LLM Tokenization
The pre-processing technique dividing natural language text into discrete tokens or subwords for model processing.

THE TECHNICAL LANGUAGE OF DIGITAL B2B INFRASTRUCTURE
The sequence of interactions, decisions and experiences a person has while pursuing a goal with or around an organisation.
Understanding journeys helps teams coordinate fragmented functions, locate friction and prioritise improvements around customer goals instead of isolated channel metrics.
A B2B team maps the path from problem recognition through research, consultation, contracting, onboarding and support, combining interviews with analytics and service records.
Journey maps are models, not complete records of every customer. Assumption-led maps, over-broad personas, linear stage models and stale evidence can conceal variation; findings require ongoing validation with real customers and data.
A journey spans touchpoints, channels and time rather than following an internal department or funnel alone. Teams reconstruct it from research, behavioural data and operational evidence, then map stages, actions, needs, emotions, pain points and supporting processes.
Data Engineering, Revenue Operations
Nielsen Norman Group — Journey Mapping 101 — https://www.nngroup.com/articles/journey-mapping-101/; Nielsen Norman Group — Customer Journey Maps — https://www.nngroup.com/articles/customer-journey-mapping/
The pre-processing technique dividing natural language text into discrete tokens or subwords for model processing.
A modern hybrid data platform uniting the flexible storage of data lakes with the transactional integrity of warehouses.
A security exploit targeting generative AI models by crafting deceptive inputs that bypass system guardrails.
A visual and analytical model tracking prospective buyers through sequential stages from initial awareness to final sale.
Deliberate activity generating invalid impressions, clicks, or conversions to extract illicit financial or competitive advantage.