In 2018, data-related challenges were the biggest problem areas identified by marketers worldwide. These challenges directly impacted business operations by hampering real-time analytics. In Big Data training institutes in Bangalore, candidates are learning to identify the data-related issues that obstruct digital transformation and to get smart with various data science aspects affecting Marketing analytics.
According to new research on marketing trends, a majority of e-commerce retailers and in-store brands are looking at opportunities with the Internet of Things and Big Data technologies to help them manage their inventory. The coming years are expected to be completely driven by data and Big Data analytics would deliver the desired accuracy for inventory management.
So, how exactly Big Data Analytics training and learning actually help marketing teams?
By 2020, Big Data and Marketing Analytics would be the top technologies that CMOs invest in. Powered by the growing forces in Artificial Intelligence (AI), machine learning, Natural Language Processing (NLP) and programmatic media buying, marketing teams would be able to manage their inventory better. With the dizzying array of Marketing and Sales technologies, big data case studies could enable in learning from the success or failures of earlier adoption.
Where is Big Data leveraged in the Marketing supply chain?
Marketing is the largest user of Big Data analytics. This business group largely uses the analytics to identify user base, target customers across omnichannel platforms, mitigate risks in ROI optimization and competition analysis.
Here are seven clearly defined marketing functions that use Big Data analytics to increase their business ROI.
- Analytics or Predictive modelling
- Marketing inventory management, including CRM and data visualization
- Data Management
- Social media and PR Management
- Content or User experience with personalization
- Chat, live messages and video streaming
- E-commerce direct sales/ B2B Marketing and branding
Here are five steps to help any business achieve desired results with Big Data and analytics.
Step 1: Identify the areas that data can solve
Step 2; Pick the technology stack that could be run with Data, including Data Management Platforms, Customer Data Platforms, Audience Data Monitoring, Marketing Attribution and Email Marketing Automation
Step 3: Converge with research and case studies convened by the experts, data analysts and IT Engineers
Step 4: Bring together the right data, filtered from Big Data
Step 5: Re-evaluate the opportunities, challenges and threats; future-proof the future with further data analysis.
Big Data analysts could use a battery of tools and visualization techniques to conduct and sponsor research to establish market size and demand. This would help the Marketing teams to acquire new business opportunities and raise fresh capital to explore alliances in new geographies.