Machine Learning in simple word is when the machines begin to learn like humans and not only execute the instructions contained in the algorithms present in their processors.
It is therefore the automatic learning of any (re) programmable system, which presupposes that the notion of algorithms does not disappear but that other elements, in this case the data, are added to the algorithms. The goal is to allow the systems to learn and evolve towards performances not only of calculations but also related to actual thoughts. In fact, at this level, the systems know how to adapt the results according to available algorithms and all the data which is available and has been acquired, interpreted.
It is also really important to state the difference between data mining and machine learning. In fact, data mining is a discipline already known and which consists of reprocessing the already known data to leave properties and precisions still unknown. On the other hand, thanks to the ‘known data’ Machine Learning tries to teach systems to predict what the result could be obtained from the data still unknown.
Enough with theory, let’s see how Machine Learning can affect businesses:
According to a recent study published by the consulting firm Accenture, French companies are receiving and suffering two to three effective cyberattacks per month. Given the increasing amount of data, identifying illegal activities among a stream of legitimate actions is becoming increasingly complex. Manual scanning of such a large amount of data is no longer possible.
Nowadays, there are two ways of detecting cyberattacks and intrusions which, both, have their own limits: the human and the machine. In addition to the constantly increasing data volume, the typology of attacks is becoming ever more diverse.
The AI is a revolution in cybersecurity mostly because it takes a similar approach to the human one. Indeed, the AI is looking for an abnormal fact and the differentiation between a legitimate action and an attack is therefore based on the experience of what it has already seen in the past. It is precisely on this principle that an anomaly detection operated by artificial intelligence is based: with time, it will learn (via machine learning) what is the usual behaviour and qualify it as normal. Any other behaviour will then be considered as suspect.
Machine learning gradually tends to revolutionize the medical world as well.
Researchers from Stanford University created a new algorithm with a database of nearly 130,000 clinical images of skin lesions, representing more than 2,000 different diseases. The machine learning massively ingested the huge quantity of information and then processed them by algorithms. And it allowed to classify the lesions into three categories: non-cancerous, benign cancer and malignant cancer. The test has shown impressive results with a number of 69.4% accuracy for the machine against 65.8% for dermatologists.
Machine Learning in the marketing:
In marketing, the identification of combinations of factors is crucial because it has a real impact on sales.
We can take the example of the retail industry and more specifically the clothing’s industry. In certain periods of the year, clothing sales are determined and set up in advance. In fact, winter is associated with warm clothing (hats, coats, sweaters), while summer comes with light clothing (shorts, skirts, sandals, short sleeves). It can be biased when the seasons are not following the usual cycle with cold temperatures in winter and warm ones in summer. Significant variations are increasingly taking place today because of the climate change and the global warming. Machine Learning will, then, allow retailers to provide clothes that people are the most likely to buy in the event of severe temperature fluctuations. Machine Learning will take into account the weather and each customer will have items personally suggested according to many factors and temperatures will be one of them.
For example :
I am working as an Inside Sales at ContentSquare and I am helping online businesses to change their culture by empowering all digital teams to understand the impact and effectiveness of every piece of content and user experience they create.
As a guide within the ContentSquare solution (a user experience and optimisation platform), ARTI, the Artificial Intelligence, is present in all the analysis modules.
This machine learning has a simple objective: contribute to the optimization of the conversion of e-commerce websites. Thus, ARTI suggests operational recommendations to accompany, in a daily routine, digital teams in optimizing the user experience for their Internet customers.
The three key points to remember is that ARTI helps to identify the pages of the e-commerce site and the areas that need to be worked on and optimized. Mr Robot also transmits methodological expertise, giving teams advice on how to analyze a given page or area. And last but not least, ARTI acts as a guide within the modules of the solution. The autonomous access to the data makes it possible to offer the teams a better knowledge of the users who are always more demanding and in search of personal relations with the brands. This constitutes a real vector of change: the more competent in behavioural analysis, the latter can finally give meaning to their actions by placing the users at the heart of the reflection.
The main idea with machine learning at ContentSquare would be to go from a SaaS model to a Site as a Service. Meaning that, thanks to AI and Machine Learning, it will be possible to propose a different user experience and interface for each one.
Facing the surge of articles on user experience, I felt the need to go back to fundamentals. When we talk about UX, what are we really talking about?User experience is the way in which a user perceives the service as a whole. A good user experience must induce a propensity to use the service durably, or even to contribute to its evolution. On the other hand, a bad experience makes ” the customer flee “. The challenge is therefore huge because the quality of the user experience determines the crystallization and the development of a service relationship. By definition, user experience is “the answers and perceptions of a person resulting from the use or anticipation of the use of a product, service or system”.
This definition is clearly a matter of ergonomics. The term user experience as formulated by Donald Norman, a professor of cognitive science at the University of California in the 1990s, refers to psychology and therefore to emotions. Its aim is to provide the most appropriate approach to a targeted audience according to any offer (products, services, companies, etc.). The more adapted the approach, the greater the satisfaction of this offer.
Why is it so important?
The whole purpose of UX is to reduce the cognitive effort, a somewhat barbaric expression which means, in a simple way, the fact of dispensing a user to spend all his capacities to fulfill a task at a given moment.
Companies are taking User Experience more and more seriously for several reasons:
The first one is because of the competition. In fact, what differentiate TrainLine and Voyages SNCF? nothing, because both are selling train tickets. And that was the crazy challenge Captain Train took: bet everything on the interface and offer one of the best User Experience of the market: the interface is clear, really easy to understand and it takes less than 3 mn to order a train ticket. Nowadays, that’s exactly what users are looking for: being able to have access to a specific service or buy a specific thing without any frustration and friction throughout the customer journey.
The second reason and one of the most important is the following: nowadays with the rise of internet usage, there is no longer physical vendors helping customers. Salespeople have been replaced by the interface. The consumer is alone in front of his device, and a smooth user experience is one of the main reason why consumers will choose to buy online or leave the website.
Moreover, the challenge for online businesses is to truly understand the customer journey. In fact, since 2007, all the investments from online businesses were focusing on acquisitions. Acquisition consists on bringing and attracting as much people as possible on the website. Problem is: with acquisition strategies, it is very difficult to prove the Return On Investment. Attracting people on a website is necessary and extremely important but one has to make sure that those people are converting. In addition to that, acquisition costs have been multiplied by 40 over the past five years. Today, e-Commerce companies focus on understanding customer paths to increase conversion rates and business performance. 94% of CMOs declared that user experience would be their priority marketing inverstment in 2017. Their first goal is to improve the Web and Mobile customer journey on their website to increase their revenues.
Which businesses are concerned?
ALL OF THEM. All businesses from any sectors are affected by the importance of a better user experience.
Obviously, at the very beginning of the growing awareness of the importance of UX, the more mature were and still are e-retailers. In fact, a better user experience and a smooth customer journey can make a HUGE difference on their revenue. But today, all businesses feel affected through the different challenges they are facing. For example, a retailer will not have the same challenges as a bank or a luxury brand or even an online media.
Banks for example are facing very specific challenges. In fact, the retail banking market is known to be particularly cumbersome and volatile. Even if in average 25% of French people say they are unsatisfied with their bank, only 3% of them will change bank each year. Banks need to provide a great user experience, making it easy to open an account or transfer money. A good interface coupled with great services and functionality is the key to perform well.
Online media are even more specific. Indeed, they have two objectives: monetize their audience and increase their subscription rate. In order to monetize their audience as much as possible they need to provide a great user experience that is going to make the reader willing to stay as long as possible on the website. By boosting the users’ retention, they are going to be able to display more ads.
User Experience and customer journey are no longer fashion and trendy words but remain challenges for online businesses, regardless of the sector.
To be able to provide a great user experience the first and most important things is to be able to KNOW WHO your customers are and UNDERSTAND THEM. Companies are using several tools and solution to be able to optimize their website : Traffic analytics, such as Adobe, Google Analytics and AT Internet, will help them to make statements: bounce rate, time spent, number of pages viewed. Behavioural analytics, such as ContentSquare, will make them understand how users are interacting with their website, mobile and app: basically it is answering the following question ‘why did my user leave the website without buying or subscribing?’ And then, once all of these has been understood comes the e-merchandizing, customisation, content and testing solution such as Qbit, ABtasty or Kameleoon.
Like in any other industry, luxury companies have to face several challenges. The quality of the service is the most important aspect for luxury brands. In a normal and real store, customers are pampered and valued. One of the biggest challenge is then to be able to reproduce the quality of the service online. And it is really hard.
With the rise of the internet but also all the new social media and technologies, customer’s expectation are evolving and changing a lot. I am not a big fan of calling us (and by ‘us’ I mean my generation) generation Y, but we have to admit that we grew up with the rise of internet and our behaviours pushed all the brands to modify the way they communicate and sell.
One of the most known, used and effective digital strategy for luxury brand is the brand content.
The brand content is something different from ads. Brands produce brand content themselves and the main objective is not selling but attracting people, making them dream and distract them. It can be web series, short movies, reports, magazines that will bring the customers into the heart brand’s atmosphere.
But creating content costs a lot of money to companies. In fact, shooting and producing really high level videos or photos is extremely expensive. The user experience has to be perfect to value the content and be sure that it will impact the consumer’s behaviour.
Companies providing great user experience:
One of the first luxury brand to appear online was Hermes. In fact, they opened their online store in 2002. Hermes managed to develop an original digitalisation with its contents and the ability to create a magic and enchantment atmosphere to its online shopping experience.
Almost all luxury brands are present online: Burberry uses digital as a Hollywoodian blockbuster, attracting thousands of fans. They also are famous for creating a whole atmosphere and experience around their trench. Myboucheron.com is offering an augmented reality experience in order to “e-try” the jewellery or Dior made a huge buzz with the Second Life experience…
All those brands are investing a lot online but they do respect their values and images. This shows that Luxury and digital can work together perfectly.
Digital allows improved services both online and offline
Digital allowed luxury companies to significantly improve their customer relationships by giving them the opportunity to have access to several services. For example, here are a few that make our life easier and much better:
Some brands offer the possibility to check on line and in real time the availability of products in store. It Makes the whole ordering process faster and easier. Real time data and information are exactly what we, as customers, are looking for!
Geolocalisation helps the clientele to spot where the stores are or the special services they offer (for example one can knows in which store it’s possible to drop the used Nespresso capsules)
It also helps enhancing and improving the distance relationship with their customers: For example, Longchamp, Gucci, Cartier, Louis Vuitton take care of proposing an ultra personalised service via a phone assistance or by email or even plan in store’ meetings.
The idea is not to make customers buy more but to improve their experience.
For example, that’s exactly the case with Nespresso and their automatic cashiers. It won’t make the customer buy more coffee or a new machine but it will improve the in-store experience significantly. It’s extremely quick and as Nathalie Gonzalez (Marketing and Communication director @Nespresso) said: “the concept of freedom belongs to the luxury’s values: digital reinforces it. It contributes to improve the experience before, during and after the purchasing act”
In 2017, online and offline must be more than complementary and compatible:
In store, digital will have two goals: make the customers willing to share its experience on the internet and improve significantly the purchasing act.
Online the digital has to provide a smooth user experience either to encourage customer to buy online or to provide impactful and useful contents in order to develop the ROPO ( Research Online, Purchase Offline )
Nowadays, marketing in a company HAS to be and IS necessarily data driven!
In fact, one moved from in-bound marketing to all-bound marketing, targets are now buyers personas which can be associated with an extremely complex customer journey. Furthermore instead of talking about multi-channel, one has to consider omni-channel marketing.
What is Data Driven Marketing?
A data driven strategy consists of understanding all the characteristic of a digital ecosystem and base all marketing decision on that data.
In short, it is a marketing strategy where studies have been replaced by data and where our beloved marketing mix has been replaced by mastering the customer journey. Better data collection makes it possible for businesses to get a grasp of their customers’ behaviour, trace and get in touch with the customer throughout their journey
The marketing strategy is no longer based on classical knowledge or intuition but on the relevant data about the consumer’s behaviour.
Why should company use Data in their marketing strategy?
It was the biggest trend back in 2013 and now big data is everywhere, used at a lot of endpoints and can be intimidating. Data can be collected from everywhere, especially since the rise of the Internet of Things. The only problem with big data is the huge volume of information that is collected. Most of the time the information is either not usable or not pertinent. It takes a lot of time to perform data mining, which means analysing and exploiting data ignorer to extract the right and actually useful information from the abundance of existing data.
Instead of using all the data we can collect from a customer (and there is a lot!), Smart Data allows you to focus on the relevant data. It is the only data useful for making decision and drive efficient marketing and CRM strategies.
In fact, a data driven strategy will enable the marketing team of a company to work much more efficiently and faster and process information more productively. Information that is used to put marketing data in perspective will make the data more coherent. More accurate date provides the ability to obtain a better customer knowledge.
Technology also enables one to process all the data in real time, which will make analysis much faster. In fact, real time data analysis can be used to perform predictive marketing. As customer behaviour is analysed, as he (the customer) is using a product, predictive marketing can influence the customer journey by using real time data. This will improve the experience the customer has with a product that is consistently changed using data driven marketing. And it is going to be more precise as data driven marketing enables companies to send user much more personalised, targeted and accurate messages and product experiences.
Nowadays, the time given to a company to make a decisions is extremely short. In fact, according to IDC, almost half of the managers have only 24 hours to make important decision. This is the exact point where being a data driven company changes everything. It would allows them to be more focus on people: in fact, members of the company will be able to determine if their decision are pertinent or not.
For instance, ContentSquare (a SaaS solution that captures online and mobile behaviours to measure user experience, increase engagement and improve conversion rates) gives the ability to each member of the e-commerce team to make decision based on the data. For example, the content manager will be able to understand exactly which contents work the best, how long people spend on it and if the description of its image is read. A solution like ContentSquare provides a lot of KPIs to the marketing department of a company, enabling the whole team to judge if their action, changes on the website or decision are positive or negative.
This is what data driven marketing truly means. Instead of trusting a gut feeling and using traditional marketing methods, companies can actually rely on data. Decisions will be made based on facts instead of assumptions and the customer will experience an overall better journey, as a product will adapt to the users behaviour thanks to real time analysis of collected data.