Adapting to the environment or to the user’s needs

I recently read Erik Vermeulen’s interesting post about the different ways for start-ups to grow in a digital age and he mentions three specific considerations: building an eco-system, leveraging technology to deliver constant innovation, and adapting to the environment. In his article on hackernoon (click here for full details) Erik uses the example of an Indonesian start-up, Go-Jerk, which he says is definitely NOT a ride sharing company, or even a company in the conventional sense, despite appearances (again, I strongly suggest you read the article as I do not want to do it an injustice here).

Behind the “cool” start-up life

We hear all the time that the most important element for a start-up to succeed is its strategy relating to product, value proposition, raising funds, etc. But what is a bit less put forward is that HR is the one of first things you should consider as part of your strategy!  Understanding the culture of a start-up and understanding what drives its employees can ensure you make the right decisions for the future of your company and help prepare it for success.

Unleash the power of Amazon ML - providing the means to truly harness the power of Amazon ML and RedShift to get powerful and meaningful insights from your data

It’s an all-too-familiar story: you have the data, a lot of data. And you’re convinced you can improve your business through exploiting that data, be it better conversion rates, reduced churn or simply a clearer understanding of your customers thanks to Predictive Analytics. There’s no question that having your data to hand in RedShift provides tremendous benefits, nor that Amazon ML simplifies the predictive element.

Enhance Business Intelligence with AI

Too much information kills information, until new tools come along to help...

Making savvy decisions based on business data are core to almost all organisations. As the complexity of the output increases, it becomes more and more difficult to obtain fast and accurate results.  Artificial Intelligence can help. Automatic data enrichment provided by drastically shortens the process. I show a video example with Amazon QuickSight. Demo: Go!

After a lot of coffee and discussions on how best to explain what is and how to use it when analysts need to understand what explains their customer behaviors, we decided to go one step beyond writing tons of posts and articles. And, boom!, we ship a demo app of instead. We cunningly named it … Demo (I know, this was the output of a lot of brainstorm sessions!). Wait, you do not know the best: it is a free (Boom again!) single session, SaaS application available here

How AWS Marketplace made a happy CEO out of me…

We were just back from the 2017 AWS Summit in London and as we were looking at the figures of the last quarter, I noticed something was definitely changing at PredicSis. We were been growing at a pace we had never experienced before. Of course, we’d had improvements in the product recently but it could not explain such a sudden rise in sales. We disrupted predictive analytics a couple of years ago by enabling anyone, with or without any data science skills, to benefit from Predictive Analytics in minutes to better understand what drives their customer behaviours and improve their conversion, upsell or retention campaigns. But we also learned that B2B sales mean a significant amount of time overcoming barriers to close deals.

Super Boules 2017. Where the Paris start-up community chills playing pétanque.

This week on Wednesday evening was the super boules 2017. I hadn’t heard of it up until yesterday morning so, for those of you not familiar with it, the super boules is an annual event organised by Stootie, a growing French marketplace. It is, as you might have guessed by the name, a “petanque” competition, the perennial French game that is played in summer times (usually played with a glass of pastis in hand).