Shopify SEO Agent: Automating Fixes and Blog Posts Safely

A Shopify SEO agent is software that handles the repeatable parts of search optimization on your store, from metadata fixes to drafting blog posts, and hands them to you for approval. Some SEO work is mechanical and suits automation well. Some of it is judgment, and no tool should touch it.

This article separates the two, explains how to find pages that are close to ranking, and gives you a checklist for approving AI-written content without publishing something thin or wrong.

What is mechanical enough to automate

On a typical Shopify store, a large share of SEO work is repetitive. Hundreds of products need titles, meta descriptions, and alt text. Blog posts need internal links. Pages need structured data. Nobody enjoys this work, and it rarely gets done consistently.

That is what an agent is good at.

Titles and meta descriptions. Rewriting them to match what the page is actually about and what searchers type.
Image alt text. Describing images accurately across a catalog.
Internal links. Connecting blog posts, collections, and products so related pages support each other.
Schema markup. Adding structured data such as Article or Product markup consistently.
Striking-distance pages. Finding pages that already earn impressions and are close to page one, then improving them.

What is not

Other parts of SEO are not tasks. They are strategy.

Positioning. Deciding which searchers you want, and which you would rather lose, is a business decision.
Original expertise. Search engines and readers reward content that says something new. An agent summarizes what already exists. Your experience, your data, and your product knowledge have to come from you.
Link earning. Other sites linking to you comes from being worth citing, from relationships, and from real outreach. It does not come from a content pipeline.
Site speed and theme quality. Slow themes and heavy apps hurt rankings and conversion. That is engineering and app hygiene. Our Core Web Vitals checklist for ecommerce covers what to check.

A useful rule: if the task has a right answer you could describe in a spreadsheet, automate it. If the answer depends on what your brand believes, do it yourself.

Persona-led versus volume-led keyword research

Standard keyword research starts with volume. You pick terms people search often and try to rank for them. That works for big sites. For a small store, high-volume terms are usually dominated by publishers and large retailers.

Persona-led research flips the order. You start with the questions your actual customers ask, the objections they raise, and the words they use in reviews and support emails. Then you check which of those have search demand.

The volume is lower. The intent is clearer and the competition is often thinner. A search like “does this fabric shrink after washing” tells you far more about the buyer than a broad category term does.

Volume still matters as a filter. It should not be the starting point.

Finding pages you almost rank for

The most efficient gains in SEO often come from pages that already have traction. Google Search Console can show them.

Open the Performance report and set the date range to the last three months.
Turn on average position, impressions, and clicks.
Filter or sort by pages with meaningful impressions and an average position somewhere past the first page or near its bottom. Positions roughly between 8 and 20 are a common working range.
Look for pages with plenty of impressions and few clicks.
Open each page and ask what is missing. It might be a clearer title, a better answer near the top, a missing section, weak internal links, or thin content.

These are often the fastest wins because the page already has relevance. You are improving something search engines have already decided to show. One vendor’s material makes the same point, describing pages you almost rank for as usually the fastest wins.

The risks of AI blog content

Automated blog posts can hurt a store if you publish them carelessly.

Thin content. A post that repeats the top results in different words adds nothing.
Duplication. Posts targeting near-identical queries compete with each other.
Unverified claims. Language models can state things confidently that are not true. On a store, that can mean wrong product, safety, or shipping information.
Voice drift. Posts that sound nothing like your brand weaken trust.

An approval checklist

Before approving any AI-drafted post, check each of these.

Is the topic tied to a real customer question? If you cannot name the customer, skip it.
Does it add something a top-ranking page does not? Add your own experience, a photo, a test, or a specific detail.
Is every factual claim true? Check product details, materials, sizing, and guarantees against your own records.
Does it avoid overlap with existing posts? One page per intent.
Does it sound like you? Edit until it does.
Are internal links relevant? Links should help the reader, not just pass around authority.
Are the title and meta description accurate? They should describe what the page delivers.
Would you be comfortable putting your name on it? If not, do not publish.

Our guide on using AI for ecommerce product descriptions applies the same review habits to product copy.

Task suitability at a glance

SEO task	Agent suitability	Human check
Meta titles and descriptions	High	Accurate to the page, not misleading, within sensible length
Image alt text	High	Describes the image, no keyword stuffing
Internal links	Medium	Links are relevant and the anchor text reads naturally
Schema markup	High	Validates and matches visible page content
Striking-distance page updates	Medium	Changes answer the real query and add substance
Blog post drafts	Medium	Claims verified, original detail added, voice edited
Keyword clustering by persona	Medium	Clusters match how your customers really talk
Positioning and topic strategy	Low	You decide what you want to be known for
Link earning and outreach	Low	Entirely human relationships and reputation

How Tilly implements this

Tilly is one example of an SEO agent for Shopify. Everything below is what the product says about itself, not the result of our own testing.

The product says its SEO agent does technical fixes, content for customer search queries, and freshness updates. Its keyword research starts with your customers, grouping terms around personas rather than only volume. That fits the persona-led approach above.

It writes SEO titles, meta descriptions, and image alt text to Shopify on approval. Blog posts publish to your Shopify blog as drafts or live, with metadata, internal links, and schema. The product describes five steps: pick a keyword cluster, outline from competitor analysis, write in your store voice, add schema, and publish with your approval.

Search Console is optional and read only. When connected, the product says it finds pages you almost rank for, which it describes as usually the fastest wins.

Consistent with its wider positioning, the product says nothing leaves without an approval against your name and that it does not invent reviews, numbers, or claims.

On cost, at the time of writing, a blog post is 15 credits and an SEO fix is 8 credits. The SEO audit is free. Plans at the time of writing are Start at $0 with 100 credits one-time, Store at $49 per month with 500 credits, Growth at $149 per month with 2,000 credits, and Agency at $399 per month with 6,000 credits.

Honest limits

No cover images yet. Per the product, posts have no cover image yet. You will need to add your own before publishing.
Competitor-based outlines are still derivative. An outline built from what competitors wrote can only be as original as you make it. Add your own knowledge.
Rankings are not guaranteed. No agent controls how search engines respond.
Speed and technical health sit outside it. Theme performance and app bloat need separate attention.
Slow feedback. SEO results take weeks to months. Judge on that timescale.

Where to start

Run a free audit or a manual crawl first, and fix the metadata and alt text gaps across products.
Connect Search Console and list the pages sitting just off page one. Improve those before writing anything new.
Pick keywords from customer questions, then check volume as a filter.
Approve every blog post with the checklist above, and add your own detail before it goes live.