How to leverage AI to power your retail brand’s SEO

How to leverage AI to power your retail brand’s SEO

Nov 15, 2023

“AI-powered long-tail SEO” may sound overly technical, but its purpose is surprisingly human. By listening to how shoppers speak, we help them find the products they’re actually looking for. 

Let’s say a shopper searches for “lengthening mascara for sensitive eyes.” They know exactly what they want and are ready to purchase it — as long as they find the right product. By leveraging AI, retailers can seamlessly: 

  1. Connect this micro-category to relevant products in their catalog

  2. Curate a custom landing page for that unique search

  3. Most importantly, capture that purchase

This advanced, AI-powered SEO experience is the digital version of a personal shopper. Imagine a friendly, knowledgeable concierge walking you through a brand’s offerings and hand-selecting the perfect products for you. 

Because enterprise retailers have such large catalogs, it’s normally resource-intensive to deliver this kind of service. That’s where artificial intelligence comes in as the best way to create niche, personalized online shopping experiences at scale. 

To begin leveraging AI for your retail brand, follow this three-step playbook and seamlessly elevate your SEO. 

Step 1: Conduct semantic keyword analysis

Typically, a retailer’s taxonomy is not detailed enough to reveal long-tail, high-intent keywords. Instead, brands should analyze what customers are actually saying about their products. 

Discover keywords you didn’t know you could rank for

Start by building a machine learning model to analyze the natural, non-branded ways customers describe your products. 

  • Do reviews often call one of your lawn mowers “quiet” or “not too loud”? 

  • Do multiple shoppers describe one of your mascaras as good for “sensitive eyes”? 

  • Does “compact” or “apartment” keep coming up to describe one of your washing machines? 

By ingesting data like customer reviews, Q&As, an AI model can uncover these semantic relationships — and the long-tail keywords they correspond to. 

Decide which long-tail keywords to target

Once your AI model has compiled a list of keywords, identify which ones are in high-demand, less competitive, and non-cannibalizing. 

The semantic analysis revealed that you already have the products to target these keywords — you just need the right content to help Google find you. A tool like Optiversal automates this step of the process. Otherwise, retailers can use a keyword research tool like Ahrefs, SEMrush, or Moz. In addition, select your keywords while considering these two tips: 

  1. The greater your site’s domain authority, the higher-competition keywords you can target. 

  2. Ensure you do not rank for these keywords anywhere else on your site, or you may risk competing with internal pages and cannibalizing traffic. 

Step 2: Generate dynamic landing pages

Once you’ve found the right keywords, use AI to build dynamic landing pages that target these terms. The goal is to show customers a selection of products that align closely with what they’re looking for. 

For instance, Optiversal’s AI model automatically builds landing pages and populates them with products to match each long-tail keyword. Brands can also accomplish this manually by: 

  1. Building an internal search engine

  2. Linking it to a product database

  3. Querying that database to extract the right listings

Generate high-quality landing page copy

Product listings alone aren’t enough. For your site to rank well, it also needs high-quality text content. To do this at scale, retailers need to build multiple custom AI models for every type of copy needed on the page, such as introductory copy, footer copy, and product FAQs. 

Unfortunately, ChatGPT can’t help you here. Public online tools can base their content on internet knowledge that hasn’t been vetted for quality or accuracy, harming results and your brand. 

Instead, build an AI model for each type of content, and train them on well-executed examples. As best practice, Optiversal re-trains our model on each new client’s unique brand voice and guidelines. 

Index and cluster landing pages 

Once you have your landing pages, ensure they’re linked to each other and back to the rest of your retail site. Make sure you have a full site map, registered with Google, that can be crawled and indexed so it will display in search results. 

Then, cluster the pages into a taxonomy of related categories. For instance, mascara is a category of eye makeup and contains subcategories like black mascara, waterproof mascara, and lengthening mascara. 

Step 3: Monitor and maintain your landing pages 

The work doesn’t stop once your pages are live. To keep delivering results, they must be continuously updated and monitored. 

Maintaining and updating landing pages

Build an AI-powered monitoring system to keep pages up-to-date. This model should be able to: 

  • Maintain accurate pricing

  • Replace out-of-stock products

  • Adjust products for seasonality

  • Ensure all keywords are still worth targeting

  • Check for cannibalization against other internal pages

At the same time, the retailer should be able to update these pages manually. For instance, if a certain brand or product is the subject of a large marketing campaign, you may want to pin those products to the top of the page. 

Monitoring landing pages for continuous improvement

Finally, performance monitoring shows retailers what’s working and what’s not. If a page is bringing in plenty of traffic and sales, you may want to create even more pages within that cluster. If a page isn’t delivering results, you may want to redirect it to something similar but higher-performing. 

Try Optiversal: an AI-powered engine to automate and supercharge SEO

When executed well, this three-step playbook is incredibly powerful. However, it takes an immense amount of resources, time, and labor for retail brands to build and maintain an AI-powered SEO solution themselves. 

Fortunately, there’s a better way — Optiversal is an AI-powered content platform designed for retail. We streamline every step of this process with our proprietary AI model and train it on your product data, customer data, and unique brand voice. Take it from leading retailers like Sephora, Petco, and Best Buy, who use Optiversal to produce differentiated, high-quality content at scale. 

Instead of building dozens of AI models from scratch, Optiversal clients simply share their content feeds and product catalog. Within four weeks, their landing pages are live, and Optiversal is already iterating to improve every page’s performance. 

Want to see this in action? Book a demo today to learn how Optiversal can elevate your content creation, scale organic reach, and drive new revenue. 

Book a demo today