Masse seeks to improve product recommendations by building a friends network

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Ecommerce sites have a trust problem. More than 80 percent of consumers believe friends and family — not influencers or traditional advertisements — are the most reliable sources of information about products, according to Nielsen. But try telling that to Amazon, which prioritizes sponsored content and first-party brands in search results. (By some accounts, nearly 8 percent of views on Amazon product pages now come from sponsored links.)

The growing disconnect between online retailers and their customers drove former Jet.com product managers Elizabeth Shaffer and Lizzy Brockhoff to start Masse (as in “en masse”), a product discovery platform built on two core pillars: community and credibility. It launched in beta a few weeks ago, and today marks its general availability on iOS.

“We’ve spoken to so many consumers over the years and watched their shopping habits, and the key takeaway that was that they’re spending a huge amount of time researching and evaluating products online and trying to decide what to buy,” Shaffer said. “At the same time, they’re [dealing with] an increase in the amount of content that’s being sponsored by brands. [As a result,] they’re going back to their trusted friends and family for product recommendations — back to people who have their best interests at heart.”

The two experienced it firsthand 18 months ago, when they both became new mothers a day apart.

“We had to put together baby registries, which are incredibly time-consuming and cumbersome,” Shaffer said. “You’re navigating a world of products [online] that you don’t have any familiarity with.”

Their solution — Masse — is a friend-forward product feed that looks a bit like a stripped-down Twitter timeline. It’s filled with suggestions from other users you explicitly choose to follow during the onboarding process, each complete with comments and videos detailing buyers’ experiences with the knickknacks they’re recommending.

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Masse has a zero-tolerance policy regarding paid and sponsored content, Shaffer said, and a transparent profile system that shows recommenders’ demographic information and tidbits about their preferences, tastes, and styles. And it employs human moderators and an automated AI platform to flag offensive content, lest a nefarious user hijack a post with a nasty comment.

The features almost read like a wishlist cooked up by disgruntled Amazon shoppers. Masse, unlike its competitors, deemphasizes product ratings, which research has shown are susceptible to manipulation by unscrupulous vendors.

Instead, recommendations are organized by categories like Baby Products, Beauty and Personal Care, Home and Garden, and Health and Wellness, and Masse affords you the freedom to dive into a friend’s suggestion history or solicit a recommendation for a specific product from your network (“I need a onesie for a 15-month-old toddler”).

Perhaps the app’s standout feature, though, is its product search. Instead of filtering by price or availability, you select the members of your network from which you’d like to see results.

“We’ve built it in such a way that you can say, ‘Hey, what are my friends of friends recommending?’,” Shaffer said. “It surfaces second-degree network people that might have a similar taste style demographic to you.”

Masse operates on an affiliate model currently — it acts as a middleman between its community and ecommerce giants like Amazon and Walmart, which pay out a percentage of completed sales. That’s its only form of monetization, and Shaffer and Brockhoff don’t foresee it changing anytime soon.

“Consumers are savvy — they can figure out when they’re being marketed to,” Shaffer. “What we’re doing at Masse is [making] it a lot easier to ask for and share recommendations with friends — we’re unifying conversations that are happening across multiple different platforms right now.”

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Source: VentureBeat

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