What are the Current & Future Trends in Predictive Marketing
Predictive Learning is estimated to grow from a $3.89 Billion in 2016 to $14.95 billion by 2023 at a CAGR of around 21%. The factors of influencing predictive learning are:
- Adoption of Big Data and other related technologies
- Bloom of E-commerce
- Growing Online and Data Traffic
- The rise of Machine Learning & Artificial Intelligence (AI)
However, there are some factors that are restraining the growth:
- Time Consumed in Analysis
- Lack of Awareness
- Unqualified Professionals
Predictive Analytics uses techniques like data mining, statistics, modeling along with machine learning & AI. The objective is to go beyond predicting future and also take the past into consideration for the best possibility of the future trends. This allows avoiding predicted problems like equipment failure or stock depletion or capitalizing market opportunities.
In recent times, predictive analysis has taken a new twist with the model of Predictive Advertising. This allows predicting new potential customers and target advertising to them with relevant content at the right place at the right time. Marketing Automation has gained momentum for targeting customers with offerings based on past behavior to drive sales. The predictive analytics has risen due to four major issues:
- Complications of Big Data
- Artificial Intelligence is able to predict future scenarios.
- Proactive is better than being reactive
- Optimizing micro-moments and hidden unused data that could be potential in the future.
As a result, these insights are no longer restricted to digital giants like Amazon, Google or Facebook. However, with the leaks of Facebook, the question of the privacy of data arises allowing companies to be skeptical about the usage of Big Data. This is due to the fear of the loss of trust with the consumers who divest their details to the company. The security and safety of these data are essential for effective predictive marketing as well as analytics.
DATAVLT has found a solution to this with their predictive analytics on top of a blockchain allowing for privacy of data. The scalable model allows for SMEs to have access to data for analytics at a cost-effective price enabling DATAVLT will play major role in capturing the $15 billion industry by 2023.