Sector-based analytics will ramp up in 2018 to address the common challenges facing individual industries.
1. Analytics invades sectoral clouds
We are witnessing a dramatic increase in new types of data with the integration of connected devices that has intensified over the past year. Businesses are looking for ways to make the most of the information that flows from it. In 2016, instead of building a new data analytics infrastructure, they will increasingly adopt “Sector Clouds” for analysis. These are specific analytics infrastructures hosted in the cloud that can be used by companies to solve some common problems in their industry. This trend is particularly useful for data-rich sectors that use connected devices, such as telecommunications, utilities, transport, and logistics and distribution.
For example, in data analysis, utilities have similar needs. Whether they distribute electricity, gas, or water, these companies must control and process huge amounts of data. A sectoral cloud for analysis allows them to do this at a lower cost and more efficiently. Today, in the transport and logistics sector, most vehicles are equipped with at least one surveillance sensor that produces data. If every engine owned by a company has an additional sensor, tens of thousands of additional data must be processed, which companies are not yet able to do. However,
2. Data for the greatest number
In 2016, the data analysis will really be democratized for companies. Until now, only “a few select companies” had the resources and skills to fully exploit the data. Now, thanks to technological innovations, all companies can access the data they need.
The distribution sector illustrates this concept of democratization. For example, store employees can now access relevant data that makes their jobs easier, which is essential for front-line employees who have direct contact with in-store customers. The physical representation of this evolution is characterized by more customers in stores with mobile devices such as iPads, which use applications that can provide them with information directly. The process of analysis thus democratized now allows an employee who did not know the customer in front of him to immediately establish a good relationship with him and improve his experience.
This availability of real-time data for the greatest number also means that businesses can now predict future trends very finely. This level of knowledge in real time will be a real advantage of the data for the greatest number.
3. “The experience of the relationship” becomes paramount
2016 will mark a change in consumer buying habits. With more and more consistent products and services, consumers will make choices based more than ever on trust and the customer experience. Of course, data security is an important differentiator to build customer loyalty and build trust-based relationships, but soon data theft will no longer be needed to belittle today’s cynical consumers. : their misspelled name or incorrect delivery address will be enough to lose their trust.
According to a study recently conducted in the United Kingdom by YouGov, the main factor that would motivate the loss of consumer confidence vis-à-vis a brand is not the theft of data as such, but a lack of communication after flight. This study also reveals that companies are now forced to win the trust of customers. Transparency on the use of personal information (50%), the application of a confidentiality policy (43%) and the rapid resolution of problems (38%) are the three main measures that companies can take to earn their trust.
In 2016, brands that leverage data to get a 360-degree view of the customer and maximize customer relationship will quickly stand out from the competition. Specific pricing strategies have already been put in place in most industries, but next year companies will focus more on “value-adding” to make these strategies more personalized and supportive for customers .
Take the tourism sector, for example. Today, technology allows airlines that intelligently use data to strengthen customer relationships to improve their travel experience, including customizing airport check-in and the proposed entertainment and dining service. On board the plane. The data can also promote a number of choices once the customer has moved away from the website. For example, if the data indicates that you are a driver, the airline can offer you a car service for the same price as a parking spot. If the data highlights your favorite brands, it can offer you offers within the terminal. If it is connected to your social networks,
To conclude, according to the service providers, both the markets and the customers, Big Data and therefore the evolution of data should be extended to new business sectors and new businesses, also affecting the general public via personal devices (tablets, laptops …). It is in this context also that new marketing models should emerge, including the question of monetizing data.