Big Data defines the use of technologies and methods to analyze sets of data. It is a question of detecting and making certain market trends, or consumer behavior exploitable.
Big Data is particularly used by marketing professionals to refine their targeting and analyze all facets of consumer behavior. The data resulting from their purchases on the internet or in stores, their preferences on social networks and their internet browsing history thus serve as references for understanding overall behavior.
In the same company, several departments can be concerned by the implementation and use of Big Data: IT, sales, and marketing. Marketing departments make the most use of Big Data. They are considered as precursors in the implementation of new strategies.
The implementation of new processes related to Big Data can also allow the improvement of the supply chain, the decision-making mechanisms and a significant competitive advantage.
Big Data allows the adaptation or implementation of strategies for the marketing of the company. They offer a new answer to the problems of the company or its projects.
Two major angles can be isolated:
Predictive analysis, i.e. the adaptation of a marketing message to a probable action by the consumer. Example includes an advertising message for a hotel in Canada when the Internet user is looking for a trip to Canada.
The marketing automation. Big data can be used for automated marketing based on a set of conditions. Example includes sending an advertisement based on geolocation or anniversary date.
The data can come from different channels, which do not necessarily correspond to the same professions and the same departments in each company. Channels can be digital or not, or have their own analytical application. It is then a matter of centralizing this data in the same set.
We can also distinguish between internal data, which the company produces and stores, and external data to which it can access.
The large flow of data and information can present a risk for the company, by drowning the objectives in the volume.
To avoid this risk, the customer or prospect must be placed at the center of the analysis: how can data improve their shopping experience? What information do you need to adapt the product or service to your expectations or behavior?
A company's Big Data project can be developed around several axes:
Our developers at Hyperlink InfoSystem work according to proven, agile development methods. In addition, we adhere to the current design guidelines of the respective platform and develop your solution using coding best practices. Current design guidelines are often criteria for posting in the application stores. Using best practices means that the source code we create is clean, maintainable, and of high quality.
The use of Big Data analytics helps you with an improved decision making ability. Big Data technologies help develop strategies that promote agile work environments, increase productivity, help reduce cost, and enrich the company's commercial approach.
Big Data is rising at the service of HR to identify more broadly and more reliably the right candidate profiles from business databases, job search engines, and social networks. At the same time, we are assessing whether they are in line with company policy.
Prior knowledge of customer expectations and needs is an approach that enriches the commercial relationship by making it possible to offer relevant services. Enough to promote a long-term relationship between the customer and the brand and increase orders' repetition.
Creating differentiated pricing strategies helps develop competitive pricing and generate more revenue.
Big Data analysis helps refine customers' classification using demographic data that will support salespeople in their efforts.
In addition to promoting decision-making, Big Data technologies provide the tools to analyze and validate these same decisions' results. Organizations can thus recalibrate their strategies based on new requirements and using proven business strategies.
In parallel with automation and Artificial Intelligence, Big Data solutions allow the implementation of efficient manufacturing processes, with production-oriented towards demand and optimal use of raw materials. This helps to reduce production and operating costs.
To increase the productivity and efficiency of the workforce, we must build confidence and support data-driven decision-making. This will have the effect of increasing the efficiency of the organization as a whole.