Want to find insights in your Data?
Big data analytics is an important investment for a growing business. Through implementing big data analytics businesses can achieve competitive advantage, reduced the cost of operation and drive customer retention. There are various sources of customer data that businesses can leverage. As technological advancements continue, data is becoming readily available to all organizations. Technically, it is fair enough to say that organizations already have data at their disposal. It is up to the individual organizations to ensure they implement appropriate data analysis systems that can handle the huge data. Does your business have big data analysis mechanism in place? Learn from the above examples of successful brands and implement one today.
The Data can we held in different ways. Throught ETL methods, we will able to make your data analyzable.
The data always has a story. We will let you know what your data is saying through visualization methods, and we will assist you finding the insights.
Fortune 1000 companies are investing in Big Data or AI
The market of Big Data analytics in healthcare could worth by 2025
Tagged Data analyzed in 2012
Is what Netflix saves per year on customer retention by using big data
Why using it?
Advantages in using Data Science
The incredible power behind the Data, and the unlimited potential it might been hidden.
When a company invests in structuring its data, it can work with what we call predictive analysis. With the help of the data scientist, it is possible to use technologies such as Machine Learning and Artificial Intelligence to work with the data that the company has and, in this way, carry out more precise analyses of what is to come. Thus, you increase the predictability of the business and can make decisions today that will positively impact the future of your business.
A data scientist examines and explores the organization’s data, after which they recommend and prescribe certain actions that will help improve the institution’s performance, better engage customers, and ultimately increase profitability.
Data-driven Marketing is a universal term nowadays. The reason is simple: only with data, we can offer solutions, communications, and products that are genuinely in line with customer expectations. As we have seen, data scientists can integrate data from different sources, bringing even more accurate insights to their team. Can you imagine obtaining the entire customer journey map considering all the touchpoints your customer had with your brand? This is possible with Data Science.
During their interaction with the organization’s current analytics system, data scientists question the existing processes and assumptions for the purpose of developing additional methods and analytical algorithms. Their job requires them to continuously and constantly improve the value that is derived from the organization’s data.
Data Science is a great solution when we want to cross different data to understand the business and the market better. Depending on the tools we use to collect data, we can mix data from “physical” and virtual sources for better visualization.
Of course, from what we have exposed so far, you should already imagine that one of the benefits of Data Science is improving the decision-making process. This is because we can create tools to view data in real-time, allowing more agility for business managers. This is done both by dashboards and by the projections that are possible with the data scientist’s treatment of data. As you can see, Data Science is the solution for your company to become more efficient in this digital age. The most incredible thing is that the benefits of Data Science that we mentioned so far are just an example. There are infinite possibilities. Do you want to know what it can do for your business? Contact us, and let’s discover these possibilities within your business together.
Tools we use
We use state-of-the-art libraries to develop the required programs depending your needs, and the data to be analyzed.Contact Us
How Data Science is changing the world
Companies using Data Science for improving their activities
These are some examples on how companies, small, medium or big, can take better decisions by using data-driven strategies.
Company that uses Big Data for Customer Acquisition and Retention
A real example of a company that uses big data analytics to drive customer retention is Coca-Cola. In the year 2015, Coca-Cola managed to strengthen its data strategy by building a digital-led loyalty program. Coca-Cola director of data strategy was interviewed by ADMA managing editor. The interview made it clear that big data analytics is strongly behind customer retention at Coca-Cola. Below is an abstract of the full interview on what Coca-Cola had to say about the role of big data in achieving customer retention. https://www.adma.com.au/resources/how-coca-cola-uses-data-to-supercharge-its-superbrand-status
Example of a Brand that uses Big Data for Targeted Adverts
Netflix is a good example of a big brand that uses big data analytics for targeted advertising. With over 100 million subscribers, the company collects huge data, which is the key to achieving the industry status Netflix boosts. If you are a subscriber, you are familiar to how they send you suggestions of the next movie you should watch. Basically, this is done using your past search and watch data. This data is used to give them insights on what interests the subscriber most. See the screenshot below showing how Netflix gathers big data. Netflix will be able to achieve this through machine learning, and even though machines still can’t understand human emotions, it is something we can expect in the near future. And when it comes to the bottom line – this will greatly reduce the cost and time needed to create the trailer and put Netflix on the right path to achieve their goal of ultimate personalization.
The way they collect data is by providing their customers with Starbucks rewards programs and mobile apps which help them learn more about the buying habits of each of their customers.
Starbucks is then using that data to recommend products to their loyal customers, create better marketing campaigns and new menus, as well as decide where they’ll open their next store. This system is so organized that it will offer their customers products based on the season, weather and location they are at. They also send out personalized emails with offers to customers who haven’t visited the store in a while, so they can re-engage them or send them discounts.
Example of use of Big Data to Drive Innovations
You have probably heard of Amazon Fresh and Whole Foods. This is a perfect example of how big data can help improve innovation and product development. Amazon leverages big data analytics to move into a large market. The data-driven logistics gives Amazon the required expertise to enable creation and achievement of greater value. Focusing on big data analytics, Amazon whole foods is able to understand how customers buy groceries and how suppliers interact with the grocer. This data gives insights whenever there is need to implement further changes.
Example of a Brand that uses Big Data for Supply Chain Efficiency
PepsiCo is a consumer packaged goods company that relies on huge volumes of data for an efficient supply chain management. The company is committed to ensuring they replenish the retailers’ shelves with appropriate volumes and types of products. The company’s clients provide reports that include their warehouse inventory and the POS inventory to the company, and this data is used to reconcile and forecast the production and shipment needs. This way, the company ensures retailers have the right products, in the right volumes and at the right time. Listen to this webinar where the company’s Customer Supply Chain Analyst talks about the importance of big data analytics in PepsiCo Supply chain.
Dynamic pricing & Product recommendations
What affects these price changes are factors like shopping patterns, competitor’s prices, and whether the product is a common one or not. It doesn’t matter if the person buys the products, puts it in the cart or even just takes a look at it – Amazon will use that data. That way they can learn what each customer wants and likes, and can recommend that same product or similar ones to them when they return to the shop.
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