This is a brief note to explain why we are changing our name from BrandsEye to DataEQ. (The short answer is that BrandsEye no longer reflects our positioning, product strategy and the kind of enterprise data use cases we serve. Read on for the full story.)
BrandsEye started over ten years ago as an “online reputation management” tool, largely supporting campaign and brand reporting. Whilst we still do a lot of work for CMOs and their teams, the nature of this work has fundamentally evolved.
Today, our core USP is the use of a Crowd to improve the quality of the data we provide. Our Crowds are large, distributed workforces who we curate, train and then pay (mostly in BTC these days) to log into our gamified platform. They then apply their human intelligence to accurately mark-up unstructured customer and public feedback, enriching it for analysis. Interpreting tone, local context, sarcasm and slang still confuses even the best machine learning algorithms, so human “EQ” remains essential for reliable insights.
Our Crowds also work alongside our powerful AI in a symbiotic relationship, continuously training it to improve data quality. For example, our AI is excellent at identifying neutral conversation – which is of lower value, but often dominates any raw data set. By using AI to pre-screen this neutral conversation, we can eliminate irrelevant data and focus the Crowd’s efforts on valuable, sentiment-bearing data, enabling us to process much higher volumes of relevant data through the Crowd in real time.
Ultimately, this unique combination of using scaled human intelligence alongside machine learning allows us to create best-in-class data and, importantly, structure the raw data for things that AI cannot achieve on its own. This, in turn, unlocks enterprise data use cases in the customer experience, customer service and compliance management space that cannot be supported by “AI-only” social listening competitors. For example, many of our financial services clients now use our Crowd to accurately identify complaints and then structure these against the Treating Customers Fairly (TCF) market conduct framework – a task that is impossible for AI to achieve, but one that is now a legal requirement in many markets.
So, we needed a new name that spoke to our evolved enterprise data positioning and reflected our USP of using scaled human intelligence to produce quality, actionable data from unstructured customer feedback. We believe DataEQ does just that.
To visually capture this change, we’ve updated our logo to a “tilted Venn diagram”. We believe that this new logo neatly represents the coming-together of machine and human intelligence, but also hints at the complexity of interpreting nuanced human emotions – something our Crowd technology solves every day.
What hasn’t changed? We’re still the same team of sharp minds, committed to helping our clients find value in unstructured data. We still pride ourselves on providing world-class customer service, support, data analysis and reporting.
Please give us a shout if you’d like to unpack anything further around our new name and corporate identity, better understand our technology or get more information on the use cases we support.
We look forward to pioneering new ways to create valuable first-party enterprise data under the DataEQ brand.
Nic Ray CEO