The inundation of consumer data thanks to the proliferation of mobile devices and social media has inspired the term ‘Big Data.’ The majority of data out there is unstructured and non-actionable causing many companies across industries to be overwhelmed by the volume.
Luckily, cross-media marketing or communications is a solution as it establishes an interaction between the different media elements. Cross media opens a line of communication with an existing or potential customer produces results that are measurable. Cross-media communications are structured to move the audience or prospect across the different media using strong “calls-to-action.” Each touch point builds on the experience and the “narrative bridge” teases you to investigate.
Since the inception of mass communication, marketers have been issuing the same message on multiple channels. Coordinated TV, radio, and print ads are nothing new. What makes a campaign become cross media is how the responses are funneled into a single data collection point to generate a dialogue. Marketers need to gather information from their clients and use that information to generate the follow on communications ‘ regardless of channel.
These days, marketers have to deal with the overflowing amount of data that businesses are having trouble keeping track of. They are being bombarded with information about their customers via television, print, digital, social, and mobile. As a result, there is an issue of understanding the level of awareness, favorability and purchase intent amidst all of this data.
Jorge Ruiz, partner and director of Media Analytics at Ogilvy, knows effective methods that help businesses utilize this valuable information. He sat down with IIR’s Marc Dresner at last year’s TMRE
to discuss key approaches to media data in order to go beyond purchase intent. ‘There are effective methods for executing brand studies with research partners. But, I have to go beyond that because I have another component to look at, which is ‘how is it selling or how is it moving acquisition numbers”? Ruiz told Dresner.
According to Ruiz, here are 3 approaches to cross media data:
This works great for time-sensitive purchases. If you do cross media studies and are able to send out the surveys and tag all your media to recognize it the day after the event, you can ask purchase questions to sample people who purchased it in the last 24 hours. It is important because you want to be able to translate that number into an estimate ROI within the survey data.
Cross Media Study Data
According to Ruiz, this works when you have the ability to match to a sales panel. This is very scalable in the consumer packaged goods world. It’s a matter of combining digital exposure data with sales panel data and finding ways to create a probability model for your offline exposure data.
Google Search Data
Using data and long-term trends discovered from it, you can use search as an indirect variable. As you are building consideration you are actually seeing changes in search and it makes sense for certain categories. As long as you know people are going to search for product line, it makes perfect sense.
‘There are a lot of different approaches and methodologies, but I love every single one of them,’ said Ruiz. ‘I worry less about which approach has the best methodology, and worry about there is not enough scale.’
To watch the full interview, click here: http://bit.ly/12QG68P
Media Insights & Engagement
The trends and changes in media consumption habits binge viewing, companion devices, social TV, cord cutting, the new watercooler – are challenges you face every day. Not only do you need to understand how media is being consumed, but also how to better engage with consumers on all screens wherever they are watching. We invite you to join us at the Media Insights & Engagement Conference taking place on Jan.29-31, 2014, in Miami to collaborate with all the key players in the media industry, including Cable, Broadband, OTT, Satellite, and Telecommunications, navigate content and explore new opportunities with insights-rich decision making.
* Republished with permission from original here.