Getting the most out of enterprise analytics systems is not easy. A lot can go wrong on the way from gathering business requirements to getting actionable insights. While most of my posts are focused on the analysis or reporting capabilities of Adobe Analytics, this post is focused on how I plan and build my implementations. With an analytics system like Adobe Analytics, even small implementation choices can have large consequences later down the value chain. Errors and misjudgments can lead to skewed data that is affected in a non-obvious way. The implications range from more effort during analysis or higher maintenance to wrong conclusions and business decisions. This post will walk you trough the number of steps I take when planing a new Adobe Analytics implementation. While I’ve been successful in delivering value by following those, there might be situations where a different approach is better suited to the task […]
Tag: Tracking
Building your own Web Analytics from Log Files – Part 5: Building our first Dashboard
This is the fifth part of the six-part-series “Building your own Web Analytics from Log Files”. At this part of the series we have our log files in Elasticsearch with indices like “custom-filebeat-tracking-logs-7.4.0-2020.01.03”. First thing is to set up a Kibana index pattern for this. Kibana Configuration In Kibana we go to Management -> Index Patterns -> Create index pattern. As Index pattern we use “custom-filebeat-tracking-logs-*”, which gives us all the indices with our daily index pattern. In the next step, we set the Time Filter field name to “@timestamp”. This is the timestamp that marks the point where Filebeat indexed the document. This is fine for now, we click “Create index pattern” and are done with this part! Checking our Data Now, let’s head to the Discover section in Kibana and look at our index pattern. And there it is: Our log entries show up like we wanted: This […]
Building your own Web Analytics from Log Files – Part 4: Data Collection and Processing
This is the fourth part of the six-part-series “Building your own Web Analytics from Log Files”. Legal Disclaimer: This post describes how to identify and track the users on your website using cookies, IP adresses and browser fingerprinting. The information and process described here may be subject to data privacy regulations under your legislation. It is your responsibility to comply with all regulations. Please educate yourself if things like GDPR apply to your use case (which is very likely), and act responsibly. In the last part we have built a configuration for OpenResty to generate user and session IDs and store them in browser cookies. Now we need a way to actually log and collect those IDs together with the requests our web server handles. OpenResty Configuration To be able to log our custom variables we need to announce them to Nginx. This is done right in the server-part of […]
Building your own Web Analytics from Log Files – Part 3: Setting up Nginx with OpenResty
This is the third part of the six-part-series “Building your own Web Analytics from Log Files”. Legal Disclaimer: This post describes how to identify and track the users on your website using cookies and browser fingerprinting. The information and process described here may be subject to data privacy regulations under your legislation. It is your responsibility to comply with all regulations. Please educate yourself if things like GDPR apply to your use case (which is very likely), and act responsibly. Identifying Users and Sessions One of our goals for this project is to be able to tell how many people are using our site. This means we need a way to differentiate between the users on our site. One approach would be to look at the IP addresses of our users. This is not very precise since all devices with the same internet connection share an IP address. Especially for […]