How to Segment & Investigate Your Analytics Data

In our last analytics post, How to turn Analytics Data into Actionable Business Insight, we explored the definition of analytics, and introduced the 3-step process for turning analytics data into insight.

In this article, we’re deep-diving into the ‘Analysis’ part of the 3-step process, focusing on how to segment and investigate your data to inform your business descisions.

Data Analysis Leads to Better Decision Making

Let’s assume we have analytics configured on our website, and we’ve been collecting data for a number of months now. We’ve set up automated reports and dashboards to be sent out to senior business stakeholders on a regular basis.

Fantastic, right?

Wrong.

By taking this approach, we bypass the ‘analysis’ phase of the process, and the insight delivered is simply summarising top level KPI movements. There is no way for the report to dig below the surface to establish and understand the determining factors contributing to the movements.

As such, insight is often limited to top-line information such as, ‘traffic was up 20% yesterday’.

On one hand, this may seem like great news, but what if we launched new a digital marketing campaign yesterday?

For example, let’s assume that yesterday we launched a new PPC campaign aimed at driving onsite purchases, with a budget of £15,000 per day.

Traffic was up 20% yesterday’ doesn’t provide any indication as to whether the extra traffic resulted in an uplift in sales.  If the data was properly analysed, we could add much more context to the traffic movements to reveal actionable business data. 

With professional analysis, the statement, ‘traffic was up 20% yesterday’ turns into:

  • Traffic to the site was up 20% yesterday, which was largely driven by the new PPC campaign which was launched yesterday.
  • PPC traffic yesterday accounted for 26% of the overall traffic to the site, up 16% vs the previous week.
  • PPC traffic also converted much higher than overall site conversion (2.47% vs 1.96%), indicating users are responding well to the new campaign.

You can see how the latter provides a much more rounded view of site performance, whilst also highlighting the impact of the PPC campaign.

This enables the business to make informed decisions around the campaign management. For example, increasing or holding the budget, or extending the campaign.

Data Segmentation - The Key to Revealing Insight

The key to turning data into insight is ruthless segmentation.

Segmentation is, ‘the process of breaking down large chunks of data into more granular groups of data, by cross-referencing one metric against another’.

For example, we can segment website traffic (sessions) by channel, in order to understand how many sessions are being generated organically from referring sites, social media etc.

We can then isolate sessions for specific analysis based on their segments, for a deeper understanding of the web traffic, (i.e. just show me direct to site sessions.)

Various segments can also be combined to reveal more granular data, (i.e. just show me direct to site sessions and users who viewed more than 5 pages.)

The typical metrics which web analysts segment data by are:

Acquisition Data
Which marketing activities are generating what volumes of web traffic? For example, how many users are coming from PPC campaigns?

Behavioural Data
Which activities are users undertaking on your website? For example, just show me users who view four pages or more.

Outcome Data
Which site activities are helping to generate value for your business? For example, how many users download a PDF?

The true value of segmentation starts to come as we add multiple layers of segments to data. This can help answer questions such as, ‘what’s our PDF download conversion for SEO traffic vs PPC traffic’?

This is all summarised quite nicely in this graphic:

analytics3

In our next post we’ll be looking at how to turn the insight you’re generating into business reports, as well as evaluating different ways of presenting data to engage your audiences.

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