Reimagine Your Content Capabilities with ginnie (formerly Kopigin)
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A Description Tool that Understands Your Products
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As more consumers turn to the web to research and purchase items on their shopping lists, product content has become increasingly important. For eCommerce sellers with larger catalogues, creating rich product descriptions can be time-consuming and costly. Until now.
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With ginnie, retailers, marketplaces and sellers on merchant platforms are able to generate thousands of unique product descriptions quickly and affordably. Utilizing Artificial Intelligence (AI), this content writing software automatically transforms raw product specifications into engaging, unique, optimized content.
Discover ginnie's Impressive eCommerce Capabilities for:
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A Better Way to Grow your eCommerce Catalogue
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Quick Turnaround: Create thousands of product descriptions in minutes and accelerate large-scale projects.
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High Volume: Automatically generate unique and consistent product content for your entire catalogue.
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Enterprise Solutions: No company or catalogue is too large for ginnie; custom programs are available.
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Competitive Content: ginnie creates rich product descriptions that leverage high-volume keywords for Search Engine Optimization.
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Fully Customized: Content is based upon brand standards and marketplace guidelines. No guidelines? No problem.
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Professional Level: The product descriptions generated by ginnie are indistinguishable from those written by human copywriters.
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Our Solution Brings Natural Language Generation to eCommerce.
- At its most basic level, AI is a group of systems that allow machines to accomplish tasks previously completed with human intelligence alone.
- Natural Language Processing (NLP) encompasses the parts of AI focused on computational linguistics, both spoken and written.
- This includes common practices like speech recognition and text-to-speech software. It also includes the practice of language generation.
With NLG, our product description generator tool only requires structured product data that can then be interpreted and transformed into human-level narratives that consider context, grammar, syntax and more.