Improve your employability: certify your digital marketing skills! Thursday, October 25 from 10:30 a.m. to 11:00 a.m. The classic model where the Gambia Email List company offers an offer to a consumer is giving way to a new relationship. From now on, it is the customer who decides when, where and how he enters into a relationship with the brand. In addition, customers have massively adopted new technologies, which has strengthened and accelerated their empowerment! Today, there is no more marketing without digital, there is therefore an urgent need to validate these essential skills in business. What has changed in recent years in marketing? What skills and digital levers should be mastered in 2018?

Why and how to choose a certification to improve your employability? One of our digital marketing specialists will provide you with the keys to find the right certification and activate the levers for better employability. Don’t wait any longer to register for our free webinar! Data science: definition The data science is a combination of disciplines ranging from statistics and mathematics to computer science. Thanks to data science, the marketer benefits from reliable, sorted, modeled information that will considerably optimize his actions, his investments and therefore his ROI ( Return On Investment ). By having this ability to integrate and analyze multiple, large data, mostly unstructured and from multiple sources (web, connected objects, CRM, etc.), data science enlightens the marketer by allowing him to make decisions based on reliable statistical data and models,

Create Recommendation Algorithms With Data Science

increasingly integrating a predictive dimension. Being (a little) ahead of its time or just in time is sometimes decisive in the face of competitors and becomes possible thanks to data science. How to use data science? The whole issue of data science when it serves marketing is to transform information into actions. If the marketer is within the company the one who knows the customer the best, the data scientist is the big data manipulator. Its talent will lie in its ability to collect and use the right data. The art of data science is to invent algorithms that will make data intelligent and above all more useful. From the data scientist, we can ask a lot: webscraping (aspiration of data from the web and allowing in particular to produce competitive intelligence in real time), recommendation algorithms, sales prediction, real-time classification of prospects, modeling and prediction of behavior consumers …

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Create recommendation algorithms with data science Reinvent the principle of the neighborhood bookseller who gradually gets to know his reader and recommends new books to him. Indeed, thanks to data science, it is possible to develop recommendation algorithms which, on e-commerce platforms, rely on online consumer behavior to suggest intelligent complementary purchases. So when the connected reader grabs the latest Flaubert on Amazon, it’s a safe bet that he will be offered to simultaneously acquire the best-of in the category: the works of Maupassant, Victor Hugo or Baudelaire with maybe free delivery to make sure you get your membership.

Data Science: Definition

More recently, the transposition of our neurons in a statistical form leads us to cross new horizons. Data scientists are constantly sharpening their skills to optimize the use of big data. Evolution and new opportunities of data science The development of artificial intelligence is not new, but it is gradually coming out of research laboratories to take a form more visible to ordinary people. The possibilities in big data are multiple even if still in consolidation. Data scientists learned the lesson from the first experiment with a chatbot for Microsoft in 2016: the intelligent robot named TAY. Based on an artificial intelligence supposed to learn in real time from its conversations with Internet users (“the more you chat with Tay, the smarter she becomes so that the experience is more personalized for you”,

Microsoft explained), TAY was quickly put in difficulty by twittos . In addition to the 96,000 tweets produced in eight hours by TAY (which is not accessible to a human hand), Internet users quickly made the robot slip by teaching it insults, inane words … From this semi-failure, data science has been able to evolve and draw conclusions to improve its algorithms. Now, data science and marketing are hard to separate. Data science at the service of customer relations Today chatbots are commonly used by marketers to respond to user questions on the web in real time. Improving the reactivity rate of brands on social networks, optimizing human resources, minimizing the risk of errors by

 

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