Predictive analytics is the sweet spot where machine learning meets the enterprise. Analytics & predictive algorithms fused together mean we can now gains insight into how future patterns and trends may develop. This type of technology has ramifications across industries, but many are left clueless about the development and applications in this field. But never fear- we’re here to help. These 10 influencers provide a fascinating and hassle-free entry point into the world of predictive analytics.

As always, a note on our methodology: we discovered and ranked influencers based on Twitter activity around “#PredictiveAnalytics” and “Predictive Analytics”, using Keyhole, FollowerWonk, Klout, and a little of our own algorithmic magic to compile the sources. The list contains influencers from a diverse range of backgrounds, including media moguls, serial entrepreneurs and academics. Still have a burning passion to tell us who our formula missed? Be sure to let us know in the comments.

1. Gregory Piatestsky (@kdnuggets)
Gregory is the President of KDNuggets, who have been covering innovations in the fields of analytics, data mining and big data for almost 20 years, so it’s no surprise to see his name come up on this list. He recently published some fantastic analysis on Gartner’s Advanced Analytics Magic Quadrant– in short, Microsoft has made leaps and bounds in this field, Alpine Data Labs & Alteryx are on the rise, and SAS continues to lead the field.

2. Vineet Vashishta (@v_vashishta)
Vineet is a consultant based out of San Francisco, with almost 20 years experience in data & statistical analysis. His consultancy firm now specialises in predictive analytics & data science. Recent predictive analytics tweets from Vineet include this fantastic article on “the ethical blindess” of algorithms & predictive models, and how to make your predicitve analytics strategy more pervasive. 

3. Aki Kakko (@akikakko)
Boasting over 32,000 Twitter followers, it’s little wonder that Aki Kakko made the final list. Aki is a serial entrepreneur, who is currently a Co-Founder & Head of Product for Joberate, a predictive analytics-fuelled HR tool which mines publically-available digital footprints to match the right candidates to companies. His Twitter is also a treasure trove of HR insights.

4. Mike Gualtieri (@mgualtieri)
I have fond memories of watching Mike’s “What is a Data Scientist?” tutorial back in my early days of researching data science, and can firmly attest that Mike Gualtieri deserves his place on this list. As Forrester’s analyst for Big Data, Hadoop, Spark & Predictive Analytics, Mike has his finger firmly on the pulse of news & insights from across the data science sphere, which he shares both on Twitter and on his Forrester blog. His Twitter bio also states he enjoys “improvisational swing dancing” with his wife- always good to know.

5. Michael Wu PhD (@Mich8elWu)
Dr. Michael Wu is the Chief Scientist at Lithium, where he uses complex data-driven methodologies to analyse the social web. As well as predictive social analytics, Michael is also passionate about gamification, analytics and data mining. Recent awesome predictive analytics projects he’s shared include predicting the Oscars and an app that can predict the future price of flights. 

6. Timo Elliott (@timoelliott)
Recently also making an appearance in our Internet of Things Influencers list, it appears our formula loves Timo’s tweets. Timo is an Innovation Evangelist for SAP, and well-versed on all things business analytics and future-facing tech. As well as tweeting about the recent release of SAP Predictive Analytics 2.0, he’s also shared this fantastic list of predictive analytics success stories– well worth a read.

7. Brian Burke (@Adv_NFL_Stats)
A niche player, but a significant one. Brian Burke runs AdvancedFootballAnalytics.com, which has been providing realtime predictive NFL analytics since 2009. Recent analytical highlights he’s shared include his own piece on the value of a good analytics programme, ESPN’s rankings of how well teams have adapted to the analytical age, and this piece on probablistic valuation on player’s contracts.

8. Dirk van den Poel (@dirkvandenpoel)
Dirk is A Professor of Marketing Analytics, Analytical CRM, Predictive Analytics & Big Data at Ghent University in Belgium. Dirk’s course focuses on using R, Hadoop, Spark and Python to delve in to the analytics life cycle, with a particular focus on predictive analytics for CRM. He regularly tweets about his classes, European lectures and events, and the odd entertaining image about being a Professor.

9. Dave Elkington (@DaveElkington)
Dave is the founder of Inside Sales, a company who offer a sales acceleration with no less than 4 predictive analytics products. The most famous of these products is NeuralView, a self-learning predictive analytics engine which claims to be able to boost sales by an impressive 30%. The company celebrated their 10th birthday last year, so it’s safe to say Elkington is a knowledgeable source on the evolution of the fast-paced predictive analytics industry.

10. Ronald van Loon (@Ronald_vanLoon)
Ronald is the Director of Business Development for Adversitement, who specialise in on & offline customer journeys. Their work involves reducing churn by predicting which customers may soon jump ship, and predicting buyer intent to offer more sophisticated and relevant product recommendations. Recent content shares from Ronald include Using Decision Modeling to Make Predictive Analytics More Pervasive, and this insightful piece from NextGov on why most companies don’t need real-time analytics- yet.

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(Featured image credit: William Warby, via Flickr. Because everyone loves a bit of Back to the Future.)

The San Francisco 49ers recently opened their new $1.2 billion Levi’s Stadium in Santa Clara, which can seat 68,500 fans. They’ve also devised a novel way of finding out more about who exactly is filling those seats- a fan engagement programme called the Faithful 49, which offers fans exclusive incentives like tickets to sold-out games and lunch with the players in exchange for one thing- their personal data.

“This is not only providing fans with a fun way to engage with the team and compete with one another,” Chris Giles, 49ers director of business operations, told Silicon Valley Business Journal. “It incentivizes them to report activity and preferences and those sorts of things.”

The privacy policy for the programme upholds the right of the 49ers to share the fan data garnered “with our owners or any of our affiliates and with all other members of the NFL Family.” The data fans provide can be anonymised, aggregated and shared “for any reason at our sole discretion”.

What 49ers fans get in return for their data (click to enlarge); source

How exactly are the 49ers going to benefit from these unique insights into customer behaviour? Julia Jacobson, a partner at the law firm McDermott Will & Emery and data privacy specialist, explains. “The most concrete and the most lucrative use of fan data for any sports team is to prove to advertisers that they have a fan base,” she remarked. “They take their audience, they slice and dice it, they figure out how to make the SAPs or the Levi Strausses — the deep-pocketed companies — pay $10, $12, $15 million a year.”

The NFL launced a similar initiative last year in conjunction with Twitter, which allowed fans “to engage with customized NFL video content”. The tool also offered fantasy football advice, tapping into an increasingly lucrative market which is valued at $4 billion.

The 49ers ranked 12th among 32 NFL teams for fan engagement during the 2012 season. Perhaps the opening of their new stadium and the power of big data are the perfect ingredients to move them up the rankings.

Read more here.
(Image credit: Silicon Valley Business Journal)

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(Image Credit: Nathan Borror)

When the Oakland Athletics first pioneered their “Moneyball” approach to baseball, they received a fair amount of scepticism. Today, however, using data to help you assemble the right team and get to know your opponents has become an ubiquitous approach across many different sports. We’ve reported on its use in basketball, football– and now, the NFL has spoken out about how emerging technology is changing the face of American football.

The first change? The NFL has its own CIO, Michelle McKenna-Doyle. “For the first time in its history, the NFL really decided it needed a CIO about two years ago, two-and-a-half years ago,” McKenna-Doyle stated at a conference on Friday. “It had various heads of IT that did various pieces and parts, but we had a very disparate technology footprint across our digital businesses and our sort of corporate, back-of-house type of businesses.” Like alot of CIOs, McKenna Doyle has overseen a shift from systems to services, from the mainframe, to a client-server model, and finally into cloud computing. “Believe it or not we still had some old applications that not that long ago were recently migrated,” she remarks. “Now, we’re all living in this third platform, which is really around all the analytics, big data, making sure it all runs on the cloud and the Internet of things.”

Although to say the NFL has been working with big data for a short amount of time would be inexact. Like many large institutions, the NFL have had big data for years, before big data became the buzzword it is today. What they perhaps didn’t have until recently was an understanding of just what this data could do for them. McKenna-Doyle outlined some of the ways the NFL are using data and new technologies to change the game, which included:

• NFL Vision- A data-driven platform which provides teams with data that can optimise scouting programs and provide insights into opposing teams. NFL Vision contains videos for each and every reported statistic; an agreement with the NCAA was recently struck, so that the Vision platform will now also include clips from the players’ college days. The public can also gain access to NFL Vision for a premium- something which die-hard fantasy team managers will undoubtedly be excited about.
• “NFL Now”- Although not yet officially named, “NFL Now” refers to a customisable app which will aggregate content on a particular user’s favourite teams and present them as a personalised channel. The app is expected to be released over the summer.
• Digitised Medical Records- In compliance with the Health Information Portability and Accountability Act (HIPAA), all of the players’ medical records are now electronic. McKenna-Doyle highlights that whilst it’s not the most glamorous of these initiatives, it was a major and significant undertaking for the NFL.
• On Field and Sideline Technologies- McKenna-Doyle highlighted this field as a considerable focus of hers. “It’s a very crowded RF space in these stadiums and it’s not getting any better,” she remarked. “Frequency coordination, and continuing to develop these communication systems and have them encrypted, is a big part of my job.” Work in this field includes establishing wireless communication between coaches and players, and establishing a communications infrastructure which will seamlessly involve the league office in New York with all instant-replay decisions.
• Bye Bye Binders- Even casual observers of American Football will have noticed coaches and players consulting a binder of still photos of the last set of plays before a player hits the field. But these binders are on their way out, slowly being replaced by Microsoft Surface tablets. Although only still photos are currently permitted, it’s possible that coaches and players will be able to access video content from the sidelines in future

These innovations will change the game for everyone- for players, coaches and enthusiasts alike.

Read more here.
(Image credit: Flickr)

Competitve Edge, a new digital platform, will be providing Big Data insights into the world of Fantasy Football from August onwards. Beyond the traditional approach of picking players based on past performance metrics, Competitive Edge will allow users to make informed decisions based on mental, physical and environmental factors which could impact a player’s performance.

Michael Wilson, a Co-Founder of Competitive Edge, discussed the advantages of using behavioural psychology when picking the perfect team. “We believe the saying that football is 10 percent physical and 90 percent mental holds true, and using data to make smart fantasy picks is an untapped advantage. We’re providing insights and information that has not been seen before with the purpose of guiding fantasy players to make more informed decisions. This will, in return, provide positive measurable results in your fantasy sports picks.”

Factors the system will aggregrate will include:

• Physical- Not just up-to-date injury reports, but also information on historical injuries which could affect performance
• Mental- ‘Intangibles’ which could affect a player’s state of mind
• Environmental- Data on weather, altitude, region, types of offence & defence

Competitive Edge will become available in time for this year’s Fantasy Football season and will cost $5 a month. They are already working on extending their platform to include baseball, basketball, soccer and boxing. With 32 million people playing fantasy sports each year in any industry that’s worth $4 billion, companies exploiting performance metrics like Competitive Edge could prove highly successful.

Read more here.
(Photo credit: Johann Schwarz)