How Pathwwway product reporting will help you succeed

Business professionals and amateurs both tend to use the words product analysis and product reporting interchangeably as though they describe the same process. Both make use of web analytics and data, but they differ greatly in regard to their purpose, what tasks they perform, the outputs they generate, how they are delivered, and their individual value to your business. Understanding the distinctions between product analysis and reporting prevents your business from selling itself short in one particular area while not receiving the full benefits of the web analytics.

What is the Difference Between Product Reporting and Product Analysis?


Product analysis is the process of examining reports and data in order to extricate worthwhile insights, which are then used to better comprehend and improve your business’s performance. Alternatively, Pathwwway product reporting is the process of organizing that data into concise and informative summaries in the interest of monitoring the performance of your business in different categories. Where reporting turns raw data into helpful information, analysis turns information and data into meaningful insights for your marketing and production departments.

Reporting also monitors your online business and alerts the appropriate team members when the reported data falls outside your expected ranges. The best reports raise questions about your business from end users. Analysis then occurs when you try to answer these questions by interpreting the data at on a complex level while coming up with actionable suggestions. Basically, reporting reveals what exactly is happening with your business while analysis explains why it is happening and what you can do to affect it.


The tasks being performed by your analytics team indicate whether you are performing product reporting or product analysis. Do not confuse “analysis” with “analytics” when determining if you need reporting or analysis. Analytics is a catch-all phrase for the strategies, implementation, and reporting of data while analysis actually breaks down the information and gives you direction for your next move. Often something being called analysis ends up being just another type of reporting.

Interested in figuring out if your business emphasizes analysis or reporting? Take a look at the primary tasks performed by the people in your analytics department. Are they spending most of their time on things like building, consolidating, configuring, formatting, organizing, and summarizing? Your analytics team is participating in reporting. Or does your team focus more on tasks like examining, questioning, comparing, interpreting, and confirming instead? They are participating in analysis, not reporting. Both play important roles in your business’s success and longevity.


The formatting of results from product reporting and analysis seem very similar on the surface with multiple graphs, tables, charts, stats, trend lines, etc. When you take a closer look, however, you will see they vary greatly in their outputs. Reporting uses the push approach, while analysis tends to be more pull.

A push approach means the reporting system pushes all the data towards your product managers who are then expected to extract relevant information themselves and then determine the next action. There are three main kinds of reports associated with Pathwwway product reporting:

Canned Reports: Standard custom or out-of-the-box reports your business can access from within your chosen analytics tool and that can be automatically delivered in intervals to your reporting team. They tend to be pretty static with a specific set of dimensions and metrics.

Dashboards: Another kind of static, custom-made report that combines various other reports and key performance indicators that provide a high-level, comprehensive understanding of how your business performs with specified, target audiences. A dashboard may also include data from alternative sources.

Alerts: A conditional kind of report triggered only when the collected data begins falling out of expected ranges or when another pre-defined boundary is reached. This keeps your team on the ball and aware of any problems brewing, so they get fixed immediately.

A pull approach is when an analyst pulls the information from these reporting systems to particular business questions. Informal and basic analysis occurs anytime someone assesses a report with their minds and makes a decision to act or not to act based on that data. The two main types of pull reports are ad hoc responses, where the analytics team must create a short, concise report without suggestions due to time constraints, and analysis presentations, where the team creates a report with key findings and meaningful and actionable recommendations.


One of the biggest differences between product analysis and product reporting is context. Reporting provides your business with almost no context about the meaning of the data. Generally, the person analyzing the reporting data possesses the obligatory context needed to interpret it correctly. Sometimes smaller businesses do not have a person with that kind of expertise on their team and the data loses significant value because it cannot be processed correctly.

Analysis differs by uncovering data points emphasized because of some unique or significant contribution they make to the company. Reporting sometimes highlights critical changes in data, but it will never explain the importance or insignificance of these changes. Analysis, by nature, includes recommendations, giving the data more context and, therefore, more value.


Since reporting is a push-type output, it allows the user to access reports through widgets, Excel spreadsheets, analytics tools, mobile devices, FTP sites, having them delivered to their email’s inbox, etc. To cut down on time and energy, your business wants these reports to automatically build and send themselves to your email. You do not need a person going through every line of data every week to find the proper info.

Product analysis does not work well with automation because it requires high-level, human analytical and reasoning skills to detect the key insights and make actual recommendations about how to proceed next.


Every business wants its products to have value. The path to value starts with data and ends with a successful, profitable, and stable brand. Every stage in between plays a vital role in the sustainability and prosperity of your business. Reporting and analysis come right after data, followed by decision, then action, and, finally, value. Miss a single step and you may be putting your business’s success at risk.

Exceptions always exist, however, and some professional analysts may assert that they do not need the reporting stage and can glean all the information they need from a database and some raw files. This rarely holds true on the organizational level and reporting still plays an essential role in transforming the data into an actionable recommendation through analysis.