When eCommerce and online shopping businesses reflect on their results, it can sometimes be difficult to decide on a strategy going forward. You may be able to produce reports and have a good grasp of ‘what sells’ but if you are to compete in this incredibly competitive market, you need metrics. You need to make fact-based decisions.
When a business takes on the task of transforming business users to Citizen Data Scientists, they might have very clear goals mind but they may not have a firm grasp on what the role means or how to provide the business user with an understanding of what the role will be (what it will not be) and how it will change their day-to-day work.
The Corona Virus (COVID-19) has taught us many hard lessons, not the least of which is the importance of being prepared, the importance of anticipating what may be just around the corner, and the importance of being able to theorize, hypothesize and predict. All of these skills are amply supplied by data scientists and analysts. But, in today’s world, it is crucial to prepare and educate the average business team member to improve data literacy and engage in digital transformation (Dx). As the idea of data popularity becomes more mainstream, and team members and industries embrace data sharing and fact-based decision making, our understanding of looming issues, collaborative possibilities and possible solutions to address these issues will improve and so will our response time and efficacy.
Your senior management team has decided to engender digital transformation and improve data literacy across the enterprise. As a primary step in this process, the team wants to implement an augmented analytics solution that will encourage business users to get involved in data analytics, to use data to make fact-based decisions and to present, report and collaborate using real, current and clear information that will support collaboration and improve results.
When an eCommerce or online business undertakes a review of product or service offerings, pricing, marketing campaigns and channels, sales results and planning for the future, it is often hard to gather all the data and details and see the way forward clearly.
As a newly minted Citizen Data Scientist, you may feel overwhelmed and uncertain how to proceed. As with any other transition and new responsibility, the first order of business is to understand what is expected of you and what the boundaries and obligations of your new responsibilities will dictate. It is also important to learn how to use any new tools that may be important to your new role.
This article describes the analytical technique of gradient boosting regression.
This article describes the analytical technique of random forest regression.
If you are a business owner with an eCommerce or online shopping site, you probably spend a lot of time trying to understand your business results. There are numerous surveys that address the market and the activity in online shopping. Regardless of which survey you read, you are probably surprised to know that more than 2 billion people shop online. But, those numbers don’t tell the whole story. It is also important to understand that people will often check prices online while they are standing in a retail store just to see if they can find something at a better price. So, they don’t always buy your services or products just because they visit your site. And, you are probably not surprised to know that your competition is growing every day. You know that better than anyone.
When a business user takes on the new role of Citizen Data Scientist, it is often with misgivings and concerns. If their business and management team have not adequately explained the expectations of this new role, or made the workflow and cultural changes required to ensure that this new role is successful, the business user and team member is likely to fail, and the Citizen Data Scientist initiative is likely to fail.
