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Web analytic success requires accurate data quality

Rachel Wheeler Archive
Data quality is an essential part of successful web analytic practices. If information is inaccurate, decision-makers could implement strategies and programs based on false numbers. To reduce the chances of following incorrect trends, companies need to properly implement data quality tools, according to an iMedia Connection report.

The effectiveness of any web analytic solution is directly proportionate to how it is used. For example, if an organization mistakenly swaps quantity and price, it will have inversed two vital metrics, creating the opposite trend of what is actually happening. As a result, businesses will lose efficiency and develop programs that would otherwise not be applicable to them, the news source reported. It is important for companies to check, recheck and possibly hire professionals to ensure web-based analytic tools are following the right information and providing the correct insight.

Running an audit report and having records reviewed by industry experts is an effective way to ensure data is accurate. These evaluations will compare the gathered records with past analyses, standards and numbers from potential competitors, according to an Xplanations report. These processes need to be well-documented so that decision-makers are able to edit and revise the process if a mistake is discovered.

Additionally, advancements in technology and the advent of big data have created new factors that may affect information quality and related trends. In the past, consumers accessed websites solely through desktops, making it easy for IT departments to analyze and deploy tracking tools. In today's world, however, tablets, smartphones and laptops can all access the internet. As a result, the same user could be visiting a webpage via multiple platforms and a company may not know it, iMedia Connection noted. In this case, a business will decipher excessive and inaccurate information, making the analyzed trends untrue.

Changes in vendor behavior also directly correlate to the quality of data. Algorithm variations, such as the way Google modified how it analyzes and classifies visits, will impact how accurately an organization can gather high-quality information. Analyzing statistics based on inaccurate visit metrics will only offer misleading information, iMedia Connection said.

In the end, data quality is essential to how a company operates, as only accurate information allows decision-makers to implement the right strategies and technologies that will promote growth in the future.