Analytics Success Lies in Digesting Related Segments

Pie

Our 10th analytics class focused on how to best analyze and understand data.

The top-level message I came away with is a data metric shouldn’t be evaluated in isolation, which is meaningless.  For example, knowing only that users spent an average of five minutes on a page offers no insight to validate or adjust your strategy. It may mean only users from a paid referral on one day of the year spent this much time on the site and on other days or referrals from organic/social/direct bounced after 10 seconds.  This would call for course corrections to improve results but without looking at the ‘big picture,’ these issues might go undetected.

Specifically, you should assess data metrics:

  • In context with the organization’s goals, what competitors are doing, industry information, internal initiatives, external events/trends…
  • Ideally in related segments, such as: referral sources (paid/social/organic/direct), days of the week (weekends and weekdays), times of the day or platforms used to access a site.

Sofia cautioned against comparing unrelated data metrics, such as tablet use with social referrals or creating compound or ‘super’ combinations like Alexa page rank with inbound links.

I found it interesting to note that higher numeric data (e.g. 10,000 contact page exits on every 100,00 visits), might deliver exactly the same statistical significance as smaller data (e.g. 1,000 contact page exits out of 10,000 visits) but is more effective when expressed as a clear outcome, such as 10%, versus a ‘muddy’ ratio like 10,000:100,000 or 1,000:10,000. However, I think higher numbers do strengthen a metric’s value.

For the class exercise, we re-examined the metrics set for our senior project, identified segments to be assessed and ways they might be visually depicted.

For my project, here are some KPI segmentation and visualization options:

  • Percentage of conversions by each referral source, such as social (fb, Twitter, Reddit), organic, paid and direct in a specific month, compared to non-conversions by referral sources in the same month.  (Visual depiction – 2 pie charts or a bar graph)
  • Specific Senior Care Share modules engaged in a specific month by referral sources. (Visual depiction – segmented bar chart)
  • Page views for a specific month, segmented by weekdays versus weekends. (Visual depiction – segmented bar chart, pie chart or even infographic with other metrics)
  • Page views in a specific month, segmented by referral sources. (Visual depiction – segmented bar chart)

However, as with all analysis, you should:

  • Find out what’s happening across the organization, such as other initiatives; business changes or help desk calls.
  • Consider external events that might impact data, such as holidays, market trends or even weather/power outages.
  • Possibly do surveys, click density analysis or other research….

….to get the full picture and extract maximum value from your data.

Illustration Source: Haml via Morgue File.
Advertisements

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s