Programmatic SEO Case Study: From 67 to 2100 Monthly Signups

When this client came to us, they had a great product but no scalable way to get it in front of users.

In just 10 months, we helped them grow from 67 to over 2,100 monthly signups using a fully automated programmatic SEO engine.

This case study breaks down exactly how we did it. 👇

Client Overview

The client is an Al image generator that helps creators and marketers AI images for different purposes and platforms without design knowledge.

Providing high-quality, customizable image templates for various use-cases, their simple creation process helps any business create 100s of visuals in no time.

With a strong product in hand but limited organic visibility, they approached us to scale their growth through a scalable and data-driven SEO strategy.

The Challenge

Before partnering with us, the client was seeing just 67 signups per month.

Despite a compelling tool and a solid product-market fit, they lacked:

visibility for long-tail search queries,
had minimal indexed pages and
lacked a programmatic strategy to scale content.

Their existing SEO content strategy relied on general blog posts and a handful of landing pages that had the potential to rank for intent-rich, long-tail keywords, which hadn’t been used completely.

Their growth was bottlenecked by:

Inconsistent and low organic traffic
Low discoverability for long-tail keywords related to AI image niches (e.g., “free ai image generator”, “cartoon ai image generator”)
No dynamic content generation engine
Underutilized blog content and no scalable content strategy in place

Before we started working on SEO execution:

👉 13 total keywords they ranked for
👉 0 keywords they ranked for in the top 10 results
👉 772 monthly search impressions
👉 102 monthly organic search clicks
👉 67 monthly signup conversions

They were just at the start.

So, we decided to help them grow their user base using proven programmatic SEO tips that we previously tested on our internal projects.

The Results

Overall, the results over 6 months from implementing the programmatic SEO strategy have been impressive:

Conversions:

👉 Within 10 months, signups exploded from 67/month to over 2,100/month (a 3,035% increase in monthly signup conversions)

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👉 Peaked at 571 unique users in a single week (Jan 20, 2025)

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👉 11k+ total signups added by Jan 2025

👉 Increased from 10.4% to 24.81% “from visitors to signups” average CR. The monthly conversion rate from visitor to trial held steady above 23% in the last 3 months

Traffic:

👉 Monthly organic traffic grew by 850% (from 102 to 8.5k)

👉 220.65% organic traffic growth in Q1 2025(17.7k) compared to Q4 2024(5.52k).

👉 300+ unique daily organic clicks on average

Keyword rankings:

👉 5,742+ organic keywords the website ranks for

👉 305+ organic keywords on the first page

👉 42+ organic keywords in the top 3 positions

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The Strategy: Scalable SEO Through Automation

We identified programmatic SEO as the ideal growth channel for the client with lots of potential within the niche.

As a programmatic SEO agency, we developed and deployed a comprehensive programmatic SEO strategy designed to attract their ICP and convert and scale their growth.

Here are the core programmatic SEO tools we’ve used in our tech stack to make these efforts happen:

Ahrefs, Keywords Everywhere, and Google Keyword Planner for keyword research and mapping
WordPress as a CMS
Spreadsheet for collecting data and creating content related to pages
WP All Import for automating the publishing of huge data in one batch
Google Analytics, Microsoft Clarity and PostHog for tracking the performance

1. Keyword Research & Intent Mapping

Here’s how we executed the strategy step by step.

Step 1. Our process began with scraping and auditing their existing library of use-cases and templates to identify naming conventions, popular product categories, and usage scenarios.

Step 2. Based on it, we identified thousands of long-tail, high-intent keywords with commercial relevance and different modifiers, such as:

“free ai image generator”
“ai image generator for real estate”
“cartoon ai image generator”

Let's take a look at some example pages in this area, and how much organic traffic they generate each month:

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Keyword/clusters example	Monthly organic traffic
ai image generator for ecommerce	7,000
ai image generator for designers	5,000
ai image generator for marketers	3,000

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Only these three keywords have over 15k searches/month.

But we haven’t focused on them from the start - they were one of our long-term goals.

To rank for each of them, we focused on the specific long-tail keywords targeting each of those clusters.

Ultimately, ranking for these keywords strategically helped us surpass big players like Canva, Kittl, which are excelling with their programmatic SEO pages.

Step 3. To get a new dimension for producing tons of specific pages, we built a keyword matrix in Google Sheets with variables like object type, format, orientation, use case, and modifiers (e.g. "free", "realistic", "anime")

Step 4. We cross-referenced this data with Google Autocomplete, People Also Ask, and competitors’ indexed pages to expand the list and cover as much queries as possible.

Then, we clustered these keywords by group, search intent, and search volume.

These search terms had low competition, high buying intent, and clear alignment with the client’s product offering.

So the next step was to create a content plan mapped to dynamic landing page templates, each targeting a specific keyword cluster.

2. Template Design & Content Automation

Firstly, we designed a modular and SEO-optimized landing page template in WordPress that could be reused across thousands of variations.

But one type of page wasn’t enough. We needed to build dynamic templates for pages that could be populated with image categories, device types, and usage intents.

The structure within all those pages was engineered for both search engine crawlability and user conversion.

The idea for these pages was to have dynamically populated meta titles, headers, alt text, and content with keyword variations, while ensuring they aligned with UX best practices.

That’s why we needed a logic on how that dynamic content will be created and automated.

3. Automated Content Generation

These pages were crafted in WordPress, enabling flexible content blocks and schema integration, which was a great start.

So, we needed to design the logic for each landing page to populate with keyword-specific elements from the matrix automatically:

Auto-generated H1 and Meta Titles: These dynamically pulled in the primary keyword and modifier (e.g., “Free Cartoon AI Image Generator – Create in Seconds”).
Intro Paragraph: A short, engaging block explaining the use case and benefits of that specific image type, generated with conditional logic based on category.
Mockup Carousel Block: Pulled images and templates from the clients database that matched the keyword category.
Primary CTA: Positioned above the fold (“Start Creating for Free”) with a secondary soft CTA (“Use this tool”).
Alt Text & Structured Data: Each image had alt text populated based on the keyword and page type, while schema markup (Product, ImageObject) helped with enhanced search appearance.

Based on this template, we designed it to auto-instrate meta titles, descriptions, FAQs, and CTAs based on keyword intent.

Once we sorted everything, the next step was publishing the pages and releasing the batches.

4. Dynamic Page Publishment with WP All Import

Using WP All Import, we built a repeatable system to launch fully-optimized landing pages directly from our keyword matrix spreadsheet. Here’s how we did it:

Step 1: Keyword Matrix Prep - In Google Sheets, each row was a single landing page. Columns included page title, URL slug, meta description, H1, intro paragraph, image type, image file path, alt text, and CTA variations.
Step 2: Custom Fields Mapping - In WordPress, we created custom fields for each element of the landing page using ACF (Advanced Custom Fields). These fields were embedded into the template using shortcodes.
Step 3: Import Setup - In WP All Import, we connected the spreadsheet (exported as CSV) and mapped each column to its respective custom field or shortcode placeholder.
Step 4: URL & Metadata - We configured WP All Import to auto-generate clean, SEO-friendly URLs, set each page’s title tag and meta description, and assign it to the correct page.
Step 5: Image Handling - Our spreadsheet included image URLs that were imported, resized, and linked to the appropriate alt text and schema block.
Step 6: Scheduling & Deployment - We ran batch imports in groups of 100–200, QA’d the outputs in a staging environment, and pushed them live in weekly sprints.

This approach allowed us to launch over 15k+ pages in less than 90 days. Each page was:

Uniquely targeting a specific long-tail keyword
Fully SEO-optimized
Structured for speed and UX
Easy to update later via batch CSV re-imports

Having Screenshots and previews
Supported with Schema markups
Having FAQs and internal links

To help these pages get discovered by search engines and index, and grow faster, we needed to make sure to create the proper internal linking strategy.

5. Internal Linking Strategy

To ensure efficient crawlability and distribute link authority evenly across the new programmatic pages, we implemented a hub-and-spoke internal linking architecture.

Hubs: These were high-value category pages (e.g., “for Marketers”, “for Ecommerce”) that acted as central navigation points.
Spokes: Each hub got linked to its relevant child pages (e.g., “Free Cartoon AI Image Generator”, “AI Image Generator for Real Estate”, etc.).
Cross-Linking: Pages within the same category dynamically linked to 5-10 related pages via a “Related pages” section using keyword and category logic.
Footer Links & Breadcrumbs: We used breadcrumbs to reinforce hierarchy and added footer links to the top-performing hubs to concentrate authority further.

This strategy helped Google index new pages faster, kept users on-site longer through suggested navigation, and maximized the flow of PageRank across the programmatic stack.

So what were the results?