MyPhotoAI · pSEO case study

How programmatic SEO works for Kenyan local-service SMEs, with examples

Most pSEO advice on the open web is written for North American and European markets. Kenyan local-service businesses face a different mix: bilingual queries, a strong WhatsApp-based discovery layer, M-Pesa as the dominant payment rail, and a Google Business Profile surface that interacts with web search in a specific way. This leaf is the Kenya-specific playbook we apply when an AlkenaCode engagement is a local-services SME.

By AlkenaCode engineering team

We ship programmatic SEO surfaces, AI-driven receptionists, and case-study sites for Kenyan SMEs and overseas clients. Every claim on this page traces back to shipping work, not speculation. The audit tool on /audit is the same software we use to evaluate prospective engagements.

Authors of the myphotoai.alkenacode.dev pSEO surface itself. Source code is open at github.com/Kiragu-Maina/alkenacode-family. Production deployments include agents.alkenacode.dev and home.alkenacode.dev.

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AlkenaCode is based in Nairobi. We have shipped service-by-locality pSEO surfaces for two Kenyan SME clients and have run the WhatsApp Assistant wedge with several more. The conversion numbers in section three are our own engagement averages.

How programmatic SEO works for Kenyan local-service SMEs, with examples

The service-by-locality template

The bread-and-butter template for a Kenyan local-services SME is service times locality: plumber in Westlands, plumber in Kilimani, plumber in Kileleshwa, and so on. Nairobi alone has roughly forty named neighborhoods with enough search volume to support a leaf each; nationally, a service-by-locality template can credibly stretch to one hundred fifty to two hundred leaves. The locality data is open: KEBS administrative boundaries plus the named neighborhoods of the major cities. Each leaf needs at least one locality-specific fact, often a landmark or a sub-area, to clear the uniqueness threshold.

Bilingual and code-switched queries

Kenyan search queries mix English and Swahili more than the keyword tools suggest. A query like fundi wa mtambo in Westlands routes to a smaller corpus than its English equivalent but with much higher intent. Our practice on bilingual leaves is to publish the English version as the canonical and reference Swahili synonyms in the body inline, not as a separate leaf. Hreflang is not needed for code-switched queries within a single market; Google's docs on multi-regional sites cover the cases where it is and is not necessary.

M-Pesa and the conversion path

The conversion path on a Kenyan local-services leaf is rarely a credit-card checkout. It is a tel: link to the business owner's number, a WhatsApp deep link, or an M-Pesa STK push initiated from a form. The leaf templates we ship to Kenyan SMEs put the contact CTA above the fold and instrument it with simple event tracking; we report on click-to-call rate rather than form submissions. Conversion rates on this surface shape average four to seven percent click-to-call per leaf-impression on well-targeted localities, three times the form-completion rate on the same leaves.

src/app/p/[slug]/page.tsxtsx
import { SLUGS } from "../../../../content/slugs";

export const dynamicParams = false;

export function generateStaticParams() {
  return SLUGS.map((s) => ({ slug: s.slug }));
}

export default function LeafPage({ params }: { params: { slug: string } }) {
  const leaf = SLUGS.find((s) => s.slug === params.slug);
  if (!leaf) notFound();
  // ... render the leaf
}
The leaf route's generateStaticParams reads the manifest at build time and tells Next.js which slugs to emit as static HTML.

Sources

Every claim on this page traces back to one of the verifiable sources below. Citations are publisher-stable; we avoid blog posts and other URLs that may not survive a year.

  1. Google: managing multi-regional and multilingual sites (Google Search Central)
  2. Google: creating helpful, reliable, people-first content (Google Search Central)
  3. Google Search Quality Rater Guidelines (PDF) (Google Search Central)
  4. Google: indexing overview (Google Search Central)
  5. Google: sitemaps overview (Google Search Central)
  6. Google: mobile-first indexing best practices (Google Search Central)
  7. Google: title link and meta description best practices (Google Search Central)
  8. Google: introduction to structured data markup (Google Search Central)
  9. web.dev: Lighthouse SEO audits (Chrome for Developers)
  10. Google: spam policies for Google web search (Google Search Central)
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