Case Studies & Service Examples

Explore how technical SEO, content, external sources and brand knowledge management support SEO and GEO work across industries.

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This page includes 7 customer case studies and 13 illustrative service examples. The examples explain our approach; their scope, workloads and business metrics are hypothetical and do not represent achieved customer results.

Construction materials · Customer case study

Service periodFeb 2026–Jul 2026

Structural reinforcement and construction materials provider

Align brand and founder information and monitor external opinions

Accuracy of reviewed factual statements

99.81%

Based on the factual statements reviewed

Bridges and structural engineering — Industry illustration; not a customer location or product.

Business and AI performance

Negative views identified within project scope: 0 views
Recurrence of negative views within project scope: 0%

The original challenge

Public information about the brand and founder was fragmented. Key details and brand descriptions needed to be checked across channels.

What we did

Organized brand and founder information and completed priority public profiles.
Monitored brand descriptions and opinions to check consistency across external sources.

Leads, closed-won business, paid conversion and AI visibility are measured separately. Scope and periods follow the notes for this case.Explore managed GEO / AEO services ↗

Industrial products and MRO distributor · Service example

Connect product selection with qualified procurement inquiries

An established distributor of automation components, instruments, and maintenance, repair and operations (MRO) supplies across multiple brands, serving business buyers and replacement-parts needs.

Figures in this service example illustrate measurement methods. They do not represent actual customer results.

Illustrative metric · AI-assisted open sales pipeline

~US$110,000

Unweighted potential contract value across 16 open opportunities with recorded AI touchpoints. These are open opportunities, not closed-won sales or profit.

Industrial product distribution and warehouse operations — Industry illustration; not a customer location or product.

GEO project scope

Target markets: United StatesGermany
Service period: Oct 2025–Sep 2026
Reference observation window: About 5 weeks
Illustrative AI platforms and search experiences: ChatGPTPerplexityGoogle Gemini
Monitoring scope: 8 topics · 96 distinct prompts

Illustrative GEO monitoring metrics

Hypothetical comparison: before → after

AI visibility

4%19%

+15 percentage points

Share of monitored answers mentioning the target brand or a priority model

Brand website citation rate

1.4%10.2%

+8.8 percentage points

Share of monitored answers citing the brand website

Top-three recommendation rate

0.8%10.4%

+9.6 percentage points

Share of monitored answers placing the brand among the top three recommendations

Qualified AI-referred procurement inquiries per month

28 → 96

Deduplicated inquiries with a company identity, part number or procurement requirements

Semrush search traffic trend

View original screenshot

Industrial products and MRO distributor: original Semrush traffic screenshot — Original Semrush reference image from the case attachment. The service example's business figures are hypothetical and cannot be inferred from this chart. The reference chart shows organic traffic in the hundreds of thousands, with a recovery after June. The illustrative service period is Oct 2025–Sep 2026; October and November show subsequent observation. (Original Chinese interface retained.)

Typical challenges

On-site · Technical SEO

Multiple brands, models and filter combinations create duplicate URLs. Pagination, canonicalization, crawling and priority SKU indexing need coordinated management.

On-site · Content coverage

Traffic is concentrated on brand and model queries, with limited coverage of substitutes, compatibility, procurement, applications and maintenance.

Off-site · Sources and consistency

Supplier catalogs, dealers and trade media describe models, market availability and service capabilities inconsistently.

Brand knowledge management

SKU attributes, substitution relationships and regional delivery information are fragmented across suppliers and versions.

Optimization approach

For an established distributor, prioritize catalog indexing, model and substitute selection content, and supplier data consistency. Connect identifiable AI referrals with inquiries and CRM opportunities.

Illustrative service plan

These modules illustrate how a service plan can be assembled. Actual workloads and delivery schedules depend on the agreed project scope.

On-site · Technical SEO

Manage catalog architecture and indexing at scale

Audit filters, pagination, canonical tags, sitemaps and crawl logs. Prioritize indexing and internal links for available SKUs, brand pages, model pages and categories.

Illustrative workloadMonth 1: one catalog SEO audit; monthly: 2 template or rule reviews and 40 priority URL checks

On-site · Content optimization

Address substitute-product and business procurement intent

Build comparisons and selection content around models, attributes, application conditions and procurement stages. Connect compatibility, availability and inquiry information with product detail pages.

Illustrative workloadMonthly: 12 procurement guides and 20 priority brand, category or product page updates

Off-site · Sources and consistency

Align supplier, brand and trade directory information

Check brand, supplier and industry information cited by target AI platforms. Maintain authorization scope, models and service markets, recording factual updates and external adoption.

Illustrative workload30 priority suppliers or sources; follow up on 10 updates each month

Brand knowledge management

Maintain SKU, substitution and delivery facts

Consolidate supplier attributes, models, compatibility evidence, availability, lead times and warranty terms. Record sources and revision dates for important changes.

Illustrative workloadMonth 1: one data-field and review standard; sample-check 100 priority SKUs or substitution relationships each month

PR and trade media

Develop procurement and supply-chain outreach

Prepare verifiable application, supplier partnership and procurement service information for industrial, automation and purchasing media.

Illustrative workload25–40 media targets; 2 topic or outreach packs per month, with publication tracked separately

LinkedIn / YouTube

Publish procurement and technical selection content

Create model comparisons, spare-parts guidance and operating-condition posts for procurement and maintenance teams. Produce technical videos from approved client materials.

Illustrative workloadMonthly: 8 LinkedIn posts and 2 technical selection videos

Project responsibilities

Dageno team: SEO/GEO diagnostics, technical and content planning, source development, outreach, weekly progress updates and monthly reviews.
Client and collaborators: Product teams provide supplier and SKU data; engineers review compatibility; procurement and sales maintain inventory, lead times, quotes and CRM stages.
Delivery and channel records: Track planning, production, launch, media outreach and publication separately. Count original content separately from adaptations for other platforms.

Metric definitions and measurement

AI visibility, brand website citation rate and top-three recommendation rate use different definitions. Comparisons use the same agreed prompts, platforms and markets; these metrics do not represent user search volume or market share.

Repeat monitoring using the agreed markets, languages and sampling method. Record citations and recommendations separately for each platform.

Unweighted potential contract value across 16 open opportunities with recorded AI touchpoints. These are open opportunities, not closed-won sales or profit.

Illustrative measurement sources: Dageno monitoring, business procurement inquiries and CRM. US$110,000 is the unweighted value of 16 open opportunities, not closed-won sales.

Industrial power supplies and electronic components · Service example

Help engineers identify substitute models, compatibility requirements and purchasing channels

An industrial power module supplier with many part numbers, generating demand through its website and authorized distributors.

Figures in this service example illustrate measurement methods. They do not represent actual customer results.

Illustrative metric · Qualified sample and quote requests per month

24requests

Deduplicate after sales confirms a part number or application requirement. Track website and authorized distributor sources separately.

Electronic circuits and components — Industry illustration; not a customer location or product.

GEO project scope

Target markets: United StatesGermany
Service period: Feb 2026–Jul 2026
Reference observation window: About 3 weeks
Illustrative AI platforms and search experiences: ChatGPTPerplexity
Monitoring scope: 7 topics · 84 distinct prompts

Illustrative GEO monitoring metrics

Hypothetical comparison: before → after

AI visibility

8%23%

+15 percentage points

Share of monitored answers mentioning the target brand or a priority model

Brand website citation rate

3.5%12.8%

+9.3 percentage points

Share of monitored answers citing the brand website

Top-three recommendation rate

2.4%13.6%

+11.2 percentage points

Share of monitored answers placing the brand among the top three recommendations

Model match rate for sample requests

62% → 84%

Share of engineers able to continue evaluation without changing the requested part number

Typical challenges

On-site · Technical SEO

Similar part-number pages and PDF specifications create duplication, indexing and readability issues.

On-site · Content coverage

Substitute parts, compatibility requirements and application questions lack a clear structure for search and AI discovery.

Off-site · Sources and consistency

Distributor information uses different versions, allowing outdated models and incorrect specifications into selection answers.

Brand knowledge management

Part aliases, compatibility relationships and discontinuation dates lack a common reference.

Optimization approach

Clarify model identities and application requirements, then combine catalog improvements, selection content and distributor consistency to support correct product discovery and sample requests.

Illustrative service plan

These modules illustrate how a service plan can be assembled. Actual workloads and delivery schedules depend on the agreed project scope.

On-site · Technical SEO

Improve part-number catalogs and accessible specifications

Check duplicate URLs, canonical tags, indexing and product markup. Put key PDF specifications into readable HTML and link related part numbers.

Illustrative workloadInitial audit of 30 part-number pages; monthly plans for 12 priority pages

On-site · Content optimization

Create substitute-part and application selection content

Use compatibility limits, test conditions and applications to build comparison pages and FAQs linked to data sheets, sample requests and authorized sellers.

Illustrative workloadMonthly: 8 application or substitute-part articles and 6 selection page updates

Off-site · Sources and consistency

Synchronize authorized distributor specifications

Provide priority distributors and component directories with current part numbers, specifications, versions and substitution information. Track updates and citation changes.

Illustrative workloadInitial review of 20 sources; follow up with 8 each month

Brand knowledge management

Maintain model identities and substitution relationships

Standardize model names, aliases, substitution conditions, certifications and discontinuation records, with engineering approval before reuse.

Illustrative workloadMonth 1: one part-number fact library; maintain 20 priority models each month

Technical PR and specialist content

Reach sources engineers use for research

Prepare test methods and application notes for relevant technical media. Use LinkedIn and YouTube to distribute selection and test explanations.

Illustrative workloadMonthly: one technical outreach plan, 4 LinkedIn posts and one video

Project responsibilities

Dageno team: SEO/GEO diagnostics, technical and content planning, source development, outreach, weekly progress updates and monthly reviews.
Client and collaborators: Engineers confirm compatibility, channel managers coordinate distributors and sales validates sample requests.
Delivery and channel records: Track planning, production, launch, media outreach and publication separately. Count original content separately from adaptations for other platforms.

Metric definitions and measurement

Repeat monitoring using the agreed markets, languages and sampling method. Record citations and recommendations separately for each platform.

Deduplicate after sales confirms a part number or application requirement. Track website and authorized distributor sources separately.

Illustrative measurement sources: Dageno model mentions, sample records and authorized distributor feedback

Commercial lighting · Service example

Clarify lighting performance, operating conditions and installation to support project inquiries

An established lighting exporter with an English catalog website, adding selection and dealer pages for projects in the Middle East and Latin America.

Figures in this service example illustrate measurement methods. They do not represent actual customer results.

Illustrative metric · Qualified AI-referred project inquiries per month

34inquiries

Project requirements are confirmed and deduplicated in CRM. Dealer referrals are recorded separately from AI referrals.

Commercial lighting and workplace design — Industry illustration; not a customer location or product.

GEO project scope

Target markets: United Arab EmiratesSaudi ArabiaBrazil
Service period: Apr 2026–Oct 2026
Reference observation window: About 6 weeks
Illustrative AI platforms and search experiences: ChatGPTGoogle AI Mode
Monitoring scope: 6 topics · 72 distinct prompts

Illustrative GEO monitoring metrics

Hypothetical comparison: before → after

AI visibility

0%17%

+17 percentage points

Share of monitored answers mentioning the target brand or a priority model

Brand website citation rate

0%9.6%

+9.6 percentage points

Share of monitored answers citing the brand website

Top-three recommendation rate

0%8.2%

+8.2 percentage points

Share of monitored answers placing the brand among the top three recommendations

Project inquiry completeness

41% → 72%

Inquiries include space, quantity and delivery requirements

Semrush search traffic trend

View original screenshot

Commercial lighting: original Semrush traffic screenshot — Original Semrush reference image from the case attachment. Business figures in this service example are hypothetical; AI leads, sales and profit cannot be inferred from this chart. (Original Chinese interface retained.)

Typical challenges

On-site · Technical SEO

The English catalog lacks regional architecture, language annotations and discoverable project resources.

On-site · Content coverage

Selection, lighting specifications and installation questions lack connected content. The illustrative AI visibility baseline is 0%.

Off-site · Sources and consistency

Regional directories and dealers publish inconsistent specifications, while the brand is absent from sources used for project selection.

Brand knowledge management

Certification scope, photometric files, regional versions and channel information are managed separately.

Optimization approach

Start with regional site architecture and selection content, then use a consistent factual reference to update dealers and support regional media and professional outreach.

Illustrative service plan

These modules illustrate how a service plan can be assembled. Actual workloads and delivery schedules depend on the agreed project scope.

On-site · Technical SEO

Build regional pages and project resource paths

Review navigation, internal links, indexing, canonical tags and hreflang. Make photometric, certification and installation resources accessible from the relevant product pages.

Illustrative workloadMonth 1: one regional site audit and plans for 8 priority pages

On-site · Content optimization

Address specification and project procurement questions

Develop selection guides for warehouses, parking areas and commercial spaces. Connect fixture comparisons, installation guidance and local certification FAQs with project inquiry forms.

Illustrative workloadMonthly: 8 selection articles and 6 product or application page updates

Off-site · Sources and consistency

Align regional directories and channel information

Check model numbers, voltage and certification scope across dealers and project directories. Submit regional information packs and record corrections and adoption.

Illustrative workload15 priority sources; follow up with 5 each month

Brand knowledge management

Manage model, certification and regional facts

Maintain versioned records of models, photometric files, certification scope, voltage, installation limits and market availability for website and channel use.

Illustrative workloadMonth 1: one brand fact library; maintain 10 priority products each month

PR and regional media

Plan regional outreach around project applications

Prepare commercial lighting application topics and engineering materials for local architecture, lighting and procurement media. Record pitches and publication separately.

Illustrative workload20 regional media targets and one outreach plan per month

LinkedIn / YouTube

Distribute project and installation content

Create application posts for contractors and dealers, using customer-approved installation and project materials for demonstrations.

Illustrative workloadMonthly: 6 LinkedIn posts and 2 video scripts or edits

Project responsibilities

Dageno team: SEO/GEO diagnostics, technical and content planning, source development, outreach, weekly progress updates and monthly reviews.
Client and collaborators: Lighting engineers approve design information; regional sales teams confirm certification and availability; dealers provide service information.
Delivery and channel records: Track planning, production, launch, media outreach and publication separately. Count original content separately from adaptations for other platforms.

Metric definitions and measurement

Repeat monitoring using the agreed markets, languages and sampling method. Record citations and recommendations separately for each platform.

Project requirements are confirmed and deduplicated in CRM. Dealer referrals are recorded separately from AI referrals.

Illustrative measurement sources: Dageno monitoring, project forms and CRM source records

AI and developer tools · Service example

Help developers make their first successful call using current examples

A developer tool offering model access and workflow APIs, with self-service trials and usage-based pricing.

Figures in this service example illustrate measurement methods. They do not represent actual customer results.

Illustrative metric · Activated AI-referred trials per month

28trials

Of 46 deduplicated monthly trials, 28 make their first successful API call within 7 days.

Developer collaboration and software tools — Industry illustration; not a customer location or product.

GEO project scope

Target markets: United StatesUnited KingdomGermany
Service period: Oct 2025–Mar 2026
Reference observation window: About 2 weeks
Illustrative AI platforms and search experiences: ChatGPT
Monitoring scope: 8 topics · 96 distinct prompts

Illustrative GEO monitoring metrics

Hypothetical comparison: before → after

AI visibility

9%25%

+16 percentage points

Share of monitored answers mentioning the target brand or a priority model

Brand website citation rate

3.6%14.4%

+10.8 percentage points

Share of monitored answers citing the brand website

Top-three recommendation rate

3.2%14.6%

+11.4 percentage points

Share of monitored answers placing the brand among the top three recommendations

Trial activation rate

60.9%

28 activated accounts divided by 46 deduplicated trials

Typical challenges

On-site · Technical SEO

Current and deprecated documentation appear together in search, with unclear version links and crawl paths.

On-site · Content coverage

Content does not directly answer API selection, task limitations and first-integration questions.

Off-site · Sources and consistency

GitHub, reviews and communities use inconsistent product names and outdated examples, contributing to incorrect recommendations.

Brand knowledge management

Interfaces, model support, billing and deprecation information lack a single approved version.

Optimization approach

Improve documentation and version control, then address selection and onboarding questions through content, developer communities and technical media. Connect AI referrals with successful API calls.

Illustrative service plan

These modules illustrate how a service plan can be assembled. Actual workloads and delivery schedules depend on the agreed project scope.

On-site · Technical SEO

Improve documentation indexing and version relationships

Check crawling, canonical tags, version navigation and internal links. Add migration guidance for deprecated content and track trial and API-call events.

Illustrative workloadInitial audit of 20 documentation URLs; update 10 priority pages each month

On-site · Content optimization

Address API comparisons and integration questions

Create content on task suitability, costs, framework integration and troubleshooting. Link working examples to current interfaces and quick-start guides.

Illustrative workloadMonthly: 12 technical articles and 4 integration or comparison pages

Off-site · Sources and consistency

Align product facts across developer sources

Check naming and versions across GitHub, tool directories, technical reviews and communities. Provide accurate materials and answer specific questions.

Illustrative workloadReview 20 priority sources; follow up with 6 each month

Brand knowledge management

Maintain API and capability facts

Manage model support, interface versions, pricing, limits, deprecation dates and approved descriptions for documentation, sales and communications.

Illustrative workloadMonth 1: one knowledge library; monthly version review

Developer communities and video

Use examples in X, Reddit and GitHub discussions

Participate transparently as the brand, offering reproducible solutions and YouTube integration demos. Evaluate usefulness rather than post or backlink volume.

Illustrative workloadMonthly: 8 community posts, 6 technical responses and 2 demo videos

Technical PR and LinkedIn

Explain product versions and developer value

Prepare media outreach and technical leadership posts around approved product updates, integrations and research.

Illustrative workloadMonthly: one outreach topic pack and 4 LinkedIn posts

Project responsibilities

Dageno team: SEO/GEO diagnostics, technical and content planning, source development, outreach, weekly progress updates and monthly reviews.
Client and collaborators: Developers run examples and confirm interfaces; product teams approve pricing; data teams connect account events.
Delivery and channel records: Track planning, production, launch, media outreach and publication separately. Count original content separately from adaptations for other platforms.

Metric definitions and measurement

Repeat monitoring using the agreed markets, languages and sampling method. Record citations and recommendations separately for each platform.

Of 46 deduplicated monthly trials, 28 make their first successful API call within 7 days.

Illustrative measurement sources: Dageno answers, documentation sources and product account events

Cross-border payments and acquiring · Service example

Clarify merchant eligibility and supported markets before qualifying sales opportunities

An acquiring platform for international merchants, operating through several entities and payment partners with eligibility screening before onboarding.

Figures in this service example illustrate measurement methods. They do not represent actual customer results.

Illustrative metric · Sales opportunities passing eligibility screening per month

45opportunities

Companies pass market, entity and business-category checks and are accepted by sales. Deduplicate by company.

Merchant payment processing — Industry illustration; not a customer location or product.

GEO project scope

Target markets: SingaporeUnited KingdomGermany
Service period: Dec 2025–Aug 2026
Reference observation window: About 7 weeks
Illustrative AI platforms and search experiences: ChatGPTPerplexity
Monitoring scope: 6 topics · 72 distinct prompts

Illustrative GEO monitoring metrics

Hypothetical comparison: before → after

AI visibility

3%12%

+9 percentage points

Share of monitored answers mentioning the target brand or a priority model

Brand website citation rate

1.2%6.4%

+5.2 percentage points

Share of monitored answers citing the brand website

Top-three recommendation rate

0.4%6.2%

+5.8 percentage points

Share of monitored answers placing the brand among the top three recommendations

Eligibility pass rate for AI-referred leads

32% → 51%

Companies passing screening divided by AI-referred companies completing screening

Semrush search traffic trend

View original screenshot

Cross-border payments and acquiring: original Semrush traffic screenshot — Original Semrush reference image from the case attachment. Business figures in this service example are hypothetical; AI leads, sales and profit cannot be inferred from this chart. (Original Chinese interface retained.)

Typical challenges

On-site · Technical SEO

Entity, market and help-center pages lack clear links, while outdated mirrored content remains discoverable.

On-site · Content coverage

Onboarding, settlement, chargebacks and pricing questions lack direct answers with clear eligibility conditions.

Off-site · Sources and consistency

Licensing, coverage and partnership information is outdated, allowing AI answers to omit important limits.

Brand knowledge management

Compliance, product and sales teams use different versions of entity and market information.

Optimization approach

Start with search and AI questions affecting merchant eligibility. Align website facts, external information and compliance approval, then use B2B content and PR to support screened opportunities.

Illustrative service plan

These modules illustrate how a service plan can be assembled. Actual workloads and delivery schedules depend on the agreed project scope.

On-site · Technical SEO

Organize entity and market page architecture

Review help-center indexing, duplicates, canonical tags and internal links. Connect coverage, licensing, fees and eligibility screening.

Illustrative workloadMonth 1: one technical audit; review 8 priority pages each month

On-site · Content optimization

Address onboarding and payment decisions

Create explanations and comparisons around merchant types, markets, currencies, settlement and chargebacks, keeping eligibility conditions explicit.

Illustrative workloadMonthly: 8 articles and 4 coverage or help-page updates

Off-site · Sources and consistency

Check partner and fintech information sources

Provide priority partners, directories and trade media with approved entity, coverage and licensing information. Record corrections and adoption.

Illustrative workloadReview 15 priority sources; follow up with 5 each month

Brand knowledge management

Manage compliance and sales facts

Standardize entities, licensing scope, service markets, excluded categories and eligibility requirements, with approval and revision records.

Illustrative workloadMonth 1: one knowledge library; monthly compliance fact review

PR / LinkedIn / YouTube

Distribute compliance facts and merchant guidance

Prepare trade-media materials and market coverage explanations. Adapt onboarding and settlement guidance into professional posts and videos.

Illustrative workloadMonthly: one PR plan, 6 LinkedIn posts and one video

Project responsibilities

Dageno team: SEO/GEO diagnostics, technical and content planning, source development, outreach, weekly progress updates and monthly reviews.
Client and collaborators: Compliance approves entity and licensing information, onboarding teams confirm eligibility and sales records opportunities.
Delivery and channel records: Track planning, production, launch, media outreach and publication separately. Count original content separately from adaptations for other platforms.

Metric definitions and measurement

Repeat monitoring using the agreed markets, languages and sampling method. Record citations and recommendations separately for each platform.

Companies pass market, entity and business-category checks and are accepted by sales. Deduplicate by company.

Illustrative measurement sources: Dageno monitoring, the client's screening system and CRM

Cloud security and IT operations · Service example

Support security shortlisting with deployment, integration and test requirements

A large enterprise cloud security and IT operations vendor serving North America, Australia and New Zealand, where buyers evaluate deployment, integration and compliance before procurement.

Figures in this service example illustrate measurement methods. They do not represent actual customer results.

Illustrative metric · Completed AI-referred enterprise demos per month

18demos

Count qualified, completed demonstrations once per company. Repeated meetings are not added to the total.

Cybersecurity and IT systems — Industry illustration; not a customer location or product.

GEO project scope

Target markets: United StatesAustraliaNew Zealand
Service period: Mar 2026–Aug 2026
Reference observation window: About 4 weeks
Illustrative AI platforms and search experiences: ChatGPTPerplexityGoogle GeminiMicrosoft Copilot
Monitoring scope: 8 topics · 96 distinct prompts

Illustrative GEO monitoring metrics

Hypothetical comparison: before → after

AI visibility

7%18%

+11 percentage points

Share of monitored answers mentioning the target brand or a priority model

Brand website citation rate

2.8%10.2%

+7.4 percentage points

Share of monitored answers citing the brand website

Top-three recommendation rate

2.4%9.4%

+7 percentage points

Share of monitored answers placing the brand among the top three recommendations

Demo-to-technical-evaluation conversion

39%

Completed demos progressing to a mutually agreed technical evaluation

Semrush search traffic trend

View original screenshot

Cloud security and IT operations: original Semrush traffic screenshot — Original Semrush reference image from the case attachment. Business figures in this service example are hypothetical; AI leads, sales and profit cannot be inferred from this chart. (Original Chinese interface retained.)

Typical challenges

On-site · Technical SEO

Integration, deployment and technical documentation do not form a clear selection journey, making important pages difficult to discover.

On-site · Content coverage

Content emphasizes features but gives limited coverage to alternatives, threat scenarios and implementation constraints.

Off-site · Sources and consistency

Reviews, trade media and communities describe capabilities inconsistently, while competitors appear in established sources.

Brand knowledge management

Security claims, test conditions, compliance scope and customer evidence lack consistent version control.

Optimization approach

Address procurement gaps through site architecture, selection content and verifiable evidence, supported by security media, reviews and professional outreach.

Illustrative service plan

These modules illustrate how a service plan can be assembled. Actual workloads and delivery schedules depend on the agreed project scope.

On-site · Technical SEO

Connect integration, deployment and procurement content

Audit crawling, indexing, documentation versions and internal links. Connect products, use cases, integrations and evidence with demo requests.

Illustrative workloadMonth 1: one technical audit; monthly plans for 10 priority pages

On-site · Content optimization

Build security selection and implementation content

Use approved test methods, deployment requirements and compliance information in comparison, alternative-product and use-case content.

Illustrative workloadMonthly: 10 specialist articles and 6 integration or deployment page updates

Off-site · Sources and consistency

Update reviews and industry sources

Identify influential reviews, directories, partners and media. Provide current product facts and methodology, recording external adoption.

Illustrative workload20 priority sources; follow up with 6 each month

Brand knowledge management

Maintain security capability evidence

Keep security claims, integration support, test versions, compliance scope and authorized case information consistent across channels.

Illustrative workloadMonth 1: one knowledge library; monthly review of evidence and versions

PR and security media

Use technical research and evidence in outreach

Prepare media materials around verifiable tests, deployment experience and industry questions. Track production, outreach and publication separately.

Illustrative workload20–30 media targets and one outreach plan per month

LinkedIn / YouTube

Distribute security selection and deployment explanations

Create LinkedIn content for security leaders and turn approved client materials into deployment and integration videos.

Illustrative workloadMonthly: 6 LinkedIn posts and 2 videos

Project responsibilities

Dageno team: SEO/GEO diagnostics, technical and content planning, source development, outreach, weekly progress updates and monthly reviews.
Client and collaborators: Security engineers review tests and capabilities. Presales confirms deployment environments and records completed demos.
Delivery and channel records: Track planning, production, launch, media outreach and publication separately. Count original content separately from adaptations for other platforms.

Metric definitions and measurement

Repeat monitoring using the agreed markets, languages and sampling method. Record citations and recommendations separately for each platform.

Count qualified, completed demonstrations once per company. Repeated meetings are not added to the total.

Illustrative measurement sources: Dageno monitoring, presales calendars and CRM technical evaluation records

Consumer electronics and office accessories · Service example

Use device and protocol tests to help buyers identify compatible models

A docking-station and charging-accessory brand selling through its website, retail platforms and authorized merchants.

Figures in this service example illustrate measurement methods. They do not represent actual customer results.

Illustrative metric · Monthly AI-referred net sales

~US$9,600

Complete month of Apr 2026, up US$6,400 from Sep 2025. Includes identifiable AI-referred orders after cancellations and refunds.

Laptops and office equipment — Industry illustration; not a customer location or product.

GEO project scope

Target markets: United StatesUnited KingdomGermany
Service period: Oct 2025–Apr 2026
Reference observation window: About 3 weeks
Illustrative AI platforms and search experiences: ChatGPTGoogle AI ModeAmazon Alexa
Monitoring scope: 8 topics · 96 distinct prompts

Illustrative GEO monitoring metrics

Hypothetical comparison: before → after

AI visibility

10%23%

+13 percentage points

Share of monitored answers mentioning the target brand or a priority model

Brand website citation rate

4.3%12.6%

+8.3 percentage points

Share of monitored answers citing the brand website

Top-three recommendation rate

3.8%14.1%

+10.3 percentage points

Share of monitored answers placing the brand among the top three recommendations

Increase in monthly AI-referred net sales

+$6,400

Sep 2025 → Apr 2026, using complete months. Attribution changes do not establish causal incremental sales.

Illustrative shopping monitoring metrics

Share of answers placing priority SKUs in the top three

14% → 32%

The denominator includes answers where the product does not appear

Share of shopping answers listing the brand website as a merchant

9% → 24%

Measured among shopping answers returning merchant information

Model and compatibility information accuracy

81% → 96%

Manually checked against product specifications and test evidence

Typical challenges

On-site · Technical SEO

Model, bundle and compatibility pages need restructuring, with weak migration controls for legacy URLs, variant canonical tags and product events.

On-site · Content coverage

Product pages lack compatibility evidence and selection criteria. Identifiers, pricing, inventory and feed information are inconsistent with landing pages.

Off-site · Sources and consistency

Outdated reviews still recommend discontinued models, while compatibility feedback and competitor pricing do not feed into routine updates.

Brand knowledge management

Test conditions, protocols, supported devices and discontinuation relationships lack a consistent version for pages, feeds and support teams.

Optimization approach

Improve model architecture, product pages and feeds, then use compatibility feedback and competitor monitoring to refine selection content. Review identifiable AI-referred net sales and model errors.

Illustrative service plan

These modules illustrate how a service plan can be assembled. Actual workloads and delivery schedules depend on the agreed project scope.

On-site · Site development and architecture migration

Rebuild model and compatibility selection architecture

Map legacy models, bundles and variant URLs, including redirects, canonical tags and internal links. Connect device selection, product pages and purchase events.

Illustrative workloadMonth 1: one model architecture and migration plan, with launch checks for 30 priority URLs

On-site · Content optimization

Use compatibility evidence in product pages

Specify devices, operating systems, interfaces, display outputs and power requirements. Clarify variant differences, warranties and returns, supported by comparisons and FAQs.

Illustrative workloadMonthly: 10 product or compatibility page plans and 12 buying guides

Product data · Feed optimization

Manage SKU, variant and shopping data

Check identifiers, model numbers, bundles, pricing, stock and images. Align Merchant Center feeds, page markup and current listings, tracking issues by channel.

Illustrative workloadMonthly: 30 SKU or variant checks and 2 feed diagnostics

Off-site · Sources and consistency

Update reviews and authorized retail information

Provide priority reviewers, retailers and technical forums with compatibility and replacement information. Track corrections, current products and merchant listings.

Illustrative workload20 priority sources; follow up with 8 each month

Brand knowledge management

Maintain compatibility and model facts

Standardize test conditions, supported devices, model aliases, variants and discontinuation relationships for content, support and outreach.

Illustrative workloadMonth 1: one knowledge library; maintain 20 compatibility or model records each month

Customer sentiment monitoring

Identify compatibility and after-sales issues

Monitor agreed retail reviews and public Reddit, X and Facebook discussions. Route compatibility misunderstandings, quality feedback and service complaints to the relevant teams.

Illustrative workloadWeekly sentiment summary, with recurring questions added to FAQs and support information

Competitor monitoring

Compare device use cases and product competition

Monitor competitor models, recommendation reasons, merchants, prices and compatibility claims in target AI experiences. Update pages when new devices or promotions affect selection.

Illustrative workload5 competing brands and 15 priority SKUs; weekly comparison review

Reddit / X / Facebook / YouTube

Extend content through compatibility answers and demonstrations

Join relevant device discussions with verifiable compatibility information. Evaluate helpful posts and demonstrations rather than backlink or posting volume.

Illustrative workloadMonthly: 12 social posts, 8 responses and 2 compatibility demo videos

Project responsibilities

Dageno team: SEO/GEO diagnostics, technical and content planning, source development, outreach, weekly progress updates and monthly reviews.
Client and collaborators: Engineers run compatibility tests, product teams maintain identifiers and listings, and channel teams work with merchants.
Delivery and channel records: Track planning, production, launch, media outreach and publication separately. Count original content separately from adaptations for other platforms.

Metric definitions and measurement

Repeat monitoring using the agreed markets, languages and sampling method. Record citations and recommendations separately for each platform.

Complete month of Apr 2026, up US$6,400 from Sep 2025. Includes identifiable AI-referred orders after cancellations and refunds.

Illustrative measurement sources: Dageno shopping answers, compatibility tests, GA4 and Shopify. Compare complete months in Sep 2025 and Apr 2026.

Cycling helmets and protective gear · Service example

Rebuild sizing and protection-level selection paths to connect buyers with suitable equipment

A brand selling cycling helmets, knee pads and elbow pads through its website and retailers, with an existing overseas site focused on the United States and United Kingdom.

Figures in this service example illustrate measurement methods. They do not represent actual customer results.

Illustrative metric · Monthly AI-referred net sales

~US$4,800

Complete month of Oct 2026, up US$4,000 from Jul 2026. Includes identifiable AI-referred orders after cancellations and refunds.

Cycling and equipment — Industry illustration; not a customer location or product.

GEO project scope

Target markets: United StatesUnited Kingdom
Service period: Aug 2026–Oct 2026
Reference observation window: About 4 weeks
Illustrative AI platforms and search experiences: ChatGPTGoogle AI Mode
Monitoring scope: 9 topics · 108 distinct prompts

Illustrative GEO monitoring metrics

Hypothetical comparison: before → after

AI visibility

5%18%

+13 percentage points

Share of monitored answers mentioning the target brand or a priority model

Brand website citation rate

1.8%10.6%

+8.8 percentage points

Share of monitored answers citing the brand website

Top-three recommendation rate

1.4%10.2%

+8.8 percentage points

Share of monitored answers placing the brand among the top three recommendations

Increase in monthly AI-referred net sales

+$4,000

Jul 2026 → Oct 2026, using complete months. Attribution changes do not establish causal incremental sales.

Illustrative shopping monitoring metrics

Average weekly appearances in product cards

120+ appearances

Appearances within 360 fixed weekly samples, not actual user impressions

Share of answers placing products in the top three

22%

Denominator: valid monitored answers returning a shopping module

Semrush search traffic trend

View original screenshot

Cycling helmets and protective gear: original Semrush traffic screenshot — Original Semrush reference image from the case attachment. Business figures in this example are hypothetical and cannot be inferred from the chart. The illustrative service period is Aug–Oct 2026. Organic traffic rises from September, with November shown as subsequent observation. Sales comparisons use complete months in July and October. (Original Chinese interface retained.)

Typical challenges

On-site · Technical SEO

Use cases, sizing, certifications and product catalogs are disconnected, with no clear migration plan for legacy series pages and regional versions.

On-site · Content coverage

Product pages lack head measurements, fit guidance, protection levels and certification scope. Feed SKUs and regional availability are inconsistent.

Off-site · Sources and consistency

Cycling reviews, retailers and user discussions describe sizing and protection differently. Competitor and sentiment changes are not monitored consistently.

Brand knowledge management

Certification reports, test conditions, sizing, regional versions and warranties lack coordinated review and version management.

Optimization approach

Prioritize catalog and selection paths, then improve product pages around cycling use, head size, protection standards and fit evidence. Follow with product feeds, specialist reviews and community activity.

Illustrative service plan

These modules illustrate how a service plan can be assembled. Actual workloads and delivery schedules depend on the agreed project scope.

On-site · Site development and architecture migration

Reorganize cycling selection and regional pages

Connect use cases, head size, protection levels and product pages. Preserve useful URLs, review redirects, canonical tags, regional versions and internal links, then validate indexing and order events after launch.

Illustrative workloadMonth 1: one catalog migration and URL map; monthly plans for 6 priority pages

On-site · Content optimization

Improve helmet and protective-gear product evidence

Add head measurement, fit testing, protection standards and certification scope to product pages. Link commuter and mountain-bike selection guides to categories and regional SKUs.

Illustrative workloadMonthly: 8 selection articles and 6 product page updates, with client approval of certification and fit information

Product data · Feed optimization

Align sizing, certification and regional product availability

Check SKU/GTIN, size variants, images, prices, stock and delivery. Align Merchant Center feeds, product pages and structured data.

Illustrative workloadMonthly: 24 priority SKU or variant checks and 2 feed reviews

Off-site · Sources and consistency

Update cycling reviews and retail information

Identify cycling media, reviews and retailers cited by target AI platforms. Supply approved sizing and certification information and track updates, product testing and adoption.

Illustrative workload15–25 priority sources; follow up with 5 each month

Brand knowledge management

Manage sizing and protective certification facts

Standardize models, head sizing, fit instructions, certification reports, scope, regional versions and warranty information.

Illustrative workloadMonth 1: one knowledge library; review 10 model or sizing information packs each month

Customer sentiment monitoring

Track sizing, fit and protection feedback

Monitor cycling forums, retail reviews and public Reddit, X and Facebook discussions. Route sizing misunderstandings, discomfort and quality complaints to the appropriate client teams.

Illustrative workloadWeekly cycling feedback summary, with recurring questions added to product pages and FAQs

Competitor monitoring

Compare cycling use cases and certification claims

Compare competitors' appearances, recommendations and sources for commuting, mountain biking and sizing questions. Review differences in specifications, pricing and certification claims.

Illustrative workload4 competing brands and 10 priority SKUs; weekly comparison review

Reddit / X / Facebook

Publish cycling selection and fit content

Adapt approved sizing, fit and product comparison guides into brand posts and community answers. Follow community rules and collect user questions.

Illustrative workloadMonthly: 10 original posts and 6 community responses; platform adaptations counted separately

YouTube and specialist reviews

Create fit demonstrations and support independent reviews

Use approved client materials to explain measurements, fit adjustments and certification scope. Track video production, review samples and external publication separately.

Illustrative workloadMonthly: 2 fit demonstration videos and one specialist review outreach pack

Project responsibilities

Dageno team: SEO/GEO diagnostics, technical and content planning, source development, outreach, weekly progress updates and monthly reviews.
Client and collaborators: Product teams confirm sizing, fit tests and certification documents; e-commerce teams maintain regional SKUs; reviewers form independent opinions.
Delivery and channel records: Track planning, production, launch, media outreach and publication separately. Count original content separately from adaptations for other platforms.

Metric definitions and measurement

Repeat monitoring using the agreed markets, languages and sampling method. Record citations and recommendations separately for each platform.

Complete month of Oct 2026, up US$4,000 from Jul 2026. Includes identifiable AI-referred orders after cancellations and refunds.

Illustrative measurement sources: Dageno shopping monitoring, certification and fit materials, GA4 and Shopify. Sales compare Jul and Oct 2026; November is subsequent search-trend observation only.

Home and cleaning appliances · Service example

Align regional models and after-sales terms to reduce unsuitable purchases and specification questions

The direct-to-consumer business of a large international appliance group, offering cleaning products with different voltages, accessories and warranty versions.

Figures in this service example illustrate measurement methods. They do not represent actual customer results.

Illustrative metric · Valid AI-referred orders per month

Approx. 44orders

Complete month of Oct 2026, up 30 orders from Apr 2026. Deduplicated by order ID, excluding cancellations and fully refunded orders.

Home and kitchen appliances — Industry illustration; not a customer location or product.

GEO project scope

Target markets: GermanyFranceJapan
Service period: May 2026–Oct 2026
Reference observation window: About 4 weeks
Illustrative AI platforms and search experiences: ChatGPTGoogle GeminiGoogle AI ModeGoogle AI Overview
Monitoring scope: 7 topics · 84 distinct prompts

Illustrative GEO monitoring metrics

Hypothetical comparison: before → after

AI visibility

6.4%19.6%

+13.2 percentage points

Share of monitored answers mentioning the target brand or a priority model

Brand website citation rate

2.2%11.4%

+9.2 percentage points

Share of monitored answers citing the brand website

Top-three recommendation rate

2.6%11.8%

+9.2 percentage points

Share of monitored answers placing the brand among the top three recommendations

Specification-related support tickets per 1,000 orders

40 → 18

Normalized by order volume

Illustrative shopping monitoring metrics

Share of product cards with incorrect specifications

19% → 4%

Manually checked against models available in the target market

Share of answers listing the brand website as a local merchant

14% → 31%

Shopping answers containing brand-site merchant information

Typical challenges

On-site · Technical SEO

Regional sites need architecture and template improvements. Hreflang, canonical tags, redirects and product variant relationships are unclear.

On-site · Content coverage

Regional product pages lack consistent voltage, accessory, warranty and installation information. Feeds and product availability are out of sync.

Off-site · Sources and consistency

Retail and review information uses different versions, while after-sales feedback and competitor changes are not consistently acted on.

Brand knowledge management

Regional SKUs, support terms, specifications and evidence lack coordinated management across websites, feeds and customer support.

Optimization approach

Coordinate four priority AI experiences across markets while improving regional architecture, product pages and feeds. Use customer feedback, competitors and support data to review valid AI-referred orders and specification issues.

Illustrative service plan

These modules illustrate how a service plan can be assembled. Actual workloads and delivery schedules depend on the agreed project scope.

On-site · Site development and architecture migration

Manage regional architecture and template migrations

Plan URL maps, redirects, canonical tags and hreflang for regional sites and legacy templates. Align navigation and internal links, then validate search entry points and analytics events.

Illustrative workloadMonth 1: one international site migration plan; monthly plans for 12 regional pages

On-site · Content optimization

Improve regional product and installation pages

Check voltage, plugs, accessories, dimensions, warranties and support by market, with localized installation, maintenance and comparison content.

Illustrative workloadMonthly: 12 regional product page updates and 10 localized articles

Product data · Feed optimization

Align product feeds across markets

Check identifiers, variants, pricing, stock, delivery and returns by market and language. Log and resolve conflicts between Merchant Center diagnostics and page data.

Illustrative workloadMonthly: 40 regional SKU checks and 2 feed reviews

Off-site · Sources and consistency

Update local retail and review information

Provide priority retailers and reviewers with regional model, pricing and service information. Track corrections and changes in merchant listings.

Illustrative workload20 priority sources; follow up with 8 each month

Brand knowledge management

Maintain regional specifications and after-sales facts

Standardize voltage, plugs, accessories, consumable compatibility, warranty territories and installation limits, with product and support team review.

Illustrative workloadMonth 1: one knowledge library; maintain 20 regional SKU records each month

Customer sentiment monitoring

Connect regional sentiment with support issues

Monitor agreed retail reviews, review sites and public social discussions about installation, specifications and service. Separate factual errors from genuine complaints and feed findings into pages and support.

Illustrative workloadWeekly regional sentiment summary and monthly support-issue review

Competitor monitoring

Compare products and channels by market

Review competing models, pricing, reviews, merchants and recommendation reasons across target AI experiences to identify regional information gaps.

Illustrative workload6 competing brands and 20 priority SKUs; weekly regional competitor review

Facebook / X / YouTube

Distribute localized installation and usage content

Adapt approved installation and maintenance information into local social posts and demonstrations. Return recurring questions to the help center.

Illustrative workloadMonthly: 10 social posts and 2 localized videos

Project responsibilities

Dageno team: SEO/GEO diagnostics, technical and content planning, source development, outreach, weekly progress updates and monthly reviews.
Client and collaborators: Product and support teams confirm models and limitations; e-commerce teams update listings; support agents classify issues by cause.
Delivery and channel records: Track planning, production, launch, media outreach and publication separately. Count original content separately from adaptations for other platforms.

Metric definitions and measurement

Repeat monitoring using the agreed markets, languages and sampling method. Record citations and recommendations separately for each platform.

Complete month of Oct 2026, up 30 orders from Apr 2026. Deduplicated by order ID, excluding cancellations and fully refunded orders.

Illustrative measurement sources: Dageno product checks, regional stores, GA4 and support records. Valid orders compare complete months in Apr and Oct 2026.

Beauty and skin care · Service example

Clarify ingredients, application order and skin suitability to support informed purchases

A skin-care brand selling cleansing, moisturizing and daily-care products through its website and retail channels.

Figures in this service example illustrate measurement methods. They do not represent actual customer results.

Illustrative metric · Monthly AI-referred net sales

~US$9,000

Complete month of Sep 2026, up US$7,000 from Nov 2025. Includes identifiable AI-referred orders after cancellations and refunds.

Skin-care and daily-care products — Industry illustration; not a customer location or product.

GEO project scope

Target markets: SingaporeAustraliaNew Zealand
Service period: Dec 2025–Sep 2026
Reference observation window: About 3 weeks
Illustrative AI platforms and search experiences: ChatGPTGoogle Gemini
Monitoring scope: 8 topics · 96 distinct prompts

Illustrative GEO monitoring metrics

Hypothetical comparison: before → after

AI visibility

13%28%

+15 percentage points

Share of monitored answers mentioning the target brand or a priority model

Brand website citation rate

5.6%15.4%

+9.8 percentage points

Share of monitored answers citing the brand website

Top-three recommendation rate

5.4%17.2%

+11.8 percentage points

Share of monitored answers placing the brand among the top three recommendations

Increase in monthly AI-referred net sales

+$7,000

Nov 2025 → Sep 2026, using complete months. Attribution changes do not establish causal incremental sales.

AI-referred share of net sales

4% → 15%

Up 11 percentage points, using total net sales from the same store and period as the denominator.

Illustrative shopping monitoring metrics

Share of answers placing priority SKUs in the top three

26% → 48%

Denominator: valid monitored answers returning a shopping module

Brand appearances per 100 shopping answers

11 → 27

Deduplicated by answer, excluding repeated mentions within the same answer

Semrush search traffic trend

View original screenshot

Beauty and skin care: original Semrush traffic screenshot — Original Semrush reference image from the case attachment. Business figures in this service example are hypothetical; AI leads, sales and profit cannot be inferred from this chart. (Original Chinese interface retained.)

Typical challenges

On-site · Technical SEO

Store navigation and collection pages need restructuring, with inconsistent management of legacy URLs, bundles and product variants.

On-site · Content coverage

Product pages lack ingredient, usage and purchase details. Prices, inventory and feeds are out of sync.

Off-site · Sources and consistency

Creators, ingredient information sites and retailers use different descriptions, with no systematic review of sentiment or competitor recommendations.

Brand knowledge management

Ingredient evidence, SKUs, suitability limits and approved wording are not maintained consistently across site migrations, feeds and social content.

Optimization approach

Build a clear shopping journey and product pages, then use feed consistency, sentiment and competitor changes to guide content and channel activity. Review AI-referred net sales, supported by channel share.

Illustrative service plan

These modules illustrate how a service plan can be assembled. Actual workloads and delivery schedules depend on the agreed project scope.

On-site · Site development and architecture migration

Rebuild skin-type selection and product architecture

Organize collection, ingredient, product and bundle pages. Map URLs and redirects, review canonical tags, indexing and internal links, and preserve purchase measurement through migration.

Illustrative workloadMonth 1: one store restructuring or migration plan; monthly plans for 10 pages

On-site · Content optimization

Improve ingredient and skin-care product pages

Complete ingredient, usage, limitation, size, evidence and support information. Create skin-type and routine comparisons linked to collection and purchase pages.

Illustrative workloadMonthly: 8 product or collection page updates and 12 buying guides

Product data · Feed optimization

Align bundle, variant and product availability data

Check SKU/GTIN, bundle contents, variants, images, prices, inventory, delivery and returns. Keep Merchant Center feeds consistent with page markup.

Illustrative workloadMonthly: 20 SKU or bundle checks and 2 feed reviews

Off-site · Sources and consistency

Check ingredient, retail and creator information

Provide approved ingredient, specification and usage information to correct verifiable factual errors while respecting independent opinions and experiences.

Illustrative workload20 priority sources; follow up on 6 updates or collaborations each month

Brand knowledge management

Maintain ingredient and product-claim evidence

Manage ingredients, evidence levels, suitability, precautions, approved wording and information versions for website and creator use.

Illustrative workloadMonth 1: one knowledge library; maintain 12 SKU information packs each month

Customer sentiment monitoring

Monitor skin-type, ingredient and service discussions

Review agreed ingredient sites, retail reviews and public Reddit, X and Facebook discussions. Separate experiences, factual errors and complaints, with responses reviewed by the client.

Illustrative workloadWeekly sentiment summary and monthly review of recurring questions and content gaps

Competitor monitoring

Compare competitor propositions and selection visibility

Monitor competitor appearances, recommendation reasons, ingredient descriptions and product data in target AI answers. Turn findings into page, content and source updates.

Illustrative workload4 competing brands and 10 priority SKUs; weekly competitor review

Reddit / X / Facebook

Publish skin-type and care-selection content

Adapt approved guides into brand posts and community answers. Explain suitability and usage limits in context, and collect questions to improve content.

Illustrative workloadMonthly: 12 original posts and 8 community responses

Project responsibilities

Dageno team: SEO/GEO diagnostics, technical and content planning, source development, outreach, weekly progress updates and monthly reviews.
Client and collaborators: Product specialists review wording, e-commerce teams maintain product information and collaborators independently decide whether to use supplied materials.
Delivery and channel records: Track planning, production, launch, media outreach and publication separately. Count original content separately from adaptations for other platforms.

Metric definitions and measurement

Repeat monitoring using the agreed markets, languages and sampling method. Record citations and recommendations separately for each platform.

Complete month of Sep 2026, up US$7,000 from Nov 2025. Includes identifiable AI-referred orders after cancellations and refunds.

AI-referred share of net sales

Calculation: net sales from identifiable AI-referred orders divided by total store net sales for the same period. Use consistent deduplication and refund rules before and after.

Monthly comparison on a consistent basis	AI-referred net sales	Total store net sales	Share
Before (Nov 2025)	$2,000	$50,000	4%
After (Sep 2026)	$9,000	$60,000	15%

Up 11 percentage points. Values are in USD. Net sales are after discounts and returns, excluding taxes and shipping. Join and deduplicate AI-referred orders by store order ID. Track Google Search, unidentified sources and assisted touchpoints separately; product-card appearances alone do not establish a sale.

Illustrative measurement sources: Dageno shopping answers, product reviews, GA4 and selected store orders. Compare complete months in Nov 2025 and Sep 2026.

Study abroad admissions consulting · Service example

Connect application years, program requirements and deadlines with qualified consultations

An admissions consultancy serving Chinese applicants to undergraduate and master's programs in the United Kingdom, Australia and Canada.

Figures in this service example illustrate measurement methods. They do not represent actual customer results.

Illustrative metric · Qualified adviser appointments per month

38appointments

Bookings follow checks of applicant background and service eligibility. Completed initial consultations are recorded separately.

University and international education — Industry illustration; not a customer location or product.

GEO project scope

Target markets: Mainland China
Service period: Oct 2025–Jun 2026
Reference observation window: About 4 weeks
Illustrative AI platforms and search experiences: ChatGPTDeepSeek
Monitoring scope: 7 topics · 84 distinct prompts

Illustrative GEO monitoring metrics

Hypothetical comparison: before → after

AI visibility

7.6%20.4%

+12.8 percentage points

Share of monitored answers mentioning the target brand or a priority model

Brand website citation rate

3.1%11.2%

+8.1 percentage points

Share of monitored answers citing the brand website

Top-three recommendation rate

2.2%11.6%

+9.4 percentage points

Share of monitored answers placing the brand among the top three recommendations

Completed initial consultations per month

Adviser consultations completed after booking

Typical challenges

On-site · Technical SEO

Pages for old application years and programs are duplicated, with inconsistent canonical tags, indexing and links to current requirements.

On-site · Content coverage

Content emphasizes university introductions, with limited support for eligibility, costs and application deadlines.

Off-site · Sources and consistency

Directories, social posts and older guides cite outdated requirements that conflict with official information.

Brand knowledge management

Application year, program, applicant status and admission rounds lack consistent facts and update dates.

Optimization approach

Organize site architecture and content around applicant intent, current program information and deadlines. Use external source updates and content distribution to support adviser bookings.

Illustrative service plan

These modules illustrate how a service plan can be assembled. Actual workloads and delivery schedules depend on the agreed project scope.

On-site · Technical SEO

Organize application-year and program pages

Check indexing, duplication, canonical tags and internal links. Update or archive previous-year content and connect readers to current programs.

Illustrative workloadMonth 1: one content and technical audit; maintain 10 priority pages each month

On-site · Content optimization

Address program selection and application questions

Use official sources to explain degree choices, universities, eligibility, costs and timelines, with clear consultation paths.

Illustrative workloadMonthly: 10 articles and 6 priority program page updates

Off-site · Sources and consistency

Check official requirements and external consultancy information

Use official university requirements as the factual reference. Check program and service descriptions across directories, older guides and social content.

Illustrative workload15 priority sources; follow up on 5 updates each month

Brand knowledge management

Build application-year and program facts

Maintain deadlines, eligibility, fees, required documents and verification records, reviewed by advisers before website, social and consultation use.

Illustrative workloadMonth 1: one knowledge library; maintain 12 priority programs each month

Application content and video

Distribute deadline and application guidance through relevant channels

Adapt approved guides into Chinese social content and application videos, using channels relevant to applicants. Do not promise admission outcomes.

Illustrative workloadMonthly: 8 social posts and 2 explainer videos

Project responsibilities

Dageno team: SEO/GEO diagnostics, technical and content planning, source development, outreach, weekly progress updates and monthly reviews.
Client and collaborators: Advisers approve requirements and deadlines. Consultation operations records bookings and completed initial consultations.
Delivery and channel records: Track planning, production, launch, media outreach and publication separately. Count original content separately from adaptations for other platforms.

Metric definitions and measurement

Repeat monitoring using the agreed markets, languages and sampling method. Record citations and recommendations separately for each platform.

Bookings follow checks of applicant background and service eligibility. Completed initial consultations are recorded separately.

Illustrative measurement sources: Dageno answers, university requirement checks and booking systems

Dermatology and aesthetic medicine clinics · Service example

Clarify clinicians, suitability and risks to support appropriate initial consultations

A group of dermatology and aesthetic medicine clinics in Singapore, with assessment and treatment provided by licensed physicians.

Figures in this service example illustrate measurement methods. They do not represent actual customer results.

Illustrative metric · Attended AI-assisted consultations per month

49consultations

Reception confirms attendance and recorded AI touchpoints. These are assisted consultations, distinct from directly AI-referred visits.

Clinical consultation — Industry illustration; not a customer location or product.

GEO project scope

Target markets: Singapore
Service period: Dec 2025–Jul 2026
Reference observation window: About 5 weeks
Illustrative AI platforms and search experiences: ChatGPTGoogle AI Mode
Monitoring scope: 6 topics · 60 distinct prompts

Illustrative GEO monitoring metrics

Hypothetical comparison: before → after

AI visibility

5.2%14.8%

+9.6 percentage points

Share of monitored answers mentioning the target brand or a priority model

Brand website citation rate

1.6%8%

+6.4 percentage points

Share of monitored answers citing the brand website

Top-three recommendation rate

1%7.2%

+6.2 percentage points

Share of monitored answers placing the brand among the top three recommendations

Of these, identifiable directly AI-referred consultations

21 consultations

A subset of the 49 attended consultations; do not add the two counts

Typical challenges

On-site · Technical SEO

Clinician, location, procedure and booking pages are poorly connected, with inconsistent service information.

On-site · Content coverage

Suitability, risks and recovery information are mixed with promotional copy and lack clear professional review.

Off-site · Sources and consistency

Factual errors recur across local profiles, directories and reviews. Genuine complaints and incorrect information are not handled separately.

Brand knowledge management

Qualifications, clinic schedules, procedure limits and approved descriptions lack coordinated management.

Optimization approach

Prioritize accurate local profiles, professionally reviewed content and booking paths. Use appropriate outreach and social activity to support suitable consultations without broadening treatment claims.

Illustrative service plan

These modules illustrate how a service plan can be assembled. Actual workloads and delivery schedules depend on the agreed project scope.

On-site · Technical SEO

Connect clinic, clinician and procedure pages

Audit indexing, internal links, languages and booking journeys. Verify local business and service information.

Illustrative workloadMonth 1: one website and local-profile audit; monthly plans for 8 pages

On-site · Content optimization

Create physician-reviewed procedure explanations

Explain suitability, risks, recovery and first consultations, with clinic and booking links. This content supports rather than replaces an in-person assessment.

Illustrative workloadMonthly: 6 specialist articles and 4 procedure page updates

Off-site · Sources and consistency

Manage local profiles and factual corrections

Check clinic, clinician and procedure facts across priority business profiles and specialist directories. Handle factual corrections separately from genuine complaints.

Illustrative workloadReview 12 priority sources; maintain correction records monthly

Brand knowledge management

Maintain clinical and location facts

Standardize qualifications, schedules, suitability limits, risks and approved wording, with professional review by the clinic.

Illustrative workloadMonth 1: one knowledge library; monthly review of clinician and location information

Facebook / X and professional education

Distribute reviewed clinic content

Publish educational and location information on initial consultations, risks and suitability through relevant channels. The clinic handles genuine complaints.

Illustrative workloadMonthly: 8 social posts and one professionally reviewed educational article

Project responsibilities

Dageno team: SEO/GEO diagnostics, technical and content planning, source development, outreach, weekly progress updates and monthly reviews.
Client and collaborators: Physicians review medical content; the clinic handles complaints and risk disclosure; reception confirms referral sources and attendance.
Delivery and channel records: Track planning, production, launch, media outreach and publication separately. Count original content separately from adaptations for other platforms.

Metric definitions and measurement

Repeat monitoring using the agreed markets, languages and sampling method. Record citations and recommendations separately for each platform.

Reception confirms attendance and recorded AI touchpoints. These are assisted consultations, distinct from directly AI-referred visits.

Illustrative measurement sources: Dageno local answers, booking systems and reception source records

International logistics and freight forwarding · Service example

Help importers assess trade lanes, cargo and pricing before requesting a quote

A freight forwarder with an established Chinese website and customer base, adding English trade-lane pages and inquiry paths for overseas importers.

Figures in this service example illustrate measurement methods. They do not represent actual customer results.

Illustrative metric · Qualified AI-referred quote requests per month

42inquiries

Average over the final three months of the illustrative service period. Sales confirms enough lane and cargo information to quote, deduplicated by company requirement.

Container ports and international shipping — Industry illustration; not a customer location or product.

GEO project scope

Target markets: United StatesUnited KingdomGermany
Service period: Apr 2026–Oct 2026
Reference observation window: About 6 weeks
Illustrative AI platforms and search experiences: ChatGPT
Monitoring scope: 7 topics · 84 distinct prompts

Illustrative GEO monitoring metrics

Hypothetical comparison: before → after

AI visibility

3.8%16.2%

+12.4 percentage points

Share of monitored answers mentioning the target brand or a priority model

Brand website citation rate

1%8.8%

+7.8 percentage points

Share of monitored answers citing the brand website

Top-three recommendation rate

0.8%8.6%

+7.8 percentage points

Share of monitored answers placing the brand among the top three recommendations

Quote-request completeness

38% → 71%

Share of inquiries requiring no additional essential lane or cargo information

Semrush search traffic trend

View original screenshot

International logistics and freight forwarding: original Semrush traffic screenshot — Original Semrush reference image from the case attachment. Business figures in this service example are hypothetical; AI leads, sales and profit cannot be inferred from this chart. (Original Chinese interface retained.)

Typical challenges

On-site · Technical SEO

English trade-lane, service and inquiry pages lack clear architecture for search and AI discovery.

On-site · Content coverage

Trade lanes, cargo types, pricing and responsibilities are scattered across sales documents, with limited unbranded content coverage.

Off-site · Sources and consistency

Logistics directories, partners and trade media do not clearly describe current coverage and service limitations.

Brand knowledge management

Transit-time conditions, surcharges, excluded cargo and regional information lack a consistent version.

Optimization approach

Start with overseas importers' search and AI questions. Combine English-site technical SEO, trade-lane content, industry sources and B2B outreach to support quote-ready inquiries.

Illustrative service plan

These modules illustrate how a service plan can be assembled. Actual workloads and delivery schedules depend on the agreed project scope.

On-site · Technical SEO

Improve English trade-lane and service architecture

Check crawling, indexing, canonical tags, language relationships and internal links. Connect lanes, cargo, pricing and quote requests.

Illustrative workloadMonth 1: one technical audit; monthly plans for 8 priority pages

On-site · Content optimization

Build content around trade lanes and quoting questions

Create guides, comparisons and FAQs by transport mode, region, cargo and cost components, using approved information with conditions and effective dates.

Illustrative workloadMonthly: 8 articles and 6 priority trade-lane information updates

Off-site · Sources and consistency

Align logistics directory and partner information

Check company, lane and service coverage information across directories, partners and media. Prepare verifiable updates and outreach materials.

Illustrative workloadReview 20 priority sources; follow up with 6 each month

Brand knowledge management

Maintain trade-lane and pricing facts

Manage transit-time conditions, charges, trade terms, cargo restrictions and revision records for website, sales and communications use.

Illustrative workloadMonth 1: one knowledge library; review priority trade lanes twice monthly

PR and trade media

Distribute trade-lane and specialist service content

Prepare industry articles and outreach plans around route changes, pricing explanations and approved business information. Record outreach and publication separately.

Illustrative workload20–30 media targets and one outreach plan per month

LinkedIn / YouTube

Publish importer decision and process content

Adapt trade-lane and pricing guides into LinkedIn posts and process videos linked to relevant services and quote forms.

Illustrative workloadMonthly: 6 LinkedIn posts and one process video

Project responsibilities

Dageno team: SEO/GEO diagnostics, technical and content planning, source development, outreach, weekly progress updates and monthly reviews.
Client and collaborators: Operations and commercial teams approve lanes and prices. Sales assesses quote readiness and maintains source records.
Delivery and channel records: Track planning, production, launch, media outreach and publication separately. Count original content separately from adaptations for other platforms.

Metric definitions and measurement

Repeat monitoring using the agreed markets, languages and sampling method. Record citations and recommendations separately for each platform.

Average over the final three months of the illustrative service period. Sales confirms enough lane and cargo information to quote, deduplicated by company requirement.

Illustrative measurement sources: Dageno answers, English-site referrals and sales inquiry records

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Case Studies & Service Examples

Composite materials manufacturer for medical equipment

Business and AI performance

The original challenge

What we did

Structural reinforcement and construction materials provider

Business and AI performance

The original challenge

What we did

Connect product selection with qualified procurement inquiries

GEO project scope

Illustrative GEO monitoring metrics

Semrush search traffic trend

Typical challenges

On-site · Technical SEO

On-site · Content coverage

Off-site · Sources and consistency

Brand knowledge management

Optimization approach

Illustrative service plan

Manage catalog architecture and indexing at scale

Address substitute-product and business procurement intent

Align supplier, brand and trade directory information

Maintain SKU, substitution and delivery facts

Develop procurement and supply-chain outreach

Publish procurement and technical selection content

Help engineers identify substitute models, compatibility requirements and purchasing channels

GEO project scope

Illustrative GEO monitoring metrics

Typical challenges

On-site · Technical SEO

On-site · Content coverage

Off-site · Sources and consistency

Brand knowledge management

Optimization approach

Illustrative service plan

Improve part-number catalogs and accessible specifications

Create substitute-part and application selection content

Synchronize authorized distributor specifications

Maintain model identities and substitution relationships

Reach sources engineers use for research

Clarify lighting performance, operating conditions and installation to support project inquiries

GEO project scope

Illustrative GEO monitoring metrics

Semrush search traffic trend

Typical challenges

On-site · Technical SEO

On-site · Content coverage

Off-site · Sources and consistency

Brand knowledge management

Optimization approach

Illustrative service plan

Build regional pages and project resource paths

Address specification and project procurement questions

Align regional directories and channel information

Manage model, certification and regional facts

Plan regional outreach around project applications

Distribute project and installation content

CRM and growth management platform

Business and AI performance

The original challenge

What we did

Semrush search traffic trend

Cloud data infrastructure provider

Business and AI performance

The original challenge

What we did

Semrush search traffic trend

Help developers make their first successful call using current examples

GEO project scope

Illustrative GEO monitoring metrics

Typical challenges

On-site · Technical SEO

On-site · Content coverage

Off-site · Sources and consistency

Brand knowledge management

Optimization approach

Illustrative service plan

Improve documentation indexing and version relationships

Address API comparisons and integration questions