Imagine this scenario: a digital first consumer is walking down the street and tells their smart assistant to book a hairdresser for 7 PM. Automatically, the smart assistant completes the operation. This scenario will be possible starting in the fall of 2025.
To intercept and satisfy the needs of this Digital First Consumer, it is essential that the retail sector recognizes and integrates Artificial Intelligence into its strategies.
Retail Managers must be aware that consumers are increasingly relying on smart devices and voice assistants for their purchasing decisions and for accessing local services.
Structured Data for Retail: The Key to Communicating with AI and Conquering the Market
To make their business visible and accessible to these advanced systems, Retail Managers must know and leverage structured data markup. These tools allow for the communication of strategic data in a format understandable to devices such as search engines and other systems, including AI. By correctly implementing structured data, your store will be able to provide the key information requested by smart assistants, thereby increasing the opportunities to intercept Digital First Consumers at the exact moment they express a need. In this article, we will explore how Structured Data becomes an indispensable strategic lever for the Retail Manager aiming to thrive in the era of AI Based Marketing.
96% of consumers use the internet to discover nearby services, and a significant 46% of all searches performed on Google have local intent: this is why a Retail Manager must know how to leverage structured data for Retail and Local Businesses for their physical locations.
In this digital scenario, the ability of a physical store to stand out and be easily found by its target audience is fundamental.
In my consulting activities for Retail and training for internal Teams in the Retail world, I therefore focus on structured data for retail and local businesses, leveraging them to help Digital First Consumers enter local realities.
Why Consumers Have Become Digital First Consumers
The Retail Marketing Manager faces a Digital First consumer, a person who, before entering a physical store, always begins their journey in the digital world.
When you ask Alexa if store X is open now, or look on Maps to see if there is a queue, or if a product is available at point of sale X, you are effectively starting a Digital First visit to the point of sale.
Enrico Giubertoni
For more insights into the characteristics of the Digital First Consumer, I recommend this article.
What Changes for the Promotion of Local Businesses in 2025?
The implementation of structured data presents itself as a key strategy to achieve this goal. In fact, web pages that use structured data for Retail have recorded a 40% higher click-through rate (CTR) compared to those that do not².
Furthermore, enriched search results, made possible by structured data, obtain an average CTR 17% higher than standard results. This data highlights how the adoption of this technology can significantly increase the opportunities for a local business to intercept potential customers online.
Structured Data for Retail: What They Are, How to Use Them, and What Benefits They Bring
Structured data for Retail and local activities represent a standardized format for providing information about the content of a web page and for allowing digital devices (search engines, artificial intelligence-based systems, voice assistants) to classify it.
Think, for example, of a page dedicated to a recipe: structured data allow you to clearly specify the ingredients, cooking time, temperature, and calories.
Essentially, it is a method for organizing and “tagging” the content of a web page so that search engines can understand it in detail, thus improving the site’s visibility in search engine results pages (SERPs).
This data is implemented through specific code formats, such as Schema.org, JSON-LD, RDFa, or microdata. This standardization, made possible by vocabularies like Schema.org, allows search engines to generate enriched search results, extracting specific elements from different websites and presenting them in a more user-friendly format. This process involves structured data markup.
It should be emphasized that the integration of structured data for retail is the responsibility of the marketing area and more precisely for retail managers.
Ultimately, structured data act as a translator, converting the information present on a website into a language that search engines can easily process and understand.
Structured Data Brand: Why They Are Useful for Branding
The usefulness of structured data extends well beyond the simple indexing of content; they represent a valuable tool for the structured data brand of a local business.
Thanks to structured data, a company can make its web page suitable for the display of enriched search results, such as frequently asked questions boxes or product reviews.
These rich snippets can include elements such as star ratings, product availability, and event details, capturing users’ attention and increasing their trust in the business.
The display of reviews and star ratings directly in search results can significantly increase click-through rates and conversions.
Essentially, 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 Retail: Examples in Real Life for Stores and Franchises
Numerous concrete structured data examples in real life illustrate how stores and franchises use structured data to improve their online branding.
A local bakery, for example, could use structured data markup to show star ratings, a photo, structured data opening hours, and an “Order online” button directly in search results.
Similarly, a bookstore could highlight the dates of author presentations, while a home renovation company could show 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, structured data address, phone number, and services offered.
Specific retail stores, such as bicycle shops, hobby shops, bookstores, and men’s clothing stores, can use more specific types of structured data to highlight details relevant to their products and services.
A cinema could use structured data to show movie reviews, while an electronics retailer could highlight product availability and ratings, potentially including the structured data price range.
These examples demonstrate the practical application of structured data in improving the online presence and branding of various retail businesses.
Structured Data for Retail: how to intercept Google Search
Getting Found
Structured data for retail play a crucial role in improving a local business’s ability to be found on Google. The implementation of structured data markup for local businesses helps search engines understand and display relevant information about the company, such as name, structured data address, phone number, and structured data opening hours, improving visibility in local search results and in Google’s Local Pack.
This structured data for retail allows 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” 9. In essence, accurate and complete structured data for retail act as a digital business card, ensuring that the essential contact information of a local store is easily accessible to potential customers searching on Google.
Appearing in the Local Pack is fundamental 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 Business: Showing Reviews
Structured data allow businesses to display customer reviews and ratings directly in search results as rich snippets, building trust and credibility.
The display of positive reviews in search results acts as powerful social proof, influencing potential customers to choose a particular retail store over competitors.
By using the AggregateRating type of structured data, companies 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 reliability of the feedback.
Structured Data for Local Activities: Highlighting Events
Retail businesses that host events, such as workshops, promotional events, or product launches, can use structured data to mark up 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 activities can increase awareness, boost participation, and ultimately attract more customers to physical locations.
By using the Event type of structured data, Retail Managers can promote their in-store activities, maximizing their reach and attracting more customers to their physical locations.
Other Ways to Improve Visibility
In addition to basic local business information, reviews, and events, there are other types of structured data that can further enhance visibility.
Implementing FAQPage structured data markup on relevant pages (e.g., product pages, service pages, contact pages) allows retail stores to directly answer frequently asked customer questions in search results, providing immediate information and potentially reducing the need for users to visit the website.
For stores that offer services (e.g., repairs, consultations), using the Service type of structured data can help highlight the types of services offered and their key features in search results, making it easier for customers searching for those specific services to find the business.
The following table summarizes several relevant schema types and their potential impact:
| Schema Type | Description | Potential Impact on Search Results | Relevance for Retail Businesses |
|---|---|---|---|
| LocalBusiness | Provides general information about a local business, including NAP, structured data address, structured data opening hours, and location. | Improved visibility in local search results, eligibility for the Local Pack and Google Maps. | All physical stores and franchises. |
| Offer | Information about the sale structured data price range, availability, and conditions of a product or service. | Helps highlight special offers and discounts in search results, attracting price-sensitive customers. | Retailers offering promotions or discounts. |
| AggregateRating | Provides an overall rating and review count for a product or service. | Display of star ratings in search results, building trust and encouraging clicks. | Businesses with customer reviews for products or services. |
| Review | Individual customer reviews for a product or service. | Presentation of specific customer feedback in search results, providing more detailed social proof. | Businesses wanting to highlight individual positive reviews. |
| Event | Information about an organized event, such as date, time, location, and performers. | Display of events in Google’s event listings and search results, increasing visibility for in-store events. | Retailers hosting workshops, promotional events, product launches, or other in-store activities. |
| FAQPage | Questions and answers related to a specific topic. | Display of questions and answers directly in search results as rich snippets, providing quick information to users. | Retailers wanting to answer frequently asked customer questions on product, service, or contact pages. |
| HowTo | Step-by-step instructions for completing a task. | Potential for rich snippets with steps and images/videos, useful for DIY or product assembly instructions. | Retailers selling products that require assembly or have specific usage instructions. |
| BreadcrumbList | Helps users understand a page’s location in the site hierarchy. | Display of breadcrumbs in search results, improving navigation and user experience. | All retail websites. |
| Organization | Provides information about the organization, such as name, logo, and contact details. | Can contribute to Knowledge Graph panels and improve structured data brand visibility. | All retail businesses. |
Structured Data Machine Learning: The New AI Search and Voice Assistants
Structured data are also becoming increasingly important for search engines based on structured data machine learning, such as Search GPT, Bing Copilot, and Google Gemini.
These platforms use structured data to understand the content of web pages, build knowledge graphs, and provide more accurate and contextually relevant answers.
Unlike traditional search engines, which rely primarily on keywords, AI search engines aim to provide direct answers by understanding the 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 the knowledge graphs that are the foundation of these AI search engines.
By providing clear and consistent information about a retail business, AI is enabled to connect that business to relevant concepts and user queries, increasing its chances of being displayed in search results. This facilitates efficient structured data retrieval.
The Case of New Voice Assistants
Voice assistants like Siri, Alexa, and Google Assistant rely on structured data to quickly and accurately understand the content of a website, allowing them to provide concise and relevant answers to voice queries about local businesses.
When a user asks, “What time does [retail store name] close?”, the voice assistant uses the structured data present on the store’s website (specifically the openingHours property within the LocalBusiness schema) to quickly and accurately structured data retrieval and verbalize the structured data opening hours.
The implementation of specific types of structured data, such as LocalBusiness for basic business information (structured data address, structured data opening hours), Product for product details (including structured data price range), 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 up its product information using the Product type of structured data 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 local business. 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 platforms based on structured data machine learning 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 the ones that benefit most from implementing structured data markup for local businesses and other relevant types of structured data.
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.
We Are Entering a World Where Access to Information Is Changing
The way consumers access information is undergoing a significant transformation, evolving towards smarter, more conversational, and personalized experiences, powered by artificial intelligence and voice technology 5. Structured data are the linchpin that enables this change, providing the necessary structure for machines to understand and interpret large amounts of information accurately.
For retail businesses, this evolution means that simply having a website is no longer enough. 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.
Companies 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 continues to be discoverable and accessible to their target audience in this constantly evolving landscape.
Ultimately, structured data facilitate a smoother and more informative search experience for users, providing key details upfront and potentially leading to increased customer satisfaction and loyalty.
