AnalyticsAnalyzing Customer DataBuilding Out a Web Analytics Team

Building Out a Web Analytics Team

To be effective, a digital marketing analytics team needs these three skill sets. Can one person possess them all?

Despite tough economic times, organizations in the U.K. are building out their Web analytics capabilities and teams. It’s a trend I’ve observed and expect will continue.

A number of clients I work with are looking to bring on new people. And the job market for Web analysts remains reasonable healthy. In some cases, companies are looking to appoint their first person into a new role. Increasingly, some organizations are looking to expand the team to two, three or more people.

When organizations build up an analytics team, they encounter an interesting challenge. They must determine the right mix of skills to manage the variety of tasks that a Web analyst team must handle. There are three main competencies that companies must look for: insight generation, data integrity management, and data management and manipulation.

Insight Generation

An analytics team must be able to produce actionable insights that the organization can use to make decisions and drive the business forward. To do this, someone must extract value from investments that have been made in data and technology. This is the Web analyst‘s true role. Skills and competencies for insight generation are business orientated rather than technically orientated. In my view, a good Web analyst is an internal consultant with strong data pattern recognition skills, possessing the ability to communicate findings to the business in terms it can understand. Attributes of a good Web analyst include curiosity, a desire to understand why things are the way that they are, and what can be done about it. For me, most analysis is about pattern recognition, the ability to identify trends and associations in the data, and by the same token, things that don’t look right.

Data Integrity Management

Most people don’t like making decisions on dodgy data. It’s vital to get data integrity right. Generating good quality data from a Web analytics system requires continuous management and maintenance, representing another competency required in a Web analytics team. This attribute, which is more technical, requires a different set of competencies and skills than insight generation. Most Web data is collected using page tags these days and most data quality problems stem from data collection issues. Pages aren’t tagged in the first place or the tag is wrong and collects the wrong data or data isn’t collected at all. As an organization’s analytical requirements become more sophisticated, the data integrity issue becomes more complex. Deep-level skills are required to ensure that the right data is being collected in the right way and that the system configuration is right to produce the right databases and reports for insight generation.

Data Management and Manipulation

If organizations are building out their Web analytics team, it probably means that the Web is becoming a more strategic and mainstream channel for them. At the same time, the business wants to know how the digital channel interacts with other channels. As a result, integration becomes more of an issue, so the analytics team needs to have good data integration and management skills. Often, it’s necessary to take data from one system and import it into another or to take data from two or sources and created a new data repository.

Can One Person Do It All?

Can these competencies be found in one person or are different types of people needed in a team? In my experience, it is rare for one person to have all the competencies described here. Someone who has strong insight generation skills may have a good understanding about data integrity issues but is probably not the person best suited to wiring a specification document for tags for a new piece of the site’s functionality. In the same way, someone with good data management skills may not feel comfortable presenting findings to a group of executives. As digital analytical teams grow, organizations must determine more carefully the competencies required on those teams and recruit accordingly.

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