Search Influence
Case Western Reserve University - Web Writing + AI Search Training
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CWRU Team Session · June 2026

Web Writing + AI Search Training

Shared standards for useful, accessible, findable Case Western Reserve University pages.

Audience
CWRU web, content, communications, and marketing teams
Outcome
Clearer pages that serve people first and AI interpretation second
Search InfluenceCWRU
Overview

What we will cover

The deck starts with decisions content owners can make now, then shows how those same choices support AI search.

01Web writing standards

Purpose, audience intent, skimmability, headings, CTAs, and page structure.

02Content accessibility

Readable links, headings, lists, tables, and alt-text judgment.

03Live page work

CWRU examples from program, giving, research, and newsroom pages.

04AI-search layer

LLMs, grounding, entities, semantic clarity, citations, and measurement.

05Carry-forward standards

Prioritize fixes, owners, reusable rules, and open questions.

Facilitation Model

How this training will work

Live instruction

Short teaching sections set up practical decisions the group can use immediately.

Guided examples

CWRU screenshots anchor the discussion so the advice does not stay abstract.

Practice moments

Exercises ask participants to diagnose, rewrite, compare, and name the reusable rule.

Question capture

Policy, platform, governance, and ownership questions get separated from quick content edits.

Source Grounding

What the training is grounded in

Usability

Can a real visitor understand the page quickly enough to keep moving?

Accessibility

Do headings, links, image choices, lists, and tables reduce friction?

Findability

Does the page expose the entities, facts, relationships, and proof search systems need?

Governance

Which fixes belong to content owners, and which need platform, policy, or brand decisions?

Session Flow

Two-day training arc

Session 1

Make pages easier for people to scan, understand, trust, and act on.

Session 2

Make page meaning easier for AI systems to retrieve, connect, and cite.

Throughline

Good AI-search content starts as good human-readable web content.

End point

CWRU leaves with rules it can reuse beyond the pages discussed in the room.

Outcomes

What you should leave with

01

A shared page-quality framework you can use immediately.

02

A practical explanation of why AI search changes visibility, not the need for clear pages.

03

Before/after patterns for CWRU program, giving, research, and newsroom content.

04

A short list of priority changes CWRU can standardize after the training.

Day 1

Web writing foundations before the AI layer

People, purpose, structure, accessibility, and live CWRU page work

Session 1 Run-of-Show

Day 1 agenda

Opening and outcomes

15 minutes

How people read online

25 minutes

Page purpose and audience intent

35 minutes

Hierarchy, headings, CTAs

40 minutes

Content-level accessibility

35 minutes

Live CWRU page workshop

65 minutes

Question capture and close

10 minutes

Workshop Method

How to work through page examples

Start with control

Focus first on decisions content owners can change.

Ask before telling

Diagnose the page before jumping to rewrites.

Use CWRU examples

Keep the discussion concrete and useful.

Separate issue types

Distinguish quick content fixes from policy, platform, and governance questions.

Reader Lens

Opening discussion

Prompt

Which kind of web reader are you: skimmer, swimmer, or diver?

Compare readers

Notice how different teams read the same page.

Connect to design

Every page has to support all three behaviors.

Apply the frame

Use this lens when reviewing CWRU pages.

Day 1

Reader behavior and page jobs

Start with how people move through pages, then define what each page needs to accomplish.

Reader Behavior

Skimmers

Need

Headings, summaries, and visible next steps.

Risk

They bounce if the page hides the answer below institutional setup.

Help them with

Precise H1/H2 language and scannable lists.

Reader Behavior

Swimmers

Behavior

They read more if the structure keeps rewarding them.

Need

Enough context to trust the page and keep moving.

Help them with

Short sections, proof points, and links that explain where they go.

Reader Behavior

Divers

01

Need depth, specificity, and evidence.

02

Often include internal stakeholders, faculty, donors, applicants, or parents.

03

Benefit from clear internal links, FAQs, deadlines, requirements, and proof.

Page Purpose

The web page is still the source of record

01

CWRU pages remain the public source that people, search engines, and grounded AI systems can inspect.

02

AI search makes clear public pages more important, not less important.

03

The goal is not more output; it is better discernment about what belongs on each page.

Page Purpose

Useful page standard

01

A useful page answers a real reader question.

02

It gives the reader enough confidence to take the next step.

03

It exposes the facts and relationships machines need without making the page robotic.

04

It removes institutional clutter that does not serve the page job.

Page Purpose

Page job statement

Use this before editing copy

This page helps [audience] understand [question] so they can [next action].

Failure sign

If the room cannot finish the sentence, the page is trying to do too many jobs.

Why it helps

This is the simplest way to move from opinion-based editing to standards-based editing.

Practice Block

Mini exercise: page job statement

Write a one-sentence job statement for one CWRU page.

7 minutes

1Pick page
2Name audience
3Name question
4Name next action
Reader Alignment

Reader intent vs. institutional habit

Readers usually want
  • Answers
  • Evidence
  • Next step
  • Confidence
  • A reason to keep going
Institutions often publish
  • Background
  • Internal language
  • Committee-shaped copy
  • Unclear ownership
  • Everything at once
Day 1 Workshop

CWRU page examples

Use real CWRU pages to make page purpose, headings, calls to action, and rewrite choices concrete.

Page Set

CWRU pages we will use in workshop discussion

Engineering area of study

Top-of-funnel undergraduate exploration.

MSN

Complex graduate program with multiple specialties and application paths.

MSW on-campus

Graduate/professional program with strong conversion needs.

Ways to Give

Action page that needs clarity, confidence, and motivation.

Medicine and Engineering Research

School-level authority hubs.

Newsroom stories

Institutional reputation and external-signal examples.

Undergraduate Program Page

CWRU example: Engineering area of study

Teaching use

Broad, top-of-funnel audience intent.

Strength

Strong visual signal and clear topic.

Opportunity

Connect the page more quickly to student questions, proof, outcomes, and next steps.

AI-search angle

Make the relationship between CWRU, engineering, research, hands-on learning, and undergraduate pathways unmistakable.

Source: https://case.edu/admission/academics/areas-study/engineering

CWRU example: Engineering area of study screenshot
Graduate Nursing Page

CWRU example: MSN program

Teaching use

Complex program information and conversion clarity.

Strong program specificity

MSN majors, specialties, recognitions, deadlines, and contacts.

Opportunity

Help scanners understand which path fits them before they hit dense detail.

AI-search angle

Use consistent language around Frances Payne Bolton School of Nursing, MSN, nurse practitioner specialties, and recognized program strengths.

Source: https://case.edu/nursing/programs/msn

CWRU example: MSN program screenshot
Graduate Social Work Page

CWRU example: MSW on-campus

Teaching use

Graduate/professional program page with clear admissions and inquiry intent.

Strong conversion surface

Request Information, program overview, numbers, admissions details.

Opportunity

Make the top of page answer fit, format, outcomes, and path faster.

AI-search angle

Express who the on-campus MSW is for and what the program prepares them to do.

Source: https://case.edu/programs/socialwork-msw-on-campus

CWRU example: MSW on-campus screenshot
Advancement Page

CWRU example: Ways to Give

Teaching use

Task-completion page for donors.

Strength

Strong functional list of giving methods.

Opportunity

Pair transaction options with why-give signals, confidence cues, and donor path clarity.

Accessibility angle

Link and button text should be meaningful when read out of context.

Source: https://case.edu/give/ways-give

CWRU example: Ways to Give screenshot
Page Purpose

Engineering page job statement

Job statement

This page helps prospective undergraduates and families understand what engineering at CWRU looks like so they can explore programs, hands-on opportunities, and admission next steps.

Content test

Does every major section support exploration, confidence, or action?

Page Purpose

MSN page job statement

Job statement

This page helps prospective graduate nursing applicants understand MSN paths, specialties, requirements, and deadlines so they can choose a fit and start an application or inquiry.

Content test

Does the page reduce specialty confusion before adding detail?

Page Purpose

MSW page job statement

Job statement

This page helps prospective social work applicants understand the on-campus MSW format, outcomes, requirements, and admissions process so they can request information or apply.

Content test

Does the page answer fit and next step before institutional background?

Page Purpose

Ways to Give page job statement

Job statement

This page helps donors choose a giving method and complete the gift confidently while reinforcing why CWRU is worth supporting.

Content test

Does the page offer both transaction clarity and donor confidence?

Day 1 Workshop

Headings, language, and calls to action

Turn page diagnosis into reusable writing rules participants can apply after the session.

Headings & Language

Headings are wayfinding

01

A reader should understand the page from the headings alone.

02

Use one clear H1 tied to the page job.

03

Make H2s answer real reader questions.

04

Use headings to expose structure, not add decoration.

Headings & Language

Heading audit pattern

Start

List the current H1/H2 sequence.

Ask

Can a skimmer tell who this page is for?

Ask

Does the sequence move from orientation to decision to action?

Then rewrite

Fix headings before rewriting paragraphs.

Headings & Language

CWRU heading issue to teach

01

Automated extracts show some pages include navigation headings before content headings.

02

That is not automatically a content failure, but it is a useful teaching moment.

03

Content owners should know the difference between visible page structure and CMS/navigation structure.

04

For AI/search, meaningful content headings still matter because they create retrievable sections.

Headings & Language

Better H2 questions for program pages

01

What can I study here?

02

Who is this program for?

03

What will I be prepared to do?

04

What makes CWRU's version distinctive?

05

What are the requirements, deadlines, and next steps?

Writing Standard

Plain language without flattening expertise

01

Use precise institutional language where it matters.

02

Remove internal phrasing that only staff understand.

03

Prefer direct verbs and specific nouns.

04

Do not make expert content vague in the name of simplicity.

Structure Practice

Exercise: heading-only page read

Read only the H1/H2s. What do you know, and what is still unclear?

10 minutes

1Hide body copy
2Read headings
3Name gaps
4Rewrite 2 H2s
Calls to Action

CTA clarity

Weak CTA patterns
  • Learn more
  • Click here
  • More information
  • Multiple equal CTAs competing for attention
Better CTA patterns
  • Request information about the MSN program
  • Start your application
  • Explore engineering majors
  • Make a gift online
Calls to Action

CTA placement rule

01

Put the next action near the decision point.

02

Use the CTA to complete the reader's current task, not the institution's internal funnel label.

03

If a page has multiple audiences, label the paths clearly.

04

Do not make readers infer the destination from surrounding copy.

Action Practice

Exercise: CTA rewrite

Make one CTA more specific without making it pushy.

8 minutes

1Show example
2Rewrite alone
3Compare pairs
4Debrief pattern
Day 1

Content-level accessibility

Practical editorial decisions, not a compliance lecture

Scope Boundary

Accessibility scope for this training

01

Focus on content decisions the room can control.

02

Clear link text, useful alt text, meaningful headings, readable tables and lists.

03

Capture technical/platform questions separately.

04

Accessibility, usability, and AI-readable clarity often improve together.

Accessibility

Alt text judgment

01

Useful alt text names the meaningful content of the image.

02

It fits the page context.

03

It does not repeat adjacent caption text.

04

It does not stuff keywords or turn into a marketing paragraph.

Accessibility

When alt text should be empty

01

Decorative image that adds no information.

02

Visual flourish already described in nearby text.

03

Icon with adjacent visible label.

04

Avoid forcing screen-reader users through irrelevant image details.

Accessibility

When alt text needs more detail

01

Image conveys unique information.

02

Chart or infographic includes data not otherwise available.

03

Photo identifies specific people, places, or moments relevant to the page.

04

Image is also a link or action trigger.

Accessibility

Link text rule

01

The destination should be clear if the link text is read by itself.

02

Avoid repeated 'learn more' links on the same page.

03

Use button text for actions and link text for navigation where possible.

04

Specific links help accessibility and page comprehension.

Accessibility

Tables and lists

01

Use lists for grouped items that do not need row/column relationships.

02

Use tables only when comparison or data structure matters.

03

Name columns clearly.

04

Do not use tables for layout.

Exercise

Accessibility quick audit

Find three content-level accessibility improvements on a selected CWRU page.

12 minutes

1Headings
2Links
3Images
4Debrief
Day 1

Live page review workshop

Apply the standards to real CWRU pages

Review Process

Live review method

Start with the page

Show the page before showing the answer.

Ask

What is the page job?

Ask

What is the first point of friction?

Sort issues

Separate copy fixes, design/CMS issues, and governance questions.

Then reveal

Show a recommended pattern after the room diagnoses.

Review Criteria

Page-quality framework

Audience

Who is this page for?

Question

What do they need to know?

Evidence

What proof builds confidence?

Action

What should they do next?

Signal

What should search and AI systems understand?

Undergraduate Program Example

Engineering page diagnosis

Audience

Broad and exploratory.

Current strength

The hero clearly labels Engineering, but the next useful question is student fit and opportunity.

Recommendation

Foreground student pathways, hands-on learning, research participation, and next step.

Possible H2

'Engineering at CWRU combines research, design, and hands-on problem solving from year one.'

Undergraduate Rewrite Pattern

Engineering rewrite pattern

Summary block

Add a short section under the hero: what students can study, how they learn, and where to go next.

Student-question H2s

Programs, Hands-On Learning, Research and Entrepreneurship, Pre-Professional Paths.

Direct CTA pair

Explore engineering majors / Plan your visit or apply.

Descriptive links

Link to makerspace, co-op, and first-year engineering experience with descriptive anchors.

Nursing Program Example

MSN page diagnosis

Audience

Nurses comparing specialties and application paths.

Current friction

The page has rich content, but complexity can overwhelm skimmers.

Recommendation

Add a decision-oriented overview before specialty detail.

Possible H2

'Choose the MSN path that matches your nursing goals.'

Nursing Rewrite Pattern

MSN rewrite pattern

Audience fit

Lead with who the program is for and how specialty choice works.

Comparison section

Create a 'Compare MSN options' section for majors/specialties.

Decision CTAs

Move deadlines and request-info/apply actions near the point where applicants are deciding.

Entity language

Use Frances Payne Bolton School of Nursing, Master of Science in Nursing, and nurse practitioner specialties consistently.

Social Work Program Example

MSW page diagnosis

Strong conversion architecture

Request info, overview, numbers, admissions details.

Opportunity is top-of-page clarity

Format, audience, outcome, and next step.

Recommendation

Make the first screen answer 'Is this the right MSW path for me?'

Social Work Rewrite Pattern

MSW rewrite pattern

Opening block

Add format, location, audience, and professional outcome.

Clear H2s

Use What to Expect, Program Overview, Admissions Details, and Request Information.

Explicit CTA

Request information about the on-campus MSW.

Proof points

Use proof sparingly and connect it to applicant decisions.

Donor Page Example

Ways to Give diagnosis

Task clarity

Multiple giving methods are visible.

Current friction

The page is functionally useful, but could do more to build donor confidence and motivation.

Recommendation

Pair giving methods with impact context and path confidence.

Primary lens

AI/search is secondary; this is primarily UX writing and accessibility.

Donor Rewrite Pattern

Ways to Give rewrite pattern

Short intro

Add a 'Choose the giving method that works for you' intro.

Descriptive links

Use clear link text for each giving option.

Donor confidence

Include tax, security, contact, and support details.

Impact path

Add a 'Why give to CWRU' path that connects philanthropy to outcomes and institutional momentum.

Undergraduate Program Screenshot

Workshop screenshot: Engineering

Ask the room

What does this section help a prospective student decide?

Next question

What is the next student question after seeing these options?

Link clarity

Which links are descriptive enough to work out of context?

First change

What would you change before rewriting any body copy?

Workshop screenshot: Engineering screenshot
Nursing Program Screenshot

Workshop screenshot: MSN

Ask the room

Where does complexity start?

Decision need

What does a prospective applicant need before choosing a specialty?

Section depth

Which sections should be scannable summaries vs. detailed explanations?

AI facts

What facts would AI need to associate with this program?

Workshop screenshot: MSN screenshot
Social Work Program Screenshot

Workshop screenshot: MSW

Ask the room

What job does this page do well?

Fit and format

Where could the page answer fit and format sooner?

CTA clarity

Which CTA language is clear, and which could be more specific?

Proof point

What proof point belongs near the top?

Workshop screenshot: MSW screenshot
Donor Page Screenshot

Workshop screenshot: Ways to Give

Ask the room

Is the giving method list enough?

Confidence cues

What confidence cues should donors see?

Link text

Which link text would fail if read alone?

Motivation

Where should motivation and impact live without slowing down the transaction?

Workshop screenshot: Ways to Give screenshot
Session 1 Reflection

Day 1 close

01

Useful pages begin with purpose.

02

Structure is not cosmetic; it changes comprehension.

03

Accessibility, usability, and findability overlap.

04

The same clarity carries into Day 2, but AI systems interpret it through different mechanisms.

Exercise

Between-day question capture

Write down one question, one example, or one point of confusion for Day 2.

5 minutes

1Capture
2Cluster
3Prioritize
4Open Day 2
Day 2

AI search, semantic clarity, and stronger signals

LLMs are not search engines, but clear web signals still matter

Session 2 Run-of-Show

Day 2 agenda

Q&A bridge from Day 1

20 minutes

LLMs are not search engines

35 minutes

Higher-ed AI-search behavior

30 minutes

Entities and semantic writing

45 minutes

Newsroom and external signals

35 minutes

Tools and measurement

25 minutes

Priority workshop and close

45 minutes

Carry-Forward Questions

Day 1 to Day 2 bridge

01

Yesterday was about human comprehension.

02

Today is about how that same clarity becomes machine-interpretable signal.

03

AI search does not eliminate SEO or web writing standards.

04

It raises the cost of vague, inconsistent, disconnected content.

Day 2

AI search fundamentals

Clarify what changes in AI-assisted discovery before moving into entities, citations, and measurement.

AI Search Fundamentals

LLMs are not search engines

Search engines

Retrieve and rank documents.

Large language models

Generate answers from learned patterns and/or retrieved sources.

Grounded answers

May cite sources when the system retrieves supporting material.

Content strategy

Make the facts, entities, relationships, and evidence clear enough to be retrieved, understood, and corroborated.

AI Search Fundamentals

Search engine vs. large language model

Search engine

Index, retrieve, rank, snippet, link.

LLM

Predict/generate language from model weights and context.

Grounded AI answer

Combines generation with retrieved sources.

Google AI Overviews

A hybrid of retrieval and generation.

AI Search Fundamentals

How AI answers are sourced

Training data

The model answers using learned patterns and may provide no citation.

Grounding/RAG

The model consults external sources and may provide citations.

CWRU opportunity

The grounded layer is the more actionable short-term opportunity.

Source context

AMA deck slides on training data vs. grounding.

AI Search Fundamentals

Google AI Overviews are hybrid

Retrieval layer

Pulls from Google's index and search-quality systems.

Generation layer

Synthesizes a compressed answer.

Citation pattern

Citations often map to pages Google can understand and trust.

Source context

'And Google AI Overviews?' from AMA AI Search deck.

AI Search Fundamentals

What changes for content owners

01

Keywords still matter, but alone they are not enough.

02

Entities, relationships, and citations become more important.

03

Pages need clearer chunks and facts.

04

External corroboration matters because AI systems recognize patterns across sources.

Comparison

SEO then and now

Foundational SEO
  • Keywords
  • Content
  • Links
  • Technical health
AI-search emphasis
  • Entities
  • Semantic relevance
  • Citations
  • Structured meaning

Source: Source context: AMA 2025 How to Win AI Search, slide 25

AI Search Strategy

The three pillars of SEO for AI search

Entities

Help AI recognize your brand, programs, people, places, and topics.

Semantic relevance

Answer questions, connect topics, and add context.

Citations

Build trust through mentions, links, and corroboration across the web.

Source: Source context: AMA 2025 slide 26; UPCEA 2026 slide 17

AI Search Strategy

AI authority is a probability game

Core idea

Ubiquity increases probability.

Pattern strength

The more CWRU's perspective appears clearly across credible sources, the more likely it becomes the pattern AI pulls from.

Boundary

This is not about spamming the web; it is about consistent, authoritative, corroborated language.

Source context

UPCEA 2026 Winning AI Search, slide 16.

Higher-Ed Behavior

Higher-ed search behavior: new baseline

Still true

Prospects rely on search engines and university websites.

What changed

AI tools are now part of the search journey.

Baseline

Presence in search engines and AI answers is now a minimum requirement.

Practical message

CWRU pages have to serve search, site visitors, and AI-assisted discovery.

Source: AI Search in Higher Education: How Prospects Search in 2025, UPCEA & Search Influence

Evidence Base

Research data to use in the room

01

50% of prospects use AI-powered tools at least weekly.

02

79% read Google AI Overviews.

03

56% are more likely to trust brands mentioned in AI Overviews.

04

Use these as orientation stats, not as a reason to abandon web fundamentals.

Source: Source context: AMA 2025 and UPCEA 2026 AI Search decks

AI Search Strategy

AI citations influence trust before the click

01

AI Overviews and AI answers can shape the consideration set before a student reaches the university website.

02

The cited or mentioned institution gets an early trust advantage.

03

This is why CWRU's pages, newsroom, profiles, and external coverage should reinforce the same priority facts.

AI Search Strategy

Visibility is the competitive advantage

Consideration

You have to be found to be considered.

Differentiation

Differentiation starts with discovery.

Practical shift

Spend as much effort on getting found in AI/search contexts as you spend on what happens after the click.

Source context

AMA 2025 AI Search deck, slide 14.

AI Search Strategy

Without SEO, you do not show up in AI

Legacy framing

Weak SEO vs. strong SEO.

Important caveat

AI search is not a replacement for organic visibility.

Grounded AI

Organic visibility and citation quality are part of the input layer.

Use carefully

Not every AI answer is search-index grounded, but strong public SEO signals still matter.

AI Search Strategy

Current marketing already influences AI search

01

Program pages

02

Blog posts and articles

03

Newsroom

04

Homepage

05

Videos

06

External placements

07

Social profiles and posts

08

Directories and profiles

Source: Source context: UPCEA 2026 slide 18; UPCEA webinar slide 30

Day 2

Entities and semantic clarity

Make the relationship between CWRU and its priority concepts unmistakable

Semantic Clarity

What is an entity?

Plain meaning

A named person, place, organization, program, topic, credential, or concept.

Examples

Case Western Reserve University, Frances Payne Bolton School of Nursing, Master of Science in Nursing, Cleveland, AAU, research expenditures.

Why it matters

AI systems use entities and relationships to infer what content is about.

Semantic Clarity

CWRU entity map

Institution

Case Western Reserve University.

Schools

School of Medicine, Case School of Engineering, Frances Payne Bolton School of Nursing, Mandel School.

Programs

MSN, MSW, engineering areas of study.

Topics

Research growth, biomedical innovation, hands-on engineering, professional education.

Locations and affiliations

Cleveland, Ohio, AAU.

Semantic Clarity

Semantic triples

Pattern

Subject -> Predicate -> Object.

Example

Case Western Reserve University offers undergraduate engineering programs connected to research and hands-on design.

Example

Frances Payne Bolton School of Nursing offers MSN majors and specialties for nurses advancing clinical practice.

How to use it

Use triples as an editing tool, not as visible jargon for every page.

Semantic Clarity

Program boilerplate pattern

Formula

[School] offers [program] for [audience] who want [outcome].

Reuse

Good boilerplate can be used in program pages, newsroom context, social copy, and PR talking points.

Constraint

Keep the language factual and consistent; do not make every page invent a new description.

Semantic Clarity

Engineering semantic boilerplate

01

Case Western Reserve University offers undergraduate engineering programs for students who want hands-on design, research, entrepreneurship, and technical problem solving in Cleveland.

02

Use consistently across area-of-study, admissions, research, and news contexts where appropriate.

Semantic Clarity

MSN semantic boilerplate

01

Frances Payne Bolton School of Nursing at Case Western Reserve University offers Master of Science in Nursing pathways and specialties for nurses preparing for advanced clinical, leadership, and specialty roles.

02

Use to connect program detail, school reputation, and applicant outcomes.

Semantic Clarity

MSW semantic boilerplate

01

Case Western Reserve University's on-campus Master of Social Work prepares students for social work practice through graduate study, field education, and community-connected learning.

02

Use to connect audience, credential, format, and outcome.

Semantic Clarity

Ways to Give semantic boilerplate

01

Case Western Reserve University's giving options help alumni, friends, and partners support students, research, faculty, programs, and institutional priorities.

02

Use to connect transaction paths to impact and authority signals.

Semantic Clarity

Content chunks AI can retrieve

01

Definition or plain-English summary.

02

Program or page facts.

03

Eligibility/requirements/deadlines.

04

Outcomes and proof.

05

FAQs or decision-support sections.

06

Internal links to authoritative related pages.

Semantic Practice

Exercise: entity mapping

What should this page make unmistakably clear to AI systems?

12 minutes

1Name entities
2Name relationships
3Name evidence
4Name missing signal
School Authority Signal

CWRU entity example: School of Medicine

Teaching use

School-level hub that should connect education, research, clinical expertise, people, and news.

Opportunity

Make entity relationships explicit through headings, summaries, internal links, and consistent boilerplate.

Ask

What should AI understand about this school after reading only the top-level page?

Source: https://case.edu/medicine/

CWRU entity example: School of Medicine screenshot
Research Hub Signal

CWRU entity example: Medicine Research

Teaching use

Research hub as institutional authority signal.

Opportunity

Connect research themes to faculty, centers, grants, news, programs, and Cleveland/healthcare context.

Ask

Which topics should this page make CWRU known for?

Source: https://case.edu/medicine/research

CWRU entity example: Medicine Research screenshot
Engineering Research Signal

CWRU entity example: Engineering Research

Teaching use

Research hub with clear authority and internal-link potential.

Opportunity

Connect 'Boundless Ideas,' departments, centers, institutes, experiential learning, and headlines into a clearer knowledge graph.

Dependency note

Design and CMS dependencies should be captured separately from content edits.

Source: https://case.edu/engineering/research

CWRU entity example: Engineering Research screenshot
Day 2

Newsroom and external signals

CWRU's authority is reinforced beyond program pages

Authority Signals

Why newsroom belongs in AI-search training

01

Newsroom stories connect people, topics, discoveries, gifts, rankings, research, and institutional momentum.

02

They often become the source material for external coverage.

03

They can corroborate what program and school pages claim.

04

They give AI systems repeated patterns around what CWRU is known for.

Authority Signals

Newsroom language should connect dots

01

Name the institution consistently.

02

Name the school, department, faculty, program, topic, and partner when relevant.

03

Explain why the story matters to audiences beyond campus.

04

Use boilerplate intentionally so external pickup carries the right facts.

Authority Signals

External corroboration

01

A CWRU page says what CWRU says about itself.

02

External pickup says other sources recognize or repeat the claim.

03

AI systems often reward patterns repeated across credible sources.

04

This is why PR, newsroom, and SEO should not be separated in the AI-search conversation.

CWRU Proof Points

Official story: fastest-growing AAU research university

Teaching use

Official source for institutional authority.

Strong signal

CWRU frames itself as the #1 fastest-growing research university in the AAU.

Opportunity

Connect this claim to school research pages, faculty expertise, graduate programs, and external pickup.

Caution

Keep date/source context visible for ranking and research-expenditure claims.

Source: https://case.edu/news/cwru-now-1-fastest-growing-research-university-aau

Official story: fastest-growing AAU research university screenshot
External Proof

External pickup: Ohio Tech News

Teaching use

Official CWRU story becomes third-party sector coverage.

Corroboration

This is a concrete example of external corroboration.

Ask

What phrases, facts, and entity links from CWRU's original story made it into external coverage?

Discussion frame

Use as a discussion about consistent language, not as a press-release lecture.

Source: Ohio Tech News coverage of CWRU research-growth story

External pickup: Ohio Tech News screenshot
Reputation Proof

Ranking story: use with date context

Teaching use

Reputation proof and context management.

Watchout

Ranking stories can support authority, but they age and may include updates/corrections.

Recommendation

Visible date, source, and context should stay attached to claims.

AI/search angle

Stale or ambiguous claims can be repeated without nuance.

Source: https://case.edu/news/case-western-reserve-university-named-among-worlds-top-universities-time

Ranking story: use with date context screenshot
External Proof

External distribution example: EurekAlert

Teaching use

External distribution and institutional boilerplate.

Discussion note

Even when the page blocks text extraction, the slide can discuss distribution surfaces and press-release pickup.

Opportunity

Every external release should carry clean entity language about CWRU, the gift/story, people, school/unit, and institutional priorities.

Source: https://www.eurekalert.org/news-releases/1126599

External distribution example: EurekAlert screenshot
Authority Signals

PR and media best practices for AI search

Locked-in phrase

Consistent verbiage used in each release or talking points about the university, program, or priority topic.

Reuse the facts

Use the same factual description across newsroom, program page, social, and external pitch materials.

Name the entities

Include the institution, school, program, people, location, topic, credential, audience, and outcome.

Source context

UPCEA webinar slide on PR and media best practices for AI search.

Authority Signals

Where CWRU can build citations

01

Online directories that are industry, topic, or locally relevant.

02

Sponsored or contributed content where appropriate and labeled.

03

Media mentions from local, regional, national, and sector publications.

04

Thought leadership interviews, podcasts, webinars, and conference pages.

05

Faculty and program profiles on authoritative third-party sites.

Source: Source context: AMA 2025 slide 41; UPCEA 2026 slide 55

Authority Signals

Supportive and derivative content

01

LinkedIn posts and articles can reinforce program/faculty/newsroom language.

02

YouTube/video transcripts create another AI-readable surface.

03

Blog and newsroom summaries can point back to program/research pages.

04

The point is not volume; the point is consistent, useful, corroborated signals.

Source: Source context: AMA 2025 slides 37-38

Authority Signals

How to address inaccurate AI answers

01

Ask AI for its sources.

02

Google the claim to find likely source pages.

03

Search CWRU's own site for outdated or conflicting language.

04

Fix the owned source first, then reinforce with stronger external signals.

Source: Source context: UPCEA webinar slide 36

Day 2

Tools and measurement

Use tools to find gaps, not to outsource judgment

Tools & Measurement

Tool categories to consider

01

AI visibility tools

02

Technical/site-quality crawlers

03

Accessibility and content-quality tools

04

SEO research platforms

05

Brand/reputation monitoring

06

Approved internal AI access, if available

Tools & Measurement

Measurement caveat

01

AI visibility tools are directional.

02

One platform is not the whole truth.

03

Prompt wording changes results.

04

Use tools to find page priorities and citation gaps, then apply editorial judgment.

Tools & Measurement

GA4 AI referral traffic

Tools

Which AI tools drive traffic?

Pages

Which pages are clicked from AI citations?

Growth

How much is AI referral traffic growing?

Engagement

How engaged are AI-referred visitors?

Source context

AMA 2025 slide 47.

Tools & Measurement

Google Search Console question queries

What they reveal

Question-style queries show what users ask before they reach the page.

How to find them

Use regex/query filters for what, why, who, how, where, when, can, and should terms.

How to use them

Turn question patterns into headings, FAQs, and page sections.

Source context

AMA 2025 slide 48.

Tools & Measurement

Prompt visibility checks

01

Prompt around priority audiences and real decision moments.

02

Record whether CWRU is mentioned, cited, absent, or misrepresented.

03

Capture the sources AI uses.

04

Turn findings into page edits, citations, or newsroom/PR priorities.

Tools & Measurement

Using tools without losing judgment

01

The tool should support the content decision, not become the focus.

02

Use one CWRU prompt cluster and one page example when a live demo is appropriate.

03

Show result, cited sources, missing entities, and recommended page action.

04

Use examples that keep the discussion focused on findings and next actions.

Day 2

Priority workshop and next steps

Turn examples into standards CWRU can carry forward

Prioritization

Priority matrix

Rows

Page/content issue.

Columns

Impact, effort, owner, next action.

Sort separately

Separate page edits, governance questions, and external-signal work.

Use examples

Pull from live examples discussed across both days.

Prioritization

Quick wins

01

Rewrite vague H2s into reader questions.

02

Replace repeated 'learn more' links with descriptive links.

03

Add page job statements to priority pages before editing.

04

Add short summary/fit blocks to complex program pages.

05

Standardize program/school/entity boilerplate.

Prioritization

Reusable rules

01

Every page has one primary job.

02

Headings should orient a skimmer.

03

CTAs should name the action or destination.

04

Alt text should fit the image's page context.

05

Priority entities should be named consistently across pages and external materials.

Governance

Owner decisions

01

Which team owns program boilerplate?

02

Which pages get edited first?

03

What needs CWRU brand/legal/accessibility review?

04

Which newsroom patterns should be standardized?

05

What can be handled in CMS now vs. future redesign work?

Governance

What not to overcomplicate

01

Do not turn every page into an AI page.

02

Do not keyword-stuff alt text or headings.

03

Do not chase every prompt variation.

04

Do not create content only because a tool surfaced a gap.

05

Do not hide the human reader behind machine optimization.

Carry-Forward Standards

Post-training recommendations

01

1-3 page written summary.

02

Top examples discussed.

03

Recommended standards or governance changes.

04

Open questions and dependencies.

05

Priority next steps with owners where known.

Next-Step Options

Recommended follow-up work

01

Optional deeper diagnostic for one school/program/content cluster.

02

AI visibility baseline across selected prompt clusters.

03

Program-page rewrite direction for priority areas.

04

Newsroom/PR boilerplate and citation strategy.

05

Governance support for distributed content standards.

Priority Practice

Final exercise: fix, standardize, leave alone

For one CWRU page, decide what to fix now, what to standardize, and what to leave alone.

15 minutes

1Fix first
2Standardize
3Assign owner
4Capture next step
Wrap-Up

Participant takeaway

01

Use the page-quality framework before editing.

02

Use real reader questions as headings.

03

Make important entities and relationships explicit.

04

Connect program, school, newsroom, and external signals.

05

Let AI-search tactics sharpen editorial judgment, not replace it.

Wrap-Up

Closing discussion

01

What changed in how you read your own pages?

02

What one rule should CWRU standardize first?

03

Which page or content type needs the fastest follow-up?

04

What question should be answered in the written recommendations?

Case Western Reserve University

Thank you

Web Writing + AI Search Training

Presented by
Search Influence
Training dates
June 9-10, 2026
Search InfluenceCWRU