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Case 09 · B2B fintech · white-label credit platforms · Kenya · 7 weeks

From 35 to 259 citations in seven weeks: how CodHob took hold in AI answers in Kenya's credit platform market

CodHob · Kenya

CodHob started AI visibility from zero in April 2026. In seven weeks its domain grew from 35 to 259 citations across five AI engines, second in Kenya's credit platform niche.


Engines lifted

  • ChatGPT
  • Perplexity
  • Yandex
  • Gemini
  • Google AI Overviews

Before · April 2026 → After · August 10, 2026

Before · April 2026

0 citations

Neither ChatGPT, nor Perplexity, nor Yandex knew that CodHob existed in Kenya's credit platform market.

After · August 10, 2026

259 259 citations

The second domain in the niche by citations after LinkedIn, ahead of all competing vendors.


The numbers in detail

What moved — CodHob


35 → 259

Citations across 5 AI engines

Over seven weeks, June 23 to August 10, 2026.

4.5×

Growth on comparable engines

35 → 159 excluding Gemini and Google AI Overviews, added to the panel in August.

21.4% → 54.8%

Decision stage of the funnel

Share of decision-stage queries whose answer links to CodHob.


#2

Position in the niche

Behind LinkedIn; first among product domains excluding UGC platforms.

15 → 105

#1 positions for own URLs

Growth in top positions in cited results over the same period.


When CodHob, a Singapore-based vendor of white-label credit platforms, launched its AI visibility program in April 2026, it had zero citations in AI answers. Neither ChatGPT, nor Perplexity, nor Yandex knew such a player existed in the Kenyan market.

By June 23 the situation had changed. 35 links to codhob.sg and third place among the niche's domains is a rare case in B2B fintech where a brand breaks into AI answers from zero in two months. That was the first milestone.

What follows is a case about what happens when a breakthrough has to become a system. Here is how over the next seven weeks the domain grew from 35 to 259 citations, passed all vendor competitors, and became second in the niche after LinkedIn.


Section 01

Where we started

CodHob is a platform for launching complex technology products under your own brand. Its CRYSTAMO product targets the Kenyan market. The site was built on Tilda. That is good enough for a quick content start, but the platform has a ceiling on E-E-A-T signals, the very signals AI engines rely on when choosing sources for an answer.

The client's task was specific: when a user asks AI about a credit platform in Kenya, CodHob and its expert content should appear in the answer. Not a one-off mention, but measurable, growing dynamics that decision-makers inside the company and investors can both understand.

By April CodHob had neither an AEO program nor regular funnel monitoring. The starting point was zero.


Section 02

How we measured: two layers of signal

Monitoring rested on two metrics that grow at different speeds and should not be confused.

  • Citation is when an AI engine gives a link to a specific URL in its answer.
  • Mention is when the brand is simply named in the text, without a link.

The first is easier to grow with content. The second requires the brand name to settle in the model's "memory" as a recognizable source.

We measured across a four-stage funnel (Awareness, Evaluation, Consideration, Decision) and 160 queries in the Kenyan B2B fintech market. By August the panel was expanded from three AI engines to five: Gemini and Google AI Overviews were added to the already tracked ChatGPT, Perplexity, and Yandex.


Section 03

What we did: content for specific intents

Publications went out on three platforms: the site's /news/ section, LinkedIn, and Medium. After the June measurement came a wave of publications on June 30 and a piece on data migration on July 8. Some of these URLs entered AI citations for the first time in the August snapshot.

We wrote content not "about everything" but for specific decision stages: implementation risks, key platform features, the deployment process, regulatory compliance, and launch readiness testing. That mattered, because general introductory articles about what a credit platform is were almost never cited.


Section 04

Result: 35 to 259

Over seven weeks, from June 23 to August 10, total citations of codhob.sg across five AI engines grew from 35 to 259.

Platform Jun 23 Aug 10
ChatGPT 0 36
Perplexity 7 79
Yandex 28 44
Gemini not in panel 21
Google AI Overviews not in panel 79
Total 35 259

The number of pages from results grew from 9 to 16, and the number of #1 positions for the site's own URLs grew from 15 to 105. In the overview block the site became one of the sources for 47 of 158 queries, about 30% coverage.


Section 05

An honest count: not all growth was organic

Here the case has a fork that would have been easy to skip, but we deliberately count both figures.

Of the jump from 35 to 259, about a hundred citations came from the new measurement channels, Gemini and Google AI Overviews, which were not in the June panel. If we remove that effect and compare the same three AI engines that were measured in June, growth is 35 to 159, a factor of 4.5. That is the figure worth building forecasts on, and it does not depend on how many new panels get added to the measurement.


Section 06

Funnel: growth is strongest at the bottom

The most telling change is not even the total number of citations but where they appeared.

Cluster Jun 23 Aug 10
Awareness 9.8% 36.6%
Evaluation 18.4% 39.5%
Consideration 15.4% 48.7%
Decision 21.4% 54.8%

Decision queries look like "is the platform ready to launch," "go-live," and "onboarding." At this stage the user is already choosing a contractor, not studying the market in general. More than half of such queries now return an answer with a link to CodHob. That is the effect of content on implementation risks, deployment, and launch readiness, the topics that collected the most citations.

/news/ section page Citations
Risks and problems in credit platform deployment 43
Key features of a credit platform 37
Credit platform deployment and launch 32
Go-live readiness testing 27
Regulatory compliance 25
Loan processing problems 20
When to commit to a credit platform 18
How to evaluate credit platform readiness 12

The pattern is simple: materials on risks, features, deployment, go-live, and compliance win. They are specific, factual, and tied to a decision. General overview articles almost never make it into citations.


Section 07

Competitive field

As of August 10, CodHob is the second domain in the niche by citations, behind only LinkedIn.

Domain Citations Role
linkedin.com 310 UGC, first place
codhob.sg 259 our domain, #2
youtube.com 134 UGC
loanpro.io 73 vendor
hesfintech.com 56 vendor

If we remove the sites with user-generated content, LinkedIn and YouTube, CodHob is first among product domains in the niche, ahead of specialized credit platform vendors.


Section 08

Where growth has not happened yet

The case has a weak spot, and it is worth stating too. The site link appears in answers often, but the brand name is rarely spoken.

Platform Queries with a brand mention
Gemini 8.8% (14 of 160)
ChatGPT 6.9% (11 of 160)
Google AI Overviews 1.3% (2 of 158)
Yandex 0.6% (1 of 160)
Perplexity 0% (0 of 160)

Perplexity is the platform that cites CodHob URLs most willingly (79 citations) but almost never names the brand. That is the next point to work on. Citing a URL and the model recognizing the brand are different layers, and the second grows more slowly than the first.


Section 09

What this means

Three conclusions worth taking from seven weeks of work with CodHob.

  • First, citation growth is not linear and depends on the coverage of the measurement panel. Compare on equivalent platforms, otherwise it is easy to pass off an expanded methodology as organic growth.
  • Second, content tied to a specific decision stage, such as risks, deployment, and go-live, works better than general overview material and moves the bottom of the funnel the most, where customers ready to buy are.
  • Third, citing a URL and mentioning the brand by name are two separate metrics that grow at different speeds. For CodHob the second is now the next growth point.

Section 10

FAQ

Q: How much did CodHob's AI citations grow, and over what period?

A: Total citations of codhob.sg across five AI engines grew from 35 to 259 in seven weeks, from June 23 to August 10, 2026.

Q: How much of that growth was organic?

A: About a hundred citations came from two new measurement channels, Gemini and Google AI Overviews, which were not in the June panel. On the same three engines measured in June, growth is 35 to 159, a factor of 4.5. That is the figure to use for forecasts.

Q: Which content got cited the most?

A: Specific, factual materials tied to a decision: implementation risks (43 citations), key platform features (37), deployment and launch (32), go-live readiness testing (27), and regulatory compliance (25). General overview articles almost never made it into citations.

Q: Where in the funnel did growth appear?

A: Growth was strongest at the bottom. The Decision cluster rose from 21.4% to 54.8%, so more than half of Decision queries now return an answer with a link to CodHob.

Q: Where does CodHob stand against competitors?

A: As of August 10, CodHob is second in the niche with 259 citations, behind only LinkedIn (310). If the UGC sites LinkedIn and YouTube are excluded, CodHob is first among product domains, ahead of specialized credit platform vendors.

Q: Do AI engines name the CodHob brand, or only link to the site?

A: Mostly they only link. Brand mentions appear in 8.8% of Gemini queries, 6.9% of ChatGPT, 1.3% of Google AI Overviews, 0.6% of Yandex, and 0% of Perplexity. Perplexity cites CodHob URLs most often (79 citations) but never names the brand. Citing a URL and recognizing a brand are different layers.


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