DDA Can Drive Conversions and Reduce AdWords Costs- Learn How

DDA Can Drive Conversions and Reduce AdWords Costs- Learn How


There are more moments throughout the day for businesses to connect with consumers than ever before. It’s critical for marketers to know which moments matter, and which ones don’t.

The search process doesn’t start and end with “buy the exact product I already know I want.” People tend to click on multiple ads before converting. This process makes it challenging to assign the proper credit where it’s due. Last-click attribution, the default choice in AdWords, ignores everything except for the final, “buy the exact product I already know I want” ad click.

As marketers, it’s crucial to understand which of your clicks are the most impactful, whether or not they’re the last click before a conversion.

Data-driven attribution (DDA) uses Google’s machine learning technology to determine how much credit to assign to each click in the user journey. With DDA, you can understand how much credit should be assigned to the click on an ad for “features for product I think I want.” Even though it doesn’t convert immediately, you might see that people who click on that ad are much more likely to become customers later on.

DDA was introduced to AdWords back in May 2016, and since then, we’ve been studying how it affects performance. A recent analysis of hundreds of advertisers using DDA revealed that performance improved when compared to last-click attribution:

When compared to last-click attribution, DDA typically delivers more conversions at a similar cost-per-conversion

For Search, data-driven is now the recommended model for all eligible advertisers. It is a better way to measure and optimize performance.

How data-driven attribution works

DDA is different from rules-based attribution models. It uses your account’s conversion data to calculate the actual contribution of each search ad click along the conversion path. By comparing the paths of customers who convert to those who don’t, DDA determines what truly matters for each conversion path.

As long as your account has enough clicks and conversions, you’re eligible for DDA. We automatically train a model that’s unique to each of your conversion types. The model observes what your customers do before converting, and what they do when they don’t convert, to measure what’s important. Using Google’s machine learning, the models continue to improve over time. Read more about DDA.

The benefits of knowing which clicks matter

Here’s how DDA has already created value for other companies:

Select Home Warranty, which provides warranties to homeowners for household repair projects in the United States, saw a 36% increase in leads and a 20% decrease in cost-per-conversion after making the change to DDA.

“Switching to a data-driven attribution model unlocked growth for our business because it allowed us to give proper credit on mobile devices and non-brand keywords, resulting in a significant increase in overall conversions.” – Joseph Shrem, Founder, Select Home Warranty

Medpex is one of the largest mail-order pharmacies in Germany. Using Smart Bidding  and data-driven attribution, they drove 29% more conversions while reducing cost-per-conversion by 28%.

“An algorithm is better equipped than any manual optimization to react to dynamic changes such as price changes of competitors or delivery bottlenecks.” – Frank Müller, Chief Marketing Officer, medpex

H.I.S., a travel agency with global presence in over one hundred cities worldwide, combined DDA with Smart Bidding and Dynamic Search Ads to grow conversions by 62% at a constant cost-per-conversion.

“Data-driven attribution helped us to acquire new users because we could strengthen our approach to users in the consideration phase.” – Ryoko Kume, Customer Communications, WEB Promotion , H.I.S. Head Office WEB Division

Updating your model

Making this change is straightforward. When you change your conversion action settings, use the dropdown in the Attribution Model section to select Data-driven as your attribution model:

Going forward, your “Conversions” column in AdWords will report your conversions based on the new DDA model. Smart Bidding will automatically adjust to this new way of measuring conversions. If you’re bidding manually, use the “current model” columns to make the initial set of adjustments. You can find these under the set of attribution columns.

Making the most of DDA

Updating your “Conversions” column is a big step, but there are a couple of other steps to ensure that your account sees the most potential improvement:

• Adjust bids considering your new DDA-based conversions. Once you’ve updated your attribution model, your “Conversions” columns will begin to populate with stats that reflect your choice. From there it’s easy: Optimize your bids to account for the numbers in those columns. The recommended approach is to adopt an AdWords Smart Bidding strategy, like Target CPA or Target ROAS. Historical performance for that model can be found in the “current model” columns, which you should use as you make initial bid changes.

• Give DDA some time. Those multiple clicks in a user’s conversion path take some time to happen. Give users a chance to convert or make a purchase before evaluating results. Once your account has settled into the new method, allow a couple of weeks to pass where you gather results.

• Re-evaluate keywords that tend to be earlier in the click path. Last-click attribution could have favored some keywords at the expense of others. Now that you’re doing a better job measuring what matters, you may find that some campaigns make a big difference in the user journey. That difference may not have been measured appropriately in the past.

• Stop reviewing assisted conversion metrics. In the coming months, we’ll be removing columns that reference assisted conversions from your statistics tables and reports.

Watch this video for more information about getting started with data-driven attribution. For more detailed guidance, including the steps to follow to properly test a new attribution model, check out our best practices for going beyond last-click attribution.

DDA is recommended for all Search ads, and we’re dedicated to improving DDA elsewhere. You can also take action on DDA if you use DoubleClick Search. In addition, DDA is also available in Google Analytics 360 and Attribution 360. We’ll continue to invest in DDA to make it even better across platforms.

According to analysis, when compared to a last click attribution, DDA delivers more conversions at a similar cost-per-conversion.  Have you started using DDA? How has it impacted your conversions?


Join in the conversation with your comments in LinkedIn or at our Blog below.


Source: Adwords.googleblog.com

Think Outside the Box to Score Google’s Answer Box Position

Think Outside the Box to Score Google’s Answer Box Position


Google’s Hummingbird update introduced the answer box to SERPs and began the scramble to score the coveted 0 page position.

Optimizing for the answer box is pretty simple and straightforward if you think about it.  How to Optimize Your Content for Google Answer Boxes walks you through the logic.

Oh, answer boxes. Position 0 for the majority of its existence has been mystifying as Google seems to reserve this spot for websites that just happen to get lucky. However, as more answer boxes are appearing in SERPs, we as marketers have the opportunity to obtain these highly coveted positions.

In this post, I’ll share how answer boxes first came about, why formatting is crucial for answer boxes and lastly, a real-life example of how Seer has helped a client appear in position 0.

History of Answer Boxes

Answer Box Types & Formats

How to Rank for Answer Boxes

Answer Box Success Story

Quick History of Answer Boxes

In 2015, Google released the Hummingbird update which changed the search algorithm and improved the way Google helps its users. Instead of heavily relying on keywords to determine rank for answer boxes, Google began prioritizing user engagement metrics to help determine which website would earn the position 0 ranking.

With the recent release of RankBrain, Google is now able to bridge the gap between short-tail and long-tail keywords, making answer boxes even more effective at directly answering users’ queries.

For example, prior to the HummingBird algorithm update, the answer box below would have bolded keywords like “seo specialist” with a definition. Now it highlights the answer to the user’s actual question (the salary):


The answer box (pictured) now highlights the answer to the user’s searched question.

What do algorithm changes mean for answer box optimization? For starters, we know that answer boxes are appearing for more queries than ever before. This means that companies have a major opportunity to rank in Position 0 for direct long-tail and short-tail searches to ultimately address users’ questions more thoroughly.  

Common Types of Answer Boxes

Answer Boxes display various content formats within the SERPs, including paragraph, table, and list formats (in numbers and bullets). Additionally, answer boxes can pull in images. Our friends at GetStat.com studied over 92,000 featured snippet queries and found that:

“Paragraph snippets were most common, showing up in 82 percent of featured snippets. List snippets appeared in 10.8 percent, and table snippets in 7.3 percent. All three occasionally showed images, but the formats never overlapped one another.”

Check out the example answer box formats below.

Paragraph-Style Answer Box

Content that typically appears in this format addresses the following questions:





The type of content that typically ranks here is structured in a definitional, simple straightforward answer. Keep in mind that paragraph formats are the most common type of answer box. If Google does not have the desired format (table or list) to pull from existing website content, it will revert to paragraph style answer boxes. When reviewing the SERPs for the types of answer boxes ranking for a certain query, try to assess if users’ questions would be better answered in a table or list format.

Table-Style Answer Box


Content that typically appears in this format addresses questions that can’t be answer directly such as:


Different use cases



Table formats typically appear for more robust questions that need various pieces of organized information to fully address the answer, such as nurse salary ranges.

List-Style Answer Box

Types of questions that typically show up here include:



Best (Tables & Lists)

List style answer boxes appear for questions that require individual steps or a long list. Such as “types of nurses” or “best colleges in PA.” Google heavily favors content that is in a numbered or bullet list format for these types of search queries.

How do you rank in the answer box for a specific query?

Now that you know the common types of answer boxes, you’re ready to start creating your content. The two most important ways to obtain answer boxes results is by addressing the users’ queries first and foremost, and then optimizing the answer in a user preferred format.

Ask yourself the following questions:

Audience: Is my content directly answering users’ queries about the topic?

If not, tweak the content to directly address the user’s question in the best way possible.

SERP Landscape: Is there currently an answer box appearing for related terms?

Yes: Does the current content ranking in the answer box have a helpful format that clearly addresses users’ questions that you’d want to emulate in your content?

No: Would an answer box help users answer a query related to my content? (Refer to the common formats above and reflect on what format would make sense for your content).

Just because Google is not currently showing an answer box for a search, does not mean one won’t appear in the future.  Perhaps no one has created content that is relevant and purposeful enough for Google to rank in position 0.

Using audience research to guide you, test out different formats that you think would best answer users’ questions for your piece of content.

Optimizing: Is my content formatted correctly for the answer boxes?

Is the answer quick and easy to find within the content?

Is the question and answer presented in the relevant user preferred format (tables, lists, or paragraphs) with proper markup?

Identifying users’ preferred format is truly the secret to success when it comes to answer boxes. As Google continues to add more answer boxes in the SERPs, marketers can find areas where the answer box is displaying the “wrong” type of snippet, aka a format that doesn’t provide users with a format that answers their questions.

For example: “[online nursing schools]” isn’t using a clear table format, instead it’s showing a bulleted list. A table with facts next to each school would better address this search query.

After choosing the correct format, it’s important to pose the related question in an h2 or table header, while including the answer in a table format. The page should also be marked up to include the correct code such as <table>.

Answer Box Success Story

In February 2016, Seer and one of our education clients optimized a Nursing Salary Guide for answer box results. The guide provides information to potential nursing students when they first begin seeking degree information online, such as what is the average starting salary of nurses?

After analyzing the SERPs and reviewing audience data, we came to the conclusion that paragraph formats would be the most relevant type of answer box format to optimize for, as users are looking for a quick answer when searching for this information.

After tweaking the copy, we altered our H2s into questions and answered the question directly in the copy beneath the headers.

Since mid-June this page has ranked in the answer box result for “what is the starting salary of a nurse” and other related keywords.

Behind the organization’s homepage, this guide is the second highest traffic source. Crazy to think that before we had optimized this page, the guide had barely made it into the top 20 ranking positions!

In addition, the answer box result has begun to pull in images from the page, showing that Google includes different visual formats and information over time depending on what will best answer users’ questions.

Join in the conversation with your comments in LinkedIn or at our Blog below.


Source: Seerinteractive.com


You’re So Vain – I Bet You Think This URL is About You: Using Vanity URLs to Track Off-line Marketing

You’re So Vain – I Bet You Think This URL is About You: Using Vanity URLs to Track Off-line Marketing

For as long as marketers have been advertising they’ve been collecting data on ad performance.  Unique phone numbers and promotion codes were the standard tools for calculating print and radio advertising ROI.  These days, the judicious use of Google Analytics and vanity URLs give you the ability to measure offline marketing campaigns with the ease of their online counterparts.

Brandon Wensing explains how to deploy this tactic in How to Measure Offline Advertising with Google Analytics.

Since I’ve been in the digital space, I have worked under the title “web analyst,” using “web analytics” tools like Google Analytics, Adobe Analytics, and WebTrends. However, the preface “web” is misleading. The term “digital analytics”, though broader, still doesn’t do justice to the capabilities of these platforms.

We can measure so much more than just web or digital efforts. We can even go as far as measuring and analyzing the effectiveness of offline or non-digital efforts as well. Because of this, a more suitable classification for this field is simply “analytics”.

Organizations of all sizes, from small companies to enterprises, often overlook this capability. Their offline marketing efforts go unmonitored and they continue to throw marketing dollars at a wall, hoping something sticks.

By measuring offline marketing tactics with tools like Google Analytics (GA), you can directly tie those efforts to downstream behaviors, leads, and even sales. This then grants the ability to refine those efforts, much like you do with digital efforts such as Paid Search. Below are the steps you can take to measure your organization’s offline marketing with Google Analytics.

How Offline Campaign Tracking Works

Campaign tracking with Google Analytics is pretty simple. In order to differentiate campaign traffic from standard referral or direct traffic, GA relies on URL parameter values. For more information about how campaign tagging works, check out Google’s official documentation. This is pretty straight forward for digital / online advertising, however offline advertising is a bit more involved.

The key to tracking offline campaigns is the vanity URL. A vanity URL is a short, easy to remember alternative to standard, and typically longer page URLs. The vanity URL is preferable when it comes to offline advertising like billboards, as drivers typically only spend a few seconds at most viewing it. A longer URL would be difficult to remember. For example, if my landing page is www.mysite.com/products/widgets/widget-5000, a much less-wieldly vanity URL could be www.mysite.com/go. The vanity URL is typically set to redirect to the full URL.

To track this with Google Analytics, you can set the vanity URL to redirect to a campaign-tagged variation of the full landing page URL. For example, let’s pretend that the above Vanity URL is used on a billboard:

Instead of telling the server to just redirect www.mysite.com/go to the full landing page URL, you can have it redirect to a tagged version, like:

So after a person sees the billboard, they go home and remember to check out your company’s site. Not only that, they recall that easy-to-remember vanity URL and go to www.mysite.com/go. When they do that, the server redirects them to the tagged URL. Once it loads, Google Analytics recognizes that they came to the site with the following identifiers:

Source: billboard

Medium: offline

Campaign: widget-5000-fall-campaign

Keyword(utm_term – re-purposed to detail messaging of ad): tired-widgets

Content(utm_content – re-purposed to detail location of ad): route-422

The most important part of tracking these ads is thinking ahead and mapping out your needs. Below are some steps to take to do offline campaign tracking right.

Plan Ahead

Like all analytics efforts, great insights only come from great measurement strategies. Look at your marketing calendar for the next 6-12 months. You’ll not only want to identify what offline marketing campaigns you’ll be running and when, but also how many variations and placements as well. Highlight any areas where an ad variation will appear across multiple channels or mediums (for instance the same messaging across radio and print ads). It’s important to know the landscape and where overlap might exist, as it might be valuable to be able to view data at those levels.

Identify and Prioritize Questions

Now that you know what non-digital advertising you will be running over the next year and in what flavors, it’s time to identify the questions you’d like to answer about them. Aside from wanting to know ROI for these efforts, you should ask yourself some additional questions:

Do you need to differentiate between customer segments that arrive from these ads?

What level of granularity do you need to slice and dice this data by? At the individual billboard level, or simply at a regional level?

How will you need to analyze performance of these channels and campaigns over time (quarterly, yearly, etc.)?

Knowing how granular your data needs to be will dictate how you go about tracking these campaigns. It will also help you future-proof your campaign measurement strategy so historical analysis is as easy as possible. Need help building a measurement strategy? Send us a line!

Identify Landing Pages and Set Up Campaign Tagging

Now that you know what questions will need to be answered about these efforts as well as how success will be gauged, it’s time to create / identify all of your landing page variants. Depending on your answers to questions like those listed above, you’ll need to create tagged versions of these landing page URLs that follow the needed hierarchy.

For example, let’s say you have two billboards with the same messaging that you’d like to point to the same landing page. One is set up on one highway (Route 422), the other is set up on another (Route 76). Your stakeholders have noted they’d like to know how many online sales come from customers that saw each of these. To differentiate these you will need 2 unique vanity URLs (one for each billboard). Both vanity URLs will redirect to the same landing page of <b>www.mysite.com/products/widgets/widget-5000</b>, however the campaign tagging will be slightly different for each:

Billboard 1 – Route 422

Vanity URL: www.mysite.com/go

Redirects to tagged URL:

As you can see, we identify that it came from the Route 422 billboard via the utm_content parameter.

Billboard 2 – Route 76

Vanity URLwww.mysite.com/now

Redirects to tagged URL:

Note the different vanity URL for this billboard. Once again, you can see that we used the utm_content field to specify that this traffic came from the Route 76 billboard.

NOTE: This is assuming that the above 2 vanity URLs are only used in those instances. They should never be used anywhere else (online or offline) unless you wish to also track multiple ads with the same identifiers.

This was just one example. You could also use the other URL parameters to differentiate between billboards and print, different campaigns or messaging on the same channels, etc. The combinations are endless. It just depends on how you need to see the data. This is why planning ahead with your campaign tagging strategies is so crucial.

Once all URLs are tagged and vanity URLs are set up to redirect accordingly, ALWAYS test before sending the vanity URLs out to be printed or used! You should ensure that they redirect properly, preserve the campaign tagging parameters, and that everything works as intended. Unlike digital ads, offline ads are much more permanent and changes cannot be made easily.

Leveraging the Data

Once everything’s implemented and the ads are live, you should start to see data for traffic coming from them. So what can you do with this data? Just about everything you can do with data from digital ads!

Just like anything else, this method isn’t perfect. It obviously cannot help identify people that may have seen the billboard or heard the radio ad but proceeded to the main domain or used Google to find it when they got home.

This can give you great insights into specific target audiences depending on messaging or even geographic location, and not just based on the location that GA picks up based on their IP address. If you followed a similar method as the above example, you can use this data to gauge effectiveness based on WHERE the person actually saw the ad.

This data can also provide insights into customer decision process and journeys. It can answer questions on when brand exposure first occurs, and how messaging effectiveness could vary depending on channel, timing or location. It can also shine more light on how channels work together to get customers to purchase.

As you can see, setting up the mechanisms for offline tracking is the easy part. It’s the measurement strategy that requires the most attention. But once you have it all thought out, the process becomes regimented and the insights gained become invaluable. Gone are the days of throwing advertising at a wall and hoping something sticks.

Take the guesswork out of calculating ROI. Vanity URLs are an effective means of gathering in-depth data on off-line marketing efforts.  Have you used vanity URLs?  What were the results?


Join in the conversation with your comments in LinkedIn or at our Blog below.