Google Announces Plan to Use Credit Card Data to Measure Ad Effectiveness Offline

Peter Roesler, President - Web Marketing Pros

By Peter Roesler

President, Web Marketing Pros

Google-HQ-2016One of the hardest things to do in online marketing is showing the effect online content has on in-store sales. This problems is faced by all forms of advertising. Customer rarely go to a business and tell the business owner they are shopping for items they saw on a television commercial during the second ad break for CSI: Miami.

This is why advertisers and marketers have had to use proxies like clicks to the website, circulation numbers and other kinds of data to show that a campaign or platform is worth using. Google has announced an ambitious, but controversial, plan to use credit card purchase data from offline purchases to see if online ads are effective.

Earlier this week, Google announced the upcoming release to Google Attribution. Google Attribution will allow advertisers to see whether online ad campaigns generate offline sales, by matching data from AdWords with credit and debit card transaction data. And make no mistake, Google has a lot of credit and debit card data to work with. According to the statements quoted by the BBC, Google captures around 70 percent of credit and debit card transactions in the US.

“Today, we’re announcing Google Attribution, a new product to answer the question that has challenged marketers for ages, “Is my marketing working?””, wrote Sridhar Ramaswamy, Google’s Senior Vice President of Ads & Commerce. “For the first time, Google Attribution makes it possible for every marketer to measure the impact of their marketing across devices and across channels — all in one place, and at no additional cost.”

Google is being a little coy about how all of this works. They will be able to collect credit and debit card data via third-party partnerships. The data won’t show individual purchases, but will have some information about spending that can be combined with other Google sources to produce the results seen in Google Attribution and the upcoming Store Sales Measurement (which is due to come out in a few months).

Attribution Diagram cropped

Here’s how Google describes how Google Attribution works:

“Google Attribution also makes it easy to switch to data-driven attribution. Data-driven attribution uses machine learning to determine how much credit to assign to each step in the consumer journey — from the first time they engage with your brand for early research down to the final click before purchase. It analyzes your account’s unique conversion patterns, comparing the paths of customers who convert to those who don’t, so you get results that accurately represent your business.”

Needless to say, the new plan has drawn the ire of privacy advocates who say Google already has too much information about consumers. These are certainly valid concerns, but it’s worth remembering that Google already has a wealth of information about consumers based on their search history and mobile data alone. Google has used that data in the past to help marketers and the company has tried to balance the concerns of consumers and the needs of advertisers. It has worked relatively smoothly for the past few years and there’s no reason to think that Google will go into full Big Brother mode now.

For business owners and marketers, Google Attribution can be an extremely helpful tool for seeing what is or isn’t working in their online ad campaigns. If the people who saw a particular variation of an ad were more likely to use their credit cards to purchase something from the physical retailer, more budget can be spent on that ad variation.

Online platforms like Google, Facebook and Twitter have taken a lot of flack over the inability to directly show the effectiveness of online ads for brick and mortar stores. By being able to track the offline actions of people who were shown certain ads could give Google another leg up on its competition.

For more recent news for online marketers, read this article on recent changes to the search algorithms on Facebook and Google.

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