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The IBMStreams/streamsx.clickstream repository is an open source Streams project focused on the development of a toolkit of basic functions and operators to build an application for click or tap stream analytics. It also provides a streaming architecture based sample application for clickstream analytics.
The real-time streaming analytics of click or tap streams bears an indispensable significance for digital transformation of all growing enterprises. It provides a way to monitor, qualitatively and quantitatively, the effectiveness of web or mobile applications. In the large scale mobile enterprises environemnt, a real-time clickstreams analytics is imperative to:
- Continously improve customer experience
- Monitor the effectiveness of the web or mobile applications
- Remove frictions from customer journeys
- Positively impact business growth
- Clinch the points of inflection impacting the revenue streams
A typical IBM Streams based clickstream applicaion is built around several microservice applicaitons as following:
- Acqusition and Enrichment
- Clickstreams log/data acqusition
- Decryption and sterilization
- Sessions or user level enrichment
- Hierarchical identification of the events
- Hierarchical categorization of service flows
- Events identification and classification
- Deduplication of events with various hirarcies
- Transition detection at various hirarcical levels
- Aggregations and sequencing of events
- Primary and secondary aggregation
- Sequancing of event transitions into hirarcical graph
- Statistical data analytics
- Common subsequence analytics
- Dectection and extraction of common subsequences
- Detection of frictions from customer journeys
A scalable and dynamically updated set of classification rules are defined in a JSON file. Each JSON rule specifies string attribute of the input stream, to be matched against a specified string, partial string, or regex. When a rule is matched the specified attributes of the output stream are updated as per the given classification by that rule.
Instead of “sliding windows aggregates”, cascaded “tumbing window aggregates” are used to produce Count-By-Distinct function.
A custom SPL operator to produce a graph JSON for:
- Customer journey visualization
- Path analytics, e.g. Visit count, abandon count, etc.