Consider these three challenges when measuring performance of an integrated marketing campaign.
I like integrated marketing. No matter if it is multi-channel or cross-platform, the challenge of running an integrated marketing campaign always brings me more satisfaction as a marketer. Of course, part of the satisfaction is from the process of scientific measure of my campaign performance.
Recently I have been drawn to the study of possibility and practicality of monitoring integrated marketing performance. Google Analytics is transforming itself into a Universal Analytics solution. The universal solution could be universal, but the end solution to measure online-offline marketing performance can't be very integrated.
To demonstrate my point, I would like to build a scenario and then to hypothesize what is needed for preparing an integrated analytics model.
The above diagram (moving from left to right) illustrates an O2O marketing journey. The online experience starts when a trade buyer researches an event on a search engine. He is first engaged by the social content on Facebook and then RSVPs online for the event. Then when he arrives at the event venue, the offline experience begins with his registration for a badge printed with a QR code that contains his personal identification. After his badge is scanned by a mobile device, he can interact with the event contents upon his arrival at an exhibiting booth.
For a marketing journey like the above, we can easily collect online intelligence via the web analytics. Although the online intelligence is mostly anonymous, we can get a universal representation whether you are relying on clickstream data or traffic segmentation. You still get a sense of the result from what you are measuring. When the journey moves into offline, our challenge is to deal with the issue of information heterogeneity. At this point, all the information that we collect is no longer universal and they are hardly integrated.
Challenge 1: Uncontrollable data model
The first challenge of offline marketing analytics is the uncontrollable data model. For instance, in the diagram above, the data used for registration and printing the visitor's badge is not connected with the online user profile even though the online RSVP traffic is recorded as a conversion. They are simply a series of individual entries of the online conversions that will be used to match with the offline registration entries. Since the online and offline data registration are handled by different parties most of the time, the data matching only serves as a data interface, but not a universal user profile. It inevitably creates a gap for realizing the behavioral relationship between the offline turnouts and how people are influenced, engaged, and converted online.
Challenge 2: Changing data characteristics
The change of data characteristics is the second challenge of measuring integrated marketing. When we measure marketing performance, we should avoid the obsession of numbers because numbers are all passive and aftermath. Throughout a marketing journey, data is just some numbers and reflects different stages of marketing. In other words, how do we interpret the changing user actions from micro and macro conversions that represent the state of business from lead to opportunity? Most importantly, please bear in mind that in a non-line world, the online conversion is not the result. Instead, it only leads to the beginning of the macro conversion that happens on the ground like what I have presented in my diagram. The macro conversion, in fact, happens when the buyer interacts with the booth content rather than when he RSVPs for the event over the web.
Challenge 3: Developing useful insight
The third challenge is to develop useful insight from the data. I believe that a decent integrated marketing analytics should be able to answer three simple questions for three business insights: (1) What has been enquired? Acquire the product insight. (2) When do the inquiries happen? Identify the best moment of the truth. (3) Who makes the inquiry? Obtain the business leads. Although at the moment there is no single solution available in the market for generating such integrated insight, with a carefully crafted analytics plan you will be able to connect the dots. What you need to do is to generate a universal identifier at the time when the online conversion happens and then to use it throughout all the marketing touch points. It is like the URL for all offline marketing actions as a subset of the online URL.
In theory, when each offline URL is visited by a source of interaction, it registers itself with a virtual page view. Take my diagram as an example again, you will see the following possibility:
At the moment, I am still in the early stage of practicing the possibilities. The offline URLs will be used in all my marketing channels. Following the vision of our founding fathers of the Internet, I am adopting the uniform resource locator to reference all the touch point activities for both online and offline marketing. And then I will use GA as a universal data container to consolidate all the traffic for generating a holistic marketing insight.
I hope I can give you more exciting updates in the future posts.
Eddie is the founding partner of Frontiers Digital and the Executive Director of Milton Exhibits Group. Although Eddie studied classical theory of sociology in college and has a MBA, technology always has been a passion with him. He believes that a combination of technology and communication is what the modern marketing is heading towards in the future. Eddie is a member of Search Engine Strategies Global Advisory Board.
2015 Holiday Email Guide
The holidays are just around the corner. Download this whitepaper to find out how to create successful holiday email campaigns that drive engagement and revenue.
Three Ways to Make Your Big Data More Valuable
Big data holds a lot of promise for marketers, but are marketers ready to make the most of it to drive better business decisions and improve ROI? This study looks at the hidden challenges modern marketers face when trying to put big data to use.
December 2, 2015
1pm ET/ 10am PT
Wednesday, December 9, 2015
5pm HKT / 5am ET