Machine Learning Lessons to Optimize your Google AdWords Campaigns
Machine learning is one of the most relevant developments for companies who deal primarily with data. With more than 25% of companies investing 15% or more of their IT budget in machine learning, the technology has a permanent place in the future of business, especially SaaS and other online services. Its applications range from building entire Artificial Intelligence softwares to obtaining better customer insights and optimizing internal business processes.
This guide will focus on a very practical aspect of machine learning, namely, how it can be integrated into your online marketing strategy to optimize your Google AdWords conversions.
Use Dynamic Search Ads for more precise customer targeting
Google defines Dynamic Search Ads as follows:
When someone searches on Google with terms closely related to the titles and frequently used phrases on your website, AdWords will use these titles and phrases to select a landing page and generate a clear, relevant headline for your ad.
In other words, the texts shown on the advertisements change based on the content of your landing page, and the appropriate landing pages are selected based on the user query. This facilitates the process of aligning your AdWords message with the product offered on your landing pages, and it allows you to create more specific landing pages targeted at different customer segments (based on product functionality, geographical positioning, budget targeting, among other dimensions).
For a detailed implementation guide, make sure to check Google’s comprehensive guide on how to setup your first Dynamic Search Ads.
Implement Smart Bidding for more efficient budget allocation
Smart bidding is an advanced form of automated bidding on AdWords. It uses three main functionalities that implement machine learning algorithms to learn about your audience’s behavior patterns:
- Bids based on single auctions: the bid is set for each individual search. This means that the context of each single user search is fully considered by the algorithm when setting the auction price for your ad.
- Simultaneous analysis of signals: Google’s machine learning algorithm considers how different signals – time of the day, geographical location, previous queries, among others – affect the effectiveness of conversions in different platforms. This empowers the Smart Bidding functionality to optimize even further the auction process.
- Learning based on similar campaigns: Smart Bidding learns from your previous campaigns and applies the best practices to newly created ones. It looks for similar patterns between your existing and new ads and implements optimizations based on the data it has already analyzed.
To get started on Smart Bidding and benefit from optimized auction strategies, check this guide offered by Google AdWords.
The next step: AdWords Scripts and Cloud Machine Learning Engine
AdWords Scripts and Google’s Cloud Machine Learning Engine present the opportunity to automate several AdWords-related tasks and couple them with the machine learning features offered by Google. To implement these functionalities properly, however, you will need some IT background (AdWords Scripts, for example, are set up in JavaScript).
While there is a steeper learning curve for this process, its benefits are considerably higher than just automating isolated parts of your AdWords campaigns. You can set up your own reports based on specific actions or statistics from AdWords, and the information can be fed to machine learning algorithms automatically.
As a good starting point for the process, we recommend checking this in-depth training by Google about how to create AdWords Scripts.
Machine learning presents great potential not only for your online marketing strategy but also for all the other sectors of your SaaS business. The sooner you start implementing artificial intelligence algorithms to automate tasks for your business, the sooner you will obtain a significant competitive advantage in the market!
