PIM for social commerce

Sixty-four percent of digital buyers discover brands and products through social media, and one in three consumers actively look for products that are trending within their social circles. 

Platforms like TikTok Shop, Instagram Shopping, and Facebook Shops have already moved the entire purchase journey inside the app, from discovery through checkout, with no redirection to an external website required. 

However, visibility is not where most brands lose ground; the real gap lies in whether their product data is accurate, complete, and correctly structured for each platform that serves their products. 

In this article, we cover the real data demands of social commerce across formats, why product content quality directly affects shopper trust, and where a product information management system becomes the deciding factor.

How consumer behavior in social commerce has shifted from traditional e-commerce

The way people shop has changed significantly, and social commerce is at the center of that shift. Here is what the data shows about how shoppers behave differently today compared to traditional e-commerce.

1. Discovery happens inside the feed, not on a search engine. 

According to Deloitte’s research on social commerce, 64% of digital buyers now discover brands and products through social media. Shoppers are no longer starting their journey on Google or a brand website. They’re finding products mid-scroll, often without actively seeking them out.

2. Peer influence and trending content carry more weight than traditional brand advertising.

Deloitte’s findings show that 1 in 3 consumers prefer discovering products based on what is trending in their social circles, and 43% of Gen Z specifically seek out trending topics on social media before making purchasing decisions.

3. Influencers have replaced the traditional consideration phase. 

In traditional e-commerce, a shopper would research, compare, and deliberate before purchasing. In social commerce, that consideration phase is compressed by influencer credibility. Deloitte reports that 67% of social media users would consider a brand promoted by their favorite influencer, with 41% wanting to purchase directly and easily from those influencers without leaving the platform.

4. Shoppers expect to buy without leaving the platform. 

A study by Beyari and Bahaaudeen, published in the Journal of Posthumanism, found that 94.7% of respondents had made at least one purchase via social media in the past six months. Redirecting shoppers to an external website creates friction that costs conversions. 

5. Live shopping and AR experiences are becoming expected, not experimental.

Deloitte’s research found that 40% of global shoppers want live streaming as part of their shopping experience, and 60% are interested in augmented reality-driven shopping. Shoppers increasingly expect interactive, real-time formats that let them engage with products before purchasing.

6. Social commerce is now a primary channel for fashion, beauty, and apparel purchases. 

In a survey of 412 social commerce customers, Beyari and Bahaaudeen found that fashion and apparel accounted for 78.4% of purchases, followed by beauty and cosmetics at 68.9%. These categories lead because they are driven by visual content, trends, and social validation, exactly what social platforms are built to deliver.

Social commerce requires product data that supports platform-specific formats, real-time updates, and AI-driven discovery. See how to manage product information across all social channels.

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Social commerce channels and their product data requirements

Most brands treat social commerce as a single channel and adopt a single content approach to cover it all. That is where product data problems start. 

Each platform has its own digital shelf requirements, attribute structures, and content specifications, and a product that is correctly set up on one platform can fail to publish, display incorrectly, or get rejected on another.

1. TikTok Shop 

TikTok requires product titles, category taxonomy, pricing, and inventory to be correctly mapped to TikTok’s own classification system before a product can go live inside the app.

According to Chodak’s research on social commerce, TikTok Shop completes the entire shopping experience within the app, so every product attribute must be accurate and complete before a shopper ever sees it. There is no fallback to an external website to fill in missing information.

2. Instagram Shopping 

Instagram feeds product data through Meta’s catalog API, where each product requires a correctly mapped product ID, a compliant title and description, and imagery that meets platform specifications. Deloitte identifies Instagram Shops as one of the leading social media commerce formats, where brands like Clinique have used in-app checkout to let users purchase directly on the platform without redirection.

3. Facebook Shops

Facebook shares catalog infrastructure with Instagram but operates under its own checkout rules. Full in-app checkout is currently available only to US users, meaning product data must account for shoppers’ locations and available purchase paths. Managing that variation manually across a large SKU catalog is where inconsistencies typically surface.

4. Pinterest Shop

Pinterest surfaces products through product pins, where pricing, availability, and product descriptions are structured as metadata that shoppers can act on without leaving the platform. Chodak notes that Pinterest product pins include essential information such as pricing details, product availability, and product title and description, making attribute completeness a direct factor in whether a product pin drives a conversion or gets ignored.

5. Live commerce 

This platform is the most demanding format for product data. A host moving through dozens of products in a single session needs accurate pricing, real-time inventory status, and rich product content ready before the broadcast starts.

Beyari and Bahaaudeen’s study ranks live shopping events as the third-most-effective customer-acquisition channel in social commerce, behind influencer partnerships and user-generated content campaigns. A pricing error or stock mismatch during a live session is visible to everyone watching and cannot be corrected mid-broadcast.

6. Conversational commerce

This is where shoppers discover and purchase products through natural language prompts inside AI-driven tools. ChatGPT’s Merchants program, for instance, allows consumers to find and buy products directly in a chat interface, with products ranked by the relevance, completeness, and consistency of their product data. As Inriver notes, there are no paid placements or boosts in this environment, which means visibility depends entirely on how well-structured your product information is.

What agentic commerce means for your product data strategy 

The same product data problems that hurt your performance on TikTok Shop and Instagram Shopping will follow you into agentic commerce. McKinsey’s State of Fashion 2026 reports that shopping-related searches on generative AI platforms grew 4,700% between 2024 and 2025, and 53% of US consumers who used generative AI for search in that same period also used it to shop.

• AI agents parse structured data; they don’t browse as humans do.
  Unlike a shopper who can interpret a vague product title or overlook a missing size chart, an AI agent relies entirely on explicit attribute values and defined relationships to understand what a product is and whether it matches a query.
• Incomplete product data means your products won’t surface.
  An agent comparing two similar products will favor the one with complete, well-structured data. Inconsistent naming, missing attributes, and incomplete specifications remove your products from those comparisons entirely.
• The infrastructure you build for social commerce today is the same infrastructure agentic commerce will use tomorrow.
  Structured attributes, governed enrichment, and channel-ready product content serve both environments. Brands that get this right once benefit across every channel that follows.
• Structuring your product content for AI readability is now an executive priority.
  McKinsey says brands need to structure product content and data-sharing feeds so AI agents can interpret and display the product catalog. Understanding how MCP and UCP protocols interact with your product data is a practical starting point for building that infrastructure.

Why PIM is the foundation your social commerce strategy is missing

Every problem covered in this article traces back to the same root cause: product information that is not governed, structured, or built for the speed social commerce demands. A PIM system resolves this by providing every channel with a single, accurate source of product truth.

New Balance is a clear example of what that looks like in practice. As the global footwear and apparel brand expanded across multiple markets and partners, managing complex product information and assets across wholesale, retail, and e-commerce platforms became increasingly difficult. Inconsistent data was slowing content delivery and undermining the digital product experiences the brand needed to stay competitive. 

After implementing Inriver PIM, New Balance unified its global product data, improved product discovery and customer trust across digital channels, increased click-through and add-to-bag conversion rates, and reduced product returns through accurate, detailed product content. 

“In a world where digital experiences are increasingly interactive and immersive, the Inriver PIM helps us continuously evolve how we handle and integrate our data and assets.”

John Fister

Senior Digital Product Manager at New Balance

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Inriver addresses this through three capabilities that matter directly to social commerce.

1. Built for constant change.

Inriver coordinates how product information moves across systems, teams, and channels so updates, corrections, and new content do not break when platform requirements shift.

2. Product information ready for AI decisioning.

Structured attributes and governed enrichment support direct answers for shoppers and AI agents alike, while rich product narratives provide the context needed to compare and recommend.

3. A governed foundation at scale.

Inriver enables teams, automation, and AI agents to work together within clear rules, approvals, and traceability. Syndicate Advance handles API-driven syndication across every social commerce platform, keeping your product content current and channel-ready at scale.

Start with the data, and the rest of social commerce gets easier

Your social commerce strategy is only as strong as the product data underneath it. If your content is inconsistent across platforms, slow to update, or missing required attributes, you’re losing sales that your channels were already positioned to capture.

Getting your product data governed, structured, and channel-ready is the most direct investment you can make in social commerce performance. If you’re ready to see what that looks like for your business, book a personalized demo with Inriver today.