Uncovering hidden pattern and business insights have become crucial for making proper decisions. Big Data (BD) analytics helps in doing just that. Put simply; it involves examining a large amount of stats from various business operations to predict future events.

Why Is Big Data Important?  Do Big Data And Business Intelligence Go Hand In Hand?

Data and predictive analysis have been around for several decades. However, the combination of Big Data and ERP, CRM, has changed the entire game. It has transformed the way sales, and customer service teams work.

Business Intelligence (BI) tools consist of systems or software that can turn a large chunk of stats into meaningful, readable information.

Recent trends have already proved that companies that focus on BD and BI can run better, remain more profitable than those whose decision makers work on “what feels right” basis. Big Data application development adds more value to the existing BI tools and enhances them further.

Brands and Big Data: A correlation

Brands have realized the importance of functioning as a learning organization. Thus, embracing technology and data-driven approach is the new trend. Here’re four examples that show how brands are benefiting from BD analytics.

• Costco Uses Data To Amplify Customer Acquisition And Loyalty

Retail giant Costco is unable to gain traction online and compete with Amazon and Walmart. However, its customers keep on coming back at its bricks and mortar stores. The firm has also developed a positive reputation as it pays better wages and offers impressive benefits to employees compared to competitors. As one of CNN’s reports pointed out, it manages to thrive even in the Amazon era. The chain offers the next level of physical shopping experience to customers with the help of BD, AI.

The way Costco handled listeria-contaminated fruits recall in 2014 with the help of Big Data is considered as a case study around the world. It has helped the organization to solidify customer loyalty.

While sharing details about Costco’s commitment to quality assurance, the firm’s VP Craig Wilson had pointed out that BD helps them to know items that every customer purchases at their store each day. Thus, if there’s any quality issue in the product, they can quickly call the customer and share the information regarding recalled items.

• No One Can Extract Insights From BD Analytics Like Netflix

Netflix tracks the viewer’s zip code, list of movies watched throughout the day along with date and time, the device type used for viewing the content, user’s search history, and even the details for the points when the movie was paused, rewind, fast-forwarded.  Events like scrolling and browsing behaviour are also under the lens. The data derived out of such tracking helps Netflix to understand what viewers would like, and it offers personalized recommendations for movies, TV shows accordingly.

Netflix’s recommendation algorithm uses all this information and offers 10 to 20 movies/shows suggestions within 60 seconds to retain the customer’s interest.

Netflix’s decision to invest $100 million on the American version of House of Cards was also based on analytics. BD helped the media giant to understand that its viewers appreciated the House of Cards British version. The same set of individuals also watched films directed by David Fincher and movies featuring actor Kevin Spacey. Thus, these three factors were brought together for making the American version a sure-shot hit.

Perhaps, it won’t be wrong to claim that Netflix learned the art of deriving valuable insights from viewers’ watching habits back in 1997 itself when it started adding new releases to its inventory as per the interest shown in titles by the members of its DVD rent-by-mail service.

• Burberry Using AI And BD To Boost Sales And Customer Satisfaction

British luxury clothes label Burberry does not need much of an introduction. However, their AI and BD approach to boost sales have helped it turn into an end to end digital enterprise.  It offers loyalty and rewards to customers who won’t mind sharing a bit about their likes and dislikes. Both online systems and physical store associates use this data shared by consumers to offer personalized product recommendations.

The in-store sales reps identify the customer when he or she enters the store and suggest the specific range of products that the consumer might buy.  For example, if a customer who has entered the store has recently purchased a coat, the AI-powered customer management program linked with the tablet pc application for sales reps would encourage them to offer handbags that match with the jacket.

The brand operates more than 500 stores in various countries around the world. The company has implemented the technology used in online retail into bricks and mortar setting. As per data released by the brand in 2015, the combination of AI, IoT technology has helped it in convincing 50 percent of its first-time customers to come back for more.

• Pepsico Uses Stats To Manage Warehousing And Shipping Logistics

PepsiCo uses machine learning (ML) and AI in several aspects. The food-and-beverage giant that operates in 200 plus nations looks at technology as a necessity.

Efficient supply chain management involves a massive amount of data. Decoding it helps in ensuring various types of products reach retailers’ shelves before they go out of stock.

Solutions from Tableau, Trifacta, help the firm with accurate, faster reporting. Supply chain analysts use Tableau Desktop and BD to analyze finance, logistical, inventory requirement, and create forecasting reports for their country within minutes. The system helps in spotting possible future trends, future demand for products, adjust sales targets, manage warehouse inventory as well as the point of sales inventory, and ultimately sell more than competitors.

If you are looking for tailor-made apps and solutions to help your organization derive the best out of the existing data, you should get in touch with specialists at Smart Sight Innovations. The firm’s developers have helped many small and large firms with AI, IoT, and ML applications used in various business operations.