Predictive Analytics: How Data Becomes the Core Component of Future Marketing
Genuine creativity has no limits. Over the past few decades, our technological advancements have given sci fi characters like Brainiac an objective reality. As each day passes the technological complexities to simplify life is adding an additional layer to the evolutionary cycle. AI (Artificial Intelligence with predictive analytics) has slowly permeated into our day to day life, a majority of the systems that we use is capable enough to make informed decisions (currently on small scale).
The fusion of technology with mankind has wide implications in the real world. Whether it’s to predict/ diagnose the risk factor with medical conditions or to clearly define and understand the customer so as to make a clearly defined offering the end user cannot overlook. We are slowing advancing to the world where information is the key to conquer the world (data when collectively analyzed gives meaning), the same ideology to that of Brainiac.Data to increase online conversion
Information (data), when monitored, analysed, and used constructively, can bring great competency to the market. The lean strategy has attracted wide recognition in terms of eliminating excess resources making it possible to identify the cause and to treat it at the earliest. With the availability of extensive customer data, a business entity will be able to expand the horizon and implement the lean strategy more effectively. Once the morbid figmentation quantifying data start to slowly demystify, great minds start to recognise the future possibility of adapting, integrating, and evolving with digital transformation.
What is Predictive Analytics?
Predictive analytics is a calculated approach in identifying the likelihood of an opportunity based on the information the system analyses. The availability of structured data helps an organization to extrapolate on measurable variables, past and present data to predict the future probability of an outcome. The scalability of the matrix allows marketers to add more information to the machine learning algorithm (when additional data is available). An information driven predictive model helps to arrive at a decision with an acceptable tolerance of reliability.
Every time we interact with digital systems we leave behind traces of information. Information, when segregated and plotted, will give meaning to it. It can be simplified as connecting fifty different pieces of an automobile and reaching at the conclusion that it’s an SUV rather than a 747 Jumbo.
Big data led way to predictive and descriptive analytics. Big data when used simultaneously with machine learning help find correlations and muster deeper business intelligence. Once the predictive modelling identifies a pattern it then enables the marketers to make strategically informed decisions.
Predictive Analytics and the Market
The invention of portable electronic gadgets dramatically intensified the interaction we had with the digital world. Stats published on Hackernoon says that on an average, an American adult spends around 2:51 hours every day on their mobile phone. Another study by Flurry revealed that the time spent by U.S consumers with mobile gadgets have increased to 5 hours a day. These stats are a clear reflection detailing the intense penetration of digital technology among mankind.
A good wodge of entrepreneurs around the world makes projections to identify the market demands in order to decide how to meet the market needs. For a business entity, it’s important to calculate the Lifetime Value of a Customer (VLTC) and to identify the next best offer that suits the customer needs. The market is volatile, customers preference changes. Continuously keep tracking of the customer’s online activity and staying tuned help a business to tailor a customised offering to the end consumer, that way a personalised experience can be delivered.
Emotional Artificial intelligence, it is no wonder that AI is slowly creeping into our daily life and rigorously learning us. In the near future itself, AI’s cognitive learning will be capable to anatomize data, create a customer mapping and make smart decisions based on customer emotions. A smart move to transform business offering based on customer emotions will be the game changer, entities that can accommodate this change will have a competitive advantage.
How Predictive Analytics Help an eCommerce Business?
When it comes to an eCommerce business, Big data helps a digital entrepreneur to create individual customer personas for their target audience and iterate it based on the latest information feed directly from the market. With a projected growth (in terms of GMV) of $80 billion by 2020, India is expected to see a big leap in the ecommerce sector. The growth comes with unprecedented opportunity to explore the market, concurrently fueling competition. So, it becomes obligatory for an entrepreneur to design his ecommerce website in a way that increases the online conversion.
Let’s see how predictive analytics help increases your ecommerce sales. Consider your ecommerce website sells apparels. Prior to Christmas, you decided to tweak your strategy that it gets the best from seasonal sale. The problem comes when you ask yourselves a couple of questions:-
- What are the current market trends?
- How will the current market trend influence the seasonal sale?
- Why can’t I go ahead with my previous year data?
- How relevant is the previous year data?
- To what percentage the technology consumerization has changed when compared to last year? etc.
In a sporadic world with dynamically changing customer preferences, historic data cannot be treated as a benchmark when making crucial decisions.
For eg: Historic data tells the level of engagement a customer had when he last interacted with the business. On the contrary, a predictive analytics help understands the customer’s latest buying behaviour, search patterns, etc and based on which the business can identify who their most valuable customer is. Predictive analytics help marketers to create and implement informed marketing strategies that succour to present hyper personalized offers targeted to increase online conversions.
Data, when used wisely, shares great customer insights which can be leveraged to add value to the market. With predictive analytics, a business entity will be able to strategize and invigorate the desired engagement with target customers. As an entrepreneur always know that quality data when managed properly will blitzkrieg the puzzle.
Nishant Maliakel Oommen
Nishant Maliakel Oommen is a digital marketer by profession and a blogger by passion. Nishant is currently working as a digital marketing consultant for Cloudnix. Nishant takes pride when people acknowledge his work and finds that his work is adding value to people. Nishant thrives on staying updated on topics related to the digital realm and technologies that are revolutionizing the world. Inbound marketing is one of Nishant’s forte.Read Full Bio