DataSwarm Analytic Engine
FINDING THE ZEITGEIST
BBC: Needed “to understand the Zeitgeist” – find the differences in tropes and topics between its news output and its competitors, in real time across all media output.
SOCIAL + ENTERPRISE DATA
Large UK Telecoms Provider: Combined social data and customer services data and tailored its service operations to optimise the service delivery for customer satisfaction and retention
INNOVATION & INSIGHT
Global Cosmetics Co: Identified zeitgeists to understand the differences and similarities in future trends between markets enabling focussed product development.
SALES & MARKETING
Global drinks supplier: Located customer sub-groups to understand the cultures and requirements to optimise product advertising messaging by geography and media type.
Monitoring & Alerts
Receive alerts and specified data in real time about events, emerging trends, risks and issues e.g. for crisis management work.
Smart Systems
Integration and monitoring data sources of large scale systems such as Smart City and Internet of Things applications
Swarm Intelligence
Swarm intelligence, NLP and other advanced high speed data analytics enable us to design bespoke client solutions for advanced business intelligence e.g. game theory based scenarios.
Stock Prediction
Capable of understanding and predicting people’s intentions such as stock price tracking, spotting language shifts and predicting election outcomes.
About DataSwarm
The DataSwarm Analytic Engine (DAE) uses advanced analytics to create highly valuable intelligence across all areas of the value chain. Core technologies include use of dynamic algorithms, language processing and high speed data analytics.
The system was originally designed to solve the problem of finding and sequencing tropes, trends and memes quickly and efficiently across vast quantities of media data, and can integrate social media, internal enterprise and "Internet of Things" datastreams. It is designed for flexibility and for example has been used for applications from front end social media analytics to back end customer service improvement, and from Influencer identification to election prediction.
The DAE is format independent, and so can work in most languages (human or machine).
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Sales and Marketing
Expose deep industry trends and uncover sub-tribes. Build on memetic insights to develop campaigns with context. Crisis management applications in real time.
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Customer Experience
Pinpoint factors of customer satisfaction and discontent. Establish key drivers to predict defection and enhance customer retention.
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HR & Internal communications
Highlight trending topics and trigger meaningful actions across the organisation. Build employee engagement and help with employee retention.
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Product & Service Innovation
Detect and predict trends & tropes across all industries to identify product demands enabling focussed product development.
Management Team
Janet Parkinson
David Short
Alan Patrick
Andy Wise
Clients
Applications of DataSwarm technology
We believe the best solutions require both algorithms and human expertise. Combining the DataSwarm Analytic Engine (DAE) with our deep consulting experience allows us to create innovative approaches and tailored solutions. We were finalists in the IET (Institute of Engineers and Technologists) Innovation Awards 2017. Learn more about the DataSwarm Analytic Engine.
Latest News
Predicting the EU Referendum
Daily Relative shifts in sentiment vs volume for the last 31 days – the widely variant yellow signal is the Liberal Democrats, if we get this prediction wrong we’re blaming them! We turned the DataSwarm system onto the UK Local Elections, it did “OK” – saw the Tory & UKIP crashes, the Labour small drop[…]
Tracking IPOs – Lyft vs Uber
In testing the Dataswarm Analytic Engine on stock analysis and prediction, we are tracking the events leading up to the IPOs of a number of “Unicorns” – Uber, Lyft, AirBnb and Slack – to see if there is anyhing that can be learned from the social (and other) media coverage to predict what the IPO[…]
We have Lyft off – tracking the Lyft IPO
Chart end of day March 29 – Volume of “analyst” discussion on 4 key unicorns, starting with Lyft S-1 filing on March 1st A number of the better known large private Tech companies (the “Unicorns”) recently announced they are going to hold Initial Public Offerings (IPO’s) of public shares (or stock) in 2019, in fact[…]
Brexit Today: Revoke Article 50 vs No Deal – Day 2
Above – comparing traffic between “No-Deal” and “Revoke” tropes on Twitter, 1.30pm March 22nd. Note the “dip” on the curves on the last day is because we are ony half way through the day and yesterday was a major peak, it will rise as the day progresses and traffic count increases. Below – comparing traffic[…]
Brexit Today: Revoke vs No-Deal
Above – Graph and text updated c 10.30 pm In the twisting and turning of Brexit, yesterday (20th March), 9 days before the UK should have left the EU, the Government finally (after weeks of it being clear it was inevitable) sought to delay the date of leaving. The “Remain” grouping were hoping for a[…]
Brexit Today – What are the various political parties talking about?
We’ve been looking at what actual Members of Parliament (MPs) are saying about Brexit. This is the output by all the MPs with Twitter accounts over the late Jan – early March period. This is the first post on this analysis and is about volume. The lines show daily number of tweets and are independent[…]
The challenge for Challenger banks (Revolut edition)
Graph shows change in cumulative perception over time for Monzo, Revolut, NatWest and Lloyds. Over the last few weeks the Challenger bank Revolut has had a very challenging time with its market perception, due to a catalogue of errors. We won’t list their problems here, but there is a good summary on Bloomberg.[…]
Perception drag in Retail Banking
We have now completed our analysis of the pereception of “traditional” high street banks vs new “Challenger” banks. We analysed social media from October 2018 to January 2019 for the “Traditional” banks NatWest and Lloyds, and “Challenger banks” Monzo and Revolut to understand how they were perceived, how it differed, and what lessons could[…]
Retail Banking in the Fintech Age
Retail banking in the UK is supposed to be undergoing a transformation. With relatively limited choice & competition between the main incumbent players, the Government is keen to encourage a new breed of banks, the so called “Challenger Banks”. We used our DataSwarm system to understand the difference in customer perception and usage between the[…]
Brexit Today – Are we headed for Martial Law?
Today the newsfeeds have been full of a story about the UK Government preparing for martial law in the event of a Brexit No-Deal. So, are we really headed for Martial Law? When we looked at this, it was interesting to note that this story has a large spikes round about once a month –[…]