Role Of Big Data In Digital Marketing To Drive Successful Business

Online Stores And Success

Even a decade or so back, a company with a web store or e-commerce site was well settled. Not so anymore. Online business competition has reached the zenith, and digital appliances have become ubiquitous. The web can be accessed from anywhere in the world - with just a Smartphone in hand! Of course, the users carry out a range of tasks other than placing purchase orders. They search and scout the web for information, entertainment, news, and knowledge. The new generation also chats, tweets, posts, and sends bulk email or SMS with a few key presses and touchscreen swipes.

An online company has to strive to capture the attention and imagination of such buyers. Traditionally, the digital marketing consultants assisted the businesses with great learning methods taught during Big Data Analytics course. These were banner ads, pay per clicks, mailing lists, branding, and promo offers. Subsequently, the gears have shifted to online reputation management, social media integration, corporate videos, and mobile apps. Now, the pitch has risen further, and digital market is abuzz with Social Media Tools, Cloud Computing, and Big Data Analytics.

The idea is to deliver personalized experiences to targeted customer groups. Valuable data of the online citizens and communities are collected and analyzed for predicting behavior, values, tastes, and habits. The data sources include Facebook, LinkedIn, Twitter, Pinterest, Blogs, WhatsApp, Web sites, and Search Engines. The online visitor's browsing and search histories are mined and analyzed to determine his or her digital personality. The suitable marketing strategies are employed afterward using a variety of tools and techniques.

Why Go Big?

Have a look at these fascinating facts and figures to comprehend the scale of challenges -

• In the 1940s, Big Data was just a Sci-Fi concept about voluminous historical data, analysis, and accurate predictions.

• By 2013, the data volumes have reached a staggering 4.4 Zettabytes (10 21).

• The data growth is expected to reach up to 44 Zettabytes by the end of 2020.

• In the coming two years, More than 35% of this predicted data volume will have semantic value.

• Semantic value means humans can make sense of this data by capturing its essence.

• This success is achieved through machine learning techniques (AI) and accurate data collection methods.

• The confluence of Big Data and Cloud Computing enables Data as a Service (DaaS).

• A web store or e-commerce site can collect real-time intelligence and use it to deliver customized browsing experience.

• For example, a visitor from a cold country will be shown winter wear on the catalog page of a clothing website.

Espy, this industrial data to assess the impact of Analytics on Digital Marketing strategies -

• The analytic software market's revenues are predicted to reach $200 billion by 2019.

• Surveyors say that an overwhelming 80% of businesses are willing to try Big Data.

• Targeted email marketing can assure 40% return on every invested dollar.

• More than 48% of this analytical technology focuses primarily on customer analytics.

• Business operations contribute only 21% to the marketing consultancy attention.

• Innovation, Data Warehousing Optimization, Fraud/Compliance take up 10% each. 

• Predictive Analytics is the popular investment choice for 37% of high growth companies.

• Approximately 50% of corporate executives are satisfied with the results of marketing.

Note

USA market is normally a good indicator, and the financial benefits of Big Data are very promising. Their retail sector is expected to see a net margin increase of 60%. Spectacular $300 billion revenues are predicted to be generated in health care. The product development and assembly costs in the manufacturing sector have been decreased by 50%.

Marketing Tips and Tricks

Big Data is all about data storage and manipulation to gather valuable information. The well-trained analysts rely on sophisticated software tools and statistical methods. Their inputs make sense only if the marketing plan is implemented with efficiency. The strategy or campaign itself is redoubtable due to cutting-edge visualization tools. Actionable insights are generated for inventory flows, customer preferences, and shopping peaks and lulls. The stocks can be managed more efficiently, and customer loyalty is also enhanced.

Data Collection

The web is thoroughly mined to collect useful information for data compilation. Automated processes extract structured and unstructured data from server logs, search history, web documents, page content and site links. Browser cookies and search behaviors are also captured to understand customer's intention or desire.


Social Media posts, likes, followers list, comments, shares, and tweets are also a storehouse of data. Background apps and services can collect large volumes of data from Smartphones. Online communities, crowdsourcing websites, surveys, and polls also deliver important data. Finally, Financial and business data is mined in the form of purchase orders, insurance claims, deposits, online bookings, credit card usage, and cryptocurrency account.

Analysis

The collected data is structured and analyzed to extract intelligent and intelligible information. The suitable analytical tools and platforms are selected and utilized in a planned manner. The analysis is conducted from business, consumer, and resource perspective to generate viable solutions. Market trends, hidden patterns, customer preferences and unknown correlations are identified and processed.

Marketing Solutions

• A digitally addressable set of clients list can be prepared from preferences. Consumers are matched to their online profiles and ID details (On-Boarding).

• The analyzed data is used for designing and launching new products and services. The brands, logos, site designs, and layouts can be quickly generated using online platforms.

• Hot email campaigns are launched after factoring in email engagement, peak activity, and accurate messaging time.

• Content distribution, display notifications, outlays, and alerts can be timed to perfection. Positive customer reactions such as opening, clicking, subscriptions, etc., are maximized.

• Customer insights and pricing strategies are implemented to deliver a personalized experience. This improves the conversion rate and business sales receive a boost as the marketing solution fits the demand.

Conclusion

Digital marketing has evolved in recent years due to rapid changes in data analytics with great learning. Cloud computing, AI, and Big Data technologies are storming the IT sphere. The business world has taken notice and it is adapting very swiftly. Statistical models and data analysis methods have the power to deliver viable solutions. The voluminous business and consumer data from online sources are stored and processed using the high-quality software. The visualization tools generate actionable insights and meaningful solutions. They include customer onboarding, targeted advertising, personalized experience, and well-timed content display.

Deepak Sachdeva is an Internet Marketer and digital consultant. Loves exploring new online marketing techniques and helping businesses build online brands. He likes writing on topics like Digital Marketing and Education. In education, his favorite space is Big Data Analytics, Artificial Intelligence, and Cloud Computing.