How Decision-Making Data Products Can Help
With data being the most valuable currency of our age, companies are spending small fortunes on collecting, storing, and analyzing such data to its outermost limits. One of the main reasons for analyzing data is to help organizations make better more ground-based future decisions.
In this article, we will discuss decision-making data products, which are data products that specialize in analyzing massive amounts of data to provide hidden insights and make the decision-making process easier and straightforward. It is worth noting that factors such as the getting good quality data and choosing the right data analysis method as per the situation will greatly affect the final result of a decision-making product.
In the the following sections, we will state four ways in which decision-making data products can help companies and users make informed decisions using data when handling complex and tough business questions about the path of their product and company.
Even though the utilization of such products will result in unique benefits depending on different industries, in this article, we will state the 4 general benefits that will be useful in every industry. Furthermore, we are going to look at some examples of decision-making data products that are available today.
Benefits of Decision-Making Data Products
1. Make Better and Cheaper Choices
Nothing tells the truth better than numbers. By backing up our choices with evidentiary data like statistics, easy-to-understand charts, and graphs, choices are made based on more than hunches and intuition. This way, decision-makers can always bet on the decision with the highest probability of success and fruition.
In addition to making better decisions, this allows you to avoid making mistakes with can cost you money. So, resources are not misspent, leading to huge savings across long time periods. It’s worth mentioning that companies invest millions if not more when moving on with a new decision, be it entering new markets, building new products, or expanding their advertising budget.
2. Reduce Risks
If not for money, then companies should make an effort to reduce their risks for their brand image. Having multiple failed products or services can damage the general view of an organization as a whole, causing companies to suffer in the long run. By making more educated choices, organizations can reduce or even eliminate unnecessary risks in future endeavors.
3. Increase Revenue
It’ll come as no shock that if more risk-free decisions are made, more revenue can be generated. This can be achieved in two ways. The first way is by having the company itself move towards a better-studied choice. For example, introducing a new product line, removing a failing one, or increasing their advertising budget. Done right, these decisions will definitely lead to more revenue.
Another common way is incorporating decision-making algorithms in your product for your users to use. Such a product will help customers with simple daily tasks, like deciding which products to buy or tv shows to watch.
4. Improve Products or Services
Saving the best for last, companies can utilize customer feedback such as online reviews, surveys, etc., to improve the quality of a product or service. The process of feedback and improvement is a continuous loop that ultimately leads to further sales and a better market image. Such feedback is just as valuable for new products in testing environments as for pre-existing products that have been in the market for years.
Examples of Decision-Making Data Products
a) Netflix Recommendation System
First on our list is the streaming giant Netflix. With the Netflix recommendation system tracking your favorite tv shows and movies, they can keep on recommending future content that keeps customers hooked. Needless to say, Netflix spends fortunes on improving its recommendation system. This is not out of mere fun, but because the recommendation system generate a massive part of the company’s revenue.
Moreover, Netflix can keep on creating future top-rated content by reproducing trending shows and genres that are most loved and viewed. A similar idea is followed by other companies such as Amazon, which uses its recommendation system to recommend new products for its customers.
b) Starbucks Location-Analytics
As the name implies, the Starbucks location-analytics system uses decision-making products in order to calculate the most profitable real-estate locations in which to build new Starbucks branches. The average income, population density, and traffic in an area is used to estimate the profitability of opening a new Starbucks store in a given location. Needless to say, using such an algorithm saves Starbucks a lot of unnecessary costs in the long run.
c) Uber
With a couple of clicks, Uber can match its customers with a ride in a couple of minutes wherever they are. While it seems simple on the outside, this process is extremely complex and does require the storage and analysis of massive amounts of data. Luckily for us, when it comes to storing and benefiting from data, no one does it better than Uber. So, how does Uber benefit from its stored data? By logging every trip taken, Uber can predict future demand by area along with the estimated ride fares allowing it to accommodate for areas with higher demand and low supply.
Conclusion
In this article, we started by introducing the concept of a decision-making data product along with some of the benefits of using such a data product. The four benefits stated here were it enables you to make better and cheaper choices, reduces risks, increases the generated revenue, and boosts product quality. We divided into each point to understand how utilizing data can help companies in the long run. Moving on, we gave three unique examples of how decision-making data products are being utilized in the market today.
I hope that after reading this short article, you have gained a better understanding of what a decision-making data product is and how it can improve your business’s prospects.
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