The evolution and convergence of data
When I first started to work in marketing back in the 90s, data was already seen as gold. We could use data to know better our prospects, we could use data to target potential customers and finally we could know our customers profile.
Data has since evolved and now we face ourselves with a limitless potential with data.
As the world has gone digital since then, we have traces of everything online.
We go from one place to another? GPS tracks us, mobile phone tracks us.
We use connected devices? We leave a trace – Internet of Things
We buy on line? We leave a trace.
We answer an email? We leave a trace.
We play a game online? We leave a trace.
We leave our email address on a site? Guess what????
We communicate using messaging services, mobile phones and social media…. You got it!
What is very interesting is to see that not only data has evolved and now represents a limitless amount of 0 and 1 but also more and more, it is converging.
Online and offline data offer a power unprecedented when used together. On top of your online activity, your offline activity will also bring a much more precise view of your behavior or activity. This will mean personalized customer support like no other. This will mean an increase in revenue for companies who will master their data best. Why? The company that knows its customers best will serve them accordingly; plan their customer’s desire well in advance by reducing or eliminating the delay in ordering the products they would want to order as it would have been scheduled and will be able to offer special discounts at the right time for their customers because they would have noticed customers order cycles (for example after an annual bonus or period of savings and therefore feel more comfortable spending money at those times).
What makes it even more powerful is the explosion of open data. Anyone can use these data and create, innovate and analyze anything their imagination desires.
We see new marketing technics coming out to help with recruiting data and using it to its best ability. For example gamification, which is the use of game mechanics in a non-gaming situation. This allows people to engage more with the site they are on, the form they have to fill out, the information they have to give and also allow people to learn in a much more efficient way. Basically, it helps with people’s behavior and leads to much better data quality than ever before. Today, we are all drowned with emails that we don’t want, with games that we are not interested in, with solicitations of all kinds and on all channels. Gamification helps us to have a good time, engage with the brand that we are involved with and give correct information (because there is probably something to win at the end and I want to make sure they can contact me). As an example, please try to remember when you are very focused had a great time. You forgot how long you were feeling that way, enjoyed yourself so much and were totally engaged in what you were doing. This is what gamification is all about. Using a fun angle to ensure you enjoy and engage in any activity.
Companies also recognize the benefits of data. Today’s marketing focus is to help companies transform their activity into a digital one. They realize that with a digital transformation they can optimize all their activities (making them cheaper and faster), they can optimize their processes (from HR to technical departments and all others) and they can better serve their customers. In fact they can always be available to their customers 24/7 on all channels favored by their customers (social media, mobile phones, blogs, forums…), the service is becoming totally personalized, fast and optimized.
The analytics you can expect from such quantity of data, cross channels and qualified data is also changing. Up until recently, data was monitored by web analytics activities. Thanks to a tag (java script program), we could let companies know about their traffic, where people came from and how long they would stay on a page (there are many more key performance indicators but in order to keep this paper simple, I have decided to keep this to a minimum). Now companies manage DMP (Data Management Platform) which is a the heart of all cross channel activity and which can help to provide much deeper analytics than ever before. All company campaigns as well as all their online activities are now mixed together and providing very detailed information about how to improve digital activities and how to optimize ROI on any given digital marketing spent.
Artificial Intelligence (AI) is now being mixed with data management. Indeed back in early 2000, robots were based on AI and we would be programming on AI based on neuronal architecture where we had micro programs with either a 1 or a 0. AI would make the robot decide which activity to prioritize. Even though the first robots where so called independents, it was actually micro programs that would be a higher priority. Things have evolved. Now AI is about predictive analytics and behavior analysis (of course all the work around robotics uses AI as well and you can see real time operating systems working to make robots more independent and performing more complex tasks). AI today is still based on a neuronal architecture but it now uses more than before all data available to help build analysis around behavior. AI and data together is the assurance of great quality of data, great analysis and very precise tasks like we have never seen before.
So now we have quality data, we have quantity of data, we have great analysis and we know that no matter how hard we try, we leave traces on line: digital traces.
Technology had to evolve to allow all these changes. First we have seen Big Data appearing. Big Data is the base of it all. It is how this huge quantity of data is organized and how it is structured to come out and give analytics of such a massive amount of data. The Big Data databases are structured in such a way that the information comes out crossed analyzed and crystal clear to do all types of analytics. One new element of this is the appearance of predictive analytics. Thanks to all this new data management, computers can now predict anything around your behavior. It will be tailored for you and will be optimized for your wishes and desires.
Again I will not explain in detail about the structured databases (NoSQL vs SQL and Hadoop clusters…), I want this paper to remain simple. However, if you are interested, please feel free to ask me.
Once we have the base structured, we can address all type of activities:
Ecommerce: Ecommerce activity is becoming much more precise in terms of logistics, marketing and customer support. As all data is now used for analytics, companies will know better how to serve you, how not to make you wait – have products available even before you think of it and how to optimize your wallet by displaying special offers to you at a time when you have money to spend. Look at Amazon, they have mastered all angles of this.
Digital marketing: As mentioned above, with data being cross channel (on and off line) and with data being more cross-analyzed, digital marketing has become much more precise. While DMP (Data Management Platform) is being launched everywhere, we can see like with ecommerce, an optimization of campaigns that become more appropriate and where people can be more engaged.
Politics: No need to mention what happened in the US election but we can talk about what is happening in the French election. Data is always available and whatever was published a while back is still available. Transparence is the key and maybe it will teach our politician some lessons. In any case, data is at the heart of everything and can change the course of a country.
Press: Data is making journalists jobs much more difficult. In a sense as information is more available and is everywhere, we could think that journalists would have it easier. This is not the case. They now need to check the truthfulness of the information they get as the channels are very numerous. Anybody today can create information and can broadcast information (thanks to a multitude of platforms such as Youtube, Twitter (used by the US president to broadcast his own information, blogs, forums and news platforms…). Data is again at the heart of any journalist’s activity.
Insurance/Banks: Artificial Intelligence, Big Data and Gamification will allow insurance companies and banks to have very precise and true information about their customers. With AI and Big Data combined, they will be able to have access to past and future information giving their customers a risk free assessment and a very fast decision on their potential contract. It is true that you could worry about the combination of predictive technologies and we need to ensure that these institutions will remain sane in terms of their decisions and the power of the information that will be soon given to them. On the other hand, we could also see decisions based on more realistic and more global information making it fairer to all.
Education: Education is the activity that can best benefit from the convergence and the evolution of data. Not only thanks to gamification can students learn while having fun, they can also engage more with the subjects and be much more productive. AI and Big Data as well as IoT can also make students better at their subjects. The variety of data will make them more precise and more complete in their studies, but also information is available in a ubiquitous way, all the time, anywhere, in any format. Education will become much more productive and efficient.
Human Resources: The HR market, function and departments will also see a major transformation in their activity. The cross analysis between all available data will allow them not only to verify the facts on CVs, it will also show them how the person has performed tasks in the past and based on big data and AI it will show them predictive behavior of the applicants. This will ensure a good match for the jobs and also a much hihger success rate in every application. When somebody will be chosen, it will be the right person and for the right length of time as data will show when people get bored in their jobs and therefore are more likely to leave.
Medical: Health professionals will be able to diagnose better and to prevent potential diseases. The data available not only will cover your past information, your parents and grand parents information but also all research data available from researcher and universities. It will also compute predictive analysis on diseases and conditions. AI combined with this will give a strong chance to prevent all type of cancers and other chronic diseases. Life expectancy will then increase.
This list is not exhaustive. These examples are just what I have been thinking about for this paper and many more industries will be able to benefit from the convergence and the depth of analysis based on available data.
In conclusion, we now see great data potential. New technologies such as AI, Connected Objects (IoT – Internet of Things), robots and all type of bots, DMP, Ecommerce platforms, Social Media Platforms are allowing precise and optimize analysis and information. Companies can better serve their prospects and customers allowing a stronger ROI on all activities. Companies can predict better what you wish and serve you better ensuring you do not wait long to get your products, solution or services. We have started to forecast that very soon ecommerce site will see more bot to bot activities than human to bots (hence the new phrase B2B standing for Bot 2 Bot – communication between robots ordering for you).
Man will never stop innovating. This path we are on is limitless.
However we need to be careful because with new technology comes new responsibility. Anything that has to do with data privacy and data ownership needs to be strictly monitored. Everybody is allowed data privacy and data ownership needs to be respected. Let’s enjoy the power of technology and the ease in everybody’s life but let’s be careful about the other side and how it could damage our lives, if we are not careful.