96% of consumers use the internet to discover nearby services, and a significant 46% of all searches on Google have a local intent: here’s why a Retail Manager must know how to leverage Structured Data for local businesses.

In this digital landscape, the ability of a physical store to stand out and be easily found by its target audience is crucial.

In my Retail Consulting and Training for Internal Retail Teams activities, I focus on structured data for local businesses, using them to help Digital First Consumers engage with local realities.

Why Consumers Have Become Digital First Consumers

The Retail Marketing Manager faces a Digital First consumer, someone who always begins their journey in the digital world before entering a physical store.

For more insights on the characteristics of the Digital First Consumer, I recommend this article.

What Changes for Local Business Promotion in 2025?

Implementing structured data emerges as a key strategy to achieve this goal. In fact, web pages using structured data have recorded a click-through rate (CTR) 40% higher than those without.

Moreover, enriched search results enabled by structured data achieve an average CTR 17% higher than standard results. These figures highlight how the “adoption of this technology can significantly increase opportunities for a” local business to capture potential customers online.

Structured Data: What They are, how to Use Them, and Their Benefits

Structured data for local businesses represent a standardized format for providing information about the content of a web page and allowing digital devices (search engines, AI-based systems, voice assistants) to classify it.

Consider, for example, a page dedicated to a recipe: structured data allows you to clearly specify the ingredients, cooking time, temperature, and calories.

Essentially, it’s a method for organizing and “tagging” the content of a web page so that search engines can understand it in detail, thereby improving the site’s visibility in search engine results pages (SERP).

These data are implemented through specific code formats, such as Schema.org, JSON-LD, RDFa, or microdata. This standardization, made possible by vocabularies like Schema.org, enables search engines to generate enriched search results, extracting specific elements from various websites and presenting them in a more user-friendly format.

It should be noted that the “integration of structured data falls under the” marketing area.

Ultimately, structured data act as a translator, converting the information on a website into a language that search engines can easily process and understand.

Structured Data for Local Businesses: Why They Are Useful for Branding

The “utility of structured data extends far beyond simple content indexing; they represent a valuable tool for the branding of a” local business.

Thanks to structured data, a company can make its web page suitable for displaying enriched search results, such as FAQ boxes or product reviews.

These rich snippets can include elements like star ratings, product availability, and event details, capturing the “attention of users and increasing their trust in the” business.

Displaying reviews and star ratings directly in search results can significantly increase click-through rates and conversions.

In essence, structured data facilitate the presentation of key branding elements directly in search results, building trust and credibility even before a user visits the website.

By providing detailed and accurate information, brand consistency is ensured across various online platforms where search results are displayed.

Structured Data for Local Businesses: some Examples for Stores and Franchises

Numerous concrete examples illustrate how stores and franchises use structured data to enhance their online branding.

A local bakery, for example, could use schema markup to display star reviews, a photo, opening hours, and an “Order Online” button directly in search results.

Similarly, a bookstore might highlight author presentation dates, while a home renovation company could showcase service areas and customer testimonials.

Franchises can leverage structured data to ensure a uniform brand presentation across all their locations, providing consistent information such as business name, address, phone number, and services offered.

Specific retail stores, like bike shops, hobby stores, bookstores, and men’s clothing stores, can use more specific markup schemas to highlight details relevant to their products and services.

A cinema might use structured data to display movie reviews, while an electronics retailer could highlight product availability and ratings.

These examples demonstrate the practical application of structured data in enhancing the online presence and branding of various retail businesses.

Structured Data for Google Search

Getting Found

Structured data play a crucial role in improving a local business’s ability to be found on Google. Implementing schema markup for local businesses helps search engines understand and display relevant information about the company, such as name, address, phone number, and opening hours, enhancing visibility in local search results and Google’s Local Pack.

These structured data allow search engines to accurately interpret important information about the business, such as its geographical location, services offered, and operating hours, increasing the chances of appearing in Google’s Local Pack, on Google Maps, and in organic search results for queries like “restaurants near me.” In essence, accurate and complete structured data act as a digital business card, ensuring that essential contact information for a local store is easily accessible to potential customers searching on Google.

Appearing in the Local Pack is crucial for local businesses, and structured data significantly increase the likelihood of this happening by providing Google with the necessary information to rank businesses for local searches.

Structured Data for Local Businesses: Show Reviews.

Structured data allow businesses to display customer reviews and ratings directly in search results as rich snippets, building trust and credibility.

Displaying positive reviews in search results serves as a powerful social proof, influencing potential customers to choose a particular retail store over competitors.

Using the AggregateRating schema markup, businesses can communicate their overall customer satisfaction score to Google, which can then be displayed as star ratings in search results. This provides a quick and easily understandable summary of the company’s reputation.

Structured data ensure that these reviews are accurately attributed and displayed by Google, maintaining the “integrity and the” reliability of the feedback.

Structured Data for Local Businesses: Highlight Events

Retail businesses hosting events, such as workshops, promotional events, or product launches, can use structured data to tag event details, such as date, time, location, and ticket prices.

This allows these events to appear in Google’s event listings and increases visibility in local search results.

By making event information easily available in search results, structured data for local businesses can increase awareness, boost participation, and ultimately attract more customers to physical locations.

Using the Event schema markup, Retail Managers can promote their in-store activities, maximizing their reach and attracting more customers to their physical locations.

Other Ways to Improve Visibility

Beyond basic local business information, reviews, and events, there are other types of structured data that can further enhance visibility.

Implementing the FAQPage schema markup on relevant pages (e.g., product pages, service pages, contact pages) allows retail stores to directly answer customers’ frequently asked questions in search results, providing immediate information and potentially reducing the need for users to visit the website.

For stores offering services (e.g., repairs, consultations), the “use of the Service schema markup can help highlight the types of services offered and their key features in search results, making it easier for customers looking for such specific services to find the” business.

The following table summarizes different relevant schema types and their potential impact:

Structured Data for AI: the New AI Search and Voice Assistants

Structured data are gaining “increasing importance for AI-based search engines, such as” Search GPT, Bing Copilot, and Google Gemini.

These platforms use structured data to understand web page content, build knowledge graphs, and provide more accurate and contextually relevant responses.

Unlike traditional search engines, which primarily rely on keywords, AI search engines aim to provide direct answers by understanding relationships between different entities and concepts.

Structured data, with their clear and organized format, allow these AI systems to quickly identify and interpret key information about a retail business, such as its products, services, location, and customer reviews.

Structured data contribute to the construction of knowledge graphs that underpin these AI search engines.

By providing clear and consistent information about a “retail business, it allows the” AI to connect that business to relevant concepts and user queries, increasing its chances of being displayed in search results.

The Case of New Voice Assistants

Voice assistants like Siri, Alexa, and Google Assistant rely on structured data to quickly and accurately understand website content, enabling them to provide concise and relevant responses to voice queries about local businesses.

When a user asks “What is the ‘closing time of [retail store name]?’, the” voice assistant uses the structured data present on the store’s website (particularly the openingHours property within the LocalBusiness schema) to quickly and accurately retrieve and verbalize the “closing time.”

Implementing specific types of schema, such as LocalBusiness for basic business information, Product for product details, and Event for upcoming activities, significantly increases the chances of a retail business being included in voice search results for relevant queries.

For example, if a user asks, “Where can I buy [product type] near me?”, a retail store that has marked its product information using the Product schema is more likely to be recommended by the voice assistant.

Who should Use Structured Data and Why

Essentially, any local retail business that wants to improve its online visibility and attract more customers should use structured data. This includes physical stores, franchises, and even online retailers with a local presence.

The benefits of structured data—better understanding by search engines, eligibility for rich snippets, improved local search ranking, and superior performance on AI-based platforms and voice assistants—are universally advantageous for businesses aiming to grow and succeed.

Businesses that rely on local search for customer acquisition, such as restaurants, clothing stores, electronics retailers, bookstores, and service-based retail businesses (e.g., repair shops), are those that benefit the most from implementing local business schema markup and other relevant types of schema.

Even businesses that operate primarily online but have a local customer base or offer local services (e.g., local delivery, in-store pickup) can benefit from structured data to highlight these local aspects and attract nearby customers.

Conclusions: Entering a World where Access to Information Changes

The way consumers access information is undergoing a significant transformation, evolving towards smarter, conversational, and personalized experiences powered by artificial intelligence and voice technology. Structured data is the core that enables this change, providing the necessary framework for machines to understand and interpret large amounts of information accurately.

For retail businesses, this evolution means that merely having a website is no longer sufficient. To remain competitive, they must actively participate in this new information ecosystem by making their data easily understandable to these intelligent platforms through the implementation of structured data.

Businesses that do not adopt structured data risk becoming invisible to the growing number of users who rely on AI search and voice assistants for their information needs. By adopting structured data, Retail Managers can ensure that their business remains discoverable and accessible to their target audience in this ever-evolving landscape.

Ultimately, structured data facilitates a smoother and more informative search experience for users, providing key details upfront and potentially leading to greater customer satisfaction and loyalty.

Additional references

Google Guide for Local Businesses