00 · Self-applicationKAIS — the method applied to ourselves
The site you are reading is our first testing ground — verifiable live
We eat our own cooking
ProgrammeInternal application
Sector / activityKAIS self-application
Reported periodOngoing activity, no single measurement period
StatusInternal reference
Reported production and transparency indicators
No client performance indicator — this is a KAIS self-application reference.
Scope, means and other contextual information
4
barometers published, real data
3
languages · 40+ optimised pages
5
AI platforms tracked continuously
100%
public and transparent pricing
Initial situation
No distinct initial situation is stated; this is an internal KAIS implementation example.
KAIS intervention and reported observations
Check for yourself: our robots.txt explicitly welcomes every AI crawler, each page carries validated JSON-LD, and the 2026 Barometer publishes its full methodology — queries, platforms, and how the KVS is computed.
AI Search VisibilitySystematic JSON-LDPublic methodology
Measurement framework and verifiabilitySee evidence still to be documented
- Baseline / end dates
- Calendar start and end dates are not supplied in this case description.
- Measurement window
- Ongoing activity, no single measurement period
- Tested sample / prompt panel
- Internal reference; no single client or fixed external measurement panel.
- Published primary evidence
- No dated primary-data export or other supporting measurement evidence is attached to this case card.
- Evidence needed for verification
- KAIS site pages, dated Barometer versions and change history — to be provided, not claimed as attached.
- Attribution
- Results are reported alongside the interventions described; the causal contribution of each intervention is not isolated here.
KAIS LOCAL GROWTH
Local Growth results
Reputation, Google Business Profile, Maps, reactivation, repeat business and multi-client deployment.
01 · Client case · 90 daysSpecialist dental group — Singapore
Local Growth · Local reputation · Google Business Profile · Google Maps · Website booking · WhatsApp
Singapore
ProgrammeLocal Growth
Sector / activityDental clinic
Reported period90 days
StatusPublished case
Reported results
53 → 284
Google reviews in 90 days
4.1 → 4.8
average rating / 5
#12 → #2
Google Maps for the tracked local query
+63%
inbound calls from the Google profile
Initial situation
With only 53 reviews, a 4.1/5 rating and a #12 Google Maps position, the clinic was losing a significant share of local demand to better-rated and more visible competitors.
KAIS intervention and reported observations
We implemented an automated post-appointment journey covering review requests, direct access to the Google review path, centralised patient feedback and reputation monitoring. Within 90 days, the clinic gained 231 new reviews, improved its rating to 4.8/5, reached #2 on Google Maps for the tracked local query and recorded +63% inbound calls from its Google Business Profile. We also implemented website booking and direct WhatsApp communication for promotions and reminders, creating a faster and more consistent patient communication journey.
Singapore90 daysGoogle Business ProfileGoogle MapsPost-appointment automationWebsite bookingWhatsAppLocal reputation
Measurement framework and verifiabilitySee evidence still to be documented
- Baseline / end dates
- Calendar start and end dates are not supplied in this case description.
- Measurement window
- 90 days
- Tested sample / prompt panel
- Local Google Maps rankings are reported; exact queries, location and measurement procedure are not provided.
- Published primary evidence
- No dated primary-data export or other supporting measurement evidence is attached to this case card.
- Evidence needed for verification
- Dated Google Business Profile exports (reviews, calls), Maps rank screenshots with query and location, and dated baseline reports — to be supplied, not claimed as available.
- Attribution
- Results are reported alongside the interventions described; the causal contribution of each intervention is not isolated here.
02 · Client case · 120 daysNuffield Dental Raffles Clinic — Singapore
Local Growth · Local reputation · Google Business Profile · Google Maps · Web chat · WhatsApp Bot
Singapore
ProgrammeLocal Growth
Sector / activityDental clinic
Reported period120 days
StatusPublished case
Reported results
235 → 639
Google reviews in 120 days
4.4 → 4.9
average rating / 5
#27 → #5
Google Maps for the tracked local query
+71%
inbound calls from the Google profile
Initial situation
With 235 reviews, a 4.4/5 rating and a #27 Google Maps position, the clinic was losing a significant share of local demand to better-rated and more visible competitors.
KAIS intervention and reported observations
We deployed a reusable Local Growth model combining automated post-appointment review requests, direct access to the Google review path, centralised patient feedback, reputation monitoring, web chat and local listing synchronisation. Within 120 days, the clinic gained 404 new reviews, improved its rating to 4.9/5, reached #5 on Google Maps for the tracked local query and recorded +71% inbound calls from its Google Business Profile. We also implemented a WhatsApp Bot directly on the website to add a direct patient communication channel.
Singapore120 daysGoogle Business ProfileGoogle MapsReview automationWeb chatLocal listingsWhatsApp BotLocal reputation
Measurement framework and verifiabilitySee evidence still to be documented
- Baseline / end dates
- Calendar start and end dates are not supplied in this case description.
- Measurement window
- 120 days
- Tested sample / prompt panel
- Local Google Maps rankings are reported; exact queries, location and measurement procedure are not provided.
- Published primary evidence
- No dated primary-data export or other supporting measurement evidence is attached to this case card.
- Evidence needed for verification
- Dated Google Business Profile exports (reviews, calls), Maps rank screenshots with query and location, and dated baseline reports — to be supplied, not claimed as available.
- Attribution
- Results are reported alongside the interventions described; the causal contribution of each intervention is not isolated here.
03 · Client case · 90 daysNeighbourhood dental & medical clinic — Paris 16th arrondissement
Local Growth · Local reputation · Google Business Profile · Google Maps
Paris · France
ProgrammeLocal Growth
Sector / activityDental clinic
Reported period90 days
StatusPublished case
Reported results
28 → 184
Google reviews in 90 days
3.9 → 4.8
average rating / 5
#12 → #2
Google Maps for the tracked local query
+65%
inbound calls from the Google profile
Initial situation
With only 28 reviews, a 3.9/5 rating and a #12 Google Maps position, the clinic was losing a significant share of local demand to better-rated and more visible competitors.
KAIS intervention and reported observations
We implemented an automated post-appointment journey covering review requests, direct access to the Google review path, centralised patient feedback and reputation monitoring. Within 90 days, the clinic gained 156 new reviews, improved its rating to 4.8/5, reached #2 on Google Maps for the tracked local query and recorded +65% inbound calls from its Google Business Profile.
Paris 16th90 daysGoogle Business ProfileGoogle MapsPost-appointment automationLocal reputation
Measurement framework and verifiabilitySee evidence still to be documented
- Baseline / end dates
- Calendar start and end dates are not supplied in this case description.
- Measurement window
- 90 days
- Tested sample / prompt panel
- Local Google Maps rankings are reported; exact queries, location and measurement procedure are not provided.
- Published primary evidence
- No dated primary-data export or other supporting measurement evidence is attached to this case card.
- Evidence needed for verification
- Dated Google Business Profile exports (reviews, calls), Maps rank screenshots with query and location, and dated baseline reports — to be supplied, not claimed as available.
- Attribution
- Results are reported alongside the interventions described; the causal contribution of each intervention is not isolated here.
04 · Client case · 4 monthsNeighbourhood restaurant & local business — Paris 15th arrondissement
Local Growth · Customer reactivation · Reputation · Google Maps
Paris · France
ProgrammeLocal Growth
Sector / activityRestaurant / local business
Reported period4 months
StatusPublished case
Reported results
+310
new Google reviews recorded
+28%
repeat visits generated
Top 3
for 8 strategic local keywords
Scope, means and other contextual information
1,500
former customers targeted for reactivation
Initial situation
The restaurant had a largely dormant customer database, low repeat-visit frequency and limited visibility for neighbourhood searches such as “restaurant [area]”.
KAIS intervention and reported observations
Targeted SMS reactivation of 1,500 former customers, a short in-store QR-code journey, structured feedback collection and automated follow-up. After four months, the restaurant had recorded +310 Google reviews, generated +28% repeat visits through reactivation campaigns and reached the Top 3 Local Pack for 8 strategic keywords.
Paris 15th4 months1,500 reactivated customersSMSQR codeGoogle Business ProfileRetention
Measurement framework and verifiabilitySee evidence still to be documented
- Baseline / end dates
- Calendar start and end dates are not supplied in this case description.
- Measurement window
- 4 months
- Tested sample / prompt panel
- Eight local search terms are mentioned; the exact terms and locations are not provided.
- Published primary evidence
- No dated primary-data export or other supporting measurement evidence is attached to this case card.
- Evidence needed for verification
- Customer reactivation logs, review exports, repeat-visit calculations and local ranking snapshots — to be supplied, not claimed as available.
- Attribution
- Results are reported alongside the interventions described; the causal contribution of each intervention is not isolated here.
05 · Client case · 5 monthsB2B marketing agency — deployment across 40+ local SMBs
Local Growth · Multi-client deployment · Reputation · Search & Maps
France · B2B
ProgrammeLocal Growth
Sector / activityB2B marketing agency, SMB portfolio
Reported period5 months
StatusPublished case
Reported results
3.8 → 4.7
average Google rating
+112%
average Search / Maps impressions
88%
agency client retention rate
Scope, means and other contextual information
Initial situation
The agency wanted to offer tradespeople, garages, hair salons and other local SMB clients a standardised reputation-led local growth solution without rebuilding the system manually for every account.
KAIS intervention and reported observations
We created a reusable deployment model covering automated review requests, web chat and local listing synchronisation. Across the portfolio of 40+ SMBs, average results after 5 months showed Google ratings improving from 3.8 to 4.7/5, average Search and Maps impressions increasing by 112% per business profile, and agency client retention reaching 88%.
40+ SMBs5 monthsStandardised deploymentReputationGoogle SearchGoogle MapsB2B retention
Measurement framework and verifiabilitySee evidence still to be documented
- Baseline / end dates
- Calendar start and end dates are not supplied in this case description.
- Measurement window
- 5 months
- Tested sample / prompt panel
- A portfolio of 40+ SMBs is mentioned; the cohort list and aggregation method are not provided.
- Published primary evidence
- No dated primary-data export or other supporting measurement evidence is attached to this case card.
- Evidence needed for verification
- Client-cohort register, per-business Google Business Profile exports, impressions and retention calculations — to be supplied, not claimed as available.
- Attribution
- Results are reported alongside the interventions described; the causal contribution of each intervention is not isolated here.
AI SEARCH VISIBILITY · GEO · AEO · E-E-A-T
B2B, SaaS & Tech Enterprise results
Measuring visibility across conversational engines, structuring direct answers, deploying structured data and improving technical delivery so expertise is easier for AI systems to identify and use.
AI-01 · Client case · Business IntelligenceBusiness Intelligence Group (BIG)
International consulting & Business Intelligence · KaiZen AI Strategy (KAIS)
B2B · SaaS & Tech Enterprise
ProgrammeAI Search Visibility
Sector / activityBusiness intelligence
Reported periodNot specified
StatusPublished case
Reported results
25 → 75%
AI visibility score · 3x
+151%
traffic from AI engines
2x
revenue from the conversational segment
Scope, means and other contextual information
4
ecosystems tracked: ChatGPT, Perplexity, Claude, Gemini
Initial situation
BIG had an initial AI visibility score of only 25% and could not accurately identify traffic originating from ChatGPT, Perplexity, Claude and Gemini.
KAIS intervention and reported observations
User-prompt auditing and purchase-intent mapping, content restructuring with direct 2–3 sentence answers at the top of key pages, deployment of FAQPage markup and server-side HTML rendering optimisation. Documented results show the AI visibility score tripling from 25% to 75%, +151% traffic from AI engines, and 2x revenue on the customer segment originating from conversational engines.
Business Intelligence GroupGEOAEOE-E-A-TFAQPageServer-side HTMLPrompt mapping
Measurement framework and verifiabilitySee evidence still to be documented
- Baseline / end dates
- Calendar start and end dates are not supplied in this case description.
- Measurement window
- Not specified
- Tested sample / prompt panel
- Specific prompt wording, model versions, repeated runs and geographic settings are not itemised in the case card.
- Published primary evidence
- No dated primary-data export or other supporting measurement evidence is attached to this case card.
- Evidence needed for verification
- Dated prompt/response exports, model and source logs, analytics dashboards and the measurement methodology — to be supplied, not claimed as available.
- Attribution
- Results are reported alongside the interventions described; the causal contribution of each intervention is not isolated here.
AI-02 · Client case · LegalTech SaaSLegalTech SaaS platform
LegalTech SaaS · KaiZen AI Strategy (KAIS)
B2B · SaaS · LegalTech
ProgrammeAI Search Visibility
Sector / activityLegalTech SaaS
Reported period9 months
StatusPublished case
Reported results
0 → 39+
key prompts with dominant presence
+20%
demo bookings vs forecast
Scope, means and other contextual information
9 months
documented growth period
Initial situation
The platform had no presence at all in AI-generated answers when legal professionals searched for the best client portal solutions.
KAIS intervention and reported observations
Creation of a dedicated LLM information page, restructuring of content into question-and-answer formats that AI crawlers could extract easily, and priority targeting of high-intent Bottom-of-Funnel queries. Over nine months, the brand moved from zero presence to a dominant position across 39+ key prompts, with +20% demo bookings versus forecast and +19% organic sessions QoQ.
LegalTech SaaSLLM information pageGEOAEOBottom-of-FunnelGPTBotPerplexityBot
Measurement framework and verifiabilitySee evidence still to be documented
- Baseline / end dates
- Calendar start and end dates are not supplied in this case description.
- Measurement window
- 9 months
- Tested sample / prompt panel
- Specific prompt wording, model versions, repeated runs and geographic settings are not itemised in the case card.
- Published primary evidence
- No dated primary-data export or other supporting measurement evidence is attached to this case card.
- Evidence needed for verification
- Dated prompt/response exports, model and source logs, analytics dashboards and the measurement methodology — to be supplied, not claimed as available.
- Attribution
- Results are reported alongside the interventions described; the causal contribution of each intervention is not isolated here.
AI-03 · Client case · Enterprise B2B SoftwareEnterprise B2B Software
B2B Enterprise Software · KaiZen AI Strategy (KAIS)
B2B · Enterprise Software
ProgrammeAI Search Visibility
Sector / activityEnterprise B2B software
Reported period14 months
StatusPublished case
Reported results
49x
revenue from LLM referrals
Scope, means and other contextual information
14 months
documented growth period
CORE
Complete Organic Revenue Engine framework
Initial situation
The company was losing share of voice to newer competitors increasingly recommended by ChatGPT and Claude.
KAIS intervention and reported observations
Implementation of the CORE — Complete Organic Revenue Engine framework, encyclopedic restructuring of the knowledge base and reinforcement of topical authority to make the brand easier for conversational engines to identify, understand and recommend across strategic topics. Over 14 months, revenue from LLM referrals increased 49x and AI referral traffic increased 26x.
Enterprise SoftwareCORE FrameworkTopical AuthorityKnowledge BaseChatGPTClaudeLLM Revenue
Measurement framework and verifiabilitySee evidence still to be documented
- Baseline / end dates
- Calendar start and end dates are not supplied in this case description.
- Measurement window
- 14 months
- Tested sample / prompt panel
- Specific prompt wording, model versions, repeated runs and geographic settings are not itemised in the case card.
- Published primary evidence
- No dated primary-data export or other supporting measurement evidence is attached to this case card.
- Evidence needed for verification
- Dated prompt/response exports, model and source logs, analytics dashboards and the measurement methodology — to be supplied, not claimed as available.
- Attribution
- Results are reported alongside the interventions described; the causal contribution of each intervention is not isolated here.
AI-04 · Client case · Time Management SaaSTime Management SaaS — $30M+ ARR
B2B SaaS · KaiZen AI Strategy (KAIS)
SaaS · $30M+ ARR
ProgrammeAI Search Visibility
Sector / activityTime-management SaaS
Reported periodNot specified
StatusPublished case
Reported results
#1
rankings on key target queries
>75%
reduction in paid-search budget
Scope, means and other contextual information
E-E-A-T
expert content + deep topic clusters
Initial situation
The company was heavily dependent on paid acquisition campaigns and was losing visibility as AI-generated summaries captured a growing share of the search journey.
KAIS intervention and reported observations
Production of expert-written industry content to strengthen E-E-A-T, followed by deep thematic clusters targeting conversational search intent. Documented results include 7 million impressions, #1 rankings on key target queries, and a reduction of more than 75% in paid-search spend, offset by growth in AI and organic traffic.
B2B SaaS$30M+ ARRE-E-A-TTopical ClustersConversational SearchOrganic GrowthPaid Search Reduction
Measurement framework and verifiabilitySee evidence still to be documented
- Baseline / end dates
- Calendar start and end dates are not supplied in this case description.
- Measurement window
- Not specified
- Tested sample / prompt panel
- Specific prompt wording, model versions, repeated runs and geographic settings are not itemised in the case card.
- Published primary evidence
- No dated primary-data export or other supporting measurement evidence is attached to this case card.
- Evidence needed for verification
- Dated prompt/response exports, model and source logs, analytics dashboards and the measurement methodology — to be supplied, not claimed as available.
- Attribution
- Results are reported alongside the interventions described; the causal contribution of each intervention is not isolated here.
INDUSTRIAL B2B · TECHNICAL PRODUCTS · BANGKOK
AI Search results for technical B2B suppliers
Semantic product architecture, crawler-accessible HTML, Entity Profiles, expert documents and GEO alignment designed to turn technical catalogues into clearer sources for high-intent B2B queries.
AI-15 · Client case in progress · B2B Industrial SupplyB2B Ink Supplier Company — Bangkok
Technical products · B2B supply · GEO · AEO · E-E-A-T · KaiZen AI Strategy (KAIS)
Bangkok · Thailand · Ongoing
ProgrammeAI Search Visibility
Sector / activityIndustrial B2B supplier
Reported periodLast 4 months (qualified leads)
StatusOngoing
Reported results
≈0 → 18/month
average qualified B2B prospects over the last 4 months
Scope, means and other contextual information
4 months
current documented performance period
$0 increase
additional advertising budget
3 territories
high-intent query territories targeted
Initial situation
The company wanted to capture more qualified B2B demand through three specific query territories as a growing share of new prospects began discovering suppliers through ChatGPT answers. Qualified prospects attributable to this channel were previously close to zero.
KAIS intervention and reported observations
We rebuilt the website’s semantic foundations, with particular focus on the technical product catalogue. Product imagery, use-case descriptions and technical information were reorganised to make the offer easier to understand for both buyers and machines. We reduced JavaScript-dependent delivery and replaced it with cleaner, crawler-accessible HTML, developed Entity Profiles, aligned GEO content around complex high-intent questions and created expert documents to reinforce authority. Over the last four months, this ongoing programme has generated an average of 18 qualified B2B prospects per month, compared with close to zero previously, without increasing the advertising budget.
BangkokB2BIndustrial SupplyInk SupplierGEOAEOE-E-A-TEntity ProfilesSemantic CatalogueCrawler-Accessible HTMLExpert DocumentsQualified Leads
Measurement framework and verifiabilitySee evidence still to be documented
- Baseline / end dates
- Calendar start and end dates are not supplied in this case description.
- Measurement window
- Last 4 months (qualified leads)
- Tested sample / prompt panel
- Specific prompt wording, model versions, repeated runs and geographic settings are not itemised in the case card.
- Published primary evidence
- No dated primary-data export or other supporting measurement evidence is attached to this case card.
- Evidence needed for verification
- CRM lead exports, lead qualification criteria, acquisition channels, baseline and comparison dates — to be supplied, not claimed as available.
- Attribution
- Results are reported alongside the interventions described; the causal contribution of each intervention is not isolated here.
LOGISTICS · CARGO · INTERNATIONAL TRANSPORT
AI Search results for international transport
Service-page alignment, E-E-A-T, third-party authority and Question Territories designed to improve international discoverability for transport, cargo and market-specific logistics queries.
AI-14 · Client case · Logistics & International TransportCargo & International Transport Company — Bangkok
Cargo · International transport · GEO · AEO · E-E-A-T · KaiZen AI Strategy (KAIS)
Bangkok · Thailand
ProgrammeAI Search Visibility
Sector / activityInternational freight
Reported period60 days
StatusPublished case
Reported results
0 → 34+
average monthly AI mentions within 60 days
Scope, means and other contextual information
60 days
documented improvement period
Systematic
presence across tracked recommendation answers
ChatGPT + Google
tracked presence in ChatGPT and Google AI Overviews
Initial situation
Despite a strong local presence in traditional Google Search, the company was barely visible in ChatGPT and Perplexity suggestions for international transport services and related queries. The objective was to develop international visibility across selected target markets.
KAIS intervention and reported observations
We optimised service-page data and content around high-intent international transport searches, strengthened E-E-A-T signals to better demonstrate the company’s expertise, and reinforced third-party data sources commonly used by LLMs. We also defined strategic Question Territories aligned with the company’s commercial goals, service capabilities and target markets. Within 60 days, AI mentions increased from 0 to an average of 34+ per month, with systematic presence across the tracked recommendation answers in ChatGPT and Google AI Overviews for queries within the targeted territories.
BangkokThailandLogisticsCargoInternational TransportGEOAEOE-E-A-TQuestion TerritoriesThird-Party AuthorityChatGPTGoogle AI Overviews
Measurement framework and verifiabilitySee evidence still to be documented
- Baseline / end dates
- Calendar start and end dates are not supplied in this case description.
- Measurement window
- 60 days
- Tested sample / prompt panel
- Specific prompt wording, model versions, repeated runs and geographic settings are not itemised in the case card.
- Published primary evidence
- No dated primary-data export or other supporting measurement evidence is attached to this case card.
- Evidence needed for verification
- Dated prompt/response exports, model and source logs, analytics dashboards and the measurement methodology — to be supplied, not claimed as available.
- Attribution
- Results are reported alongside the interventions described; the causal contribution of each intervention is not isolated here.
E-COMMERCE · RETAIL · CONSUMER PRODUCTS
GEO results for product brands
Optimising recommendation signals, high-intent product micro-categories, third-party sources cited by LLMs and E-E-A-T to improve visibility in AI-generated buying recommendations.
AI-05 · Client case · Cosmetics & HaircareInternational cosmetics & haircare brand
Beauty & haircare products · KaiZen AI Strategy (KAIS)
E-Commerce · Retail · Consumer
ProgrammeAI Search Visibility
Sector / activityCosmetics / haircare
Reported period60 days
StatusPublished case
Reported results
86 → 282+
AI mentions in 60 days
3.3x
increase in AI mentions
Scope, means and other contextual information
60 days
documented growth period
Systematic
presence in AI buying recommendation lists
Initial situation
Despite leading in traditional Google search, the brand was nearly invisible in ChatGPT and Perplexity recommendations for specific product problems such as hair loss and frizz.
KAIS intervention and reported observations
Product-page alignment around high-intent micro-categories, optimisation of presence across third-party review and product-testing platforms frequently cited by LLMs, and reinforcement of E-E-A-T signals on the brand website. Within 60 days, AI mentions increased from 86 to 282+, a 3.3x increase, with systematic presence in AI-generated buying recommendation lists.
CosmeticsHaircareE-CommerceGEOE-E-A-TProduct Micro-CategoriesThird-Party Authority
Measurement framework and verifiabilitySee evidence still to be documented
- Baseline / end dates
- Calendar start and end dates are not supplied in this case description.
- Measurement window
- 60 days
- Tested sample / prompt panel
- Specific prompt wording, model versions, repeated runs and geographic settings are not itemised in the case card.
- Published primary evidence
- No dated primary-data export or other supporting measurement evidence is attached to this case card.
- Evidence needed for verification
- Dated prompt/response exports, model and source logs, analytics dashboards and the measurement methodology — to be supplied, not claimed as available.
- Attribution
- Results are reported alongside the interventions described; the causal contribution of each intervention is not isolated here.
AI-07 · Client case · Retail E-CommerceRetail E-Commerce Company
E-Commerce Distribution · KaiZen AI Strategy (KAIS)
E-Commerce · Retail
ProgrammeAI Search Visibility
Sector / activityRetail e-commerce
Reported period5 months
StatusPublished case
Reported results
6.5x
revenue generated by AI queries
Scope, means and other contextual information
5 months
documented growth period
3
engines tracked: ChatGPT, Perplexity, Claude
Product Data
LLM-readable product attributes
Initial situation
The company wanted to capture a growing share of shoppers using AI assistants as product search and recommendation engines.
KAIS intervention and reported observations
Category-page restructuring with structured comparison tables, followed by the integration of LLM-readable product entity attributes such as materials, use cases, characteristics and comparisons. Over 5 months, revenue generated by AI-driven queries from ChatGPT, Perplexity and Claude increased 6.5x.
RetailE-CommerceGEOProduct EntitiesComparison TablesChatGPTPerplexityClaude
Measurement framework and verifiabilitySee evidence still to be documented
- Baseline / end dates
- Calendar start and end dates are not supplied in this case description.
- Measurement window
- 5 months
- Tested sample / prompt panel
- Specific prompt wording, model versions, repeated runs and geographic settings are not itemised in the case card.
- Published primary evidence
- No dated primary-data export or other supporting measurement evidence is attached to this case card.
- Evidence needed for verification
- Dated prompt/response exports, model and source logs, analytics dashboards and the measurement methodology — to be supplied, not claimed as available.
- Attribution
- Results are reported alongside the interventions described; the causal contribution of each intervention is not isolated here.
AESTHETIC MEDICINE · SKINCARE · CLINICS
AI Search results for aesthetic medicine
Question-territory mapping, E-E-A-T, third-party authority and community signals designed to increase recommendation visibility for treatment, skincare and pathology-related queries.
AI-10 · Client case · Aesthetic MedicineSeoul Aesthetic Central — Hong Kong
Aesthetic medicine & skincare · KaiZen AI Strategy (KAIS)
Hong Kong · Aesthetic Clinic
ProgrammeAI Search Visibility
Sector / activityAesthetic medicine
Reported period90 days
StatusPublished case
Reported results
6 → 94+
AI mentions in 90 days
Scope, means and other contextual information
90 days
documented growth period
Systematic
presence across tracked AI recommendation answers
ChatGPT + Google
ChatGPT and Google AI Overviews presence documented
Initial situation
Despite leading in traditional Google search, Seoul Aesthetic Central was nearly invisible in ChatGPT and Perplexity recommendations for specific skincare concerns, treatments and pathology-related queries.
KAIS intervention and reported observations
We aligned treatment and service pages around high-intent micro-categories and pathology-related search intents, strengthened E-E-A-T signals on the clinic website, and improved presence across third-party review and specialist sources frequently cited by LLMs. We also mapped priority question territories aligned with the clinic’s growth objectives and deployed a Reddit authority strategy to reinforce relevant third-party discussion signals. Within 90 days, AI mentions increased from 6 to 94+, with systematic presence across tracked AI recommendation answers in ChatGPT and Google AI Overviews.
Hong KongAesthetic MedicineSkincareGEOAEOE-E-A-TQuestion TerritoriesThird-Party AuthorityRedditChatGPTGoogle AI Overviews
Measurement framework and verifiabilitySee evidence still to be documented
- Baseline / end dates
- Calendar start and end dates are not supplied in this case description.
- Measurement window
- 90 days
- Tested sample / prompt panel
- Specific prompt wording, model versions, repeated runs and geographic settings are not itemised in the case card.
- Published primary evidence
- No dated primary-data export or other supporting measurement evidence is attached to this case card.
- Evidence needed for verification
- Dated prompt/response exports, model and source logs, analytics dashboards and the measurement methodology — to be supplied, not claimed as available.
- Attribution
- Results are reported alongside the interventions described; the causal contribution of each intervention is not isolated here.
AI-11 · Client case · Aesthetic Medicine & Facial AestheticsDoctor Tim Face Clinic — Hong Kong
Facial aesthetics & specialist clinic · KaiZen AI Strategy (KAIS)
Hong Kong · Specialist Clinic
ProgrammeAI Search Visibility
Sector / activityAesthetic medicine
Reported period4 months
StatusPublished case
Reported results
+52%
AI Discoverability Score
Scope, means and other contextual information
4 months
documented improvement period
Structured Data
clinic, expertise and service information made machine-readable
Direct Intent
summaries aligned with priority specialties and target queries
Initial situation
Doctor Tim Face Clinic had a low discoverability score across LLM-generated answers and limited visibility for its priority specialties and targeted queries.
KAIS intervention and reported observations
We carried out a complete restructuring and strategic organisation of the clinic’s information and data, strengthened its online reputation and expert authority, and then integrated structured data and direct-intent summaries aligned with its priority specialties and target queries. Within 4 months, the clinic’s AI Discoverability Score increased by 52%.
Hong KongAesthetic MedicineGEOAEOE-E-A-TStructured DataExpert AuthorityDirect Intent Summaries
Measurement framework and verifiabilitySee evidence still to be documented
- Baseline / end dates
- Calendar start and end dates are not supplied in this case description.
- Measurement window
- 4 months
- Tested sample / prompt panel
- Specific prompt wording, model versions, repeated runs and geographic settings are not itemised in the case card.
- Published primary evidence
- No dated primary-data export or other supporting measurement evidence is attached to this case card.
- Evidence needed for verification
- Dated prompt/response exports, model and source logs, analytics dashboards and the measurement methodology — to be supplied, not claimed as available.
- Attribution
- Results are reported alongside the interventions described; the causal contribution of each intervention is not isolated here.
DENTAL · HEALTHCARE · SINGAPORE
AI Search results for dental healthcare
Entity restructuring, semantic website improvement, expert authority, structured data and citation-source development designed to make specialist clinics easier for LLMs to understand, trust and cite.
AI-13 · Client case · Dental HealthcareStraits Dental Group — Singapore
Dental healthcare · GEO · AEO · E-E-A-T · KaiZen AI Strategy (KAIS)
Singapore · Dental Group
ProgrammeAI Search Visibility
Sector / activityDental group
Reported period6 months
StatusPublished case
Reported results
+64%
AI Discoverability Score in 6 months
12 → 18 → 53
AI citations · first 45 days → next measurement → last month
Scope, means and other contextual information
6 months
documented improvement period
Authority
expert content · specialist sites · reputation · structured data
Initial situation
The clinic team wanted to increase recommendations in LLM-generated answers across clearly defined query territories aligned with its priority dental specialties.
KAIS intervention and reported observations
We strategically restructured and reorganised the clinic’s information and data to make it a more reliable citation source for LLMs, improved the website’s semantic structure, and developed expert content across relevant blogs and specialist websites. We also strengthened online reputation and expert authority, then integrated structured data and direct-intent summaries aligned with key specialties and target queries. Within six months, the clinic’s AI Discoverability Score increased by 64%. AI citations progressed from 12 during the first 45 days to 18 at the next measurement, reaching 53 in the last month.
SingaporeDental HealthcareGEOAEOE-E-A-TSemantic StructureExpert ContentSpecialist WebsitesStructured DataDirect Intent SummariesAI Citations
Measurement framework and verifiabilitySee evidence still to be documented
- Baseline / end dates
- Calendar start and end dates are not supplied in this case description.
- Measurement window
- 6 months
- Tested sample / prompt panel
- Specific prompt wording, model versions, repeated runs and geographic settings are not itemised in the case card.
- Published primary evidence
- No dated primary-data export or other supporting measurement evidence is attached to this case card.
- Evidence needed for verification
- Dated prompt/response exports, model and source logs, analytics dashboards and the measurement methodology — to be supplied, not claimed as available.
- Attribution
- Results are reported alongside the interventions described; the causal contribution of each intervention is not isolated here.
FINTECH · PAYMENT INFRASTRUCTURE
GEO results for financial platforms
Technical accessibility, server-side rendering, structured data and direct intent summaries designed to improve Fintech discoverability in AI-generated answers.
AI-06 · Client case · FintechZamp
Fintech / Payment Infrastructure · KaiZen AI Strategy (KAIS)
Fintech · Payment Infrastructure
ProgrammeAI Search Visibility
Sector / activityFinTech / payments
Reported period4 weeks
StatusPublished case
Reported results
+22%
AI Discoverability Score
Scope, means and other contextual information
4 weeks
documented improvement period
Server HTML
simplified rendering for AI crawling
Structured Data
structured markup + direct intent summaries
Initial situation
Zamp had a low discoverability score across AI-synthesised answers, limiting its ability to be identified and cited for relevant queries.
KAIS intervention and reported observations
Removal of client-side JavaScript-dependent rendering in favour of server-rendered HTML to improve accessibility for AI crawlers, followed by the integration of structured data and direct intent summaries. In just 4 weeks, the AI Discoverability Score increased by 22%.
ZampFintechPayment InfrastructureServer-side HTMLStructured DataAI DiscoverabilityGEO
Measurement framework and verifiabilitySee evidence still to be documented
- Baseline / end dates
- Calendar start and end dates are not supplied in this case description.
- Measurement window
- 4 weeks
- Tested sample / prompt panel
- Specific prompt wording, model versions, repeated runs and geographic settings are not itemised in the case card.
- Published primary evidence
- No dated primary-data export or other supporting measurement evidence is attached to this case card.
- Evidence needed for verification
- Dated prompt/response exports, model and source logs, analytics dashboards and the measurement methodology — to be supplied, not claimed as available.
- Attribution
- Results are reported alongside the interventions described; the causal contribution of each intervention is not isolated here.
AI-08 · Client case · Consumer FinTech SaaSConsumer FinTech SaaS Application
Consumer financial services · KaiZen AI Strategy (KAIS)
FinTech · Consumer SaaS
ProgrammeAI Search Visibility
Sector / activityConsumer FinTech
Reported period6 months
StatusPublished case
Scope, means and other contextual information
6 months
documented growth period
AEO
comparison matrices + citable market studies
Initial situation
The application wanted to capture users asking AI assistants high-intent comparison questions such as “What is the best alternative to [Competitor]?”
KAIS intervention and reported observations
Deployment of an AEO strategy based on neutral, factual comparison matrices, supported by the publication of citable market-data studies. Over 6 months, LLM-driven conversions increased 8x and AI referral traffic increased 25x.
FinTechConsumer SaaSAEOComparison MatricesMarket DataLLM ConversionsAI Referral Traffic
Measurement framework and verifiabilitySee evidence still to be documented
- Baseline / end dates
- Calendar start and end dates are not supplied in this case description.
- Measurement window
- 6 months
- Tested sample / prompt panel
- Specific prompt wording, model versions, repeated runs and geographic settings are not itemised in the case card.
- Published primary evidence
- No dated primary-data export or other supporting measurement evidence is attached to this case card.
- Evidence needed for verification
- Dated prompt/response exports, model and source logs, analytics dashboards and the measurement methodology — to be supplied, not claimed as available.
- Attribution
- Results are reported alongside the interventions described; the causal contribution of each intervention is not isolated here.
INSURANCE · FINANCIAL SERVICES
GEO results for financial services
Optimising trust signals, entity profiles and content to capture complex local and regional queries handled by conversational search engines.
AI-12 · Client case · Financial ServicesFinancial Services Firm — Luxembourg
Financial services · GEO · AEO · E-E-A-T · KaiZen AI Strategy (KAIS)
Luxembourg · Financial Services
ProgrammeAI Search Visibility
Sector / activityFinancial services
Reported periodLast 6 months (qualified leads)
StatusPublished case
Reported results
27/month
additional qualified prospects · average over the last 6 months
Scope, means and other contextual information
6 months
documented recurring performance period
$0
additional advertising spend
Authority
expert documents · Reddit citations · PR development
Initial situation
The firm wanted to capture more qualified demand from complex financial queries through LLMs without increasing advertising spend.
KAIS intervention and reported observations
We optimised local trust signals and entity profiles, then aligned GEO content around complex, high-intent financial queries. The programme also developed expert documents and citable resources, strengthened authority through relevant Reddit citations and discussions, and expanded digital PR and earned-media signals. Over the last 6 months, the programme has generated an average of 27 additional qualified prospects per month, with no additional advertising spend.
LuxembourgFinancial ServicesGEOAEOE-E-A-TEntity ProfilesExpert DocumentsRedditDigital PRQualified Prospects
Measurement framework and verifiabilitySee evidence still to be documented
- Baseline / end dates
- Calendar start and end dates are not supplied in this case description.
- Measurement window
- Last 6 months (qualified leads)
- Tested sample / prompt panel
- Specific prompt wording, model versions, repeated runs and geographic settings are not itemised in the case card.
- Published primary evidence
- No dated primary-data export or other supporting measurement evidence is attached to this case card.
- Evidence needed for verification
- CRM lead exports, lead qualification criteria, acquisition channels, baseline and comparison dates — to be supplied, not claimed as available.
- Attribution
- Results are reported alongside the interventions described; the causal contribution of each intervention is not isolated here.
AI-09 · Client case · Insurance & Financial ServicesInsurance Broker & Financial Services Firm
B2B / B2C Insurance · KaiZen AI Strategy (KAIS)
Insurance · Financial Services
ProgrammeAI Search Visibility
Sector / activityInsurance / finance
Reported periodNot specified
StatusPublished case
Reported results
+44
additional qualified prospects
Scope, means and other contextual information
$0
additional advertising spend
GEO
performance-led optimisation
Local + regional
search intent targeted
Initial situation
The broker wanted to capture more local and regional demand from complex queries handled by Bing Copilot and ChatGPT without increasing advertising spend.
KAIS intervention and reported observations
Optimisation of local trust signals and entity profiles, followed by a performance-led GEO content alignment designed to answer complex, high-intent queries more effectively. The programme generated 44 additional qualified prospects with no additional advertising spend.
InsuranceFinancial ServicesGEOEntity ProfilesTrust SignalsChatGPTBing CopilotQualified Leads
Measurement framework and verifiabilitySee evidence still to be documented
- Baseline / end dates
- Calendar start and end dates are not supplied in this case description.
- Measurement window
- Not specified
- Tested sample / prompt panel
- Specific prompt wording, model versions, repeated runs and geographic settings are not itemised in the case card.
- Published primary evidence
- No dated primary-data export or other supporting measurement evidence is attached to this case card.
- Evidence needed for verification
- CRM lead exports, lead qualification criteria, acquisition channels, baseline and comparison dates — to be supplied, not claimed as available.
- Attribution
- Results are reported alongside the interventions described; the causal contribution of each intervention is not isolated here.
- Methodological clarification
- The time period to which the 44 additional qualified leads refer is not specified.