Using Visual Analytics: Part Two
This post is the second in our series on using visual analytics. In our first article, we covered how to measure brand awareness behaviorally using organic search impressions and clicks to your website from brand and services phrases.
In this article, I wanted to take it a step further and discuss how to measure online consumer engagement when ultimately the purchase takes place elsewhere.
Getting to consumer engagement in a way that is tangible
If your buyer’s journey includes online purchase or lead capture, you have a fairly straightforward measure of engagement. However, if your customer’s purchase occurs offline or through another unconnected channel, tracking the effectiveness of your campaign to influence the purchase decision can be difficult. Still, there are ways to assess the impact of your marketing in these scenarios.
We ran one campaign for a CPG client where the objective was to help build awareness and consideration for the product in new markets outside their traditional regional base. The digital campaign involved a series of recipe offers inviting the consumer to vote for their favorite recipe, share and ultimately discover where they could find the product in stores.
The campaign targeted both new geographies and new demographics. Measuring how successful the campaign was across all of these variables using an Excel-style report would not have told the whole story. So instead we built a dashboard that allowed us to drill down and isolate performance by metro, by market was as well as the device type.
Getting to all of this information required a combination of tracking URLs for audience segment performance, Google Tag Manager to set up action or event tracking and Google Analytics for sessions, page views and geo-based details, as well as to aggregate the information into one version of the truth.
Levels of engagement were tracked based on interaction with the primary and secondary recipes as well as the percentage of voting consumers who printed their favorite recipe. The audience and device type filters were built into the views to allow for easy click and isolate views of the overall performance measures. Even the map was used as a filter with easy click actions on each of the key metro regions.
The result helped demonstrate strong segment response and how differently each of the audiences behaved. It went beyond simple recipe preferences and demonstrated which were more likely to share with friends and family, as well as showed purchase intent when users searched for stores near them where they could purchase the product.
Without the ability to drill into the data it would have been difficult to get to this level of intelligence on our engagement.
Next time we will look at how you can access marketing impact over time.
by Shade Wilson
Topics: Marketing Analytics