User-generated content (UGC), which includes reviews, photos, ratings and consumer posts, has always been a valuable tool to help shoppers determine what to buy. But while UCG shapes product discovery, it also feeds the AI-powered tools consumers use to find products in the first place. However, as AI-generated claims are repeated across search results and platforms, the resulting echo chamber makes authentic content harder to identify and consumer trust harder to to maintain.

This FAQ covers how UGC influences purchases, the authenticity problem, and how brands should build UGC programs in 2026.

What is user-generated content marketing?

User-generated content marketing is the strategic collection and deployment of customer-created content, including ratings, reviews, photos, videos, and Q&A. That content can appear on product pages, in ads, And across social channels and retail listings.

Unlike influencer content, UCG typically comes from customers sharing firsthand experiences as opposed to creators producing commissioned content. That origin is the asset. When shoppers deem UCG credible, it can answer practical questions about a product and reduce uncertainty before making a purchase, which is why review volume and quality correlate with conversion across categories.

In 2026, UGC carries a second function: the same ratings and reviews now feed the AI systems that filter what products consumers see at all, extending UCG’s influence beyond the product page.

How does UGC influence purchase decisions?

Reviews usually factor into the shopping journey after the shopper first discovers a product. "Looking for reviews or ratings" is the most common step consumers take (43%) after discovering a product or intending to purchase it, according to Bazaarvoice's 2025 Shopper Experience Index, a survey of over 7,000 consumers conducted by Savanta (Bazaarvoice sells UGC software, a commercial interest worth noting).

How much weight consumers give that content may depend on where they find it, and peer content outranks brand messaging when it comes to consumer trust. Nearly half (41%) of consumers say that Reddit offers the least biased recommendations, versus 24% for AI chatbots, per Partnercentric data cited by EMARKETER.

The comparison does not show that all consumers inherently trust UCG, but it does suggest that the perceived independence of its source can help determine whether UCG influences a purchase.

Why does UGC now determine AI shopping visibility?

Just as shoppers turn to UCG as a quality filter, so do AI assistants. Products with both high ratings and high review volumes get the strongest preference boost from AI agents, according to a Columbia and Yale study cited by Bazaarvoice.

EMARKETER's reporting on AI product recommendations confirms the mechanism: products need baseline credibility, including ratings of 4.6 stars or higher and substantial review volume, before content optimization can influence where they appear in AI-generated results, per EMARKETER.

With over half (55%) of consumers trusting generative AI tools and shopping agents like ChatGPT or Google Gemini, per Bazaarvoice's index, review programs have become an AI visibility investment.

What is the authenticity problem with UGC?

Reviews are supposed to offer insight into a product and how it will work, building confidence for the consumer. Instead, a shopper’s biggest frustration is deciphering whether or not they are real. "Knowing if reviews are real or trustworthy" is the single most frequently cited frustration in the shopping journey at 46%, per Bazaarvoice's 2025 Shopper Experience Index.

The problem compounds as generative AI lowers the cost of producing synthetic reviews at scale, polluting the very signal consumers and AI assistants rely on. The implication cuts both ways: unverified review sections lose persuasive power as skepticism rises, while verified, authentic UGC gains relative value as a differentiator.

Brands cannot address consumer skepticism with a badge alone; a verified purchase label only confirms that a transaction occurred, not the honest opinion behind the purchase. Screening reviews for spam and manipulation, disclosing incentivized purchases, and explaining how reviews are collected can help shoppers evaluate what they see. These practices may also limit the unreliable material available for AI systems to mischaracterize.

How does UGC differ from creator and influencer marketing?

The clearest distinction is who creates the content and the relationship the person has with the brand. UCG comes from customers documenting their unpaid experiences, although brands may request or incentivize those contributions. Creator marketing involves hiring someone to make content for a brand while influencer marketing goes a step further by paying a creator to distribute that content to an established audience.

These categories can overlap. A customer may also be a creator, and brands are increasingly commissioning paid content designed to resemble an ordinary customer post. The format alone does not make that content independent, which is why sponsorship and incentive disclosures matter.

Each type of content can also play more than one role in the purchase journey. Creator or influencer content can introduce and demonstrate a product, while reviews and customer reviews can answer questions that arise before a purchase. In either case, content loses credibility when the brand’s involvement overwhelms the person’s voice. Front-loading creator videos with brand or product messaging reduced the 25% view rate of paid Instagram and TikTok placements by 44%, per EMARKETER.

How should brands build UGC programs in 2026?

Treat UGC as conversion infrastructure and AI fuel simultaneously:

• Collect consistently. Use post-purchase requests and disclosed sampling programs to keep feedback current. Recent customer reviews are among the top factors that give shoppers purchase confidence, according to Bazaarvoice’s 2025 Shopper Experience Index.
• Defend the 4.6-star threshold. Research involving Amazon’s shopping agent found that products generally needed bestseller status, ratings of at least 4.6 stars, and substantial review volume before content optimization meaningfully affected recommendations, per EMARKETER. Those findings are platform-specific, not universal thresholds.
• Act on recurring complaints. Address the product and service problems behind low ratings instead of focusing only on the score.
• Make review sources clear. Label verified purchases, disclose incentives, and screen for manipulation without suppressing legitimate criticism.
• Extend UGC into paid media. Customer photos and review pull-quotes in ads carry the evidence quality that polished creative lacks.

We prepared this article with the assistance of generative AI tools and stand behind its accuracy, quality, and originality.

EMARKETER forecast data was current at publication and may have changed. EMARKETER clients have access to up-to-date forecast data. To explore EMARKETER solutions, click here.