Google Announces an Integration with Google Analytics and ‘DoubleClick Campaign Manager’ (DCM, the system formerly known as DFA)

Background – Innovation and Integration

Google is famous for innovating around smart software in the cloud. Originally this was just organic search, but Google has proven to be much more than a one-trick pony. It turns out that the ability to construct a brilliant algorithm is also valuable in the world of business.

The latest from Google is an integration between Google Analytics and the DoubleClick Advertising System, also known as ‘DCM’ or ‘DoubleClick Campaign Manager’ (formerly DoubleClick for Advertisers – DFA). This is important because it is another step towards providing advertisers and their marketing departments with actionable information about which marketing ideas and channels are working. Historically Google Analytics allowed businesses to measure their audiences and e-commerce in terms of their important business goals, and now this information is being married with DoubleClick’s display advertising data.

The integration between Google AdWords and Google Analytics a few years ago was big news for the same reason – end-to-end visibility across the customer experience, as people would gather information, make comparisons, and then decide what product or service to purchase. This early integration gave advertisers one clear return on investment number (ROI) that could be used to optimize digital marketing campaigns; the inherent measurability across the sum of an organizations digital assets was the reason why advertisers started to spend more on digital and less on traditional mass media channels. The DoubleClick integration provides this same measurability, and ease of integration and more.

DoubleClick is one of the largest display advertising platforms in the world reaching 80% of the internet across the Google Display Network (GDN). “Every month over 500 million users are served literally hundreds of billions of ads” (Display Advertising: An Hour a Day – by David Booth, Corey Koberg). Major publishers and advertisers enter the market for this massive ad inventory using the DoubleClick Ad Exchange, and this platform allows for hyper-targeting of ads. It is easy to identify the smart advertisers and good ad platforms because you will tend to see ads that appeal to you, and are relevant. (Did I mention the denture ads I used to get on Facebook? … hmm 40 years too soon, but they did plant the seed!)

What Challenges Do Marketer’s Face Today?

Advertising today is complex, and the hardest part is simply measuring ROI on ad spend “cleanly,” in a very messy world. Understanding how ad messaging influences consumers and target audiences is really tough to measure for several reasons:

1) We do not necessarily know all the ads a person has seen.

2) We do not know which of those ads really contributed to purchasing decisions (or what non-measurable “word of mouth” influences or “co-incidental” factors might be at play).

3) Ad messaging may be shown across channels (online, offline, display, CPC, social, email), and it is hard to piece together the end-to-end experience of those making the decision to purchase.

4) Deciding which channels (online, offline, display, CPC, social, email) should receive credit for successful conversions is an ongoing challenge (required to calculate accurate ROI for advertising initiatives).

5) Time erodes clarity because a person may see an ad and make the decision to buy a product, then not make the purchase for another month.

6) A visitor may interact with advertisements and digital collateral across several devices (I have a smart phone, work computer, home computer, iPad), so it’s tough to stitch together these interactions to form a complete picture of the customer journey leads towards conversion.

How Is Google Solving for These Challenges with the DoubleClick Integration and Google Analytics Platform Enhancements?

Google is systematically working towards solving ALL of these problems as follows (numbering as per above):

1)     The DoubleClick integration with Google Analytics will now allow us to see the effect of ad impressions on a future conversion (“view through” conversions show the touch points visitors had with ads leading up to an online visit and a purchase – it is not necessary to click the ad before conversion to tie this all together). Ad impression and view-through data is now available in Google Analytics.

2)     We will never have a perfect understanding of how all consumers think, but we will have correlations in the data to understand the dominant trends that are valuable to marketers. All the points raised in this article speak to this growing body of data and the analytical tools and capabilities needed to secure these insights.

3)     Multi-Channel Funnels in Google Analytics (with DoubleClick integration) will show how consumers interact with ad messaging leading up to a successful conversion events. We will now be able to a) see the ad exposures for visitors leading up to a purchase, and b) quantify the value of display advertising in terms of the business outcomes (revenue) that advertising campaigns drive. (Some speculate that Google Glass will allow for Google to measure ad impressions that occur offline as these ads enter the field of vision of Glass wearers (magazines, billboards, newspapers, and traditional TV).

4)     Google Analytics has rolled out attribution modeling to all users (this used to be reserved for Google Analytics Premium users), which allows marketers to test various attribution models side-by-side to see the significance of channels with different credit weighting models. A common question remains: “Which attribution model should I use?” (Google has done one better in answering this question with the release of data driven attribution (DDA) for Google Analytics Premium clients. DDA uses artificial intelligence to objectively weigh the contributions of each channel to establish the best possible attribution model weighting: http://analytics.blogspot.ca/2013/08/data-driven-attribution-better.html)

5)     Attribution modeling in Google Analytics has recently gone from a 30 day look back window to a 90 day look back model, which will usually encompass 95% + of all conversions (depending on the business’ sales cycle).

6)     The newest version of Google Analytics called “Universal Analytics” allows marketers to integrate user information across devices with a user ID, and connect in-store retail activity and the use of Google Wallet!

Conclusion

Google is redefining digital marketing intelligence, making it more accessible, insightful, and actionable. The result is convenient “one-stop shopping” for agencies and advertisers, with one integrated reporting platform to help managers gather end-to-end marketing insights into customer behaviors. This is all happening in the context of key trends:

Technology Trends

1. Integrated insight into the consumer – across digital channels, across devices, and across retail experiences
2. Integrated measurement across channels (display ad impressions, social marketing wildfire, and offline with campaign tagging in GA)
3. Real time publishing and measurement (right now, I mean now!)
4. Integration of data and reporting systems (Google Analytics will centralize all this data allowing for complex queries across all integrated systems, as if it were one business intelligence system)
5. Integration of your customized business data inside Google Analytics (Universal Analytics custom dimension)
6. Cloud infrastructure delivered with economies of scale (Thank Google-ness for that!)
7. Big Data (large volumes of ad activity across a large number of big advertisers)
8. Increasing of ad dollars online because it’s all measurable (Let’s not kid ourselves, ease of use of the advertising system interface, ease of deployment with Google Tag Manager, and out of the box system integration in the cloud are the other compelling reasons for Advertisers to choose Google’s services)
9. One-stop shopping for all advertiser needs with a global reach (appealing to multi-nationals corporations with the largest ad budgets)
10. Democratization of attribution modeling (Free attribution modeling tool inside Google Analytics)
11. Operational streamlining and quality control (Google Tag Manager (GTM) publishing – one tag container to rule them all, Google Analytics tags and DCMs tracking pixels will be pushed live to production environments quickly and with a lower error/interference rate)
12. Artificial intelligence in digital analytics (DAA  http://analytics.blogspot.ca/2013/08/data-driven-attribution-better.html & Google Analytics intelligence reports https://support.google.com/analytics/answer/1320491)