Improving Ad Rank to show more relevant ad extensions and formats

When people use Google to research and buy things, they're interested in the most relevant and useful results. Ad extensions help by providing more information to potential customers and additional ways for them to respond. For example, they can call your business number, see your business location on a map, or choose an even more relevant landing page that you're promoting with sitelinks. Ad extensions typically improve clickthrough rate and overall campaign performance because they make ads more useful.

Today, Google announced improvements in the AdWords auction that let us more consistently show more relevant ad extensions and formats.

Ad Rank improvements

 Google system for ordering ads on search results pages uses a calculation called Ad Rank. Previously, Ad Rank was calculated using max CPC bid and your Quality Score. With this update, Ad Rank will also take into account a third component: the expected impact from your ad extensions and formats. In addition, Google have increased the importance of Ad Rank in determining whether your ad is eligible to be displayed with extensions and formats.

Here are some more details and implications of these changes:

• Ad extensions and formats can now influence the position of your ad on the search results page. If two competing ads have the same bid and quality, then the ad with the more positive expected impact from extensions will generally appear in a higher position than the other.
• When estimating the expected impact of extensions and ad formats, we consider such factors as the relevance, clickthrough rates, and the prominence of the extensions or formats on the search results page.
• Because Ad Rank is now more important in determining whether your ad is shown with extensions and formats, you might need to increase your Quality Score, bid, or both for extensions and formats to appear. 
• In each auction, we'll generally show your highest performing and most useful combination of extensions and formats among those eligible. So there's no need to try to guess which extensions will help improve your clickthrough rate the most. 
• You may see lower or higher average CPCs in your account. You may see lower CPCs if your extensions and formats are highly relevant, and we expect a large positive performance impact relative to other competitors in the auction. In other cases, you may see higher CPCs because of an improvement in ad position or increased competition from other ads with a high expected impact from formats.
• For now, this update only affects search ads appearing on Google Search.

Recommendations for using extensions

Extensions make your ads more useful and can improve your campaign performance. So you should add extensions that make sense for your business type and campaign goals. With these improvements to AdRank, Google systems will do even more to automatically serve extensions in the contexts when they're most beneficial.

For example, consider someone downtown searching on a mobile phone for "auto repair." In this example, the user might be most likely to respond to your ad when they can click to call a phone number or tap a link to get directions to visit in person. So Google may show a combination of call and location extensions with your mobile search ad.

Now imagine if someone were searching for "auto repair" on a laptop computer in the suburbs. Say your ad earned the 3rd ad position above the organic results in this auction. Google might show your seller rating and sitelinks because that's the highest performing and most useful combination of extensions that could be shown with your ad in this particular auction and ad position.

Introducing Shopping campaigns: a better way to promote your products on Google

Everyday, people search on Google for the best products from retailers large and small. With Product Listing Ads (PLA) on Google Shopping, people can browse a wide selection of products, finding high-quality imagery and relevant product information like brand and price.

To make it easier for you to connect with these consumers and promote your products on Google, Google introducing Shopping campaigns, a new campaign type for PLAs. Shopping campaigns streamline how you manage and bid on your products, report on your performance, and find opportunities to grow your traffic from Google.

Key benefits

1. Retail-centric way to manage your products

Shopping campaigns allow you to browse your product inventory directly in AdWords and create product groups for the items you want to bid on. For example, if you’re a fashion retailer, you’ll see what types of shoes are in your data feed and how many boots you can promote. You use the product attributes derived from your data feed such as Google product category, product type, brand, condition, item id and custom labels to organize your inventory into product groups. Custom labels are a new, structured way to tag your products in your data feed with attributes that matter to you, such as ‘margin’ to separate your high- and low-margin products. To see all the items you can bid on, the Products tab will show you a full list of your approved products and their product attributes.

2. Advanced reporting to measure product performance

Regardless of how you choose to structure your product groups, Shopping campaigns offer the unprecedented ability to view your performance data by product or product attribute. Since performance metrics are associated with the item and not the product group, you can filter and segment data by your product attributes. This includes Google product category, product type, brand, condition, item id and custom labels. For example, you’ll see which Apparel & Accessories categories drive the most clicks, without having to break out your clothing category into a separate product group.

3. Competitive data to size your opportunity

To help you optimize and scale your PLAs, Shopping campaigns provide insights into your competitive landscape. In the Product Groups tab, you can add benchmark columns to see the estimated average CTR and Max CPC for other advertisers with similar products. The competitive performance data you see is aggregated and averaged, so all performance data is anonymous. Coming soon, you’ll have impression share columns to help you understand the opportunity lost due to insufficient bids and budgets, and a bid simulator will help you estimate the amount of impressions you’ll receive as you adjust your bids.

How to get started

Shopping campaigns are currently available to a limited number of advertisers. It will be rolling out gradually in the US, with full global availability by early next year. API support will come in 2014 as well.

New AdWords Estimated Cross-Device Conversions

A couple of months after the paid search world had to transition to AdWords Enhanced Campaigns in the name of simplified and more relevant cross-device ad management, we are finally getting some initial food for thought with regard to cross-device performance. I was calling it the “next frontier for online marketers” in a previous post, and we are now officially getting there!

A New “Estimated Total Conversion” Column Is Rolling Out

In AdWords, a new column called “Est. total conv.” was made available for some beta accounts recently. However, this column doesn’t seem to be available at the keyword level yet — only at the campaign and ad group levels.

The official field description is as follows: “This is our best estimate of the total number of conversions that AdWords drives for your business. What it means: Est. total conv. = Conv. column + Est. cross-device conv. column”

The description doesn’t say whether the “Conv. Column” field is referring to “Conv. (1-per-click)” or “Conv. (many-per-click).” However, I’d tend to think Google is using the “Conv. (many-per-click)” column for reference.

Also, Google plans to factor in other conversion types like phone calls and in-store visits in the future — not right now, though.

Leveraging The New “Estimated Total Conversion” Column

There are lots of different ways to look into this new column — let me just suggest two of them:

1. Since the “Est. cross-device conv.” column is not provided, one can easily calculate it such as Est. cross-device conv. = Est. total conv. – Conv. (many-per-click). This is assuming Google is using the Conv. (many-per-click) column rather than Conv. (1-per-click).
2. Analyzing a new ratio which could be called something like “Cross-device assist %” such as: Cross-device assist % = Est. total conv. / Conv. (many-per-click) – 1. The higher the ratio, the more cross-device conversions occurred as a percentage. A ratio of 0% means there were no additional cross-device conversions, while anything greater than 0% indicates some cross-device assists.

In the below paid search report by ad group and device, those rows with the highest cross-device assist % correspond to assists from mobile devices. That was expected; however, now we have some hard numbers.

Another way to look at it is strictly by device, such as in the below pivot table. I noticed a couple of odd things:

• The numbers in a report differ from the numbers from the AdWords interface by roughly 5-10%.
• The total number of estimated total conversion is lower than the total number of last-click conversions.
• Those additional conversions attributed to mobile devices are somehow subtracted from other devices. As a result, this advertiser’s true mobile CPA is 22% lower than it seems, looking at just the last-click, while the true desktop CPA is 5% higher and the true tablet CPA is 15% higher. You’ll definitely want to take this into consideration when adjusting your desktop/tablet bids, as well as your mobile bid modifiers.

Conclusion

With the new “Estimated total conversion” column, Google is attempting to tackle the increasingly complex issue of cross-device revenue attribution in paid search — and it is definitely a leap forward.
However, in order to make it fully trustworthy and actionable for online marketers, it’d be great to get more transparency from Google regarding the way the numbers are put together (with some kind of confidence interval?), then have the Est. total conv. column available at the keyword level for more granular insights — and ultimately across multiple channels for more sophisticated revenue attribution modeling.