Big Data has revolutionized retail. By analyzing information about consumer behavior, sellers are able to pinpoint trends, identify preferences, forecast demand, and optimize supply. Let’s talk about the current status and prospects of using Big Data in retail.
What technologies will shape the future of retail and Big Data?
Cloud technologies are gaining more and more popularity in recent years, allowing to reduce the cost of building and maintaining the infrastructure necessary for analyzing big data. Moving processing to the cloud also saves on human resources.
An important advantage that any cloud infrastructure possesses is its high scalability and flexibility. If necessary, the retailer can increase (during peak periods) or, conversely, reduce it (during periods of downtime) at no additional cost.
These capabilities greatly optimize the operation and maintenance of the infrastructure and increase its reliability.
For whom is working with data relevant?
Technologies for collecting and analyzing data are most relevant for segments that receive information in large volumes.
First of all, this applies to:
- Large chain stores – they aggregate huge amounts of information from suppliers (about commodity items), as a result of sales (content of receipts). This data has great potential for analysis and benefit.
- Large online stores, e-commerce projects – these market players receive not only data on supplies and sales, but also large amounts of information about the Internet behavior of users, their movements on the site, unfinished actions, viewed products.
Other small players in the retail market may not have enough data for big data consulting firm analysis. In these cases, the use of a business intelligence toolkit is recommended.
Thus, solving data analytics tasks for each retailer is a task that requires an individual approach.
Benefits of working with Data Science
Data analytics consulting is a versatile tool, so its benefits vary from business to business. But it is always of high quality and taking into account your needs. Again, R2D2 steers your spaceship in the right direction. Read more info at DataScience UA.
However, in general, data scientists use computer science, statistics, mathematics, machine learning, artificial intelligence, and custom software to:
- Business decision support. A trusted data science consulting company provides consultancy on data visualization, information management, and data exchange to assist stakeholders in decision making.
- Optimization of processes. Why waste resources on daily routines that smart machines can do?
- Market analysis and trends. Data science consulting helps businesses deliver the right products to the right customers. Data scientists can help align consumer trends with product logistics. For example, we can create a portrait of your client based on the content of his social networks.
- Assistance in customization and personalization. Data analysts filter and group personal data from different customers to create a better and more personalized shopping experience for them.
- Identify and mitigate potential risks and prevent fraud. Data scientists can notice data that is specifically allocated to prevent and minimize risks that can hinder business development.