Have you ever heard about Startup Weekend ?

I. What is a Startup Weekend ?

Startup Weekend is a 54 hours event created by Techstars and powered by Google for Startups. The idea is to gather at the same place people from different backgrounds and different skills. All those people put together are aimed to build teams, and then to develop a start-up by presenting an MVP at the end of the 54 hours. To do so, mentors, investors, and sponsors are also there to help participants to build the strongest project, to have an opportunity to launch the start-up in real life.

Startup Weekends are getting more and more popular and well-known in the entrepreneurship community. In fact, if we look at the numbers shared by Techstars, there were more than 23 thousand teams formed, in more than 150 countries, for a total of more than 2,9 thousand of events organised.


Want to participate to the Startup Weekend Europe Paris Edition ? Click here


II. How is composed this kind of weekend ?

A Startup Weekend is 54 hours long. It starts on a Friday night, to finish on the Saturday evening. The format is quite the same during all Startup Weekends, and has been thought and put in action with one and only goal : to give the participants everything in hand to develop the best start-up they could make.

First Day :

On Friday evening, all participants (professionals and students from all areas) are meeting all together. The idea is to meet everyone to start to get to know each other, and feel the energy of the event. People who have ideas of start-ups will pitch during 60 seconds what they have in mind to convince people that they have a strong project. Then the projects which are liked the most will be selected, and then, people will gather in teams which they will keep all weekend long (and maybe even more if the project and the team is going well !). After choosing their teams, people are invited to start working on their projects. The idea is to define as clear as possible what they are going to present as a start-up project.

Second Day :

The Saturday is essential, in fact, it is the only full day dedicated to the projects developed by the teams. To help them, mentors will be there to guide the teams and coach them depending on the problematics teams are facing. Sometimes, there are also quick master classes which are organised based on the theme of the weekend. People have then the possibility to be part of them to be guided threw their project building. Because the time is very limited, teams have to manage well their time, the pressure. That is the reason why, it is essential to create a real team spirit to work as a proper strong team although the teams are very recent. In fact, building those project is not only about the project itself but also about the cohesion of the teams.

Third Day :

After hours of work building your MVP, it is time for you to finalize your project and to prepare your pitch in front of the jury. In fact, each team will have 5 minutes to pitch what they have created during the weekend. After all pitches, the jury will decide which project is selected to win the prizes. However, not being the winners does not mean that your journey is over. A Startup Weekend is only the beginning !

After the jury’s decision, it will  be time to celebrate those hours of hard work. Mentors, jury, organisers, and participants will all be gathered for the last drink all together. It will be a great opportunity to continue to meet people from other teams as well as the mentors and jury members.


Want to participate to the Startup Weekend Europe Paris Edition ? Click here


III. You want to be part of such an event ?

To participate to a Startup Weekend, it is very easy ! You will have access to all the different weekends organised all around the world on Start-Up Weekend official website.

And we have a very good news ! 5 students of the Digital Strategy master of GEM are organising the Startup Weekend Europe Paris Edition at the end of March. You are interested in entrepreneurship ? You want to be part of an amazing adventure ? Go check our event right here !


IV. Another point of view of a Start-Up Weekend

Being part of a Startup Weekend is not only by being a participants. In fact, if the idea of a Startup Weekend attracts you but you do not feel ready to be part of one yet, there is another solution. Startup Weekends’ organizers are usually searching for volunteers to help them during the event. In that case, you would not be part of the creation of a start-up, however it will give you access to the ambiance of it. It would also give you the opportunity to meet people who have the same interest of entrepreneurship as you, and who knows, maybe one day you will meet them again during another Startup Weekend or in the business world.


For more information on our upcoming event, the Startup Weekend Europe Paris Edition, go check us out on our Facebook page, our Instagram account and on our Eventdrive Page.

Mobile UX: an Introduction Featuring the Latest Trends.

Mobile UX: an Introduction Featuring the Latest Trends.

What is mobile UX?

Literally? the letters U and X stand for User Xperience (as in ‘experience’). But according to the Interaction Design Foundation, the definition of ‘mobile UX’ means “the design of positive experiences during the use of mobile devices and wearables, and applications or services running on such devices.” (1) In other words, through efficient application designs, we can create, measure and tailor a positive user experience that may lead to conversions or continuous use of the service app.

How does it affect businesses in today’s technology? Best examples

As technology becomes even more intertwined with people’s lives, it is crucial for businesses to offer a seamless digital experience that accommodates their lifestyle. Author Goran Paunovic writes in his Forbes article that “Most business clients who engage in site design are looking for a revenue-driving product, but few are aware of how much their business can change for the better with the right UX.” (2)

Indeed, having the right UX matters. The numbers speak for themselves.
In the same article, Pauvonic reports of research done by Forrester Research: “a better UX design could yield conversion rates up to 400%”. But how can you differentiate a good UX design from a bad one? Read my next point to find out.

The good, the bad and the ugly.

One of the most recognized events that shaped UX history is, arguably, the downfall of Snapchat. A journalist for The Guardian (3)Edward Helmore writes that after their controversial redesign, they have suffered “their first decline in daily active users” as well as plummeting stock shares.
Bloomberg (4) reports that Snapchat lost over 325.1 million dollars in 2017.

On the other hand, an example of an app made famous by its unique navigation method: Tinder.
With their iconic swipe right/swipe left feature, the app designers got inspired and mimicked real-life rejection/approval movements(5). All that within the optimal on-screen thumb placement.







Smooth navigation is essential in providing good and memorable user experience, however, it isn’t the only aspect you should consider when you’re designing an app.

Do’s and don’ts.

In his article, Nick Babich, Editor-in-chief of UX planet, gives us 10 tips for a better UX.

1-      Know your customer.

2-      Don’t confuse your users, prioritize features.

3-      Don’t overcrowd the app, strive for minimalism.

4-      Make navigation feel familiar to users.

5-      Keep the right amount of space for finger tapping.

6-      Use legible font and color contrast.

7-      Provide visual feedback and animation to show app responsiveness.

8-      Make data entry easy and minimize the need for typing.

9-      Create a seamless, homogeneous, experience on all of your platforms.

10-  Test your design and constantly measure your app.

Considering that less than 0.01 of applications were predicted to be a financial success by their creators at the end of 2018, let’s have a look at the mobile UX trends of that year. (7)

Mobile UX trends of 2018

With the unleashing of the iPhone X, full screen and vibrant HD experiences dominated the trends. That trend also included apps who have integrated facial recognition and biometric fingerprints for authentication purposes.
Furthermore, Nick Babich writes that “ In 2016, Google stated that roughly 20 percent of all mobile searches were done with voice activation.  It’s easy to see why the next big thing for coming years will be voice-activated interfaces.” (8)

However, will the latter be on the list of predictions for the 2019 UX trends?
Indeed, design leader Sumit Dagar writes “Voice interfaces (VUI) is the next big thing in Human-Computer Interaction (HCI). While visual and voice interfaces have largely remained independent entities till now, 2019 will see seamless integration of both and adoption at scale.”

He also predicts that in 2019, we’ll witness a “larger adoption of design systems amongst companies” but most importantly: the “liberal customization of design systems as companies target new geographies where users have less exposure to default systems.” (9) 

The implementation of a geographically customized mobile UX would mean that businesses now have a broader audience within their reach. Hence the reason why mobile UX is an essential investment for companies looking to expand their target audience.


All in all, 2019 looks like a very promising year tech wise. As interesting as it might seem to see all of the above actually come to life, I believe it would be more so to witness the unpredicted trends that could pop up during the year. But until then, I’ll keep a lookout.



Picture credit: Basic ways of how people are holding their phones. Research by Steven Hoobe (6)
Mobile UX: an Introduction Featuring the Latest Trends.


Why not listening to good music while reading? My inspiration for this article about ethical digital is What a Wonderful World – Louis Armstrong. Play it now!

Ethics and digital keywords

Ethics and digital keywords – Picture by Julie Compagny


Even without realizing it, ethics rule our daily life and give directions about what we should or should not do. As defined by the Oxford Dictionaries, ethics aremoral principles that govern a person’s behavior or the conducting of an activity. The Business Dictionary completes this definition by stating that It includes the study of universal values such as the essential equality of all men and women, human or natural rights, obedience to the law of land, concern for health and safety and, increasingly, also for the natural environment”.

What do ethics have to do with digital? Well, it is pretty simple. Throughout the years and centuries, all activities led by humans have been linked to ethics and thus, judged as good or bad. Digital is definitely an important preoccupation for women and men today. Therefore, it is legitimate to wonder: ethics and digital, friend or foe?




There is one thing that we should never forget about digital: it has been created and is still run by human beings. Behind every new digital creation, there is an individual and this precise detail plays an important role in the fact that digital is not necessarily considered as ethical.


When talking about ethics and digital, an obvious topic to tackle is biased algorithms. Why biased? Because humans, when writing them, include preconceptions and personal ideas – called societal bias – which makes algorithms non-neutral, engendering discrimination.

Cathy O’neil – a former Wall Street analyst and writer of Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (2016) – explains in an interview to Le Monde how, for her, algorithms and Big Data determine people’s value. She says that all type of information such as “likes” on social network or requests on Google are collected and used to create profiles to determine who is considered as privileged people and who is not. Those who are will be even more with the help of the algorithms while those are not will deeply feel it too. This is how algorithms create inequalities and as a result, go against the principles of ethics.


Privileged people feeling even better vs not privileged ones feeling worse

Privileged people feeling even better vs not privileged ones feeling worse – Picture: Julie Compagny



Serious cases of biased algorithms were revealed in the last few years. Twitter’s chatbot is a perfect example. In 2016, the social network launched its first AI bot, Tay, which turned out to be an epic fail. In less than a day, everything totally drifted and all of a sudden Tay became racist, misogynist and in favour of Donald Trump. Microsoft announced that relevant public data were used to create the bot; but what are those ‘filtered public data’? and how come the final result goes against ethics?

A second example is the computer program used by courtrooms in the United States. To each new person put in jail, the program attributes a score – called risk assessment – corresponding to the likelihood the convicted commits a new crime once free. A study by Propublica analyzed this system then revealed as biased. Two elements demonstrate it. Firstly, it showed that the higher risk scores are associated with people regarding their profile and not the nature and frequency of their crime(s). As a result, black people have always higher scores than white people. Secondly, it proved that among the 7,000 people arrested in Broward County, Florida, in 2013 and 2014, no more than “20% of the people predicted to commit violent crimes actually went on to do so”. Hard to say it is ethical, uh?


White man vs White man

White man vs White man – Picture: Julie Compagny



Do you know the notion of Dark Patterns? Basically, it is the way websites are designed to strongly lead users to do what companies want them to do. The main objective for companies is to make more profit. Every method is a good one to trick the customers and push them to buy more products, for example, or subscribe to a newsletter or extra services. Collecting private data to make more sells thereafter is also seen as Dark Patterns.

If companies do not perceive it as cheating, it does not make it less unethical. Indeed, users are so influenced that they cannot make their own choices, which is totally against the principles of ethics. Harry Brignull, a UX consultant, created a hall of shame recounting the worst illustrations of Dark Patterns. Here are some of them:








On October 23, 2018, the 40thInternational Conference of Data Protection and Privacy Commission was held and the Declaration on Ethics and Data Protection in Artificial Intelligence was adopted. Several countries such as Canada, Argentina, Mexico and the European Union participated in its writing.

Why is it relevant? It starts by stressing the progress made in artificial intelligence and the role it plays in our daily life. That said, it clearly recognizes the risks linked to AI – and digital in general – when it comes to human rights. The resolutions are introduced by the following sentence:

The Conference therefore endorses the following guiding principles, as its core values to preserve human rights in the development of artificial intelligence

Declaring respect and equality as fundamental elements of the good evolution of AI is a very good beginning. Ethics are integrated into digital with this new declaration and, if all countries truly intend to apply the rules, then it is very promising.

Declaration of Ethics and Data Protection in Artificial Intelligence

Declaration of Ethics and Data Protection in Artificial Intelligence – Photo: Julie Compagny


If you have not heard about the General Data Protection Regulation (GDPR), it might be because you slept in a cave the whole year. This law – established by the Europe Union – came to effect On May, 25th2018.

Why is it in favour of ethics? It was created to protect European individuals in the entire world from the new possibilities offered with the digital progress. Companies do not have the right anymore to collect personal and sensitive data as they wish, they have to prove it is actually useful for their business. People can ask to access the information companies have on them and if they want it to be deleted, then it has to be done.

This law has been made to ensure equality is respected and companies do not badly take advantage of the digital progress to achieve their ends. It definitely promotes a more ethical way to use data which is encouraging.


So, ethics and digital, friend or foe? Hard to say, uh? I invite you to read more articles on the subject to forge your own opinion. As for me, I want to believe in our capacity to work hard so that digital and ethics become complementary.


Read this article about GDPR and Blockchain by Enzo Rieucau: https://digital-me-up.com/2018/11/15/general-data-protection-regulation-vs-blockchain/

To go further, watch this TEDxTalk by Christine Fox about “The ethical dilemma we face on AI and autonomous tech”:

Check my previous article: https://digital-me-up.com/2018/12/03/social-media-and-activism-changing-the-world-online/

How Machine Learning can improve emailing marketing?

How Machine Learning can improve emailing marketing?

Over the past years, we have seen the growth of chat apps, social media, and business tools for sharing content and communicating better.

We have also noticed the general annoyance about the number of emails received each day, both in a professional or personal context with commercial communications.

Despite all of this: email is still thriving. In fact, according to a Statistica report, 269 emails have been sent and received in 2017. This figure should get to 333 emails by 2022, that is to say approximately a 23% increase in barely 5 years.

I have worked for several months in CRM marketing and especially emailing and I am currently working in a French data marketing agency. What I learnt is that, indeed, the way brands were using emailing is totally out of date. Emailing is not over yet though, and I am truly convinced that machine learning will very soon transform emailing marketing.

For me, machine learning will have an impact on four elements that are the pillars of emailing marketing. It should help marketers send communications to the right email recipients, at the right time. Most of all, artificial intelligence will provide a better knowledge of these recipients that are actually human beings: emailing marketers will be able to meet the needs of each individual, case by case. According to a PwC and L’Usine Digitale survey*, half of the 240 leaders interviewed are exploiting less than 25% of the caught and analysed data… A reality that might change thanks to machine learning.

A better segmentation to communicate to the right recipients

The actual strategy for most of the brands is to target people based on their very personal information like their age, the geographic area where they live, or their purchase history. The future of targeting is, in my opinion, based on the analysis of their behaviours. Machine learning algorithms will permit to create newly qualified segments, receiving customized communications according to their behaviour pattern.

A very interesting new tool to improve targeting is Tinyclues. This solution helps brands and retailers with huge customers database to sort out this amount of data. Artificial intelligence is able to predict who will be more likely to open, click and buy the product or service. To realize these predictions, Tinyclues is using unassigned customer data, like the name domain of a website address, the purchase history or the link the customer clicked on. The algorithm will then find correlations between the billion of data, mostly unstructured, and learn about it in order to propose a solution.

As an illustration, this short video explains what Tinyclues is doing :

Content: a better knowledge about how to talk to customers

With machine learning solutions, A/B testings on subject lines, body copies and images will not be useful anymore. The artificial intelligence tool will be able to determine which content will perform best in terms of opening, click and conversion rates.

Phrasee explains in the video below how its algorithm permits to generate subject line :

The right timing to send communications

One of the most frequently asked question in emailing marketing is “when should I send this email to my customers?”. According to me, the answer depends on the sector and the typology of clients. However, if a brand sends too many emails, recipients are more likely to unsubscribe. On the contrary, if a brand does not send enough emails, the competitors on the market will take the place.

Machine learning will figure out both the frequency and the timing issue by analyzing the customers’ activity history. It will enable to determine habits, time zones and downtimes in order to adapt to each people individually, according to their preferences.

Personalize the content

Improving the content can go further than finding the right subject line of the image. In order to maximize the results of a commercial email, artificial intelligence will help marketers determine what type of promotion will best perform for each individual (full price product, new products, discounts, free products, free shipping…). The probability to purchase will be significantly increased. Both companies and customers are winners: companies because they will sell more, and customers because they will have communications corresponding to their needs or their wishes.

As a conclusion, it is true that people are receiving too many emails. Commercial pressure is the reality. In order to differentiate, brands need to go further than the first step of personalization (like putting the first name in the subject). Following this objective, AI will help marketers sort out the available data to determine the best messaging, deliver at the best time and including the right offer for each individual.

Therefore, he next challenge for companies is to hire machine learning talent to implement those new AI tools. It will probably be harder for small brands: according to a PwC and L’Usine Digitale survey*, 44% of companies with less than 500 employees do not think about integrating AI in their project. For companies that are already using AI, the human factor is the first obstacle to the development of AI tools: 56% of interviewed companies list the lack of knowledge and 49% the lack of training.

This might in the end build a gap with huge companies that have the means to attract and retain highly qualified talent.

*Intelligence artificielle & Big Data 2018

GDPR vs. Blockchain: An impossible love?

On the one hand, we have the General Data Protection Regulation (GDPR), newly effective in the European Union since May 2018. The purpose of the GDPR is to give people the power to know how personal data is processed. To do so, businesses need to have a single access point. This implies to have their data centralized and managed in a secure place. On the other hand, we have the blockchain technology, a decentralized data exchange and validation protocol. Blockchain technology relies on a distributed ledger managed by a peer-to-peer network. Therefore, it is difficult to imagine a world where the GDPR privacy laws and the blockchain technology would be compatible. For all that, does this mean European businesses have to put an end to their blockchain-related projects to ensure GDPR compliance?

In September 2018, the French data protection authority, the Commission Nationale de l’Information et des Libertés (CNIL) published a report on the GDPR and the use of blockchain technologies. In this paper, the CNIL provides study results and solutions to businesses that have the ambition to use blockchain technologies. As the saying goes, opposites attract…


Is there a data controller on your blockchain?

According to the CNIL, businesses should first make sure there is no better solution to process their data. In fact, blockchain technology is not always the most suitable option. Keeping in mind that they should embrace the “Privacy by design” framework as a result when they design their technical solution to collect data, businesses will remain GDPR-compliant, even if they decide to opt for a blockchain. In this case, they will also have to identify and designate a data controller in their organisation.

The CNIL identifies two distinct scenarios: either the data controller is a physical person whom needs to process data for business purposes, or a legal entity that collects personal data on a blockchain (e.g. a bank with customer data). Any participant with a right to write on the blockchain might be considered as a data controller. That is why the CNIL recommends assigning a role to each category of participants in the chain. People will know who their main contact point is to exercise their rights.


When blockchain meets the right to be forgotten

The General Data Protection Regulation gives European Union citizens the right to request the erasure of their personal data. This gives individuals more control over the ways organisations collect, store and process their data. Article 17 of the GDPR states that “the data subject shall have the right to obtain from the controller the erasure of personal data concerning him or her without undue delay”. Because of the properties of hash functions in a blockchain, the slightest change in data will change the hash of a block. Furthermore, since each block contains a hash of the previous block in the chain, this makes removing personal data from the blockchain impossible.

The CNIL, however, acknowledges that under some circumstances blockchain could be compliant with the GDPR regarding the data subject’s rights. In fact, some of these rights seem to demand technical solutions to enable individuals to exercise them properly. For example, the right to erasure is, at first glance, impossible to apply technically here. But if the data controller implements cryptographic algorithms to make personal data inaccessible, the CNIL recognizes that this anonymisation process is close enough to the right to erasure. Even though the information is not, strictly speaking, erased.


The subcontractors, the weak link of the blockchain?

Despite these promising first results, European authorities still need to examine the responsibility of subcontractors in the blockchain’s network. According to the CNIL, there are two types of subcontractors in a blockchain: the “smart contract” developers and the miners who validate new transactions and record them on the global distributed ledger. Their role is still unclear, legally speaking, and needs to be addressed. Article 28 of the General Data Protection Regulation states: “Where processing is to be carried out on behalf of a controller, the controller shall use only processors providing sufficient guarantees to implement appropriate technical and organisational measures”. If subcontractors fail to be GDPR-compliant, the blockchain will be held responsible too.

The possibilities seem endless for GDPR/blockchain partnerships. The European Union incites businesses to create innovative solutions that combine data privacy with the erasure required by the GDPR. If law has certainly challenged technology this year, this might also be thanks to the General Data Protection Regulation that we will soon witness major innovation in blockchain technologies. All’s well that ends well.


Sources – General Data Protection Regulation vs. Blockchain: an impossible love?

Commission Nationale de l’Information et des Libertés Website, https://www.cnil.fr/.
Information Commissioner’s Office website, https://ico.org.uk/.
PrivazyPlan Website, http://www.privacy-regulation.eu.
EU Blockchain Observatory and Forum, https://www.eublockchainforum.eu/.
Coinext, https://coinext.io/2018/06/blockchain-technology-incompatible-europes-gdpr/, 19 June, 2018.

If you want to know more about blockchain, read our previous article.
If you want to know more about the GDPR and its context, read our previous article.