How do project goals and processes interact with broader org. objectives and resources? Identify:

Applicable budget(s), strategic pillars and SMEs/allies, existing and/or relevant quarterly objectives

Governance: How are key decisions about and changed made to content and content strategy initiated and communicated?

Ad-hoc, "quick- fix" content gaps, e.g., determining surface issue(s) at common drop-off point(s)

Collaborative tools and process planning resources

Existing systems process flows, i.e., technical documentation/manuals

Audit Matrixes: uses 5-6 sample factors (e.g.,readability, fundability, audience, actionability, accuracy) for heuristic assessment(s) of aggregate UI content strings

Comp. Analyses: assesses current UX content against industry best- practices and further qualifies measurable content heuristics; reveals “quick-fix” opportunities to aid stakeholder buy-in

Delineate problematic patterns and modulates problematic copy types for lexile analyses and text assessments, e.g, Fleisch- Kincaid readability test

Document instructive guidance for server APIs, i.e., UI access flows and file taxonomy (content maintenance and governance parameters), e.g., internal links to individual UI msg source files

Adhere initial cataloguing of server's content files to relevant natural language conventions, i.e., optimize asset search flows by expanding a source file’s semantic naming schema to include cultural signifier(s)

Word Sense Disambiguation: map server API terminology and events to design/content-specific semantics to simplify xfn asks re: pillars' communicative disconnect

Affinity mapping as team ratification exercises:

Familarize UX Writers with technical nomeclature by mapping automating phrases to experiential language commonly expessed by users

Audit Matrix (quantitative: identifying basic stats, e.g., ID #; msg type (promo, error, etc.); interaction style (popup, push notification, etc.); creators, approval permissions/publishers; tech home (CMS, API, etc); Metadata; and, relevant metrics/pain poiints

Architecture Diagram (DB IA): situates relevant source file locations throughout database for search and retrieval flows

Content Systems Management Guides (i.e., where do new content requests come from? who prioritizes and addresses content issues? how maintains and manages planned Content trajectory within a developmental lens and who must they report to? staging environments)

Quantitative Channel Map (content assets’ source file links, UI content event triggers, access flows, and delivery processes)

Content Deletion/Archival Parameters (governance)

Collaborative workflows (SMEs, cross- functional points-of-contact)

Reverse Critical Engineering Content Systems(i.e., file asset servers) technical language familiarizes UX writers with both relevant technical process nomenclature and generative process of translating automating terms into design- centric language

Text Extraction: Extract and parse users' responses from varied feedback loops to generate tacit insights into target groups' natural language patterns, e.g., UXR and in- app surveys, CX channel logs (Inductive Reasoning)

Contextual Analyses: Survey cultural landscape and task- specific best- practices to refine content recommendations

Empathy Mapping: Developmental aspects contextualized from user’s perspective (e.g., shared goals and challenges) forming target Personas

Text Classification: Catalogue and organize keyphrases and content dev taxonomies substantiated by user insights' (knowledge capital)

Content Modeling: Document task- specific keyphrases across critical journey flows (dropoff and pain points) for testable UI copy styling benchmark(s). Delineate multivariate messages across modulated journeys

Sentiment Analyses: marry user metrics, data generated from feedback loops e.g., UXR + CX surveys for data-based insights into user sentiment across critical journey flows

Situation Analyses: Summarizes team's Discovery phase findings into tacit Knowledge capital that substantiates and drives project's iterative trajectory

Extract foundational problem statements from commonly- held issues evidenced in existing documentation, e.g., prioritize approach according to severity of pain points indicated across msg types or flows

Anchor project roadmaps to use- case Personas crafted from tacit insights and empathy map for tailored narratives that assist with continued stakeholder buy-in

Situation Analyses incl. Heuristic Eval Report w/ issues prioritized by dearth of solution required

Feature flow” (initial) roadmap(s) designating viable solutions and associated requisites (system’s flows; SMEs; obstructions; projected delivery dates; and point(s)-of-contact + preferred availability/rolling meetings)

Preliminary project statement and roadmap

Rolling, targeted content audits and use- case indexes guides Agile iteration flows

A bottom-up approach, or view of org IA relies on internal taxonomy to build out specialized (sub)categories for functional content analyses

Predictive Analytics: Multivariate testing plan documenting iterative design ideation and solutions and, related issues chronologized by version

Concepts- Only Premise + Hypothesis Graphs: establishes baseline inference models by mapping automating terms to end- user's experiential language

Lexile Scoring: Assess existing and iterative content, e.g., Semantic Differentiation Scoring, Text Difficulty Analyses, Semantic Assessments (Fleisch- Kincaid Test)

Ethnographic Storytelling: Strategically engineer and test target lexicons via associative sequence-to-sequence models that render varied meaning across keywords

Sample Data: Substantiate solutions' with quantifiable stats gleaned from sample pooling and text analyses (sample range is .100 - .333 of evaluative components, re: cumulative data set)

Editorial Considerations: Oboarding for UX writing consistency and adherence to documented Style Guides’ (Production + Delivery):

a. Substance: What kinds of content do we need (topics, types, sources, etc.)? What messages does content need to communicate to our audience?

b. Structure: How is content prioritized, organized, formatted, and displayed? (Structure can include IA, metadata, data modeling, linking strategies, nomenclature, microcopy, metadata etc.)

c. Workflow: What processes, tools, and human resources are required for content initiatives to launch successfully and maintain ongoing quality?

d. Governance: How are key decisions about content and content strategy made? How are changes initiated, communicated and executed?

Editorial Guidelines: Oboarding for UX writing consistency and adherence to documented Style Guides’ (Production + Delivery)

Core Content Strategy Statement

Intial User Personas + corresponding Lifecycle Journey Maps

Content Map (acts as benchmark segmenting user groups by use- case, i.e., specific content channels and/or assets, e.g., user grp 1 has lower tech skill level so error msg dev/task completion should utilize user grp 1’s keyphrases)

Agile Content Test Plans (denoting test guidelines, aspirational Gold standards and benchmarking Metrics for comparative analyses)

Reverse Critical Engineering automating or, highly technical, language familiarizes UX writers with the generative process of transmuting internal server taxonomies into design-centric language. Consider:

How do users refer to platform features and phrase their understanding of task and systems- related errors? Does their language align with creative UX writing guidelines?

Is UX copy iteration informed largely by infrastructural (back- end) language or, guided by tacit understanding of users' natural language paradigms?

Org. sentiment is always reflected in UX copy/ branded content.

Thematic message templates provides testable copy, establishing creative taxonomies and UI message schemas (by type) using cross- functional product nomenclature contextualized for UX copy development

Brand Voice best- practices: Friendly and empathetic, i.e., using contractions, concise syntax respective of internationalisation and localization parameters, and informed by end- users' rhetorical needs

Delivery Models : Does interaction model impact tone, e.g, formal tone best used for system- related error messages vs. friendly, educative voice user-generated errors

Typify Lexical UX Writing components across asset needs.

How does an org's existing cultural Content Models impact UX content strategy and writing development, i.e., style elements like, voice re: error msgs vs in- app promos?

Tone development:

What is someone likely to be doing when they encounter this message type?

What is their mindset likely to be?

What is the intention we’re showing up with in the UI? What do we want to offer people in the UX?

How receptive is the person likely to be to that intention?

How can we use Associative Sentiment Analyses to predict and align UI copy with users' rhetorical needs (intent?)

Broad Content Considerations:

SEO: generates sitepages' title tags (predicated on optimized content models)

Native vs 3rd-Party Content: Resources to generate the former

Paid vs Organic (Programmatic + Direct Response): Org reliance on delivery and publishing platform sustainable (i.e., current tech platforms perptually changing algorithims and features)

Style Guide for Copywriting, Copyediting

Content Curation/Aggregation Checklist (delineates content creation and sourcing methods)

Asset templates, i.e., UI Msg Mockups/Standardized Msg. Models

Editorial Calendar/Thematic Maps (i.e., engagement vs retention vs automating copy- styling

Best- practices IA aligns naming conventions(taxonomy) with users’ natural language standards for cross- functional domain knowledge share flows, e.g., internal search (discoverability) and Agile asset maintenance/file review flows

Externalization:

Reverse engineering technical terminology into cultural semantics provides streamlines cross- collaborative communications by simplifying complex taxonomy

Test communication models across project partners for streamlined collaboration efforts (what communicative phrasing worked best and with whom? Why?)

Lexical Map containing Keyphrases and Term, including associative technical nomenclature and design- centric language

Technical instructions across Content systems' and flows', tailored to UX Writing development