Types of analytics, and why they are important for your D2C brand

Updated: May 2


Importance of Descriptive, Diagnostic, Predictive, and Prescriptive Analytics for D2C Brands

In terms of our ability to use numbers to drive decisions, we’ve come a long way from using Excel spreadsheets. When Google Analytics was first introduced, it was a way for everyone to understand their website’s performance without needing to gather data manually. In just over fifteen years, we have tools today that don’t just gather data and collate it, but also use it to share highly actionable, business-specific insights and recommendations.


In the domain of data analytics, there are four types of analytics models- descriptive, diagnostic, predictive and prescriptive. In this article, let us understand how each of these analytical models are relevant for a D2C brand, and how to understand the insights that they offer.


Each of these analytics models has a role to play. Descriptive Analytics can tell you what happened in the past, and is therefore the first step in any analytics-based intervention. Diagnostic Analytics, on the other hand, helps you understand why something happened in the past.


Forecasting is vital to the growth of any retail business. Predictive Analytics predicts what is most likely to happen in the future based on past trends and market forces. Prescriptive Analytics recommends actions you can take to affect those outcomes, and precisely which action can cause what outcome.





Descriptive Analytics


Here, metrics are used by a platform to assess the status quo and help a brand understand if there is a problem within the system, and what that problem is. This is a form of business intelligence that uses graphs and tables to deliver key insights to a brand to help them understand a flaw that may exist in the system.


Descriptive analytics uses Key Performance Indicators (KPIs) such as performance, revenues, ROI, and conversion rates to detect the performance of the system compared to a previous time period.

Within the Shoptimize Growth Platform, the dashboards offer descriptive analytics that allows brands to understand if a problem exists, and what the nature of the problem is. Essentially, descriptive analytics answers the question, “What happened?”


For example, the dashboard within the growth platform compiles multiple sources and uses this data to give a holistic view of the store performance. Where the platform detects anomalies in the system, it delivers such insights through the dashboard.


Diagnostic Analytics


This is a domain of advanced analytics, where metrics are used by a platform to assess and deliver an explanation for the cause of a particular problem in a system. Through data recovery, correlations and drill down, diagnostic analytics answer the question - “Why did it happen?”


Diagnostic analytics uses key data from several sources and establishes a cause-and-effect relationship between multiple events to help brands understand the prime cause for a problem.


On the Growth Platform, you can see this in the form of insights. Diagnostic analytics can help brands identify causes for a variety of effects and offers multiple explanations, for instance:


  1. Why did yesterday’s revenue decrease compared to the previous day?

  • Possible reason 1 for the above-mentioned decrease - Yesterday's Conversion rate for Device - DESKTOP Decreased by X% compared to the day before yesterday.

  • Possible reason 2 for the above-mentioned decrease - Yesterday's Revenue for Campaign - ABC Decreased by Y% compared to the day before yesterday.


The Growth Platform identifies these focused insights and segregates them into different categories based on the geography of the customers, type of user, type of campaign, type of devices, and more.


Predictive Analytics


Taking it a notch higher, predictive analytics uses data gathered and the conclusions it offers to further predict what actions in the future would have what consequences.


In a retail context, it presents insights such as, “based on the past week’s data, you product XYZ is likely to go out of stock in the next 3 days.”


Prescriptive Analytics


In this newest frontier in analytics, metrics are used by a platform to understand the problem at hand and deliver a solution to be implemented in the future, from a series of potentially good solutions. The platform uses simulations, event processing, and graph analysis to determine the best course of action.


It answers the question, “what is the right decision to make for my particular context and at this particular time?”


On the Growth Platform, these are visible as recommendations. For example, the platform may recommend that you decrease the budget of a campaign xyz by 50% if it isn’t performing as well as it should. It can also provide you with user experience insights and inventory level insights, such as asking that you add stock for the Product xyz, or that Coupon Codes need to be displayed at Checkout for easier usage.


After delivering diagnostic analytics to help the brand understand the cause of the problem, the platform then delivers multiple recommendations in the form of courses of action that can be taken to resolve the issue. Based on the preference and strategy of the brand, the brand may choose either of these recommendations which would then be tracked by the platform for its performance.


Such real-time data-backed and mapped insights recommendations help brands make informed decisions and target specific issues with specific solutions.


Why is analytics important for D2C brands?


Brands have always leveraged the power of numbers to further their enterprise and acquire market share. Ever since the era of banking, numbers have governed businesses regardless of geography or policy. Modern brands, however, are much more reliant on data since the dynamics of the market have become more complex to understand.


Unlike old times, brands today cannot survive without understanding the numbers that surround them. This is where advanced analytics step in, providing key information about market patterns, preferences, prospects, and competition in the form of actionable insights.


Why should you choose the Growth Platform?


The Shoptimize Growth Platform is a data-driven recommendation engine that helps brands understand and consolidate their marketing efforts, spending, and performance based on a myriad of factors. It leverages data inputs from multiple sources to assess the performance and goals of the brand and delivers actionable insights to help comprehend, strategize and find solutions for a problem.


Explore the Shoptimize Growth Platform to leverage data like never before, and enhance sales for your D2C brand. Please fill in your details and experience a platform trail here.