Various business trends today, such as the use of artificial intelligence and multimedia visual marketing, are connected to the concept of Big Data. Every action internet users take generates a data trail, and the amount of machine-generated data is growing too.
Using this data effectively can give businesses an edge in today's competitive environment. Analyzing Big Data helps them to achieve better results in many areas of business with minimum wasted effort and costs.
What is Big Data?
Big Data refers to large amounts of information. Businesses used to rely on Information taken from spreadsheets and databases. Now they can capture, store and work with many types of data taken from numerous sources. Data can mean anything from databases to sensor data, photos, video, audio, and written text.
Gather right kind of data:
One of the biggest challenges for businesses is to collect the right kind of data. Email clicks, web visits, and video views are not necessarily the best indicators of business success.
The biggest challenge for businesses is not necessarily how to gather it, how to structure it, or which tools to use to analyze it, but what challenges the business wants to address. Many new online data points have become available that help business to solve challenges. Here are some examples:
Wells Fargo uses sentiment analysis to strengthen its call centers it collects voice recordings of conversations with customers and analyzes voice pitch, emotions, and tone.
Click tracking and advanced attribution
Understand the sequence of clicks that lead a consumer to a website and conversions.
Understand most relevant search terms to a product category to craft SEO-optimized blog posts etc.
Making Big Data work for businesses
The more businesses know about a given situation, the more reliably they can gain new insights and predict what will happen in the future. A comparison of data points allows them to make connections that were previously hidden and make smarter decisions.
To make sense of Big Data, businesses use cutting-edge analytics involving machine learning and artificial intelligence. Most commonly, they build models based on collected data. Simulations are run, and the value of the data points is adjusted to see how this impacts results. The process of adjusting all possible variables is automated. Eventually, a pattern or insight is found. Machines are quicker and more reliable in spotting patterns than humans.
The ever-growing stream of data is being used in ways that were not possible even a few years ago. The world of business is being revolutionized across almost all industries. For instance, businesses can accurately predict what customers want to buy, and when, with a high degree of accuracy.
A business like Walmart benefits greatly from this kind of prediction. It helps businesses to run more efficiently.
1. Understanding and targeting customers
One of the most straightforward and yet efficient uses of big data is to improve customer information. A customer profile typically consists of a name, location and purchasing history. Simply adding cookies to a website allows business to collect more data such as:
The device used by a customer. If customers are using a particular smartphone or a tablet, page format can be adjusted according to the model used.
Average time spent on a page. Knowing that a customer only spends 10 20 seconds on a particular page can raise questions. Why is this happening and what can be done to prevent it?
Browsing habits. Many experts regard this as the most important information marketers can have. Having this information can help them to offer customers exactly the right information at the right time.
2. Optimizing business processes
Analysis of big data is being used more and more to streamline business processes. When businesses take time to get into the details of every area of operations, many opportunities for improvement are found. Good data analytics is the tool that can help. Here are some business processes that can benefit.
Retailers can optimize stock based on predictions generated from web search trends, social media data, and even weather forecasts.
Better product management. Promoting the right product at the right time helps to increase sales. Sales can vary by season and region. Understand the most popular products, the combination of products and which products to promote at which time.
Improve customer service. From call centers to delivery, businesses can use analytics to improve service. For example, by understanding the impact of traffic patterns and average delivery times, they can predict their ability to deliver on time. By analysis of conversations with customers, they can track and improve customer relations.
Improve supplier management. Analysis of customer complaints and requests for refunds can allow businesses to weed out suppliers who do not perform well.
Improve customer retention. Customers talk about a product, service, pricing and company values in forums, on social networks and in reviews. Responding to this makes the difference between who stays and who leaves. Customers who stay can also help with referral of new business.
Execute highly, focused marketing campaigns. For example, money can be allocated in a more targeted way for PPC campaigns. Advertising is expensive, and A/B and even C split-testing can help with more effective placement of adverts. Landing pages, product images, and pop-ups can be tested to make sure they provide maximum results. All of this can help to drive sales and engagement.
Better allocation of energy and creative brainpower will lead to business growth. When many tasks are automated, business focus can be on other areas crucial to business growth.
Efficient billing. Predicting which customers pay on time versus those who are slower to pay enables businesses to manage billing and collection efforts.
Gordon Tredgold, founder and CEO of Leadership principles, mentions a success story in an article he wrote about using analytics to boost business growth. He talks about how Michael Chapin, CEO of a leading e-commerce company, has made analytics central to running his company.
He recruited an in-house team to run analytics rather than outsourcing or to bring in external consultants. He made every part of the business available for optimization as he believed this would give his company a competitive edge. Before using analytics, From You Flowers grew 10% every year. After using analytics, the company has grown year on year by 30% for the past five years.
Concerns related to Big Data:
Big Data creates unprecedented opportunities, but it also raises concerns. Recent data leakages have caused widespread suspicion and fear.
Increasingly, we need to strike a balance between how much personal data we divulge and the convenience we experience from using apps and services powered by big data.
Even when we are happy to give data for a specific purpose, we need reassurance that it will be kept safe and not used for other purposes.
Data can be used to discriminate. Credit scoring already determines who can borrow money and other businesses, such as insurance companies, are driven by data. Care needs to be taken not to further prejudice those who have less access to resources and information.
Businesses taking advantage of using Big Data need to address these challenges and fears. If they do not do so, they can make their businesses vulnerable to legal and financial losses as well as loss of reputation.
Big Data is growing all the time, and analytics technology is advancing too. The ability to leverage Big Data will become even more critical in the years to come. Companies who see it as a strategic asset will not only survive but thrive. Those who ignore this revolution are likely to be left behind because Big Data is becoming the lifeblood of business.