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 What I learnt is that, indeed, the way brands were using emailing is totally out of date.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

How will machine learning change our social media experience?

Nowadays, Statistica estimates that Facebook monthly active users are approximately 2,2 billion around the world. Other social networks are following the same exponential rise.

As a consequence, social networking platforms are gathering a huge amount of data by making connections between people and reaching them through generated content.

The role of Artificial Intelligence (AI) takes place when all the collected unstructured information has to be managed.

The rise of machine learning and its impact of brands strategies and user experience

Machine learning has definitely been a key trend of the past decade. It has had a tremendous impact on social media and companies are starting to understand what is at stake in using AI in their social media strategies.

According to Mia Tawilé, Freelance Digital Consultant,

the most interesting thing of observing these trends is understanding the way businesses and brands can use them to build stronger relationships – and even loyalty – with their clients.  

Thanks to machine learning, brands can easily identify their target. This type of AI allows to extract information from social media and make it highly valuable for companies. Thanks to the data they collect, a brand can convert prospects into customers by pushing the right product to the right person at the right time.


E-health and IoT : what about treat or threat ?

At a time where Google Home or all kind of connected objects are becoming part of our daily lives, they are also transforming the medical area. Between 2014 and 2016, startups in the health industry grew up by 40%.

It can be explained by two reasons, we are now used to connecting our devices and measuring our efforts and our daily activity, indeed we are becoming the own actors of our well-being.

Plus, we are facing the aging of the population with less doctors meaning that we strongly need more services with fewer resources.

Healthcare’s future is strongly linked to the technologies. It represents a lot of advantages in terms of saving time but there are some issues concerning data protection.



Benefits from the patient side:

As we are facing the aging of the population, people need a more personalized and regular follow-up. That is why we are talking about “silver economy”. New technologies within the healthcare industry are aiming at simplifying interactions between doctors and patient. For instance, patient will be more autonomous by following their health directly and consequently reassure close relatives.

Benefits from the doctor’s:

Connected objects are not aiming at becoming diagnostic tools or to encourage auto medication but are seen as an helping tool for doctors. Indeed, they will give a detailed follow-up more regularly and more personalized so they will have much more data to give a good diagnostic.

Future consultations with the doctor will be more effective with the daily data measurement of the patient. In other words e-health “More services with less resources”


But what are the limits to health-related technologies?

Regulations always lay behind innovation :

Innovation in the technology industry is developing faster than the law. It is verified for hoverboard and another new way of transportation but also for the medicine. The regulation is not updated for this kind of new technologies.

However, we see a strong will to move in this type of new medical approach. Indeed, in 2018 healthcare professionals who will follow their patients remotely with a connected solution will be better reimbursed by Social Security. Through this law, we can say that the French state shows its convictions: thanks to connected health, doctors offer a more efficient service to their patient.


As the market is emerging represents a huge opportunity for companies, everybody wants its slice of the cake. Moreover, the digital industry is a fast-moving environment, things must be done quickly.

Many connected objects are developed quickly without clinical validation which makes the industry quite dangerous. It can lead to strong damages as they deliver wrong information.

Even worse, some app pushes boundaries by offering auto diagnostic.

Data collection

At a time when developers of well-being connected objects are approaching the medical frontier, the question of data security is essential.

Data collection in the medical sector is very sensitive.

Within the European Union, its regulations and its use during and after the exchange process are very strict.

The French state shows a strong interest in protecting users from the data collection, for instance through the GDPR (General regulation on data protection; in French: Règlement Général sur la Protection des Données). This regulation will be more careful on this issue and sanction will be tougher.

On the user side, people may not be ready to share their health data as the system is not 100% secure. To counter this phenomenon, organization like ASIP, Agency for Shared Information System on health (in French, Agence des Systèmes d’Information Partagés de santé) are mandated to ensure the data security.


My selection of connected objects in the healthcare industry

  • Bioserenity : in the Brain and Spinal Cord Institute, this start-up manufactures connected clothes to monitor people with epilepsy more effectively.
  • Pkvitality: Innovation Award at CES 2017, this startup is designing a connected watch that can measure blood glucose levels in a non-invasive way.

How does it work? Biosensors remove the interstitial fluid with traces of glucose painlessly.

  • Lifeplus : This startup makes a connected watch for seniors. It measures the health and activity of the person as well as smart sensors placed in the living area that analyze the living environment.

The 3 examples above show that e-health can be very beneficial to all stakeholders. That is, as long as data privacy is enforced and the forthcoming deployment GDPR might be very useful in that report.


You must know what will be our digitized future. Read this!

You must know what will be our digitized future. Read this!

What kind of future do you think we are building?

According to Michio Kaku, an American theoretical physicist, futurist and popularizer of science, « future is about the digitization of life ».

Before reading what follows, it is useful to know that « Digitization is the cause of large-scale and sweeping transformations across multiple aspects of business, providing unparalleled opportunities for value creation and capture, as well as being a source of major risk », according to Jim Hagemann Snabe.

Let’s go for a quick sum up of some of the futurist aspects we will see in the digitized future.

1. How will we use the Internet?

The word « computer » will disappear from the English Language. In the future, no more physical computer would be needed! A virtual artificial intelligence will help us know everything whenever we need it: information will be everywhere and nowhere at the same time!

That will lead to several changes in the society: for example, education! College students will be the first to own connected contact lenses, that will instantly give them all the information they need! Therefore our teachers won’t be able to use memorization to teach anymore, but will have to create new concepts and principles.