A few weeks ago at Google Marketing Next, Google Attribution was released. Search strategists rejoiced, brands got all teary-eyed and marketing managers popped champagne bottles. Their attribution prayers have finally been answered. On the other hand, in our office eyes rolled, laughs were stifled and chairs emptied with the announcement. Yes, the integration between DoubleClick Search (DCS) and Google Analytics is definitely a step up from the attribution models offered in AdWords, but it’s still a free model that only uses Google campaign data to measure the influence on marketing decisions. If a brand is doing anything outside of AdWords (direct publisher buys, paid social, TV, print, direct mail, press releases, sponsored content, etc.), there are major issues with using Google Attribution. Conversion Windows Think of a product you’ve purchased in the past month. Not toothpaste or a product that you run down an aisle and pick up, but a purchase decision that you really put thought into – a car, a TV, a pair of headphones, etc. How long did you evaluate that brand? Was it longer than 90 days? If your brand has a product that costs more than $100, odds are the time from first interaction with the brand to the actual purchase is more than 90 days. AdWords and Analytics conversion tracking only report up to 90 days before the lookback window expires. That means that if someone came to a brand’s site 91 days ago, then did a branded search and converted on day 91, it would be reported as if that customer came to the site once and converted on the same day according to AdWords and Analytics. In Google Attribution, it’s the same thing because it also relies on conversion tracking that can’t go beyond a 90-day window. Example: An ecommerce client that we’ve been working with for a few years implemented 3rd party attribution models with tracking windows that exceed 365 days. The goal was to isolate the first interactions with the brand that are converting into sales and scale those opportunities in order drive a more efficient return-on-ad-spend (ROAS). In Analytics, 42% of their transactions have a lag time of zero days with 20% at 61 – 90 days. So Google Attribution will show same-day transactions for almost half of their campaigns. The 3rd party model tells a different story. The same time period is showing an average lag time of 63 days from first interaction to transaction. Of those transactions, 30% of their total transactions occur past the 90-day window. Optimizing campaigns based on Google Attribution would skew 30% of their revenue to the wrong originating channel. The Google Vacuum The biggest issue that I have with Google Attribution is that it only measures interactions and brand engagement that come from Google products. Yes, it integrates with Google Analytics which tracks paid and unpaid channel sessions that are tagged appropriately so it means everything is evaluated the same, correct? That couldn’t be more wrong. Google Analytics only tracks paid and unpaid sessions within a brand’s site. It doesn’t factor in impression-based interactions with digital media or traditional media that lead to a branded search or direct navigation. AdWords and DCS can measure view-through conversions and will report on those within Google Attribution. The result is performance will appear greater on campaigns running through Google AdWords because Google Attribution will be going off of view-through and click-through conversions. Any external (non-Google) campaigns will only reflect click-through conversion performance because Google Attribution only integrates with DCS, Google Analytics and AdWords. It does not integrate with other 3rd party platforms. Example: The same ecommerce client in the previous example is running a cross-channel media mix including search, email and display campaigns with publishers and programmatic partners. According to their Analytics account, only 0.5% of their revenue for the past 6 months is attributed to display campaigns. Branded search and email account for 98.1% of their revenue. Based on the Analytics data, the client should take all spend out of the display campaigns and invest in branded search and email. But customers don’t magically perform a branded search. The email fairy doesn’t just add new accounts to a CRM while a brand is sleeping. In Google Attribution, it’ll show a brand that it’s wasting money because it doesn’t integrate with 3rd party ad servers or attribution data. The same client is running a 3rd party attribution model that integrates traditional and digital media into its model. Because it measures both click- and view-through interactions across all channels, we’re able to show a 424% ROAS in a 3rd party model rather than a -88% ROAS if we used AdWords and Google Analytics data. A great villain once said, “if you’re good at something, never do it for free.” That’s just as applicable to Google Attribution as it is to the DC Universe. It’s a free product that relies on shorter conversion windows, can’t pull in 3rd party data sets and skews performance towards Google products. Brands rely on being able to pull in additional data sets accurately. If they can’t, then they’re basing their decisions on skewed data. Spend will be scaled up with Google products, and marketing managers will wonder why they haven’t seen an increase in leads or revenue. It’s because they’re working with an incomplete model. If you’re a search agency or a brand that’s 100% invested in only the Google Display Network and Google Search, this is a good product to use, but keep in mind, free isn’t always a good thing. Let us know your thoughts!