You have just discovered that you have lost a valuable customer of enormous value from your large dataset. The reason- Lack of an effective diagnostic model that failed to explain why this could have happened.
If you had the power of modern predictive analysis model that can perform advanced analytics within a single customer-facing environment; you could have avoided the disaster, right?
Events are the prime connectors of the digital world with the physical. And advanced predictive analyses alone have the power to change business decisions by increasing data efficiency across specific events. In the B2B marketing environment, modern day organizations are still facing emerging marketing issues & business dilemmas that are been proved to be weak to tackle the notable risks, because-
- Big data is unstructured, irrelevant and enormous
- Big data is not been strategically viewed by the firm
- Big data is psychologically irrelevant, not timely applicable
So, the result is purely intuition-based decision-making. With the increasing number of customer purchasing events and massive customer-centric data, each organization comes across these three business sensitive areas:
At this juncture, how will companies face the challenge to outperform in the competition by acting upon the insights generated? The answer lies in psychometric predictive analysis. Today, embedded analysis are being integrated to the marketing process to churn desired results from 24/7 digitally connected customers. With the help of statistical techniques of interpreting consumer psychology it is possible determine the likelihood of the event occurrences, under a specific set of conditions. In order to get into the roots of each decision-maker’s mind, all you need is to capture the right mental map of the customer. To tackle this, why not employ a psychological-driven predictive analytic model to determine the past experiences, temperament, current environment, behaviour, psychology etc. & interpret them in a way that can translate the best answers?
Deploying predictive models to generate insights after interpreting each customer psychology can boost organisational performance by 40%. Take a note of these three effective triggers that works best in psychological-driven predictive analysis.
Identifying customer privacy
Predictive analytics model can help to analyse & understand sensitive information for customers that can provide analytics solution to handle the information prudently for a large number of decision points.
Identifying predictive consumer attributes
Predictive targeting is no longer limited to statistics & maths. Now, with psychological-driven predictive analytic model, businesses can strike a competitive differentiation that enables sentimental analysis after studying consumer’s digital behaviour. Such information is vital in decision making that can maximize your company revenues.
Reducing the complexity of transaction
Real-time transactions that are stored within big data sets are sometimes, subject to fraudulent and credit risk. In the absence of an effective operating model it will fail to translate man-machine interactions. Predictive targeting can simplify complex calculations by drawing analytical insights that can detect the likelihood of risks & frauds, thus fine-tuning model adjustments to deliver accurate interpretations.
Capturing consumer’s sentiments from social media
Predictive models can go a long way to capture consumer sentiments that arise from ongoing promotions in social media. Social listening tools rightly integrated with predictive analysis can track consumer’s conversations and unfiltered thoughts. By such social analytics, predictive actionable insights can be pulled out and converted into business dollars!