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SmartData Collective > Analytics > Social Media Analytics > What Qualities are Needed to Be a Web Analyst?
AnalyticsJobsSocial Media AnalyticsWeb Analytics

What Qualities are Needed to Be a Web Analyst?

BIME
BIME
5 Min Read
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The number of web analyst positions has rapidly increased over the past few years particularly accelerated by the launch of Google Analytics in 2005, now by far the most popular web analytics tool. As well as on-site web analytics (analysis of ones own online property), off-site analytics has sharply increased especially with large sums of money available for the analysis of social media trends.

The number of web analyst positions has rapidly increased over the past few years particularly accelerated by the launch of Google Analytics in 2005, now by far the most popular web analytics tool. As well as on-site web analytics (analysis of ones own online property), off-site analytics has sharply increased especially with large sums of money available for the analysis of social media trends. Therefore we were interested to read French tech site – Journal Du Net’s 5 qualities of a web analyst. Here are the five qualities which they name and how SaaS BI can help.

 

1. Know the web : This may seem an obvious one but it can be broad and complex. “It is necessary to know the web ecosystem, its actors, the way it functions, the SEO, social media, AdWords, etc.. This knowledge can help identify early the correct signals on the website, help website optimization and detecting problems, it is important to know where to look and not get carried away with so called vanity metrics e.g. “time on site” “pages clicked”. Knowing the web and the way the web’s actors operate will develop the skills needed to detect what is really occurring on a site.

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How SaaS BI can help… As well as connecting to web analytics data, BIME can connect to a range of sources both online and on-premises including AdWords, Facebook, Salesforce among others. This allows web analysts to understand web data within the larger web ecosystem and within the sales pipeline.

2. Be Cautious : “Beware of jumping to hasty conclusions. Always ensure that the indicators are reliable and the method of tracking is correct”- web analysts can’t do anything constructive with inaccurate data so always check that the data coming in, is what it is supposed to be.

How SaaS BI can help… As with all analytics, nobody can work miracles with bad data but SaaS BI can help monitor web activity helping to recognise anomalous results. Calculations can also be made on the fly to double check the validity of data. A BI tool is useless with invalid data being inputted thus checks of the source data are also a must.

3. Have the ability to synthesize information : It is easy to get bombarded with data. A good web analyst will focus on the essential information first and use the data to quickly and efficiently obtain the information they are looking for. They have the ability to firstly sort and then present the data in such a way to make the data easy to digest for themselves and other interlocutors.

How SaaS BI can help… Dashboards can be built to provide an overview for both a quick snapshot of your web activity and help web analysts sort, synthesize and present the data.

4. A good listener : I recently read an article stating “To guarantee success, spend 95% of your time defining the problem and 5% of the time solving it” and this holds true with most web analytics. A good web analyst will listen : to internal or external clients, to understand the objectives, and to help both define and impact on strategy.

How SaaS BI can help… Visualizations can then be further investigated by dashboard viewers with drill down and drill through capabilities to dive into the base numbers and change metrics slightly to suit specific dashboard viewers. As strategy changes, dashboards are quick and easy to update and with the SaaS pricing model can be scaled up and down when needs and objectives change.

5. The ability to speak the lingo but also do without : Like most professions, web analytics has a myriad of different technical terms. This final skill is to firstly learn exactly what these terms mean but then be able to popularize them to relay them back to non-technical users.

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