In this article, you will find some informative content about the importance of combining, visualising and unifying data from different sources to get deeper insights about user behaviours and intentions. You will find some tips, the key points and also you will find some use cases which have been done by using Google Data Studio, Oracle Responsys, Oracle Eloqua and Adobe Analytics.
Understanding user behavior is one of the most informative & influential tools/methods for enhancing digital customer experience. It reveals what your users need and are looking for, providing actionable insights on whether you need to improve your user interface, expand your product range, or take other actions. People search, click, zoom in & out, scroll and/or browse on your assets. Every behaviour pattern could provide different insights into the visitors’ intentions and the way you should improve their experience.
To understand user behaviour, you need to analyse user signals. So, you first need to track relevant touchpoints in order to get analysis-ready data
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When reaching out to your audience, whether through a single channel or multiple channels, it’s crucial to track reactions and engagements for each one. Failing to do so means missing out on valuable data needed to analyze and understand the attribution of each channel to your overall performance. A key reason to be attentive towards different channels is that users may exhibit different intentions and behavior patterns depending on their traffic source/engagement medium.
Before enriching your data, you need to enhance your existing knowledge, and thus having a holistic approach is essential. This means integrating not only digital advertising but also customer experience (CX) marketing activities like Email, SMS, Web Push, and App Push into your digital analytics strategy, even if managed by another party. Your approach and strategy should be centralized and shared among all parties. Every stakeholder needs to appreciate the importance of tracking end-to-end user behavior. From there, it’s about leveraging your technical skills and creativity to visualize and utilize the data effectively
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Obviously, you need to have a good infrastructure, a solid measurement plan and technical skillsets necessary to execute. Key points would be having an understanding of tracking parameters, having a structured naming convention and defining which attributes you would like to pass along.
You might have several partners which manage different digital channels for you. To get a simplified analysis and to make sure that every one of your partners is addressing the right field on your data model with the right information, you need to have a structured naming convention for tracking parameters. For example, here are some basic tips to keep it structured:
Every detail counts. Why wouldn’t you want more insights into your users or the ability to delve deeper into your data? For instance, if you plan to send promotional emails, using customer IDs from your CRM system can help track user clicks and redirect them to your website. This way, you can connect any analysis on anonymous website behaviour with specific customers, even if they are not logged in. Additionally, you’ll be able to view their past interactions and traffic sources, such as whether they previously visited your site through another channel like search. Furthermore, sending CRM segments allows for detailed segment analysis. To enhance your analysis, it’s crucial to define and incorporate attributions appropriately. This approach ensures that you have a comprehensive view of user behavior and can make more informed decisions based on enriched data.
So far, we have created a structured naming convention, and we have defined the attributes that we would like to pass along to gather better insights. Now, it is time to combine all these elements and set tracking parameters. Different tools you use could have their own URL scheme to track and thus map your parameters with the dimensions. For example, while Google uses its UTM solution, Adobe uses a different scheme where dots and dashes correspond to functionalities within map fields.
Finally, we can now combine our outputs and unify them under a primary key dimension. This could be a Customer ID, Segment Name or just the Channel Name itself for a basic analysis. The examples below further elaborate how this would work.
Visualizing raw data effectively reveals valuable insights. With a range of visualization methods available—from simple tables and pie charts to more advanced options like scatter graphs and heatmaps—it’s important to keep the presentation simple, focused, and easy to understand.
It’s important to remember that our goal is not to mine data, but rather to highlight key metrics efficiently and generate insights. Instead of displaying every correlated metric, we should focus on creating calculated metrics that clearly show relationships between variables. We already have the numbers; what we need are the specific insights they provide. So, let’s make those insights stand out
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Raw Table
Simplified Visualization
When visualized like so, all our efforts are rendered worthwhile. By focusing on “actionable metrics” rather than “vanity metrics,” you’ll gain a clearer picture of your campaign’s effectiveness. Actionable metrics are those that are calculated and visualized to provide meaningful insights, showing how well your campaign performed. For instance, if an email campaign has high open rates, it might seem successful, but if it isn’t converting on your web assets as aligned with your KPIs, the open rates become less significant. In this case, web conversion rates—an actionable metric—are far more important than open rates, which are more of a vanity metric. Prioritizing actionable metrics will help you make more informed decisions and drive better results
At the time of this case study being scoped, our client used to utilize Oracle Responsys and Oracle DMP as AdTech and MarTech platforms for their marketing automation activities and to improve customer experience. Oracle Responsys was used for email and push notifications, while Oracle DMP was used to target anonymous profiles in the digital advertising world. Labrys provides expert & strategic services encompassing budget planning and platform utilization, covering all aspects of digital marketing plans.
We have developed a custom dashboard using Google Data Studio that integrates all their AdTech and MarTech stacks into a unified view. This dashboard provides an executive overview of performance. By linking Responsys activities with web asset behaviors by using campaign names as the primary key, we can track and analyze which email and push notification campaigns yield the highest conversion rates
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Our client uses Oracle Eloqua and Oracle DMP products as AdTech and MarTech platforms for marketing automation activities and to improve customer experience. Alongside they are using Adobe Analytics for as web analytics solution. Oracle Eloqua was used for sending emails and sms , while Oracle DMP was used to target anonymous profiles in the digital advertising world. Labrys provides Expert & Strategic Services as their CRM Agency and covers all areas for CX and CRM activities from planning to execution.
We have created a custom dashboard by using Google Data Studio andcombined Eloqua and Adobe analytics da
ta. Then, we’ve implemented some dynamic parameters on their redirection URLs for emails and as a result we’ve been able to passback users’ CRM attributes like segments and IDs to Adobe for combining their Eloqua activities with web asset behaviours. We managed to gain insights about specific segments where some segments were more intended to just open emails but not performing as desired on the website while others were performing better on website even they had low email interactions. These insights had shaped our segmentation and content strategy throughout the year. And as a result, users whom get communicated within this process have been activated 6 times more than whom didn’t
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