Isabel Alexandre

Meet CODE_n finalist Viewsy

Viewsy provides analytics for offline retailers by supplying insights about customer behavior patterns, such as customer loyalty and time spent in the shop. The British location analytics startup comes to solve a common problem faced by retailers: understanding customer behavior in physical space in order to manage businesses better.

Odera Ume-Ezeoke

Odera Ume-Ezeoke, founder and CEO of Viewsy

The startup, founded in 2011, is rapidly growing and already counts clients like Vodafone and ABN AMRO bank. In today’s interview, we talk to Odera Ume-Ezeoke, founder and CEO of Viewsy, about how they use Big Data to help companies effectively manage physical environments.

The first thing we read on Viewsy website is: “Measure and Manage foot traffic like never before”. Could you briefly explain how it works?

We install discrete passive sensors in store to analyze visitor movements within and between the client’s stores. This data is anonymized and then securely transmitted to Viewsy’s analytics platform, which calculates store statistics on footfall, store visitor flow, and other key metrics. The resulting analysis and data is made accessible via the Viewsy dashboard and reporting suite.

Does this technology also benefit consumers?

Absolutely – our technology has a wide range of applications, including many that have a direct benefit to customers, such as improving store layouts to avoid overcrowding, reducing checkout queue wait times, understanding surge footfall to increase safety (such as in a large arena or football stadium), and enabling better positioning of customer service or security staff. We also offer retailers the ability to provide an option for customers to opt-in and receive special offers and discounts.

How do you think physical shops of the future will be?

When I visualize the retail store of the future, I see a cross between Amazon, Argos, and Apple – A wide open retail showroom space with a very human approach to product education and support, served by an enormous, wholly-automated stockroom that can fulfil purchases within a couple of minutes. In this vision, the relationship between customers and the brands has the same directness that we are starting to see develop with virtual shops, with customers able to use their smartphones to interact with areas of the physical store to leave feedback, receive product recommendations and offers, and conduct product research.


Isabel Alexandre

Meet CODE_n finalist Aentropico

Sebastián Pérez Saaibi

Sebastián Pérez Saaibi is the CEO of Aentropico

Aentropico is a Latin American Predictive Analytics startup, based in Bogotá, Santiago and Rio de Janeiro. It helps medium and large businesses by transforming common data sources into powerful predictive insights that improve decision-making. The startup is one of the Top 50 finalists of CODE_n and will be at the CeBIT 2014 to present its Big Data solutions. 

In today’s interview, Sebastián Pérez Saaibi, CEO and Co-Founder of Aentropico, tells us how their DataApps can increase sales, cut costs and enhance the productivity of retailer companies. He also talks about their expectations of being part of CODE_n.

Aentropico is present in various Latin America cities. Does it benefit the startup in a different way?

Being in several countries is a calculated risk that we took as an opportunity to have the best of both worlds: In MassChallenge (Boston, MA) we were able to strengthen our ties to the MIT MediaLab and Harvard research groups as well as test our product with the powerful MC mentor network. On the other hand, at 21212/StartupBrasil we leveraged their strong commercial, talent, and mentor networks in Brazil to be able to have a soft landing in the country. Knowing the Chilean and Colombian ecosystems as a part of StartupChile and operating in these countries gives us a strong Pan-American expertise and connections. These ingredients have contributed to a more mature startup, ready for the challenge of becoming Latin America’s prime Predictive Analytics company.


Isabel Alexandre

Meet CODE_n finalist G|Predictive

Björn Goerke is the CEO of G|Predictive

Björn Goerke is the CEO of G|Predictive

G|Predictive is a startup based in Germany that offers individual predictions on constantly recurring questions within the marketing and sales process. The enterprise developed Customer Lifetime Suite, a software-as-a-service application which provides an up-to-date overview of the current and future behavior of customers, each of which is analyzed individually. We are looking forward to meeting G|Predictive, one of the Top 50 finalists at the CODE_n contest at this year’s CeBIT. Björn Goerke, founder and CEO of the startup, will tell us a little bit more about their Big Data solutions and also how they are preparing for CODE_n.

When was G|Predictive founded and what was its inspiration?
G|Predictive was founded in December 2009. We started off consulting in the general field of big data. We soon realized that we there was a need for products. So, in late 2011 we made a complete u-turn and subsequently withdrew from the consulting business to focus on the product business. We hired data scientists and developers, and are currently building a sales force and are delighted to report that we are gaining momentum. More…

Isabel Alexandre

Meet CODE_n finalist Precogs

Adrien Sandrini is the CEO of Precogs

Adrien Sandrini is the CEO of Precogs

Precogs, a startup based in Paris, offers tailored supply-chain solutions for the electronics manufacturing industry. As a CODE_n finalist, the company will present their predictive data analytics solutions at CeBIT.

Adrien Sandrini, the CEO of Precogs, tells us a bit more about how it uses big data to foresee critical aspects of supply and demand. He also talks about the company’s expectations for participating at CeBIT as one of the 50 most innovative big data startups.

How can predictive analytics tools help the electronics supply chain?

Predictive technologies offers a new way for electronic manufacturers to broaden their scope of what is possible to create visibility within the supply chain. The integration of big data principles is very new to the industry, but can truly change the playing field for those who integrate such solutions. The amount of data that is integrated to predict the electronics manufacturing supply chain has and will continue to substantially save companies the costs of supply disruptions.

How was the startup founded and what do Precogs’ unique solutions offer?

Precogs was founded in 2011, after my many years of working in the automotive and electronics manufacturing industry.

In terms of supply chain, both industries are quite different. The difference was the volatility of the supply chain in electronics manufacturing, and this equated to unpredictability of lead times and the imbalances in supply and demand.


Janina Benz

CODE_n14 Conference Program is here!

In addition to the 50 CODE_n14 finalists, who will present their business solutions referring to this year’s topic „Driving the Data Revolution“, the exhibition area will feature an attractive conference program throughout the entire week. Get to know the CODE_n14 startups and their big data solutions during numerous of inspiring Fireside Chats on stage. Further highlights include the Young IT-Day, the Google Data Dialogue, and of course the CODE_n Award Show.
Please note that there can be changes in the conference program during the next weeks but we keep you (and the slideshare presentation) updated of course!

Felix Jansen

BIG Data, BIG Design: Clemens Weisshaar and Reed Kram make CODE_n the place to be at CeBIT

They have been hailed as “the poster boys of a new breed of digital designers” by the International Herald Tribune; their works have been embraced by the Museum of Modern Art in New York, Centre Pompidou in Paris and Vitra Design Museum in Weil am Rheim– Clemens Weisshaar and Reed Kram are, without question, one of the most sought-after designer duos in the international scene. Their most recent stroke of genius can be marveled at in Hanover from March 10 to 14: a spectacular example of trade fair architecture, developed specifically for CODE_n at CeBIT. This is their awe-inspiring and uniquely characteristic answer to a simple question: How big is Big Data? We spoke to Clemens Weisshaar about their concept for Hall 16.

Clemens Weisshaar

Clemens Weisshaar

Felix Jansen (FJ): Hi Clemens. There are a good 30 days to go until the next CeBIT trade show in Hanover. It’s not normally the sort of event you’d put into your planner. But this time, you and your design partner Reed Kram are responsible for what’s probably the most exciting hall design at the entire trade show. What should visitors to Hall 16 brace themselves for?
Clemens Weisshaar (CW): Definitely a radical departure from classic trade fair construction– instead of lining up a series of cubicles, we’ve occupied every dimension of the hall. This is an architecture that sculpts the full volume of Hall 16. A 2,900 square meter multi-terapixel panorama helps re-imagine the hall as a forum for the exchange of ideas. This is the anathema of monotony.


Isabel Alexandre

The Google Maps for the brain – Meet CODE_n finalist Mint Labs

Paulo Rodrigues

Paulo Rodrigues is the CEO of Mint Labs

Mint Labs is a startup from Barcelona that uses Big Data to help doctors provide a better diagnostic and treatment for patients with brain diseases, creating complex 3D maps. They are one of the 50 CODE_n finalists that will be on March at the CeBIT talking about their visualization and image manipulation platform.

In today’s interview we talk to their CEO, Paulo Rodrigues, about Mint Labs’ trajectory and its intersection between Big Data and science.

How and when was Mint Labs created?

We have been working together for more than 7 years. We met in the Netherlands, where we were doing our PhDs in neuroimaging. We were developing our new brain analysis algorithms with a software program, with the goal of providing it to our medical collaborators. But we realized that there was an important gap. The tools were too complex, with complicated interfaces, and high computational needs.

That was the beginning of Mint Labs. We then moved to Barcelona in 2011, working in important research institutions, and we started shaping the business idea and the business plan. We entered the Wayra academy in 2013, when Mint Labs officially started.

Could you briefly explain your project to us? 

We build Google Maps for the brain. We use advanced MRI technology capable of capturing microstructural properties of the brain tissue to provide detailed 3D maps of the brain. Our tools evaluate the structural condition of the nerve fibers affected by a given neurodegenerative disease (multiple sclerosis, Parkinson’s, Alzheimer’s, among others). And all of this is provided in our brain imaging analysis platform on the cloud.


Isabel Alexandre

Meet CODE_n finalist Swan Insights: “Big data startups can be the Sherlock Holmes that companies need”

Laurent Kinet is the CEO of Swan Insights

Laurent Kinet is the CEO of Swan Insights

Swan Insights is a Belgian startup that combines big data with social Web analysis. It helps organizations get the most out of external data, delivering strategic insights as the fuel for decision-making and targeted action. The company is among the 50 most innovative big data startups in the world to be selected by CODE_n. 

Laurent Kinet, the CEO, talks about the big data scene, the characteristics of Swan Insights, and the company’s attendance at CeBIT in March.

How can big data change the way companies work today?

Big data enables companies to switch from “guess” to “know”. Most companies already process their internal data with data mining techniques in order to enlighten managers and guide them to make appropriate decisions. However, there is a two-fold problem with that: First, they disregard all external information available, such as social media, public data or other kinds of knowledge outside their walls; second, those analyses are structured queries in tabular databases, while the connections between pieces of information contain new kinds of insights and allow new-generation algorithms that deliver amazing results.

As a result, companies work with an incomplete view of their stakeholders, which can range from customers and suppliers to competitors or partners. For instance, customers are defined and segmented through business-specific criteria, through what they buy, what plans they subscribed to, etc. This can only capture 0.1% of an individual who, for the remaining 99.9% of the time, is making decisions outside the company. One can’t define a telecom customer only through the tariff plan he uses. He lives in a region, a city, has tastes, habits, opinions – and, above all, is connected to his network of people. His environment tells much more about him than what he says or buys.