google-attribution-online-marketing-assessment

Google earlier this week unveiled Google Attribution, a tool that uses machine learning to measure the effectiveness of online marketing campaigns across a variety of devices and channels.

Part of a series of new measurement tools introduced at Google Marketing Next, Google Attribution aims to help marketers determine what is driving consumers to make their online purchasing decisions.

Google is at an “inflection point,” noted Sridhar Ramaswamy, senior vice president of ads and commerce, when it comes to the use of technology to measure online marketing effectiveness.

“What’s exciting is that things that were really hard we’re going to be able to make easy, because technology is doing the heavy lifting,” he told conference attendees.

Seconds Matter

Page-loading time is an important factor in terms of how long advertisers have to hook a consumer online, Ramaswamy said.

As load time increased from one to seven seconds, the probability of a consumer bouncing more than doubled, found a recent study that analyzed 900,000 mobile landing pages in more than 100 countries. That translates to conversions falling by up to 20 percent for every one second delay in page-load time.

Most existing attribution measurement tools have three main shortcomings, according to Ramaswamy. First, they lose track of the customer journey when they move between tools; second, they are hard to set up; and third, they are not integrated with ad tools.

Because of those shortcomings, marketers typically are stuck with using last-click attribution, which misses the impact of most marketing touchpoints.

The new Google Attribution tool incorporates data from AdWords, Google Analytics and DoubleClick Search, which provides a more comprehensive picture of data from all marketing channels, according to Google.

Google Attribution also makes it easy to switch over to data-driven attribution, which uses ads, keywords and campaigns that have the greatest impact on a company’s goals, Google said. Using the data-driven attribution model…