Machine learning-led community marketing tool that identifies and engages top brand fans on social media.
Brands struggle to identify and engage their most loyal social media fans, relying on low-engagement influencer marketing.
Brands struggle to identify and engage their most loyal social media fans, relying on low-engagement influencer marketing.
Uses machine learning, computer vision, and NLP to detect top 1% superfans and activate them for authentic content and advocacy.
Uses machine learning, computer vision, and NLP to detect top 1% superfans and activate them for authentic content and advocacy.
Zyper was acquired by Discord in January 2021.
Event Year: 2021
Acquirer: Discord
Zyper was acquired by Discord in January 2021.
Event Year: 2021
Acquirer: Discord
Zyper developed a platform focused on community marketing for brands. It used machine learning to pinpoint the most engaged social media followers, known as superfans, and facilitated their involvement in brand advocacy efforts. This approach aimed to transform passive followers into active promoters through authentic user-generated content.
The platform employed computer vision and natural language processing to analyze social media activity. These technologies enabled precise identification of a brand's top 1% of organic fans. Brands could then invite these superfans to participate in campaigns, rewarding them with products or experiences in exchange for content creation. This method targeted everyday consumers with high engagement rather than large-scale influencers.
Zyper's system fostered hybrid loyalty programs. Superfans received incentives to produce content that sparked conversations and provided insights into products and purchases. Participating brands included companies in fashion, beauty, and consumer goods sectors. The platform emphasized peer-to-peer advertising, leveraging the authenticity of fan-generated material to boost engagement and conversions.
Zyper developed a platform focused on community marketing for brands. It used machine learning to pinpoint the most engaged social media followers, known as superfans, and facilitated their involvement in brand advocacy efforts. This approach aimed to transform passive followers into active promoters through authentic user-generated content.
The platform employed computer vision and natural language processing to analyze social media activity. These technologies enabled precise identification of a brand's top 1% of organic fans. Brands could then invite these superfans to participate in campaigns, rewarding them with products or experiences in exchange for content creation. This method targeted everyday consumers with high engagement rather than large-scale influencers.
Zyper's system fostered hybrid loyalty programs. Superfans received incentives to produce content that sparked conversations and provided insights into products and purchases. Participating brands included companies in fashion, beauty, and consumer goods sectors. The platform emphasized peer-to-peer advertising, leveraging the authenticity of fan-generated material to boost engagement and conversions.
Total Raised: $8.5 million
Last Round: Series A: $6.5M led by Talis Capital (2019)
Total Raised: $8.5 million
Last Round: Series A: $6.5M led by Talis Capital (2019)
SaaS platform for brand community management with campaign rewards
SaaS platform for brand community management with campaign rewards
Consumer brands in fashion, beauty, and goods like Banana Republic, Coty, Nestlé, Topshop
Consumer brands in fashion, beauty, and goods like Banana Republic, Coty, Nestlé, Topshop
unknown
Hiring: unknown
unknown
Hiring: unknown
Zyper participated in Y Combinator's Winter 2018 batch. The company expanded operations, establishing a presence in San Francisco alongside locations in London and New York. It pursued self-service features to onboard more brands and enhanced its predictive analytics and recommendation algorithms. Engineering and sales teams grew to support scaling.
Zyper participated in Y Combinator's Winter 2018 batch. The company expanded operations, establishing a presence in San Francisco alongside locations in London and New York. It pursued self-service features to onboard more brands and enhanced its predictive analytics and recommendation algorithms. Engineering and sales teams grew to support scaling.
By focusing on superfans with smaller but highly engaged followings, Zyper differentiated from traditional influencer marketing. It highlighted higher engagement rates and repeat content from genuine advocates. The platform sought to decentralize advertising by empowering brand communities. Plans included launching a dedicated app to broaden fan access beyond invitations.
By focusing on superfans with smaller but highly engaged followings, Zyper differentiated from traditional influencer marketing. It highlighted higher engagement rates and repeat content from genuine advocates. The platform sought to decentralize advertising by empowering brand communities. Plans included launching a dedicated app to broaden fan access beyond invitations.
Founded by Amber Atherton, Zyper drew from her experience in e-commerce and community building. Atherton advocated for leveraging everyday customers over celebrities for organic growth. The company's trajectory reflected ambitions to disrupt marketing through data-driven fan identification and community scaling.
Founded by Amber Atherton, Zyper drew from her experience in e-commerce and community building. Atherton advocated for leveraging everyday customers over celebrities for organic growth. The company's trajectory reflected ambitions to disrupt marketing through data-driven fan identification and community scaling.
