Lena Gaede

Digital transformation and customer experience – how data mining and big data analytics improve customer understanding

The customer is king and the king wishes new services nowadays. Induced by digitalization he has changed his expectations on services and products. While the customer can access product information and purchase easily mobile – whenever and wherever he wants – the competition between companies grows stronger. Thus, the most effective way to distinguish yourself from competitors remains the customer experience: it already drives two thirds of the decisions customers make, according to an insight by McKinsey. The motto is: provide a great customer experience – or you may lose your customer. And as usual, technology is your friend! Read on to find out how digital transformation and data analytics help to improve the customer experience.

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Filiz Sarah Gärtner

Meet our CODE_n CONTEST Finalists 2016: Valsight from Germany

All good things go by thirteen! Here we are with our last Applied FinTech finalist for the CODE_n CONTEST: Valsight. The Berlin based startup deals with the integration of value driver trees and advanced analytics into the controlling processes of planning, reporting and forecasting. How that works? Managing Director Khai Tran gives the answer!

What is Valsight all about? How did you come up with the idea?

valsight_logoKhai: Valsight is a SaaS solution for enterprise performance management and financial modeling based on value driver trees. The core of our software is a visual modeling editor with a powerful simulation engine that can be used to create financial models, for simulation-based planning and forecasting with predictive analytics. It makes financial controlling more focused and goal-driven by making processes more transparent, flexible and efficient. Our software is especially designed for the needs of management and financial analysts. No programming skills are needed to build financial models or to simulate different scenarios.

Our founding team came up with the idea for Valsight during many years of research with in-memory technology at the Hasso-Plattner-Institut in Potsdam. The growing importance of simulation and predictive methods in financial management combined with the maturity of in-memory technology for ultra-fast calculations was the ideal starting point. We have tested our approach early on with a Fortune 500 company, and have since then focused on building state-of-the-art SaaS software to dramatically improve corporate controlling and financial modeling.

“Digital Disruption“ – that’s the motto of this year’s CODE_n CONTEST. What makes your solution innovative, what makes it disruptive?

Khai: The idea of Valsight is to improve traditional controlling and financial modeling processes with methods like simulation and advanced analytics. Our focus is to empower business users to create complex and multidimensional models themselves and to benefit from statistical and predictive features. The core challenge is to keep a strong focus on the needs of the finance community in order to make even complicated functions easy and intuitive to use. More…

Filiz Sarah Gärtner

CODE_n Alumni | Catching up with … Massive Analytic

Massive Analytic, a pioneer in Artifical Precognition, was one of CODE_n’s finalists in 2014 and has come on leaps and bounds since its time with us in Hanover. In our next part of the CODE_n Alumni catch-up series, we talked to CEO George Frangou about the young company’s most important learnings and greatest achievements (like building a relationship with Microsoft) since then.

massiveanalytic

Following on from your time as a CODE_n finalist, what have been Massive Analytic’s greatest achievements?

George Frangou: I would say our greatest achievement has been the launch of Oscar AP on the Microsoft Azure Marketplace in June of this year. Our technology is now available for purchase. It’s exciting to be building that relationship with Microsoft. We’re also proud of our entry to the Lockheed Martin Virtual Technology Cluster. Getting both of those endorsements have been great for us.

What lessons have you learned or failures you’ve experienced and how have you coped with them?

George Frangou: The key lessons we have learned over the last year is to get our product messaging right. Often it is easy to be passionate about the product and describe it in a manner that does not resonate with the target audience. We were able to set that right on the back of our involvement in CODE_n and the client engagements that followed immediately.

What were your biggest takeaways from your time at CODE_n?

George Frangou: The biggest takeaway from CODE_n for me was seeing how many young innovative companies there are doing different and exciting things. It was great to share experiences and inspiring to see what’s going on. More…

Filiz Sarah Gärtner

GPredictive (Germany) – Knowing in advance who is bringing in the turnover

GPredictive-Björn Goerke

Goerke, Founder & CEO of CODE_n Alumnus GPredictive

As CODE_n finalists from 2014, they are attending CODE_n15 at CeBIT as start-up veterans: GPredictive from Hamburg analyzes buying behavior from customer data to derive patterns for the future. The young company offers its analytical expertise as software-as-a-service. This means that it is affordable for smaller and medium-sized companies too.

As alumni, you’re again represented at this year’s CODE_n15 at CeBIT. Looking back, what were your impressions last year of your CODE_n premiere?

Björn Goerke (GPredictive): I think the entrepreneurial spirit at CODE_n is really exciting. There was a tremendous amount of energy in the venue. And the interest that our stand generated was simply overwhelming. It was usually after 4 p.m. before I managed to get anything to eat … Being mobbed by so many interested trade fair delegates was great fun. Everyone who came to see us really enjoyed looking at our business model.

What’s happened to your start-up in the last twelve months?

Björn Goerke (GPredictive): We’ve doubled in size and we now have a ten-strong team. We sourced a major investor in the form of Target Partners, and we’re now in a position to increase our team even further. Overall, we’ve massively optimized our product approach. Our analytics solution “Scores out of a box” now runs virtually fully automatically, which means that we’re able to respond much more quickly than we did a year ago. We now have a mature product and a growing number of satisfied customers. More…

Isabel Alexandre

Meet CODE_n finalist AutoGrid System

AutoGrid System is based in Silicon Valley, more precisely, in Redwood City, California. The American startup organizes the vast and growing amount of energy data produced from an increasingly networked and automated grid. With deployments of smart meters, distributed generation, and other grid sensing technologies reaching critical mass, the electricity supply chain now has to deal with greater data volumes than ever before. And AutoGrid is here to work on this problem, improving the production and consumption of electricity.

Amit Narayan, founder and CEO of the startup, explains to us a bit more about how the company connects big data and the energy industry. He also talks about their experience at CODE_n during CeBIT.

Amit Narayan

Amit Narayan, founder and CEO of AutoGrid System

How does AutoGrid use big data, predictive analytics, and cloud computing to optimize the electrical grid?

Autogrid organizes the world’s energy data using Internet-scale, secure cloud computing to process the petabytes of information produced in an increasingly networked and automated grid. AutoGrid employs big data analytics to generate real-time predictions and implement programs for electricity generators, providers, grid operators, and their customers to optimize the use of assets across the grid and manage costs through a comprehensive Energy Data Platform (EDP)™

Apps built upon EDP™ are powered by forecasting and optimization engines, managing functions such as:

  • End-to-end Demand Response with our Demand Response Optimization & Management System (DROMS)
  • Home Energy Management through our customer portal, which Schneider is white-labeling as their Wiser product
  • Peak Charge Management for facilities with Energy Cost Optimizer (ECO), an app co-developed with NTT DATA

Who can use AutoGrid’s platform and how?

Anyone along the electricity value chain can use AutoGrid’s platform and apps, including utility companies, power retailers, ESCOs, facilities, and customers. Apps on the Electricity Data Platform (EDP) are Web-based. Users can subscribe via a Software as a Service (SaaS) model. Additionally, resellers can license the technology. Silver Spring Networks is reselling our DROMS app as their own product, as “Demand Optimizer” within their Utility IQ suite.

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Isabel Alexandre

Meet CODE_n finalist Avansera Oy

“Can you see the future? It is in your hands.” That is how Avansera Oy presents itself. The Finnish startup, that combines historic behavioral data with calculated future intent, can predict what consumers will buy.

Cormac Walsh, CEO and Founder of Avansera Oy, talks in today’s interview about how Big Data can benefit the Fast-Moving Consumer Goods companies and retailers. As one of the Top 50 finalists, he also tells us his experience at CODE_n’s hall during the CeBIT.

Cormac Walsh

Cormac Walsh is the CEO of Avansera Oy

Why create a startup like Avansera Oy?

There is a strong need from the Fast-Moving Consumer Goods (FMCG) industry to see what shoppers are doing in the physical world; this is the core of the need for our customers. To provide the necessary context, let us look at the current market analysis business. Consumer behavioral data is collected through online activity related to online activity, or through questionnaires and focus groups. These approaches are limited in terms of reach and accuracy. Online data collection related to online behavior misses the behavior in the physical world, whereas traditional questionnaires and focus grouping have low accuracy and are very expensive (non-scalable).

In Avansera Oy, we deal with both of these issues. By providing accurate and scalable consumer digital services specifically relevant to the physical world, we can offer a high-value service at a lower price point than the traditional competition.

In an average week in the EU, there are over 600,000,000 grocery trips, not much of this physical data is currently being collected. At Avansera Oy, we want to collect as much of it as we can, and use it to benefit industry and society.

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Isabel Alexandre

Meet CODE_n finalist Kreditech

Sebastian Diemer is the CEO of Kreditech

Sebastian Diemer is the CEO of Kreditech

Kreditech uses Big Data and complex machine-learning algorithms to enable faster and better credit decisions. The technology developed by the German startup identifies and scores individuals online and decides over instantly paid out loans. All based on the processing of 10,000 data points in real-time.

In today’s interview, we talk to Sebastian Diemer, founder and CEO of Kreditech. He tells us how the startup uses technology to provide banking products to customers in emerging markets, allowing unbanked people with no credit bureau history to get credit. He also tells us how they are getting prepared to present their Big Data solutions at CODE_n and CeBIT.

Could you briefly explain what Big Data scoring technology is?

Our technology takes into consideration every piece of information that can be obtained about a person. We then analyze the results with statistical methodologies collected from our self-learning technology. Several thousand individual data points are merged into one big mosaic picture within seconds. It is not about single stones being red or green but the shape of red or green areas, illustrating the importance of coherence among several different data pieces.

What sets Kreditech apart from its competitors?

In comparison to other financial service providers and established credit bureaus, Kreditech only does live scoring. That means that we rate a customer’s creditworthiness by only looking at his or her current financial status instead of historical data. We gather information at the moment the application is submitted. Unlike FICO or Schufa, we neither retain the data afterwards, nor do we sell it. Our unique sophisticated credit scoring process uses the powers of machine learning algorithms and Big Data infrastructure to allow us to analyze more than 10,000 data points in less than one minute. That is what is unique about Kreditech.

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Janina Benz

Viewsy wins CODE_n14 award

Since Monday, 50 startups from 17 countries have been presenting their innovative business models related to the topic of Big Data in the CODE_n hall 16 at CeBIT. The CODE_n jury has reached a decision: The coveted CODE_n award and prize money in the amount of EUR 30,000 were awarded to London-based Viewsy.

CODE_n14_Award_Ceremony

What does Viewsy do?

The UK startup offers retailers the possibility of understanding the behavior of their customers in detail. How much time do they spend on average in the store? Which areas do they frequent the most? How frequently do they visit the store? Viewsy’s technology acquires a variety of different data sources, such as distances walked, interprets them using statistical methods, and thus offers understanding of the behavioral patterns of customers. Brand owners can benefit from this as well by obtaining exact insights into where to best position which products in the store. Conclusions regarding the identity of individuals are purposefully excluded by Viewsy. All data is acquired anonymously. If a customer does not want to be analyzed while shopping, he can simply switch off the WLAN connection of his smartphone. More…