The world is evolving faster than we know. Brands communication and sales approach are changing and now becoming more driven by data mined, predictive and AI based decision making. With this, data driven market is growing exponentially, brands these days are not just using the data driven information for predictive sale but also using it as a decision making strategy to position itself among its competition.
The data ecosystem is growing with a fast pace and will grow manifold in the near future resulting into the data explosion. With this, brands use the data for better outcomes if used strategically through predictive analytics which helps to understand the business insights.
Using the predictive analytics at business helps to stay ahead in this competitive era where this tool can gauge the competition pattern around which is useful for the strategic decision making prowess at the work place. The practice of using predictive analytics is also gaining a lot of popularity among brands resulting into more profitability in comparison to their respective competition. It ultimately helps to understand the most complex data available, go through all the intricacies, thereby enabling the expected performance.
To encash upon the usage of predictive analytics, one needs the apt infrastructure, resources to recognize the data driven discoveries which enables them to use the right data at the right time to formulate the right decision on the basis of these discoveries.
The challenge which the brands face is that they do not know how to recognize which data to collect and how to analyse the collected data. A lot of brands are facing the same issue. Predictive analytic is very robust and dynamic in nature if the right data is accumulated and the resources can analyze it for data driven discoveries to drive the right business strategy.
It is a matter of utmost importance for any business to drive its growth manifold therefore it is necessary to build the best data experience through collecting the right data along with the right analysis to build the expected business ecosystem with the best-in-class results. The data collected needs to align with the business objective therefore brands should pay extra heed to identify and incorporate the data which is valuable for the business growth.
This entire practice of identifying and evaluation is again a challenge for the business as they do not know which data source to concentrate to seek the complex business problem. They need the appropriate data to formulate the decision.
Brands need to understand that data driven culture is very important to build the effective data. It requires business objective message to be communicated to the employees to support their action.
This initiative at any work place will be ineffective if the resources lack direction and are clueless. If this process is not executed successfully then it would be a futile exercise for the business. Brands need to inculcate and seed their employees with data driven culture and make it a priority with the crystal clear strategy and drive it to the successful zone.
We have managed to build predictive, AI, and data mining algorithms which can not only understand the data correctly, it also provides analytics, insights and most importantly drives sales and improvements suggestions in the products and services that are being provided to the market by various brands for almost all verticals and industries.
We have taken this process to the next level by also doing programmatic sales and customer engagement without human interference. The program identifies the right customer with the right fit of products and provides the right discounts at the right time. This leads to extremely high conversation almost 90%+, unheard of in any industry. This also reduces cost for the brand and we no more need to spam people with tons or promotions and ads which are not relevant to them.
(Views expressed in this article are of Shabir Momin, Co-Founder, SSN solutions)