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Wordnerds creates meaning from large volumes of unstructured data. We bring together AI, Corpus Linguistics and Data Science for language understanding on an industrial scale
About
Wordnerds creates meaning from large volumes of unstructured data. 80% of all the data that exists is in the form of unstructured text. We bring together AI Scientists, Corpus Linguists and Data Analysts to provide language understanding on an industrial scale. We have two principal products: Stargazer - Find out what your customers really think. Stargazer aggregates and analyses online product reviews to show simply, and in real time, what people like and dislike about your products. We help global brands develop better products and understand their strengths and weaknesses relative to competitors at a glance Haystack - Find new customers or monitor key issues Haystack locates hidden gems amongst the noise and madness of social media. Whether it’s leads you want, an early warning system for problems with products or just a steer on a thought or idea, Haystack turns the internet into the world’s largest focus group.
Key Benefits
When people talk about big data, mostly they mean numbers. Yet 80% of all data exists in the form of unstructured text; in emails, online reviews, tweets, customer service databases and word documents. Many organisations - particularly larger ones - would benefit from the ability to: Find specific types of text in large datasets (problems with their products on Twitter, emails relating to a person in relation to a GDPR enquiry etc.) Instantly understand large corpora of data to provide actionable insight (what learning can you glean from your 5000 Amazon reviews? What problems do you have that similarly sized competitors don’t?) Monitor sentiment/issues relating to a product, service or brand in real time (what issues are your customers happy and sad about? How is that changing over time, relative to your efforts?)
Applications
Both of our current products were developed because large organisations couldn’t find what they needed on the market: Nissan wanted to identifying problems with new cars in online comments without unmanageable levels of noise; Tommee Tippee needed to aggregate, track and understand hundreds of thousands of online product reviews, what people liked and disliked about their individual baby products.