Apmetrix Blog - September 15th, 2016 | By: Lee Jacobson | Marketing

Bad Data

This months blog post focuses on the importance of understanding what data is useful and what is not.  Single channel metrics are no longer enough to understand your customers, and if you’re not careful and using the proper tools you may be making decisions with bad data.
bad-data
Data-driven is one of those flashy terms that corporations like to throw around during press conferences. You hear statements such as, “Our new data-driven culture will lead to a 12% increase in net profit.” When sentences like that get thrown around, one has to wonder if the speaker is the victim of bad data. While using big data to support business decisions is the new norm, and a survival requirement for doing business online, the way the term data-driven is used misses the boat in many ways.

For one, it implies that all decisions made before the age of big data were not driven by quantitative or qualitative information. This is obviously and patently untrue. Good businesses have always used data as a tool. More importantly, the term imbues data itself with mystical powers to transform a mediocre or failing business into a success. This misunderstands the nature of data, the limits of data, the reasons businesses succeed and the inevitability of bad data.

Even if you’re doing everything right, asking the important questions, focusing in on the relevant areas, none of this guarantees that the analytics are going to point in the right direction. The results are only as sound as the data you analyze. While most businesses assume that there will outlier data that needs to be ignored, fewer ever stop to wonder if there might be a more systemic problem with their data. Is there a flaw in how the data is collected? Is there information that we don’t have that might make this result look more or less cheery?

Take this as a hypothetical. A small software company gets a sudden influx of orders from New Zealand, where they’ve never sold anything before. The payments all clear and the software company executives think they’ve somehow opened up a new market. They begin marketing their software widely in Auckland, where most of the orders came from. Seems straightforward, right?

What the software company doesn’t realize is that all those orders came from employees of Company Q. For internal reasons, Company Q had employees purchase the software and reimbursed them for the costs afterward. What looked like dozens of discrete customers was really nothing more than a bulk license order from one customer. It was also an order with little chance of being repeated. The software company is likely wasting its marketing budget due to bad data, or at least incomplete data.

If the software company had been aware of the context, or asked the right questions during the purchasing process, it would have viewed the sales opportunities in New Zealand much less optimistically. Data-driven decisions can be good decisions, but they depend on the quality and completeness of the data itself. Assuming that becoming “data-driven” cures all problems is shortsighted and unrealistic.

Subscribe to our monthly newsletter!

Stay up to date on the latest best practices and trends in entertainment analytics.



Apmetrix Blog - September 15th, 2016 | By: Lee Jacobson | Marketing

Bad Data

This months blog post focuses on the importance of understanding what data is useful and what is not.  Single channel metrics are no longer enough to understand your customers, and if you’re not careful and using the proper tools you may be making decisions with bad data.
bad-data
Data-driven is one of those flashy terms that corporations like to throw around during press conferences. You hear statements such as, “Our new data-driven culture will lead to a 12% increase in net profit.” When sentences like that get thrown around, one has to wonder if the speaker is the victim of bad data. While using big data to support business decisions is the new norm, and a survival requirement for doing business online, the way the term data-driven is used misses the boat in many ways.

For one, it implies that all decisions made before the age of big data were not driven by quantitative or qualitative information. This is obviously and patently untrue. Good businesses have always used data as a tool. More importantly, the term imbues data itself with mystical powers to transform a mediocre or failing business into a success. This misunderstands the nature of data, the limits of data, the reasons businesses succeed and the inevitability of bad data.

Even if you’re doing everything right, asking the important questions, focusing in on the relevant areas, none of this guarantees that the analytics are going to point in the right direction. The results are only as sound as the data you analyze. While most businesses assume that there will outlier data that needs to be ignored, fewer ever stop to wonder if there might be a more systemic problem with their data. Is there a flaw in how the data is collected? Is there information that we don’t have that might make this result look more or less cheery?

Take this as a hypothetical. A small software company gets a sudden influx of orders from New Zealand, where they’ve never sold anything before. The payments all clear and the software company executives think they’ve somehow opened up a new market. They begin marketing their software widely in Auckland, where most of the orders came from. Seems straightforward, right?

What the software company doesn’t realize is that all those orders came from employees of Company Q. For internal reasons, Company Q had employees purchase the software and reimbursed them for the costs afterward. What looked like dozens of discrete customers was really nothing more than a bulk license order from one customer. It was also an order with little chance of being repeated. The software company is likely wasting its marketing budget due to bad data, or at least incomplete data.

If the software company had been aware of the context, or asked the right questions during the purchasing process, it would have viewed the sales opportunities in New Zealand much less optimistically. Data-driven decisions can be good decisions, but they depend on the quality and completeness of the data itself. Assuming that becoming “data-driven” cures all problems is shortsighted and unrealistic.

Subscribe to our monthly newsletter!

Stay up to date on the latest best practices and trends in entertainment analytics.



  • icon

    We're Tailored

    View data your way with our suite of powerful tools. Create your own custom reports with graphics, filters, colors, visualizations using our ‘drag and drop’ interface.

  • icon

    We're Contextual

    Our unique multi-channel analytics platform does way more than just show you how many times something happened, we show you why using advanced correlations.

  • icon

    We're Cross Platform

    View all your media, gaming, crash and marketing analytics in one place. View user behaviors across all your web, mobile, PC, game consoles and other devices..

  • icon

    We're Streamlined

    Save hundreds of man hours by automating all your data collection and focus on what really matters…your bottom line.