SaaS Contract Benchmarking via Normalization SKU
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Solution Overview
Problem
Managing SaaS application contracts across multiple subscriptions becomes complex due to varying pricing models and lack of insights into comparative pricing, making it difficult for corporate entities to make informed decisions about future purchases or contract renewals.
Innovation Solution
A SaaS management platform that receives and parses contract files, normalizes terms using a normalization SKU, generates anonymized contract data, and provides benchmark data to customers, allowing them to understand their pricing relative to others through a user interface, using machine learning and fuzzy matching techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a corporate entity subscribes to many different SaaS applications, then the functionality and service coverage are improved, but the management complexity increases
Solution Approach 1:
The patent segments the complex SaaS portfolio management into distinct components: contract data collection from multiple sources, standardized term extraction using parsing logic, normalization to common metrics, and comparative analysis. This segmentation allows each component to handle specific aspects of the problem independently, reducing overall management complexity while maintaining comprehensive service coverage
Solution Approach 2:
The patent introduces an intermediary SaaS management platform that acts as a mediator between multiple SaaS applications and the corporate entity. This platform collects, standardizes, and analyzes contract data from various sources, providing a unified view and reducing the complexity of managing diverse SaaS subscriptions through a single interface
2Measurement precision
If contract terms are standardized across multiple SaaS applications, then the comparability and decision-making efficiency are improved, but the data processing complexity increases
Solution Approach 1:
The patent transforms diverse contract terms into standardized parameters through normalization logic. Different pricing models (per-user, per-storage, tiered pricing) are converted into common metrics that can be directly compared. This parameter standardization enables precise comparability while the automated processing reduces the manual data processing complexity
Solution Approach 2:
The patent replaces manual contract analysis with automated parsing logic and machine learning models. These systems automatically extract terms from contracts, normalize them to standard formats, and perform comparisons, substituting complex manual processing with automated computational processes that handle the complexity internally while providing simple comparative outputs
3Measurement precision
If detailed contract terms are analyzed for each SaaS subscription, then the pricing insights accuracy is improved, but the time and computational resources required increase
Solution Approach 1:
The patent performs preliminary actions by pre-collecting and storing contract data from multiple SaaS applications in a standardized format. This advance preparation allows for rapid querying and comparison when needed, reducing the analysis time while maintaining detailed pricing insights. The data is normalized and organized beforehand, so when comparison is needed, the system can quickly retrieve and analyze relevant information without time-consuming manual processing
Solution Approach 2:
The patent creates simplified copies or representations of complex contract terms through standardized metrics. Instead of analyzing entire detailed contracts each time, the system uses pre-extracted and normalized key terms and pricing metrics as proxies. These copied representations enable rapid comparison while preserving the essential pricing insights, reducing analysis time without sacrificing accuracy
Data Source
AI summary
A software as a service (SaaS) management platform, includes: an uploader process for receiving a plurality of contract files relating to purchases of a SaaS application; parsing logic that identifies terms in the plurality of contract files; normalization logic for assigning a normalization SKU to respective contract files based on the terms identified in the respective contract files; a background process that generates anonymized contract data by storing the terms of each contract file in association with the normalization SKU assigned to the contract file in an anonymous manner; a backend process that, responsive to a request from a client device, accesses the anonymized contract data to generate a distribution of terms of the anonymized contract data, generates benchmark data identifying an approximate location of terms of a given customer's contract file within the distribution, and returns the benchmark data to the client device for rendering through a user interface.