Google has just announced the theme of its upcoming Marketing Next, the company’s annual event wherein they reveal the latest innovations on ads, analytics, and DoubleClick.
A big theme that will be focused on would be Machine Learning, which is a technology that is critical to helping marketers analyze and study countless signals in real time in order to reach more consumers with more useful ads at the right moments. Machine learning is also the key to measuring consumer journeys that are now across multiple devices and channels from both the digital and physical worlds.
It’s a growing and critical trend for today’s marketers, and will continue to shape how you build for future success.
Hello Google Attribution, Goodbye Last-Click
Welcome Google Attribution, a new product which answers that has challenged marketers for ages: “Is my marketing working?” Google Attribution makes it possible to measure the impact of their marketing in one place, across devices and channels, and with no additional cost.
With today’s complex customer journey, a business might have a dozen interactions with a customer across several platforms such as video, search, social, etc, and all these moments take place on not just one, but multiple devices, which makes them harder to measure. The thing is, most attribution tools:
- Are hard to set up
- Lose track of the customer journey when people move between devices
- Aren’t integrated with ad tools, making it difficult to take action
The result is that many marketers are stuck using last-click attribution, which misses the impact of most marketing touchpoints. Google Attribution helps you understand how all of your marketing efforts synergize and deliver the insights you need for them to work better.
How it works:
Integrations with AdWords, Google Analytics and DoubleClick Search make it easy to combine all the data from your marketing channels. The result is a complete view of your performance.
With Google Attribution, it’s now easier to switch to data-driven attribution, which uses machine learning to intelligently determine how much credit to assign to each step in the consumer journey. From the first time a customer engages with your brand, down to the final click before purchase. It analyzes your account’s unique conversion patterns, and compares the paths of consumers who convert against those who don’t.
Finally, because Google Attribution integrates with ad tools like AdWords and DoubleClick Search, you can take quick action to optimize your ads, and the results will be immediately available for reporting, updating bids, or moving budget across channels.
Google Attribution is now in its Beta phase, and is expected to roll out to more advertisers over the coming months.
Mobile-Local Innovations Drive More Consumers to Stores
Mobile has already blurred the line between the digital and physical world, and while most purchases are still done over the counter/in-store, more and more people are turning to their mobile devices for prior research, especially in Google.com and Google Maps.
To aid consumers on deciding where to go, marketers use innovations like Promoted Places and local inventory ads to showcase special offers and what’s available in nearby stores. Now, you can also make it easier for them to find a store through YouTube video ads using location extensions.
Google introduced store visits measurement back in 2014 to help marketers gain more insight about consumer journeys that begin online and end up in a store, and in just three years, over 5 billion store visits have been measured globally using AdWords.
Google is the only company that has advanced machine learning and mapping technology to help accurately measure store visits at scale, and use these insights to deliver a better ad experience. The recent upgrade to deep models also enabled the company to train on larger data sets and measure more store visits in challenging scenarios with greater confidence. This includes visits on multi-story malls or dense cities like Tokyo, Japan and São Paulo, Brazil in which many businesses are situated close together.
Store visit measurement is already available for Search, Shopping, and Display campaigns. Soon, it will also be available for YouTube TrueView campaigns to help measure the impact of video ads on foot traffic in stores.
Regardless, measuring store visits is just one part of the formula. Insights will also be needed on how online ads drive sales for the business. In the coming months, Google will also be rolling out store sales measurement at the device and campaign levels. This allows for measurement of in-store revenue in addition to the store visits delivered by Search and Shopping ads.
If email information is collected at the POS for a loyalty program, store transactions can be directly imported into AdWords. And even if the business itself doesn’t have a large loyalty program, it’s still possible to measure store sales by taking advantage of Google’s third-party partnerships, which capture approximately 70% of credit and debit card transactions in the US. There’s no need for any time-consuming setup, costly integrations, and for sharing customer information. After opting in, Google can automatically report store sales in AdWords.
These solutions match transactions back to Google ads in a secure and privacy-safe way, and only report on aggregated and anonymized store sales to protect customer data.
Machine Learning Delivers More Powerful Audience Insights to Search Ads
Most of the time, people search with the intent to buy, and that is why Google is bringing in-market audiences to Search, to help in reaching users who are ready to purchase the products and services being offered.
In-market audiences utilizes machine learning to better understand a customer’s purchase intent. It analyzes trillions of search queries and activity across millions of websites to help figure out when people are about to buy and surface ads that are more relevant and interesting.
Tune in to the livestream to see the entire keynote at Google Marketing Next, and witness other innovations that the company plans to announce for ads, platforms and analytics.
Photo: YouTube
Emman has been writing technical and feature articles since 2010. Prior to this, he became one of the instructors at Asia Pacific College in 2008, and eventually landed a job as Business Analyst and Technical Writer at Integrated Open Source Solutions for almost 3 years.
