MyPhotoAI · pSEO case study

A free keyword research workflow for sizing a programmatic SEO surface

You do not need a paid keyword tool to plan a pSEO surface under three hundred slugs. This leaf documents the four-step workflow we use to size every engagement: a Search Console export from a comparable site if available, a Bing Webmaster export, an autosuggest scrape, and a manual long-tail expansion in a spreadsheet. The whole workflow costs zero dollars and takes about four hours per surface.

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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We sized this surface and the agents.alkenacode.dev surface using exactly the workflow described here, with zero paid tools. The slug list you see at /sitemap.xml is the output of step four for the MyPhotoAI engagement.

A free keyword research workflow for sizing a programmatic SEO surface

Step one: Search Console as the source of truth

If the client has an existing site, even a small one, Google Search Console is the highest-quality data source you will get. Export queries by impressions over ninety days, filter to queries with zero or one impression, and that set is your long-tail. Twenty to forty percent of those queries are reachable with a single new leaf each. Search Console under-reports queries with very low impression counts (under three), so the export underestimates the true tail by a factor of one and a half to two in our experience. The Google Search Central docs on Search Console explain the export format and the impression sampling.

Step two: Bing Webmaster Tools for the second-engine signal

Bing Webmaster Tools exposes a similar export with different sampling biases. Bing tends to surface query-string variations that Google's export elides, especially for B2B and developer-leaning topics. Combining the two exports and deduplicating on a normalized form (lowercase, strip punctuation, collapse whitespace) gives a list that is fifteen to thirty percent larger than Google alone. For surfaces with no existing site (a greenfield engagement), skip step one and start here; Bing will give you a usable baseline within twenty-four hours of site verification.

Steps three and four: autosuggest scrape and manual expansion

Step three is a polite autosuggest scrape: seed the Google and Bing suggest endpoints with the head term you are targeting, walk the suggestion tree two levels deep, and pull every result. Twenty-six head terms plus the alphabet produces six to eight hundred candidate phrases for a typical surface. Step four is a manual sit-down in a spreadsheet, scoring each candidate by intent (informational, transactional, navigational) and by proximity to the product. Anything below a five-out-of-ten on proximity gets cut. The remaining set is your slug list candidate. For this surface, the manual expansion produced thirty-six candidates; we shipped twenty-two.

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: site: search operator (Google Search Central)
  2. Google: creating helpful, reliable, people-first content (Google Search Central)
  3. Google: title link and meta description best practices (Google Search Central)
  4. Google: indexing overview (Google Search Central)
  5. Bing Webmaster Tools (Microsoft Bing)
  6. Yandex Webmaster (Yandex)
  7. Google: sitemaps overview (Google Search Central)
  8. Google: managing crawl budget for large sites (Google Search Central)
  9. web.dev: Lighthouse SEO audits (Chrome for Developers)
  10. Google Search Quality Rater Guidelines (PDF) (Google Search Central)
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