disclosed method allows for a discovery of purposes, an accretion of micro-journeys for a plurality of customers and a contextual nurturing of those customers on respective journeys towards their next milestones using numerical, graphical, statistical, and heuristics-based methods and proposed memory layouts of the same. Real-time staging and processing of inbound factual data and inferential dimensions into a multipartite multidimensional space of the factual and inferential dimensions to enable the mapping of customer interactions with a brand and the digital encoding thereof.

Abstract: Quantitative techniques to measure and reduce the entropy in customer centric marketing activities in large enterprises using geometric methods and heuristics. Quantitative real time representations of marketing efforts, their effects and relative returns as line segments of a triangle with their lengths denoting the digitally encoded weights of the relations of the corresponding constituents pairwise. Hierarchically entropy deduction using mathematical formulae to deduce entropy from a nine-point circle formed of the triangle constructed to empirically assess marketing activities to customer journeys. Identification means to determine effectiveness and sensitivity to such marketing efforts by particularized customer types and clusters with automated recommendations in the form of prescription of lower activity levels of a segment or total suspension of marketing activity levels to reduce the overall entropy in marketing activity.

Abstract: A system for efficiently parsing semi-structured deep packet inspection traffic data tied to a telecommunications entity. The system comprises a computing device having access to a user activity data source and is configured to progressively accumulate a plurality of incoming usage activity data into a plurality of hypercubes, classify streaming data on-the-fly into multiple grades, route it to an appropriate next stage of processing, numerically factorize it to enable drilldown to individual subscriber data, and organize into layouts for efficient data processing, anomaly detection, and subsequent access/investigation. A computerized method for performing the same.

Abstract: A system and method for collecting, organizing, and curating customer engagements across multiple interactions and touch points. The disclosed method allows for a discovery of purposes, an accretion of micro-journeys for a plurality of customers and a contextual nurturing of those customers on respective journeys towards their next milestones using numerical, graphical, statistical, and heuristics-based methods and proposed memory layouts of the same. Real-time staging and processing of inbound factual data and inferential dimensions into a multipartite multidimensional space of the factual and inferential dimensions to enable the mapping of customer interactions with a brand and the digital encoding thereof.

Abstract: A method to for real-time scoring, classification, assortment, and contextual nurturing of digital engagements using numerical, statistical, and heuristics-based techniques. Ongoing customer engagement segregation into personas based on discovered traits and collective inferences drawn from historic and ongoing engagements, clustering ongoing engagements using numerical and string manipulation techniques. Computing real time noise and focus scores for engagements, facilitating stateless nudges for increasing favorable engagements, and providing business insights on possibly undiscovered noise and focus patterns that eventually culminate as desired or non-desired outcomes. Generating interest score for engagements based on non-linear formulations of noise and focus scores, and then clustering engagements with similar interests and focus into communities to generate additional insights and facilitate secure communication among users, efficient marketing campaigns and decisioning sales lead assignment.

Abstract: A system for efficiently parsing semi-structured deep packet inspection traffic data tied to a telecommunications entity. The system is capable of parsing such records at million-records-per-second scale through use of a numerical data model, leverage on proven fundamental algebraic techniques, and shortcuts to label streaming traffic on the fly. In some embodiments, the system may perform parallel accumulation of data traffic into business grade counters using elementary techniques and subsequently identify subscribers exhibiting specific data patterns in real time for contextual targeting of promotional offers. A method of efficiently parsing the traffic data via the system of the disclosure.

Abstract: A system for efficiently parsing semi-structured deep packet inspection traffic data tied to a telecommunications entity. The system comprises a computing device having access to a user activity data source and is configured to progressively accumulate a plurality of incoming usage activity data into a plurality of hypercubes, classify streaming data on-the-fly into multiple grades, route it to an appropriate next stage of processing, numerically factorize it to enable drilldown to individual subscriber data, and organize into layouts for efficient data processing, anomaly detection, and subsequent access/investigation. A computerized method for performing the same.

Abstract: A system for efficiently parsing semi-structured deep packet inspection traffic data tied to a telecommunications entity. The system is capable of parsing such records at million-records-per-second scale through use of a numerical data model, leverage on proven fundamental algebraic techniques, and shortcuts to label streaming traffic on the fly. In some embodiments, the system may perform parallel accumulation of data traffic into business grade counters using elementary techniques and subsequently identify subscribers exhibiting specific data patterns in real time for contextual targeting of promotional offers. A method of efficiently parsing the traffic data via the system of the disclosure.