Data analysis, an opportunity to boost sales and be more productive
Thanks to data analysis, organizations today have the possibility to increase their sales and improve their productivity. Through the help of state-of-the-art technology such as AI (artificial intelligence), Big Data, and the work of data professionals who facilitate the control, storage and management of digitized information, companies can transform this resource into value, namely, make strategic decisions that turn into profit.
Firms of different sizes and industries are becoming increasingly aware that, in order to stay competitive, they have to rely on data if they want to optimize their costumers service, personalize their offer or improve their internal operations.
Indeed, in this context, both the private and public sectors are becoming major data generators. And this is just beginning: according to a survey by Splunk and True Global Intelligence, 67% of companies expect the volume of data handled today to grow almost 5 times by 2025. As a consequence, this data upgrowth will generate enormous application opportunities for business.
To thrive in this new era, companies need to know how to extract value from data. Yet many organizations don’t feel ready to take advantage of them. In the same report, which included 2,259 global business and IT managers from the US, France, China, Australia, UK, Germany, Japan and the Netherlands, 81% of them believe data is very valuable, but 57% it is worried about the fact that the volume is growing faster than their ability to keep up.
The first step that companies must take is to have a complete vision of the information they have, and then focus on the collection, analysis and management of data. In this way, they will be able to implement strategies related to their interests, even being able to avoid moments of deep crisis.
Thanks to the data driven approach, organizations can create personalized shopping experiences, apply improvements to products or optimize their operations to reduce costs. In this article we go through some examples applied to different industries.
Personalize the experience in retail
Kroger, one of the largest supermarkets brand in the United States, knew how to take advantage of the benefits of data in the best way during the pandemic and achieved resounding success: its physical stores increased their sales by 14% during 2020, driven by an increase 116% of their sales online.
What was the key to success? Kroger claims to have delivered half a billion personalized recommendations to customers, and customers appreciate the accuracy of their offers: The company’s email open rate is nearly 18% higher than the industry average. Additionally, over 95% of customer interactions on the Kroger website and app are personalized, leading to increased engagement and sales.
Add value in finance
In addition to offering personalized services, companies can add value to their products with online data that generates a positive impact. This is the case of BBVA, which has decided to make data and technology available to improve the “financial health” of its customers.
How? Using data science and machine learning to help improve the savings and investment habits of those customers who authorize the use of their financial information for this purpose.
“We look at multiple indexes related to our customers income, expenses, and debt. Based on these data, with analytical engines developed at the bank, we managed to identify the historical and daily characteristics that define the financial health of each client. This helps us define their financial situation”, explains Olga Ortega, responsible for the Financial Health Data program of this entity.
Inventory management in stores
Pharmaceutical retailer CVS, with almost a thousand stores in the United States, faced major challenges in terms of the sold items due to differences in the classification of its products as a consequence of complex inventory management.
Through Business Intelligence and Big Data, it was possible to track the movements of the products in the inventory using 160 key indicators, which allowed a more efficient inventory management, improving the customer experience and the profitability of the business.
Optimization of routes in logistics
UPS, the North American package transport company, had the challenge of optimizing its route schedule, thus making them more efficient and with the lowest costs possible. Through the development of different technologies and data analysis strategies, they managed to improve multiple aspects of their operations.
Simply put, through the use of machine learning, UPS has enabled its platform to automatically, and almost instantly, conduct the driver along the most efficient route. The use of this system gives the company a multiple benefit since, by minimizing fuel consumption and wear and tear on the trucks, it lowers costs and the carbon footprint. In addition, it helps customers: a more efficient route implies a faster delivery.
These are just a few examples of the applications of good management of the company’s data allows and how it can benefit the business and improve its operations.
If you want to know more about how data management can help your company, contact us.
Conciliac Team – email@example.com