DataSwarm Analytic Engine
Media: 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.
Stock Markets: Real Time Alerts
Capable of understanding and predicting people’s intentions such as stock price tracking, spotting language shifts and predicting election outcomes.
Innovation: Predicting trends
Global Cosmetics Co: Identified zeitgeists to understand the differences and similarities in future trends between markets enabling focussed product development.
MARKETING insights: intentions & cultures
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.
Integration and monitoring data sources of large scale systems such as Smart City and Internet of Things applications
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.
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.
The DataSwarm Analytic Engine (DAE) uses advanced analytics to create highly valuable intelligence across all areas of the value chain, across many sectors. Core technologies include dynamic algorithms and machine learning, language processing and high speed data analytics.
The system was originally designed to solve the problem of finding and sequencing trends and memes quickly and efficiently. It was built to process vast quantities of data, and integrate social media, other media, internal enterprise and "Internet of Things" datastreams. It has proved very flexible and has been used for applications from front end customer insight to back end customer satisfcation, from influencer identification to election prediction.
The DAE is format independent, and so can work in most languages (human or machine).
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.
Pinpoint factors of customer satisfaction and discontent. Establish key drivers to predict defection and enhance customer retention.
HR & Internal communications
Highlight trending topics and trigger meaningful actions across the organisation. Build employee engagement and help with employee retention.
Product & Service Innovation
Detect and predict trends & tropes across all industries to identify product demands enabling focussed product development.
Awards and Competitions
Reports and Research
In the News
Sign up for our latest report, "Retail Banking in a FinTech Age" looking at how customer perception has different impacts on Challenger and Traditional banks - what the impacts of "perception lag" are, and what banks can do about it.
DataSwarm Markets brings near real time social media data analytics to investment analysis. DataSwarm Markets processes social media messages about stocks as they occur, calculating the sentiment and publishing it in near-real time. This is useful for traders and analysts, for example for looking at pre-market opening sentiment, timing trades during the trading period, and[…]
Above – change in mindshare volume by day, by candidate, for the last 4 weeks. Boris Johnson continues to dominate polls and mindshare As they came to the first hurdle, 3 fell – Esther McVey and Mark Harper pulled out after low vote levels – and low signs of support from the DataSwarm system last[…]
Today is Theresa May’s last day as leader of the Conservative party, the “phoney race” of the last few weeks is over and from now on it is for real. The chart above shows the share of social media volume that each candidate has. As with when we first measured it, Boris Johnson tops the[…]
With today’s news that Prime Minister May will resign on 7th June, it was clearly time to have another look at the stakes for all the potential runners, following our last check in January 2019. Here is today’s graph, tracking back about a month’s worth of data of the cumulative social media conversation (there is[…]
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[…]
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[…]
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[…]
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[…]
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[…]
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.[…]