Google Re-Branding and Updates 2018 – Here's What You Need to Know
August 1, 2018
Google is re-branding and updating its entire suite of marketing products in 2018. Here is an overview of what’s happening and how it may impact your business marketing this year and beyond.
Automation and Audiences
The shifts that Google is making this year can be summed up in two words: automation and audiences.
As Google’s machine learning technology advances, more of the tactical work on the platforms is being automated. Across various products, the goal is for the business to be able to input product concepts and goals, then let Google target and create the ads – as well as some of the marketing creatives.
The products are being consolidated into three platforms: Google Ads, Google Marketing Platform, and Google Ad Manager. Via these platforms, all advertising channels and analytics can be accessed.
The idea behind these updates is effectiveness and efficiency. They want to get all these resources under one umbrella and take away the excessive task management involved with many of the tactics. For example, Google Marketing Platform connects all these tools:
Much of this is geared towards improving the optimization of ads that many businesses miss, i.e. the lack of diligence with A/B testing and data-driven modification. Google wants ads to have maximum effectiveness with minimal work required from businesses.
Next, Google is moving from an understanding of intent to predicting consumer behavior. This means that instead of focusing exclusively on data like keyword search, they want advertisers to gain a greater understanding of audience segments (often at a personal, granular level) and start predicting what they want at any moment.
Google states:
Intent is everywhere. Whether people are searching for the best products, browsing deals, or scrolling reviews, they shift between devices, channels, and across numerous touchpoints. We’ve never been closer to engaging people across their entire journey and assisting them with exactly what they need when they need it. To do so, brands must stop chasing intent and start predicting it. Brands can use predictive signals from search to create, capture, and assist people with what they need, wherever they are. And when you use machine learning and automation to tap into those signals, you can move from chasing intent to building an engine that enables you to anticipate it.
These are major shifts that will change the nature of inbound marketing. Much of what we’ll discuss here for small businesses is coming under the umbrella of Smart Campaigns, their automated local business solution. Here’s an overview of what’s bringing the biggest changes.
Responsive Search Ads
Responsive Search Ads is the new platform that best epitomizes the direction Google is heading with automation.
This ad type automates ad testing in an effort to replace A/B split testing and automated ad rotation.
With responsive ads, the business provides sets of headlines and description lines. Google automatically displays the combination that best matches the user’s search query.
The amazing thing here is that with 15 headlines and 4 descriptions, Google can serve over 43,000 ad permutations. This, of course, is beyond the capability of manual optimization.
This is about more than just serving the best performing ad like the current automated ad rotation. Over time, RSA will serve the best message for searchers depending on not just the keyword query, but their device, past browsing behavior, and how well the query matches the conversion goal.
Auto-Optimized Landing Pages
Google notes that a lot of small businesses don’t have websites, and others do a poor job of creating optimized landing pages for their ads.
As a potential solution, they are testing auto-optimized landing pages which use machine learning to pull information about your business directly from ads. This is matched to the on-page creative.
Put these first two solutions together and you have a fully automated ad and landing page system that uses machine learning to optimize results.
Local Campaigns
A welcome expansion in data tracking will be in local campaigns aimed at driving store visits. The new platforms are designed to do a better job of tracking phone call conversions, requests for directions, and walk-ins to physical locations.
For example, a person may do a search for a business and get directions from an embedded map. Then, their location is tracked (if they’re logged in to their Google account) so that when they enter the business, it counts as a conversion.
Local businesses often have the most difficult time tracking ROI from their digital marketing because many actions and results are hard to track. Hopefully, the new platform integrations will provide more in the way of actionable data for these businesses.
Cross-Device Tracking
Cross-device reporting attributes conversions to multiple devices. The new integrated platforms will offer more accurate data tracking for cross-device conversions, which are increasingly common. Now businesses can compare data across desktop, mobile, and tablet as they contribute to each stage of the conversion process.
Attempts at cross-device attribution is nothing new, but the new platform – as it ties disparate resources together – promises to offer accurate, actionable data on cross-device conversions.
Smart Shopping
On the eCommerce side of things, similar levels of automation and audience targeting are coming to Google Shopping.
Another welcome place for automation will be the creation of product shopping feeds. The current manual process for uploading products to Google Shopping is cumbersome and error-prone. If this can be done with a “touch of a button” it will be a welcome improvement.
More automated advertising is promised, with machine learning making pragmatic bid adjustments, optimizing what products to feature (based on factors such as pricing and seasonality) and optimizing ad placement.
In addition, they will be integrating these platforms into eCommerce platforms like Shopify, allowing businesses to manage and track ad performance directly from their store platform.
Control vs Convenience
These are fascinating developments that give an indication of where digital advertising is headed. Machine learning is on the cusp of being able to understand consumer audiences to the degree that it can create advertising campaigns that not only target consumer intent, they predict it.
Much of this technology is ready to be taken out of beta, so business owners will have to confront these changes before 2018 is out.
The real question with automation at this level is performance. Business owners are likely to delight in the minimization of work needed to manage and execute tactics.
But this also means less control over the process as a whole. Less control of where budgets are being directed, less control over what’s being displayed in your businesses’ name. We saw quite a bit of friction with these issues with Google Adwords Express, which is the predecessor of Smart Campaigns.
Early case studies provided by Google suggest the new platforms will outperform the manual models they’re replacing.
But machine learning and AI-guided marketing will face the same scrutiny as traditional marketing. It must deliver results and demonstrate ROI.
We also have to remember that all of these changes are at the tactical and execution level. A business still needs an offer that has a competitive advantage and a strategy to connect with the right audiences. Social media, content marketing, and creating a business image will all still require the human touch.
In the next few years, we’ll discover if machine learning is able to execute at the broad level these new platforms aspire to, or if businesses discover the loss of control isn’t worth the convenience.
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