Data Analytics Journey

February 13, 2022by Julius Onyancha0
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Data analytics journey explained

Any business looking to gain a competitive edge will fail short without data and analytics. Analytics has revolutionised the digital world. Business organisations are now using analytics to recommend custom services to end-users as well as learn their interests as they evolve. With no actionable insight, data can be meaningless. Deploying analytics helps businesses to determine what has happened, what will happen and what actions need to be taken.

 

Descriptive analytics

Involves using data to understand what has happened and the current position of the business. Key metrics captured in this stage include:

  • Number of visitors to your website
  • Visitors to your website by channel, i.e., direct, social media organic search or paid
  • Total conversions by channels
  • Number of visitors who dropped off at checkout page without placing an order

Descriptive analytics highlight the current state of the art but does not provide any insight into the direction the business will take. However, the trends and patterns from the above analytics will help the business understand what has already happened to predict future outcomes

 

Predictive analytics

Predictive analytics is about using data and analytics to determine what will happen next. For example, based on historical trends on popular products purchased by region, analytics will help the business predict regional demand as well as use customer profile data to personalise products based on previous interest. Examples include:

  • Predict customers who are likely to cancel their subscriptions based on the number of complaints they have raised over the past few months
  • Predict a possible drop in sales due to the entrant of a new competitor
  • Predict customers who are likely to default on payments based on the history of missed or delayed payments in the past

The success of deploying a predictive data model is driven by the ability to use both internal and external data. Combining data gathered from your customers and external data from competitors, the market space where the business is operating as well as social trends that influence customer buying behaviour.

 

Prescriptive analytics

At this stage, no manual input is required to predict the outcome of a business process, instead, data and analytics play a critical role in identifying, learning, and initiating corrective actions to any strategic decision-making process.  Examples include:

  • Using data such as review and feedback to contact customers who are not satisfied with the service before they even contact the business
  • Suggesting affordable plans to struggling customers before they default

Julius Onyancha

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