Learn how to optimize Smart Shopping campaigns. Using AI and machine learning, you can create local inventory ads, display ads, segment products, and test new features.
Set an average daily budget
If you are considering running a Google Shopping campaign, it is not a bad idea to have a plan in place. In October of last year, Google doubled its budget and gave advertisers the ability to set a monthly spending cap. You can also use the Adwords search engine to optimize your shopping ads and track performance on an individual basis. Smart Shopping campaigns are a great way to get your product in front of more customers without breaking the bank. However, you have to get it right the first time. So how do you go about setting up a smart shopping campaign?
The best advice is to start small, with a modest budget and test out the various ad formats on a daily basis. As you increase your budget, be sure to keep an eye on the numbers and tweak your campaigns as necessary to ensure you are getting the most bang for your buck.
When optimizing a smart shopping campaign, you’ll need to take a closer look at how you’re segmenting your products. This helps to gauge your campaign’s performance and will allow you to optimize the automated bidding process.
Smart Shopping campaigns are a powerful tool for an e-commerce business. They offer the ability to reach new audiences, expand your reach and gain branded search visibility. The key to success is creating a robust product feed and following Google’s best practices.
Segmentation can happen at a brand, category, product type or item ID level. You can also segment based on price or popularity. If your campaign includes a lot of low-margin items, you may consider using custom labels to better manage your budget.
If your smart shopping campaign is set up with a target ROI, you can adjust your spend accordingly. For instance, if you’ve created a smart shopping campaign that includes new products, you may want to reduce your ad impressions in order to reach your ROI goal.
Utilize AI & machine learning
There are many ways to optimize your smart shopping campaigns. However, you have to know where to start. One of the best ways is to make sure you’ve got a quality data feed. This is especially true if you’re trying to rank at the top of Google’s search results.
The best way to get the most bang for your buck is to take a multi-pronged approach. First, you’ll want to do some basic research and optimization. For example, you’ll want to see if you can maximize the ad budget by optimizing the product feed. Secondly, you’ll want to take a close look at your historical performance KPIs. A thorough analysis of the past will help you understand how well you are doing right now. You might also want to think about using negative keywords to filter out irrelevant traffic.
Create local inventory ads & display ads
Google Local Inventory Ads are a great way to bridge the gap between online and offline stores. This allows retailers to provide shoppers with more relevant information upfront and drive physical store visits.
The Local Inventory Ad feature provides businesses with more control over promotions and the ability to direct shoppers to their own website. Its effectiveness is bolstered by its use of the same marketing copy, images and components as other ads.
These ads can appear in Google Display Network, YouTube and Gmail. They can also be combined with other ads, such as video ads, to make shopping more interactive.
Smart Shopping campaigns are a relatively new offering on Google Ads. They combine display remarketing campaigns with automated bidding and machine learning.
In order to create Local Inventory Ads, you must have a product data feed. This feed contains important additional attributes, such as price, stock count, item availability, and more. To keep the feed accurate, it should be maintained and updated regularly.
Test new features exclusive to Smart Shopping
If you are a retailer selling products online and are considering using Google Smart Shopping for your campaigns, it’s important to know some of its features. For example, this new advertising type gives you access to machine learning to optimize your campaign. The goal is to find the best combination of campaign objectives and campaign metrics to drive the most conversions.
This can help you get more conversions from your budget. It also gives you the freedom to test products that may not be successful in traditional Shopping campaigns.
You’ll need to update your product feed to ensure that it is optimized to Google’s specifications. You can check your feed health by using DataFeedWatch. This tool automatically fills in any missing parameters for you.
You’ll also need to test your campaign with enough data to properly evaluate performance. For example, you should run the same campaign for a minimum of 15 days to see what effects it has on conversions.