A few years ago, Silicon Valley in San Francisco came under the influence of a new, mysterious thing known as Bitcoin. It swept away the tech enthusiasts off their feet. There were a wide set of rumors that Bitcoin was virtual money, invented by a pseudonymous math stalwart named Satoshi Nakamoto, who would later stir up the structure of modern finance and render government-powered currency antiquated.
To understand the phenomenon better, I once bought a single Bitcoin long time back, which then involved a strenuous labor-intensive process, where I had to go to CVS and use MoneyGram to wire dollar value of a Bitcoin to a crypto-currency exchange. After a month or so, I decided to sell it off for a slight loss, thoroughly convinced that this virtual money is nothing but just a passing fad.
Well, these two sentences have virtually similar words, but owing to their structure, they exude entirely two different meanings. Understanding the true meaning of the sentences just by having a look at the words was something only reserved for the human intelligence, until now. Breakthroughs in Natural Language Processing (NLP), also known as computational linguistics have blazed a trail in this domain, which was once dominated by humans.
Big data is expanding, and by next year almost a majority of businesses will be attracted towards the brighter prospect of this cutting edge technology. Even this year saw an enormous increase in volume, variety, velocity of data, which assures that the next year will witness more data, more numbers.
Data science pundits have predicted some of the leading trends that would be in the forefront in the big data revolution 2018. Come, let’s take a look:
In marketing, the analysis of data is a highly established one but the marketers nowadays have a massive amount of public and proprietary data about the preferences, usage, and behavior of a customer. The term ‘big data’ points out to this data explosion and the capability to use the data insights to make informed decisions. Understanding the potential of big data presents various technical challenges but it also needs executive talent devoted to applying the solutions of big data. Today, the marketers are widely embracing big data and are confident in their use of analytics tools and techniques. Let us learn about the ways in which Big data and analytics can improve the marketing efforts of various businesses around the around.
Locating Prospective Customers
Previously, marketers had to frequently make guesses as to which sector of population comes under their ideal market segment but this is no longer the scenario today. The companies can exactly see who is buying and even extract more details about them with the help of big data. The other details include which buttons they generally click while on a website, which websites they visit frequently, and which social media channels they utilize.
Tracking Impact and ROI
Many retailers have introduced loyalty card systems that track the purchases of a customer, but these systems can also track which promotions and incentives are most effective in encouraging a group of customers or a single customer to make another purchase.
Handling Marketing Budgets
Because big data allows companies to optimize and monitor their marketing campaigns for performance, this implies they can allocate their budget for marketing for the highest return-on-investment (ROI).
Personalizing Offers in Real-Time
Marketers can personalize their offers to customers in real time with the combination of big data and machine learning algorithms. Think about the Amazon’s “customers also bought” section or the recommended list of TV shows and movies from Netflix. The organizations can personalize what promotions and products a particular customer views, even down to sending personalized offers and coupons to the mobile phone of a customer when he walks into a physical location. The role of Personalized Merchandising in the ecommerce industry will continue to increase in the years to come.
Improvement in Market Research
Companies can conduct quantitative and qualitative market research much more inexpensively and quickly than ever before. The tools for online survey mean that customer feedback and focus groups are inexpensive and easy to implement, and data analytics make the results easier to take action.
Prediction of Buyer Behavior and Sales
For the past several years, sales teams, in order to rate their hottest leads, have made use of lead scoring. But, with the help of predictive analytics, a model can be generated and it can successfully predict sales and buyer behavior.
Enhanced Content Marketing
Previously, the return-on-investment for a blog post used to be highly difficult to measure. But, with the help of big data and analytics, the marketers can effortlessly analyze which pieces of content are highly effective at moving leads via a sales and marketing funnel. Even a small firm can afford to use tools for implementing content scoring which can highlight the content pieces that are highly responsible for closing sales.
Optimize Customer Engagement
Data can provide more information about your customers which includes who they are, what they want, where they are, how often they purchase on your site, and how, when they prefer to be contacted, and various other major factors. The organizations can also examine how users interact not only with their website, but also their physical store to enhance the experience of the user.
Tracking Competitors
New tools for social monitoring have made it easy to gather and examine data about the competitors and their efforts regarding marketing as well. The organizations that can utilize this data will have a distinct competitive advantage.
Managing Reputation
With the help of big data, organizations can monitor their brand mentions very easily across different social channels and websites to locate unfiltered testimonials, reviews, and opinions about their company and products. The savviest can also utilize social media to offer service to the customers and create a trustworthy brand presence.
Marketing Optimization
It is quite difficult to track direct ROI and impact with traditional advertising. But, big data can help organizations to make optimal marketing buys across various channels and to optimize their marketing efforts continuously through analysis, measurement, and testing.
What is Needed for Big Data?
At this point, talent and leadership are the major things that big data needs. In most of the companies, the marketing teams don’t have the right talent in place to leverage analytics and data. Apart from people who possess analytical skills to understand the capability of big data and where to use it, companies require data scientists who can extract meaningful insights from data and the technologists who can develop include new technologies. Due to this, there is a high demand for experienced analytics talent today.
Big Data Limitations for Marketing
In spite of all the promise, there exist certain limits to the usefulness of big data analytics in its present state. Among them, the major one is the major one is the analytics tools’ and techniques’ complex “black box” nature which makes it hard to trust and interpret the output of the approaches of big data and to assure others of the accuracy and value of the insights generated by the tools. The difficulty of gathering and understanding data also limits the capability of marketing companies to more fully leverage big data. Beyond this, the marketers are identifying many hurdles to expanding their utilization of big data tools and they include lack of sufficient technology investment, the inability of senior team members to leverage big data tools for decision-making, and the lack of credible tools for measuring effectiveness.
Conclusion
Cloud computing is also playing a major role in marketing with the Cloud Marketing process. Cloud Marketing is a process that outlines the efforts of a company to market their services and goods online via integrated digital experiences. Once the data analytics tools become available and accessible to even the smallest businesses, there will be a much higher impact of big data on the marketing sector as there will be much broader utilization of data analytics. This can only be a boon as organizations enhance their marketing and reach their customers in innovative and new ways.
Author’s Bio: Savaram Ravindra was born and raised in Hyderabad, popularly known as the ‘City of Pearls’. He is presently working at Mindmajix.com. His previous professional experience includes Programmer Analyst at Cognizant Technology Solutions. He holds a Masters degree in Nanotechnology from VIT University. He can be contacted at savaramravindra4@gmail.com. Connect with him also on LinkedIn and Twitter.
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Thanksgiving was right here! Half of the globe witnessed some crazy shopping kicking off the entire holiday season, and retailers had a whale of a time, offering luscious discounts and consumer gifts at half the prices.
Before the weekend Thanksgiving sale, 69% of Americans, close to 164 million people across the US were estimated to shop– and they had planned to shell out up to 3.4% more money as compared to last year’s Black Friday and Cyber Monday sale. The forecasts came from National Retail Federation’s annual survey, headed by Prosper Insights & Analytics.
“God created the world in seven days, because he didn’t have to port anything from legacy systems” – the CEO of a blue chip IT company once quoted. A similar idea was even echoed by MIT’s former director of computer science and AI, Mr. Rodney Brooks who penned down an article “Seven Deadly sins of AI Predictions,” which largely focused on the rate of deployment and the influence of technology over it.
But for any technological revamp, humans are the key ingredient for successful implementation of AI – because they are the ones who have invented such striking tools of automation with their own wit and determination. AI has enhanced productivity, coupled with raising standards of living. Companies all across the globe are recognizing the benefits of AI, and contemplating investments in this budding field of science to trigger greater competitiveness.
According to research, there exists a potent relationship between degree of automation and profit generation –the companies that have automated their business processes get to enjoy the perks of higher revenue growth six times more than those who didn’t. Also, they are twice more likely to supersede their pre-determined financial goals.
Now coming to our chief area of concern, how humans deliver a significant impact in coordinating automation with AI projects – their process of imagination, understanding, leadership quality, emotional intelligence and versatile management skills outweighs the very fundamentals of technology, hence it is said that for successful digital transformation, investment on human workforce is indispensable. To derive the best results, it is important to shell out money on crucial human elements that will lead to fuller automation and successful AI implementation.
Automation makes people more human. It liberates them from doing humdrum, repetitive work that pulls them back from doing something productive, or creative. Without AI, businesses can’t work or obtain competitive advantage in the future, making them defenseless. Nevertheless, you can’t expect AI to do a whole bunch of things for you, jobs that require creativity, empathy, critical thinking, leadership, artistic expression are meant for humans, and no automation will be able to fulfill those qualities. Humans are the meat and potatoes for AI, and we can’t agree more!
For better successful ventures, it is imperative to make humans and machines work together – it will only make us better in our job profiles. Also, this kind of relationships best augments the deep-rooted potentials of human beings, making humans more humane.
Research also says in the coming days, creative human skills will garner even more demand. Comprehensive training and skill development is highly advisable to remain ahead in the rat-race of advanced technology. Skills like, creativity, emotional intelligence, collaboration, critical thinking, communication and cognitive flexibility will become key skills to grab specific job titles.
An advice to make: before entering the workforce, it is better seek broad educational experiences in the field of data science or computer science, or your preferred field of study, and then amp up your CV with a professional, program-centric Machine Learning training Delhi. In this way, you will be always updated and stay ahead of the curve.
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The quality of data is the talisman of decision-making. Irrespective of the goals, the key to better decision-making lies in the quality of data. As it’s said, bad data takes its toll on organization’s data endeavors – as a result, only 25% of businesses are able to optimize the use of data for revenue generation, despite a volley of resources being thrown at them.
IBM has reckoned that bad data costs companies some $3.1 billion a year in the US alone, while as per Experian’s Data Quality survey, 83% of organizations alleged their revenue is affected by imprecise and incomplete customer or prospect data.
Big data and business analytics are like two sides of the same coin. Here, though the coin represents digital transformation – but reports from consulting and services firm HCL Technologies are pointing that many companies are not being able to harness these new-age technologies to their fullest capacities resulting in a loss of digital transformation efforts.
When asked Anand Birje, the corporate vice president and head of HCL’s digital and analytics domain, he has this to say, “Over the past four or five years, enterprises were pushed hard to do anything in the field of analytics, big data and digital transformation. They were being pushed because there was this fear about what their competitors might be doing, so there was this feeling that they had to do something digital.”
Of late, in spite of trending insurgence of cutting edge technology tools, SAS remains one of the most popular, in-demand programming languages for advanced analytics. It’s been more than two decades, yet it didn’t lose its importance in ruling the data science market. This shows how flexible this pioneering analytics tool is, and how adaptable it is in its functionality that it stood strong through the test of time and development.
Possess the Right SAS Skills, Be In Demand
Organizations are utilizing the perks of advanced analytics inside out. They are realizing that not only big data analytics has secured a niche area of concentration for itself, but it has strived to be an indispensable part of any organization that is on its walk to success.
