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IT Service Contract Prolongation Analytics
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About
Identifying which corporate clients are likely to renew their service contracts is a critical task for IT service providers. This collection facilitates binary classification to determine customer loyalty and the likelihood of prolongation based on organisational metrics and activity logs. By analysing reporting frequencies to various national funds and internal document counts, the data helps businesses distinguish between satisfied, long-term partners and those at risk of churning. It provides a structured environment for testing predictive models within a professional business context.
Columns
- id: A unique numeric identifier for each client organisation within the system.
- taxactionSystem: The specific tax framework the company operates under, such as a general taxation system or a fixed income tax rate.
- regdt: The official date the organisation was registered.
- workerCount: The total number of employees currently working within the company.
- fssdccount: A cumulative count of the reports filed with the social insurance fund throughout the organisation's existence.
- pfrdcCount: The total number of reports submitted to the national pension fund over the lifetime of the contract.
- fnsdcCount: The volume of reports sent to the Federal Tax Service by the organisation.
- hasCloudCryptCertificate: A binary indicator showing whether a cloud-based certificate has been issued for the organisation.
- OrgCreationDate: The timestamp of when the organisation's record was first created or added to the service platform.
- documentsCount: The total number of documents tracked and visible within the system's primary interface.
- cnt_users: The number of individual users registered under the specific service contract.
Distribution
The data is stored in a
test.csv file with a size of approximately 207.65 kB. It comprises 2,542 records, which are verified as 100% valid with no mismatched entries. The dataset maintains a perfect usability score of 10.00 and is provided as a static archive with no future updates expected.Usage
This resource is ideal for building binary classification models to predict whether a company will extend its contract. It is well-suited for feature engineering exercises where analysts can correlate tax systems or employee counts with administrative reporting behaviour. Beginners in data science can use it to practice handling date formats and categorical variables as part of an employment-style test task.
Coverage
The scope includes 2,542 distinct organisations, representing the client base of an IT service firm. Temporally, the data covers organisations registered over a wide range of dates, with creation records spanning from 1900 through to early 2016. The demographic focus is corporate entities with varying employee sizes, from small startups to larger firms with multiple users.
License
CC BY-NC-SA 4.0
Who Can Use It
Machine learning engineers can leverage these records to develop and refine churn prediction algorithms. Business analysts can utilise the data to identify the characteristics of loyal customers and optimise retention strategies. Additionally, students can use the clean, structured format to master data cleaning and exploratory analysis techniques required for technical recruitment assessments.
Dataset Name Suggestions
- IT Service Contract Prolongation Analytics
- Corporate Customer Loyalty and Renewal Registry
- Business Tax and Reporting Dynamics Collection
- Enterprise Service Renewal Prediction Dataset
- Organisation Metadata and Contract Retention Archive
Attributes
Original Data Source: IT Service Contract Prolongation Analytics
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