It’s time to go live. Your team has been through the weeds with your vendor of choice for months now. Your requirements have been gathered, your solution has been built and it’s almost time to take it out for a spin. You couldn’t be happier. And neither could your vendor.
The Internet of Things is at a tipping point, and it will soon give companies the ability to collect an enormous amount of data. That dawning reality poses a challenge for marketers. Are you ready to capitalize on the Internet of Things while also being sensitive to your customers' privacy expectations.
There are pros and cons when it comes to a geo-targeted campaign structure, and many considerations to identify what is right for your brand. Some clients require geo-level campaigns for reporting purposes, but there are strategies to achieve the same level of data insights without the task of creating and managing numerous duplicate campaigns based on geography.
Big Data. It’s what every marketer needs to establish competitive advantage in today’s digital world. However, there is little insight into how Merkle ensures the quality and accuracy behind each client solution. Let’s take a look inside the "test it" portion of the process to see what's involved in verifying the integrity of a world-class big data solution.
Last fall, I posted a piece, titled “Good Customers vs. Bad Customers: How CRM Can Help You Understand the Difference and Do Something About It,” in which I discussed the importance of treating “good” customers differently than “bad” customers and the ways that leading brands approach these challenges.
Google now offers demographic geo-targets for the United States based on average household income (HHI) for advertisers to use in setting bid modifiers based on the wealth of the area users are searching from. At RKG, we've fully explored how these income level targets behave, how much traffic is attributed to them in different set ups, and their usefulness in the future of geo-bidding.