In the ever-changing landscape of business, success is determined not just by intuition or gut feeling but also by data-driven decision-making. Business metrics play a pivotal role in this process, serving as powerful tools that enable organizations to measure, track, and analyze various aspects of their operations. In this blog, we will delve into what business metrics are, what are the different types of business metrics and explore the reasons why businesses use them to drive growth and success.
In the last blog, we reviewed the perils of creating multiple profiles per user. Some of it are as follows:
1) Inflate user engagement metrics such as likes, comments, shares and followers
2) Generate fake interactions
3) Distort conversion rates
4) Misrepresent user demographics
5) Distort metrics use to evaluate the influence and reach of social media influencers
6) Artificially inflate user growth and retention metrics
7) Generate fake comments or reviews leading to inaccurate assessments of public opinion
Fabricated user profiles can lead to poor user experiences and mistrust. Users might buy products based on falsely boosted sales figures, only to have unsatisfactory experiences. If users lose trust, they're less likely to engage, potentially leading to abandonment. This is critical for businesses that rely on user-generated content or engagement for revenue. A thorough understanding on the impact of business can be tracked with the Business metrics, which is the next topic for review.
Business metrics are quantifiable measures used to assess the performance, efficiency, and overall health of a business. These metrics are typically derived from data collected from various sources, such as sales records, financial statements, customer feedback, and operational processes. When analyzed and interpreted properly, these metrics offer valuable insights into a company's progress, company’s user behavior, areas of success and areas that need improvement.
One of the most important sets of metrics that every business needs to track is the User behavior-related business. These metrics play a crucial role in understanding how users are engaged with the business. By analyzing how customers interact with a company's offerings, businesses can gain valuable insights that drive better decision-making, enhanced customer experiences, and overall success. Different businesses track a variety of user-related Key Performance Indicators (KPIs) based on their industry, goals, and priorities. Here are some of the most common user-related KPIs tracked by different types of businesses and how these KPIs are impacted by users creating multiple profiles
While multiple user profiles might seem harmless on the surface, their impact on key performance metrics is profound. From conversion rates to customer retention, engagement to healthcare outcomes, each industry faces unique challenges when dealing with the complexities introduced by multiple profiles. Businesses must stay vigilant, employ robust authentication measures, and employ data analytics to detect and mitigate the distortions caused by this phenomenon.
By understanding and addressing this issue, companies can ensure the accuracy of their KPIs and make better-informed decisions that truly reflect user behavior and preferences.
In our next blog installment, we'll take a deep dive into the world of data collection, delving into the different data sources, both internal and external that we tap into and extend our reach to gather invaluable insights.
About the authors
Parth Patel
Prinicpal Data Scientist at
Elevance Health
As a data scientist with 8+ years of experience, I have a strong track record of using data-driven approaches to solve complex problems and drive business growth. I have expertise in a wide range of data science tools and techniques, including machine learning, statistical modeling, data visualization, and big data technologies.
Siddarth R
Lead Data Scientist at
Microsoft
Siddarth has 19 years experience across Tech and Healthcare. He currently works as Principal Data Science Manager at Microsoft. He is leading a team of data scientists and engineers to deliver strategies for optimization.
