We support businesses and universities in their digital transformation,
helping them to elaborate their strategies based on the most recent, accurate and relevant data. We provide them with actionable insights from benchmarks and survey data, combining machine learning and human expertise.
Keep readingWhy?
Convertible knowledge
After years providing research findings and reporting to our clients, we realized that it was useless: there were some comes and goes between teams and stake holders, some thoughtful comments, and then the data was buried and forgotten. Why? Because no data-driven strategy had been elaborated, nobody in the company was especially entitled or trained to make decisions and take specific action based on data. In the best scenario, it was a “data changed, do something” panic situation, a common pattern nowadays, with web sites traffic, marketing campaigns or sales funnels. On the other hand, we’ve seen medium size companies wasting fortunes in complex data-driven marketing automations that would finally generate a couple of hundred dollars in sales.
At Emerging Data, we consider there is no “graal” for actionable data: no machine learning algorithm, no generic big data hidden value. We believe in a case by case approach combining human analysis of a data context and machine Learning, that will lead to knowledge convertible - or not - into actions.
What we do
- Emerging Data helps you generate value from the data you own and third-party data
- Emerging Data helps you grow your product, your brand, your revenue by designing and executing the data-driven strategy that is right for you
- Emerging Data helps you make fact-based decisions and take actions that have a sustainable impact on your business.
- Emerging Data brings clarity, efficiency and transparency into your organization’s decision process.
- Emerging Data helps you align and empower your teams around shared goals and priorities.
- Emerging Data sustainably drives your performance and your digital transformation.
- Emerging Data reduces complexity, adding only elements increasing the outcome and integrating seamlessly into the existing systems.
Products
Surveys always-on
We design, implement and monitor the surveys your company need to better understand its ecosystem, react accordingly and generate conversions.
Survey panels
We design, implement the surveys and select the panels needed to achieve the best representativity. We deliver oustanding reports customly designed if needed
Data-driven transformation
From understanding the value chain to analyze, develop andfollow up, we accompany the company at each stage of its data transformation
360 Emerging Data
This circular process consists of 4 steps:- Understand the value chain of the company, design a draft of data strategy (data story, DMAIC)
- Analyze the existing data, deduce KPIs, incorporate other data sources
- Develop the surveys, dashboards, alerts, thresholds and monitor those KPIs
- Verify in time that the evolution goes towards strategy and go back to 1.
What drives us
Integrity
Integrity is a central aspect of our work and life. It defines the way we do business, how we interact with our customers, colleagues and partners, how we work. It guides us to do the right thing for the long-term success of our business.
Positive impact
We want to make a positive impact through our work and relationships. We believe that everything is connected and every action count. We‘re continuously improving the way we manage our daily challenges and our longer-term goal of developing a sustainable business.
Innovation
Innovation is at the heart of what we do. We love to experiment and take smart risks. Our aim is to foster creative thinking solve business challenges.
Team
Thomas Vié
Thomas Vié works in analytics since 1999. First as C.T.O. of several data oriented companies, then C.E.O. of an Email Service provider located in Argentina with a global reach. His focus is now on the technical side of data expertise, visualization and analysis, using the newest algorithms and tools to extract useful sense from raw material.
Caroline Depierre
Caroline Depierre has been for over 10 years a Research Director in the executive board of Trendence, a leading research agency specializing in international employer branding. She is an expert in designing and operating large-scale research projects for major brands. Her focus lies on developing concepts and methods to turn data into actionable insights for employers and universities.
Partners
Ingrid Astiz
Agile Coach with 25 years of experience working in the software industry and leading enterprise projects, Ingrid helps us in defining our internal and external strategy. With her agile experience she's also a great help in coaching our dev team.
Ricardo Colusso
Through Ricardo Colusso, Kleer is a great asset in breakthrough frameworks like product discovery and lean startup. Ricardo helped us in the early stages of our company by improving our methods and communication. Kleer is one of the leading coaching companies in South America.
Rieke Osthues
Rieke is a Data Analyst with 10 years of experience in Market Research and Product Analytics. She connects data to business strategy by raising the "right" questions to data. But shee also loves to dive deep with us into the nitty gritty math/stats and coding details on the Data Science side of things.
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Marion Prêcheur
Marion is a multi-tasking and curious business development and financial strategy expert. Spending her life between France and North Asia, she already accompanied many start-ups in various fields. She helps us not to lose the sense of our project and to structure company and products efficiently.
Blog Posts
We need to talk about university performance
As Times Higher Education reported this summer (see article here), the 10th-anniversary edition of the Global Employability University Ranking and Survey by Emerging released last month shows that Covid has accelerated the shift in the global higher education order.
Similarities in a multidimensional dataset
A fast and easy way to find the perfect match
Most of data science is oriented towards the Train, Test, Predict paradigm. But there are some cases where other implementations are needed like unsupervised classification or discovering patterns in existing data.