5 real world examples on how Artificial Intelligence and Data Science are helping enterprises

Enteprises are beginning to leverage Artificial Intelligence (AI) and Data Science provide services and product for their customers. If you would like to kick start your data science career, checkout this bootcamp from Springboard – structured to fit into your life, guaranteed to get you a job.

#1 Hubspot – Predictive Leading Scoring

Services range from predictive leading scoring as in the case of HubSpot, that claims in its website to be able to provide lead scoring estimate on the likelihood to convert leads into customers. This scoring is made possible by a machine learning model that considers features on customer behaviors over time in order to design a persona. After persona creation, HubSpot would be able to provide insight on positive and negative attributes that influence leadsconversion rates.

#2 Kissmetrics – AI on predict churn rate

Another example is Kissmetrics that delivers a pipeline to “turn insight into sales” (Kissmetrics slogan). A pipeline that begins with integrating to data sources and legacy systems, passing through data visualization capability as a first stage about getting insight on customers, moving to clustering algorithms that are able to provide customer segmentation which can be thought of as a second instance of understanding potential sales. Based on the above mentioned magic, Kissmetrics provides recommendations on how to deliver tailored, targeted email and social network campaigns.

#3 DOMO – AI to provide biz insight from biz cloud

There are other initiative as DOMO with center of gravity on providing a platform that enables AI activity. In the case of DOMO, its mission is to offer seamlessly integration to data sources and legacy systems (independent of it is on premise or on cloud) to support dashboards creation, i.e. business intelligence capability. It is a fast-growing market that aims to address medium and small companies that are no longer willing to deal with a platform maintenance; so tthey can concentrate on their core business and develop market intelligence that takes advantage from DOMO service that puts together in the same page all the information needed for business operation.

#4 Lufthansa – AI as prediction tool to implement aircraft safety

From the realm of transportation industry, there are good examples too, on the application of AI as part of B2B strategy; airline companies as Lufthansa, Flybe, KLM, BA just to cite a few; OEMs such as Airbus, Embraer and Boeing and MRO (maintenance, repair and overhaul) companies have invested on the application AI as a prediction tool to implement aircraft safety critical equipment prognostics and health monitoring. These companies have been taking advantage of the tons of data produced in every flight on the aircraft operation to unlock the potential of this data to help with maintenance optimization, reduction of ownership cost and increase of operational efficiency and safety.

#5 Airbnb – Data science and AI to derive models on pricing, customer segmentation and sentiment analysis

Airbnb has invested significantly in data science and AI to derive models on pricing, customer segmentation and sentiment analysis aiming to provide support to their users to ensure optimal assignment of people looking for accommodation to proper host. Every time a search is performed in Airbnb website, machine learning algorithms come into play to estimate the probability of assignment between guests and host. Airbnb also deploys AI algorithm outcomes to support guests on picking the best place considering historical data on their profile and hosts relating to the price to offer and improvements recommendation given guests feedbacks.

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