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seo in dubai Carrie Albright – Search Engine Land News On Search Engines, Search Engine Optimization (SEO) & Search Engine Marketing (SEM) Fri, 07 Jul 2017 17:07:17 +0000 en-US hourly 1 Your 6 new ways to use location targeting /6-new-ways-use-location-targeting-278353 Fri, 07 Jul 2017 17:07:17 +0000 http:/?p=278353 Looking to take your location targeting to the next level? Columnist Carrie Albright offers some new geotargeting ideas for your PPC campaigns.

The post Your 6 new ways to use location targeting appeared first on Search Engine Land.


As advertising platforms diversify the targeting options they provide, we are challenged to become more and more creative with exactly how we find and appeal to our customer bases.

Years ago, simply targeting the geographic region of interest was an easy win for improved relevance and reach. But times have changed, and so have the stakes.

Although location/geographic targeting is particularly advantageous to those with storefronts, there are improved tactics that impact those of us advertising goods and services that aren’t in a traditional retail space. Provided below are six new approaches to geographic targeting to boost your digital marketing strategies.

For those with brick-and-mortar operations, it’s presumed that you target a healthy radius around your stores. This should be square one.

For any moderate or advanced advertiser, it’s also expected that you target your high-performing geographic areas with location-specific campaigns or layered geo bids. But there is more that can be done to emphasize your presence to the existing or prospective customer base.

1. National vs. hyper-targeted campaigns

One example of hyper-targeted campaigns is a car rental company. It is assumed that if you offer services in Denver, Colorado, you will be targeting this region. It is also very likely that you have entire campaigns dedicated to rental car interest strictly in the Denver area.

But your next step should include all those outside of Denver with an interest in car rentals. This is the “embedded negative” equivalent of geotargeting in which all of the US is targeted, but Denver itself is excluded.

The theory:

The expectation here is that your service may be something a traveler is planning to need, even though they’re not in the area at the time. This segmentation allows you to offer customized pricing and location in your ad copy, and even send them to highly relevant landing pages.

The build:

  • Example Campaign 1: Denver — Car Rental Interest
  • Example Campaign 2: National — Denver Car Rental Interest

The major note to be made is that your new National campaign must contain a qualifier for Denver, so that you’re not wasting your budget on interest in an area you can’t accommodate.

  • Example Denver campaign — Car Rental Interest Keyword: +car +rental
  • Example National campaign — Denver Car Rental Interest Keyword: +car +rental +Denver +area

The evidence:

This approach was applied to an account that targeted certain city hubs across the US. From the data collected, we saw that volume was lower for the National campaigns, largely due to conservative budget usage, but that engagement was actually quite a bit higher.

This effectively improved our reach to those outside our target markets, while still generating a relatively similar ROAS, despite the slightly lower conversion rate.

2. Average household income

Google offers household income (HHI) targeting, which allows you to layer bids on or solely target areas based on their presumed average HHI. There are pros and cons to relying too heavily on what’s implied here, such as “My customer base skews to high economic status, so I should strictly focus on upper 20 percent.”

Instead of making assumptions and applying these levels at your own discretion, allow the data to tell you what to do. The benefit of this targeting type is that lead gen, e-comm, B2Bs and many more business models can benefit equally from this approach.

The theory:

Income targeting is yet another segment that can be used to push for improved reach or to reduce inefficiencies. Like any segment, be sure to revisit these optimizations regularly and reintroduce removed audiences every year or so to ensure traffic hasn’t changed so drastically that you’re now missing your customer opportunities.

The build:

Using the AdWords location targeting of “location groups,” apply all average income levels to your campaigns at a 0% bid adjustment:

Once you’ve created these targets, allow the data to populate in your campaigns:

As you gain confidence in the volume of traffic coming through these target levels, you may choose to optimize towards or away from a specific income level. You may even choose to exclude one group entirely or create a separate campaign for that level.

The evidence:

In the test below, we used income-level targeting, state-level locations and also ZIP codes for one specific state of interest. The results contain over 15,000 impressions (with an equal split between income and state audiences) across all types, with a strong CTR for income- and state-level targeting.

The more interesting aspect of this is the heightened conversion rate for those in the income-level target. From here, our next step is identifying whether to lean most heavily on the top-performing income brackets in the existing campaign or to break them out entirely to ensure it never wants for budget.

3. Target competitors

For those with a prominent competitor marketplace, it’s a strong prospecting strategy to keep in front of those customers who are considering your competitors. This requires that you know who your biggest competitors are and where they are located.

The theory:

These campaigns are appealing to new users who are demonstrating an interest in your product or service, and who are in the vicinity of a competitor who may cause you to miss that sale.

According to a study by DMI, 80 percent of shoppers used a mobile phone inside of a physical store to either look up product reviews, compare prices or find alternative store locations. As you build your own strategy for competitor locations, you are seeking to fulfill the latter two searches.

The build:

By placing a radius targeting on your competitor’s addresses, you stand a much better chance of appearing to them when they’re particularly low in your search funnel.

Focus this campaign’s keywords around your most successful non-branded terms and utilize promotion or price-competitive copy as you’re able. For those with online coupons, this audience is precisely the one to appeal to.

4. High-competition cities and regions

If the previous approach feels too aggressive, consider this alternative: Focus a portion of your targeting on cities or regions where competitors reside and include top non-branded terms as well as your branded terms.

The theory:

This approach may appeal to:

  1. those customers who have brand awareness of your competitors (and not you);
  2. customers who know you, but are inundated with competitor awareness; and/or
  3. customers who are searching for products/services you offer, but due to the competitor’s close range, may just as easily turn to them instead of you.

The build:

You may have your own market research on where competition is the highest. In that case, skew toward what those numbers are telling you, as they likely incorporate more channels than just paid search. However, if you’re not conducting these kinds of analyses, and you have campaigns broken into geographic targets, such as the New York search campaign below, there’s hope.

By pulling auction insights reports, you’re able to see which competitors are potentially stealing your customers in a particular region. This will allow you to prioritize where to push for more branded and non-branded coverage.

5. Target complementary behavior

There can be more to your geographic targeting than just finding your customers and selling them your goods and services. Part of a growing business’s strategy should revolve around incorporating your product/service into a bigger view. This means using behavior (or more so, location) to find complementary offers.

The theory:

Your potential customer does not operate in a vacuum. When they go grab coffee in the morning, it’s entirely possible they also want to grab a morning snack. When someone is shopping for birthday balloons and a helium tank, it is quite likely they may also need party plates, napkins and even a piñata. Thinking through how your product or service can be complemented by another can offer a new approach on location targeting.

The build:

If your service is a plumbing and electric company, it is entirely possible that visitors of home improvement stores may be in need of your assistance. In a campaign targeting “shower base installation,” you have the opportunity to not only target regions near your businesses, but also stores where these materials are being purchased.

By applying a radius target to these stores and focusing on specific services that your business provides, you are able to appeal to a highly relevant and potentially low-funnel customer.

6. Retargeting to the max

The final and arguably easiest strategy for utilizing geotargets is to apply audience lists to the preceding tactics. By adding retargeting lists to any of these, particularly competitor locations and complementary behavior targets, you stand to not only re-engage past visitors, but also reduce CPAs and improve conversion rates.

The theory:

In the example of competitor radius targeting: When better to remind your users that you’re alive and well and ready to provide the service you know they’re interested in than when they’re considering another?

The previous five strategies can all support your branding and prospecting initiatives, but for past visitors to your site, the investment is that much more assured: They’ve seen your site and potentially considered your product or service.

As their behavior indicates continued, renewed or complementary interest in your offerings, this additional layer can be the last piece of the puzzle to drive conversion.

The build:

By layering on remarketing audiences to these strategies, you can begin to see the data populate in your various past visitor groups. Once you see where top performance lies, it may behoove you to add bid modifiers to amplify or deter traffic from these lists.

And lastly, the targets and performance may dictate that an entirely new campaign is warranted to best provide messaging, bidding and budgeting to these users.

Final thoughts

Geo-targeting is an integral part of any marketing strategy, but taking your location targeted to a more in-depth degree can allow you to approach new (and returning) customers in a whole new way.

The post Your 6 new ways to use location targeting appeared first on Search Engine Land.

Making the case for mobile site optimizations: Who doesn’t want an extra $13K? /making-case-mobile-site-optimizations-doesnt-want-extra-13k-272976 Fri, 14 Apr 2017 14:43:58 +0000 http:/?p=272976 These days, the question isn't whether we should invest in mobile but to what extent. Columnist Carrie Albright explains how marketers can make the case for greater investment in mobile optimization.

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For years, the digital marketing world has asked itself, “Is now the year of mobile?” But at this point, we’ve clearly surpassed the Year of Mobile and are now in the “Age of Mobile Crisis.” Instead of considering if we should include a potential mobile audience, we are weighing the impact our lackluster approach to mobile is having on our sales and long-term revenue.

Google has consistently launched updates to their role in the mobile user’s world, from simply entering the market to moving toward higher expectations for how we treat mobile users and now, to truly committing both front-end (expanded text ads, bid modifiers, responsive ads and eventually Voice Search) and back-end (site responsiveness, speed and layout) optimizations to the smartphone user. Side note: Bing also has its own site speed tester, but across the boards, more content is written about Bing mobile targeting than by Bing.

We know all this, but the question is becoming, “Is it really worth it?” Besides being punished in Google mobile search results, how can we explain to clients or internal teams the impact our lousy mobile experience is having?

How to make the argument

Again, mobile is here, now. In fact, it was here yesterday, and even a half-decade ago. Our clients and internal departments don’t need to be convinced of this fact — they need to be assured that your plan for attracting these users is sound. Mobile marketing isn’t an “annual strategy” topic. It’s not even a QBR slide. Mobile is something that is daily.

Whether you’re avoiding, targeting or truly speaking to mobile users, you should be practicing regular optimizations, revisions and conversations regarding the 77 percent of Americans who own smartphones.

How to win the argument

The best way to win any argument is to frame it in terms your challenger values. This most often translates to dollars, but at times can be sheer customer volume as well.

Now we’re left asking, “How can I determine the number of sales/leads my company is missing out on due to users abandoning the site?”

In September 2015, SOASTA published a case study that spoke to the immediate improvement to conversion rates when page load time improved. The author reviewed performance by approximately 4.5 million mobile users over 30 days, and what she found were clear performance benchmarks in site speed, visitor retention and conversion rate.

According to a Think with Google Research Study, 53 percent of users will abandon your site if it takes more than three seconds to load. But how can you quantify that for your revenue?

To explain the direct benefit of mobile page loading optimizations, let us consider a few examples:

Client 1: Retailer with an AOV of $65

With this client, conversion rate maintains a pretty clear correlation with the average page load time:

Regarding mobile traffic, a larger portion of search traffic comes through a slower page (loading at an average of 3.63s), which has an average conversion rate of 0.56 percent. Using SOASTA’s proposed impact of load time on conversion rate, we stand to gain by improving our page load time by even 0.9 seconds.

By reducing page load time to 2.73s, the newly calculated conversion rate comes to 0.71 percent. Based on the average order value from each purchase, and knowing that we’ve just improved the likelihood that a customer will stay on the site to make a purchase, the projected lift to revenue is nearly $1,100 per month. This means by boosting their site load time by a mere 9/10 of a second, this client stands to make an additional $13,000 each year.

Client 2: A travel agency/tour operator

This client has a site teeming with images advertising all the exotic getaways one might purchase. We see fluctuating page load times and conversion rates dependent on the landing page:

A large portion of mobile traffic enters through a page with an average load time of 3.19 seconds and has an average conversion rate of 0.74 percent. If we’re able to improve the time by just the 0.9 seconds, as shown by SOASTA, average load time falls to 2.29s, and the newly calculated conversion rate comes to 0.93 percent. Based on the average numbers of visitors to this page, it’s projected that this will generate 115 additional package signups each year, simply by retaining those visitors who are already on your site and interested.

To drive this home, let’s go through one more example, shall we?

Client 3: Lead generation client in a hospitality-focused business

Plenty of site visitors are considering our competition in their decision-making process, and providing a positive experience on our site is paramount.

Mobile visitors currently comprise 49 percent of our overall site visitors, with an average conversion rate 44 percent better than desktop.

With such a strong conversion rate, should we still be concerned with mobile optimizations?

Yes, of course. Strong performance by comparison doesn’t necessarily indicate actually strong performance. Despite these great relative conversion rates, average page load time for mobile is an appalling 11.9 seconds. This is due to the beautiful images and dynamic content on the site, something we’re not too keen on sacrificing, but clearly we have room to improve.

Let’s assume we’re still looking to make minor improvements on the mobile page load time. In SOASTA’s example, we can see that a strong impact is made when moving from five- to two-second load times.

But because this client is beginning with such a long initial load time, we’ll make the conservative calculation that page optimizations will at least boost our conversion rate the 20 percent that was seen from SOASTA’s 8.1- to 5.7-second range. By providing a site that’s not just mobile-friendly, but that also possesses mobile site speed, we’re able to bring in over 275 additional leads each year.

How to improve

After some compelling projections on how improved mobile speed can impact your account, the next logical question is: What do I do to get these results?

You have two options at your fingertips:

  1. General mobile assessment from Google and Bing
  2. Detailed developer-level insights to optimizations

Mobile assessment from Google and Bing

Your friends at the major US search engines are happy to provide you with a vast scope of information and tips. Between the resources at Think With Google and Bing Webmaster Tools, it takes little more than a few clicks on the keyboard to identify your next steps.

Mobile speed can typically be measured quantitatively with Speed Index (30s or less), Total Requests (80 or less) and Page Weight (1MB).

These titles translate to mean:

  1. Speed Index: How long until all the visible parts of your page are displayed.
  2. Total Requests: How many components on your site are fighting for the same resources at once.
  3. Page Weight: Is your page filled with too-large images or just too much?

Using a tool like the Google’s “Test My Site” page not only provides a snapshot of how mobile users are experiencing your website, you can also receive an email with detailed points on where to make improvements.

Developer-level insights

For you data junkies, I highly recommend using the insights found at, which allows you to test the mobile user experience based on multiple devices (Nexus, Motorolla, iPhones), device speed, browser choice and more.

Not only does this give you very clear snapshots of the mobile user’s experience, the follow-up is a breakdown of the shortcomings on your site. It’s a harsh but fair look at where you can afford to reduce image size, adjust loading rules and simply remove the sludge that’s slowing your load time.

The process is simple: just type in the URL that you’re testing, and adjust your location (if desired), as well as your browser. The Mobile 3G connection setting will give you a look at an average smartphone experience (though we’re seeing the adoption of 4G networks sweeping the planet). Including the first view and repeat visitors will show you if any components of your site perform better if the user’s loaded it previously.

The long story cut short is that we’re no longer discussing what mobile might contribute to the world of digital marketing. We’re considering how much we’re losing as we fail to make incremental gains on our mobile agility. We watch in horror as our competitors outshine us in mobile experience. And we sit back and observe the lost sales and leads resulting from a site that is just too dang slow.

The good news is that these resources provide clear-cut recommendations on how to remedy your mobile crisis. So get to it!

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Are Dynamic Ad Varieties A Waste Of Your Time? /dynamic-ad-varieties-waste-time-237084 Fri, 19 Feb 2016 15:23:28 +0000 http:/?p=237084 Columnist Carrie Albright explores the various types of dynamic ads available to search marketers to help you decide which (if any) may be right for you.

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Dynamic ads have been in existence for years, but both Google and Bing have recognized the need to expand this feature.

Now, in 2016, we can use dynamic keyword insertion (DKI) in our ad headlines and description lines of an ad, and the text ad creation can be automated based on the product relevance through Dynamic Search ads. And the recent use of ad customizers is a marketer’s dream, particularly as we move through seasonal promotions.

The question we’re all quietly asking, however, is this:

Should you believe the hype?

Do these dynamic ad assortments actually work? Below, you’ll find a breakdown of each dynamic ad type, including a 1–5 score on effectiveness of ad type and ease of setup (based on my own experience).

Although some of these may be quite simple to implement, they may not generate the desired successes. In contrast, some dynamic ads may require a monk’s patience but pay off with phenomenal returns in the end.

The sweet spot is the point where achievable and effective meet.

Dynamic Keyword Insertion

  • Effectiveness score: 3 out of 5
  • Ease of setup: 5 out of 5

Dynamic keyword insertion, or DKI, is an oldie but goodie. There are so many delicious articles about the woes of DKI or the fumbles we see in the wild, yet we still use these ad copy shortcuts regularly.

The benefit of the DKI is the immediate search-term relevance that users experience. The fact that one’s search query can appear in an ad before your eyes used to be a mind-blower. Sadly, these days, there seems to be an overuse of DKI ads created without the same level of thought and attention that non-dynamic ads receive.

After reviewing some of my agency’s e-commerce accounts, we can see that some accounts use traditional dynamic keyword insertion as much as 80 percent of the time, while others allow for fewer than five percent of text ads to use DKI.

Dynamic keyword insertion is a straightforward setup, with the rules clearly stating: If a search query matches a keyword in your inventory and falls within the character limit for that line, the keyword will be used. If these requirements are not met, a default message is shown.

As I mentioned, there are a lot of ways this can go wrong, so do your due diligence when it comes to targets, capitalization and implementation of DKIs.

But the real question is: How do these ads compare?

Below is an example client’s data, where DKI ads are used for at least five percent of the non-branded ad copy. The DKI ads are compared to a general baseline ad running during the same time.

Client 1 DKI

The statistically significant data above is actually extremely surprising, considering the widely accepted view of DKI ads. The large discrepancy in conversion rates suggests that these DKIs just aren’t offering a better experience. Perhaps showing the matching keyword in one’s ad copy isn’t the fastest way to engage an audience.

Another client has a similar outcome as well: CTR actually does not improve compared to the baseline, and conversion rate sees a big improvement with the traffic that is clicking on these dynamic ads.

Client 2 DKI

Although we see that visits generated from this account’s DKI ads convert more efficiently, we still have uncertainty. How frequently are ads actually taking advantage of the DKI setting? How often are the default settings showing instead?

While there is certainly more to research before unabashedly adopting DKI, we can see from the examples above that it’s not just a plug-and-play feature.

Dynamic Search Ads

  • Effectiveness score: 1 out of 5
  • Ease of setup: 5 out of 5

There has been a lot of coverage about the implementation of Dynamic Search Ads (DSAs), as well as their effectiveness. Because these ads are generated based on your own site’s content and inventory, they can be a real dream for an e-commerce site with a large inventory.

The setup gets a high score, in that they are extremely straightforward: Provide your website domain, select the content you’d like to target (if any) and generate the ad’s description lines. Set it and forget it! (Okay, it may be a tad more complicated than that, but not by much.)

When taking a look at our agency’s clients, I found that compared to the baseline ads, which showed product-relevant messaging but no dynamic content, Dynamic Search Ads had less than amazing results.

Client C has an alarming disconnect between the Dynamic Search Ad performance and that of our standard text ads. And whether or not the landing page choice or relevance was better when operating through DSAs, the results show us there’s a real lack in effectiveness.

Client C DSAs

With another entirely unrelated client, we see similar, though not as extreme, results. We’ve lost some type of relevance or resonance in enabling DSAs in this account.

Client D DSAs

Although these accounts have previously seen successes with Dynamic Search Ads, the past 30 days have not been kind to either of these campaigns.

While a reevaluation of targeting and exclusions is certainly warranted with these two, the message is clear: DSAs aren’t always a sure thing.

Dynamic Remarketing

  • Effectiveness score: 5 out of 5
  • Ease of setup: 1 out of 5

Currently, one of the most challenging remarketing features to set up, dynamic remarketing, can connect shoppers with the most relevant products to their shopper history. These ads contain one or multiple products that have been viewed by shoppers or even that complement the shopper’s previous purchase.

There are a large number of remarketing strategies that one may employ to take advantage of these new ad types. In examining a couple of accounts managed by our agency, we saw successful interaction because of these ads.

The first client ran traditional remarketing image ads alongside our dynamic ad content.

Client A Dy.Rmkt example

Although each has been successful, the Dynamic Remarketing ads generated a CTR that was 157 percent better than general remarketing ads. Shoppers clicked on our client’s ads nearly twice as frequently when images were either previously viewed or complementary products. That’s a huge volume of qualified visitors entering the site to resume a shopping process.

Although the conversion rate for the dynamic ads was not as strong as with the traditional remarketing ads, the loss pales in comparison to the overall volume of on-site visitors. That is to say that the dynamic ads generated 2/3 of the volume of sales at a CPA 43 percent lower than the CPA of traditional remarketing ads.

Client B experienced improved performance with dynamic ads, as well. This online retailer experienced a 44-percent lift in CTR compared to CTR on its traditional remarketing ads.

Client B Dy.Rmkt example

The big success, however, is the leap in conversion rate. Dynamic remarketing ads saw a nearly 70-percent boost in conversion rate. Combined with the increased CTR, the overall outcome of utilizing this new ad type was a 76-percent decrease in cost per sale, or in other terms, a 340X greater ROAS. Yowza!

So why aren’t some people using it? The biggest hindrance, coupled by the greatest value, is the setup. To use dynamic remarketing, the remarketing tag must be adapted to include visitor-specific detail. Google support provides several resources for creating your customized remarketing tag, but it can still be a cumbersome process. They also offer alternative steps, such as GTM, for a slightly simpler implementation.

Ad Customizers

  • Effectiveness score: 3 out of 5
  • Ease of setup: 2 out of 5

Ad customizers are some of the newer products offered by Google. Much speculation has been made about how to use ad customizers and what feature to utilize.

The ease of setup is a 2 because of the planning and layout process. Syncing features such as an account’s inventory and location listings requires creating a reference feed and assigning it to your new ad copy. Although the setup process isn’t terribly complicated, the effective use of these types of ads can be tricky.

What are your top features or products to tackle?

To answer this question, I took a look at the ad customizers we have running in a few of our agency’s accounts.

The example of Client Red utilized the inventory-synced countdowns. This was for a seasonal product that was prone to run out as the season concluded. The ads were intended to keep shoppers in a “don’t miss out” mentality. Hesitate, and they might lose their chance to own this product. Although the strategy behind these countdown ads was sound, the results were less impressive.

Ad Customizers Client Red

When testing these ads against non-countdown ads, we saw a loss in engagement when the ad copy focused its content on the remaining inventory instead of increased product description. Worse yet, the conversion rate for this traffic was inferior to the non-countdown ads, as well.

Although the intention of these customized ads is to generate a click, the lack of conversions to follow further suggest that this application of the ad still needs improvement.

Client Orange was another account that utilized ad customizers, but for geographic relevance. This client offers brick-and-mortar locations across the US, and the ad customizer feature is integrated with the Google My Business location listings.

Because we anticipate that those associated with local stores will visit the actual location, not always convert online, the CTR here is the bigger goal.

Ad Customizers Client Orange

From the data above, we can see that telling a shopper of a location in their city improves CTR exponentially. Shoppers are drawn to ads that are relevant to their own lives, including where they go to shop.

The conversion rate suffered from this approach, but because of the nature of local listings, this outcome was anticipated. The next step is to continue striving for in-store attribution from online searches.


Here’s the round-up based on my experience:


Dynamic ads can bridge a gap between your target audience and the goods or services your business offers. Although the final outcome of these varying ad types may differ, the goal is still the same: relevant messaging for your shoppers.

Google continues to build and expand upon their dynamic features, and as they continue to do so, it will be our responsibility to find their best applications for our individual goals.

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How I Saved $1M Using Negative Keyword Lists /saved-1m-using-negative-keyword-lists-231701 Fri, 02 Oct 2015 15:58:58 +0000 http:/?p=231701 Is it worth it to use negative keyword lists? Columnist Carrie Albright shares her thoughts, plus an example that saved one client big-time.

The post How I Saved $1M Using Negative Keyword Lists appeared first on Search Engine Land.


When seeking opportunities for improved cost-efficiency, one of the most highly recommended checkpoints is the search term report in your paid search interface.

Discovering a keyword spending well beyond its CPL threshold results in a mix of joy (“Great! Another keyword to exclude!”) and pain (“How did this search term spend that much?”).

As your excluded terms accumulate, they inevitably grow into a massive list to be reviewed constantly for any chance of a mistake. Did you once exclude a term that, upon second glance, might need to be considered for an exact match negative but maybe not a broad match negative? With a list of more than 1,000 excluded terms, this type of quality check can be a huge time commitment and long-term undertaking.

Luckily, the PPC gods have released the Negative Keyword List for our excluding convenience. Now you can easily create smaller, more manageable groupings of negatives and apply them equally to whatever campaign is deserving.

But does the use of negative keyword lists really improve anything?

To answer that question, I’ve broken it down into three sub-questions for consideration:

1. Do Negative Keyword Lists Reduce Workload?


After years of mining through search queries and haphazardly adding keywords that looked suspect or were clear offenders, the list became somewhat unmanageable. Worse yet, I started to forget what I’d added or why I added it.

Then negative keyword lists came along, and my neurotic little brain was happy again. I began poring over my negatives and sorting them into categories that made sense for my clients. Although there are some General Term lists that will apply to most of us, there are many, many more that are specific to each and every business.

Although the internet waters run deep with lists of “the 100 terms your PPC account should exclude” or “the beginner’s list to excluding keywords,” I find it much more beneficial to illustrate with examples than to tell you what works and what doesn’t.

Some sample categories of Negative Keyword Lists:

Employment (a common set of exclusions for the majority of accounts)

  • career
  • hiring
  • application
  • jobs

Terms Related to Your Own Industry

Example: Business Loans

  • “interest free”
  • “payday”
  • “pay day”
  • “start up”

Product names (cross-contamination)

Example: Shoe Retailer

  • nike
  • adidas
  • converse
  • reebok

Current Events

Example: Hospitality

  • weather
  • earthquake
  • election

*Hot Tip: Creating a Google Alert for your client’s brand or industry will keep you looped into current events that may affect what prompts your ads to appear.

Branded Terms (For Non-Branded campaigns only)

Example: The Cheesecake Factory

  • cheesecake
  • cheese cake
  • “cheesecake factory”
  • “cheesecakefactory”

Upper Funnel Terms

Example: Travel industry

  • “when to visit…”
  • “arches national park”
  • [moab]
  • “things to do in…”

Converted Users

Example: Online retailer

  • “confirmation number”
  • login
  • receipt
  • return policy (Although you may want to verify that this is not being used as a successful comparison search query prior to excluding it)

These lists are not intended to fit you perfectly, but instead to compel you to look outside the “one list to rule them all” mentality and to specialize your categories. But there’s another logical question:

2. Do Negative Keyword Lists Improve Performance Transparency?


While the Shared Library interface makes creating and implementing Negative Keyword lists simple and straightforward, there is one major hangup:

Negatives aren’t shown in the Google’s search term report.

The example below is a search query that has generated some interest:

Negative exclusion example

What you can’t see in the interface is that the term “canine” has since been excluded and added to a negative keyword list. However, when we reflect on the search term report, it appears as though the term is still happily generating traffic. This kind of thing can create some confusion if you’re not prepared.

The secondary downfall to negative keyword lists is the inability to view them in the AdWords Editor. How many times have I gone to verify the addition of the negative term and panicked when it wasn’t present in the Editor? Too many to want to admit.

However, as I’ve gotten comfortable with using the negative lists, it’s a quick hop and jump into the Shared Library to search for said negative. But acclimating to this layout certainly did take a moment.

More than anything, the burning question we all have is this:

3. Do Negative Keyword Lists Actually Contribute To Improved Performance?


One client was able to make extremely detailed use of the negative keyword lists in both Google and Bing. The site was frequently affected by pop culture, celebrity news and new industry trends.

Without negative lists, we were almost running in circles with the lack of organization to our lists. We used (and continue to use) a few broad match modified keywords that frequently brought in great leads but also terribly irrelevant clicks, depending on the detail of the search term.

So we implemented some very distinct lists:

Negative Keyword Lists

As more “pop culture” terms came through, we would simply add them to their appropriate list at the most effective match type.

This saved our team time and energy and allowed us to focus on the right kinds of optimizations, based on the right traffic. This process produced an overwhelming improvement to our performance.

Because we were more effectively showing the proper ads to our most relevant users, our click-through rate increased by 132 percent for the keywords in our account. While we saw an 8 percent decrease in conversion rate, the average cost per lead was cut in half.

Specifically, cost per lead plummeted by 53 percent, meaning the average cost per lead was 47 percent of the previous average. This not only allowed us to save $1.0M on overpriced leads, but we also were able to use budget that had previously been taken by these inefficiently covered search queries and invest it in top-performing campaigns and keywords.

Final Thoughts

Implementing negative keyword lists didn’t change the types of negative keywords we use, but it did alter how we manage our lists, how we approach negative keyword mining and what applies to our industry. And by taking advantage of this, we were able to focus our real attention on the account as a whole and ultimately improve overall performance.

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Your Ideal Shopping Campaign: The Critical Segmentation Decision /ideal-shopping-campaign-critical-segmentation-decision-218439 /ideal-shopping-campaign-critical-segmentation-decision-218439#respond Fri, 17 Apr 2015 13:28:21 +0000 http:/?p=218439 Columnist Carrie Albright lays out the considerations for shopping campaign structure, including the pros and cons of brand, category, and product segmentation.

The post Your Ideal Shopping Campaign: The Critical Segmentation Decision appeared first on Search Engine Land.


Although Google Shopping campaigns have officially been widespread for over a year (and Bing is catching up quickly), the fine art of structuring and optimizing Shopping campaigns is still a mystery to many.

A common first step is to simply create an “All Products” campaign to test the waters and get a few ideas for how your feed actually performs. But where to go from there is a crucial decision, and a wrong turn may create a long path of inefficient optimizations and troubled campaign management.

Before creating your first handful of campaigns, it’s imperative that you take a moment to reflect on what strategy will work best for you and your product inventory.

Consider the following factors:

  1. Volume of your inventory. Are we talking 50 products or 50,000 products?
  2. The frequency with which your inventory changes. Do you have to account for heavy seasonality, many unique or custom items, or simply just a lot of products in rotation?
  3. Your ability to affect your feed, such as adding new columns of data.
  4. Your understanding of the profit associated with the products you sell. Do you have a set of products that contribute most to your overall revenue?
  5. How much of your data you’d like to manage. Your entire feed? Part of your feed? Only seasonal products or newest releases? Search Engine Land Paid Media reporter Ginny Marvin provided a breakdown on the impact of focusing solely on Top Performers versus an entire inventory approach.

Once you’ve identified what products, content, and metrics are going to drive your campaigns, we can begin to consider the structures to use within the platform interface. Today, we’ll cover the following three segmentation options:

  • Brands
  • Categories & Types
  • Product IDs

Product Brands

This is the first step many take in segmenting Shopping campaigns. If your brands are recognizable by brand name, such as Nike, Sony, or Kelty, this can be a quick and simple way to create more visibility and control within your account.

In Google Shopping, you simply create a product group based on Brand:

SEL_Brand Segmentation


The greatest benefit to this simple segmentation is improved budget allocation. Because an All Products campaign allows for spend to the products that get their clicks in first, a segmented-by-brand campaign can assist in providing the budget where it’s deserved, often with the brands that offer top sales and top return on ad spend.

The secondary benefit is the increased bidding within your campaign. Yes, you can use the beloved Dimensions tab for insight into the feed segments, but by building your campaigns with segments included, you can immediately adjust your bids as you review your data.


If your only segment is the brand you’re including, you leave yourself open to other inefficiencies. For example, you may expand your inventory of youth athletic equipment each fall, to account for new sports seasons. If these particular products are tucked away in a campaign only segmented by the product brand, they may be stifled. If perennial products continue to use the campaign’s budget, the seasonal products may not have the opportunity to shine and sell.


Upon creating an original shopping campaign, all products were run from a single campaign (All Products) for 90 months. After 3 months, the Nike brand was broken out into its own campaign and removed from the All Products campaign. In the following 90 days, we saw a 233% lift in conversion rate compared to the performance for Nike products in the All Products campaign.

SEL_Brand Results

We also saw a slight decline in CTR, but the fact that we more than doubled our impression volume in 90 days at a nearly consistent rate was considered just fine. And right out of the gate, this shift experienced a 61% drop in CPA and a 116% ROAS, both of which indicate the boost in efficiency this new structure created.

Publisher Categories

Both Google and Bing offer categories, recognized as “product types,” in the product feed. Then, one can incorporate these types into segmentation within your campaigns and your Dimension data. While the Bing options are a bit more rudimentary, there is still the option to segment in this way, which helpful in improving performance.

SEL_Publisher Types


The benefit of using product types is that you create clean segmentation in campaigns that may not have highly recognizable brands. Not every business sells Puma or Bose or Fossil. Sometimes you have a great product whose brand is still less well known. In this case, your best option for semi-general segmentation is to use product types.

With Shopping campaigns and ad groups by product type, your structure revolves more around the type of inventory you offer. Are some of your items “big ticket” items? Do you have replacement parts or complementary items that sell, but at a lower overall revenue?

For example, below are two campaigns which feature espresso and coffee makers, and espresso and coffee accessories:

SEL_Product and Acc

When you know that you have a subset of products that can be grouped into a hierarchy, the product type segmentation will help you keep each type running efficiently.


The first concern with this method is simply the use of these prescribed product types. Do your products accurately fall into these categories? Depending on your inventory, you may be opening a whole new can of worms of sorting and selecting your product types. While this is not time wasted, it certainly is a chunk of time that, depending on your product count, may end up being substantial.

Additionally, as you utilize segments that focus on product types, such as men’s, women’s, boots, or hats, the implementation of exclusions becomes increasingly important. A product group that contains women’s sandals should be carefully accompanied by an exclusion of non-women’s sandals.

SEL_ProductType in AdWords

This keeps searches for men’s sandals from creeping into your data, causing all sorts of incorrect adjustments based on this product type.

Product ID

Using the Product ID field of your campaign gives you the opportunity to target down to the very specific product you’re selling. In the apparel industry, this may refer to a unique size and color of shirt. In the homewares industry, it may be a glass carafe replacement for a French press.


In the event of a feed that doesn’t have a lot of consistent brands, or doesn’t segment into many different product types, segmenting by product ID may be your best choice. It allows you to include a set of products and target them individually for the best return.

Product IDs also allows you to pinpoint those products that are particularly successful. In your broader campaigns, such as Product Brand Shopping campaign, you may find through an ID report, like the one below, that a set of products have performed consistently well.

SEL_Item ID traffic

From the above list, we can make a campaign targeting our top performing products to ensure they receive the entire budget and bid attention they need.

Not only can we, but we actually did.


We identified the top selling products and gave them their very own campaign:

SEL_Prodcut ID listing

After 90 days of basic optimizations, we took a look back at how the All Products campaign performed and then how the Top Sellers compare. And the results were pretty much what we thought we’d see in a 90 Day comparison:

SEL_Top Seller Results

Conversion rate was 2.3x higher immediately upon breaking out our top performers. Cost per sale saw a drastic drop, noting the fact that when top selling products are simply lumped into broader campaigns the overall CPA was running inefficiently. The All Products also saw a bit of improvement as we continued to pull out clear performers. In the 90 days after the Top Sellers were launched at full speed, All Product CPA decreased by another 40% and conversion rate increased by 33%.


The “cons” of this strategy is plain and simple: When you’re working from specific product IDs, you suddenly have a lot of product lists to keep track of. Depending on the volume in your inventory, this task may quickly spiral out of control. Although segmentation and customization are vital to create an efficient account, it’s also imperative that you take a moment to consider the impact of what you’re doing.

Breaking out 15,000 products by individual IDs, attempting to keep them fitted with appropriate budgets, and reviewing all those delicious segments like dayparting and geotargeting is a near impossibility.

Similarly, if your product inventory changes regularly, you will be constantly chasing the tail of your Shopping campaigns. As your understanding of your product performance advances, there are even more ways you can arrange your Shopping campaigns for improved efficiency and increased revenue.

The Big Picture

After reviewing these various breakdowns, you should have an idea of what will be your most successful strategy. Shopping campaigns depend on many factors for success: Maintenance is a big one, but structure is even greater. By finding the right structure for your business and your inventory, you’ll find that managing and succeeding Shopping campaigns is easier than you think!

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2 Tales Of Clarity Using Google Analytics’ Multi-Channel Funnel Reporting /2-tales-clarity-using-google-analytics-multi-channel-funnel-reporting-213399 /2-tales-clarity-using-google-analytics-multi-channel-funnel-reporting-213399#respond Fri, 23 Jan 2015 16:04:52 +0000 http:/?p=213399 Are you making use of Multi-Channel Funnel (MCF) reports in Google Analytics? Columnist Carrie Albright offers ways to glean insights from one report in particular: Top Conversion Path.

The post 2 Tales Of Clarity Using Google Analytics’ Multi-Channel Funnel Reporting appeared first on Search Engine Land.

The goal is to turn data into information, and information into insight.
Former CEO of Hewlett-Packard Carly Fiorina

Few marketers dispute the wisdom of Carly Fiorina’s quote above — but when it comes to transforming data into valuable insights, the question is often where to look to find this data.

Analytics platforms offer entire worlds of detail for our interpretation, and in one corner of the Google Analytics universe that’s well worth exploring, you’ll find the Multi-Channel Funnel (MCF) reports.

The MCF tab of Google Analytics strictly represents those sessions that have ultimately resulted in a conversion, which means that your insights will solely be based off converted traffic.

Chapters could be authored on the uses of the Assisted Conversions, Time Lag, and Path Length reports, but this article focuses on the application of your Top Conversion Path report, my favorite of the MCF reports.

About The Top Conversion Paths Report

This report is hands down one of my most treasured possessions when it comes to evaluating the multi-channel pathways of your users. The visibility of a converter’s path contributes quantifiable value to your discussions with clients or in-house higher-ups as you highlight the impact of your marketing touch points.

Your Top Conversion Path (TCP) report can include any of the conversion goals being tracked in Google Analytics. An e-commerce business, for example, may be tracking sales as well as micro conversions such as “Find A Location” users and e-mail sign-ups. When it comes to using the Top Conversion Path report, it may be most valuable to segment these reports, looking just at online sales or a specific micro conversion for a period of time.

You can also set the period of time, called the lookback window, in which these interactions occurred. The default is 30 days from first click to conversion, but depending on the impact you’re striving for with your marketing efforts, the time period may be shorter or longer, and that can actually be reflected in this report.

Extra Tip: The Time-Lag report can be a hidden gem when establishing your best cookie window. This report reveals the specific visit in which your visitors are actually converting, and provide you with insights for how to set the best cookie length for your customers.

Using The Top Conversion Path Report To Glean Insights

Enough talk. At this point, you’re probably wondering, “How do I create and ultimately use the report?”

In creating a TCP report, one of the easiest ways to identify insights is by incorporating your campaign data. When the secondary dimension is set as “Campaign Path,” The report that you can then download will be chock full of PPC takeaways.

Campaign Path Image

Practitioner’s Wisdom: This is one of many examples in which your campaign nomenclature can make everything so much easier. In this instance, all PPC campaigns are created reflecting their role in the account, such as “Branded | Exact” — or, as you’ll see below, “Shopping | Sperry.” This structure allows for very simple filtering so that the data generated in our report all contain a “Non-branded | _______” campaign.

Two Real Applications Of MCF Reports

Tale 1: A Tale Of The Underdogs

The first example comes from a situation where we heavily suspected that purchases made through branded or direct clicks may have originated with non-branded searches. As a good (read: data obsessed and somewhat neurotic) PPC manager, it was clear to me that we needed more than a “hunch” to validate this theory.

The report that followed highlighted how frequently a non-branded (general) or third party branded (product brand) ad impacted the long-term conversion process. To begin, we can generate an Assisted Conversions report with the Campaign Path included and focused strictly on conversions that occurred with these non-branded campaigns.


This is step one in identifying the campaigns that are playing the largest part in our sales, be it through Last (or Direct) Click or simply an assisted conversion.

The next step in this process was to show how our non-branded efforts are impacting customer acquisition, not just overall sales.

To do this, we pull the non-branded PPC-initiated Top Conversion Path report, including the campaign details, and export this beauty. In Excel, we identify the conversions that 1) began with a non-branded search, and 2) contained a direct search.


The brand-initiated searches are those in which visitors only interacted with branded searches, direct visits, and referrals through email campaigns. The remaining traffic originated through non-branded searches, but eventually came to the site through a branded source. From this date range, we infer that the visitor first came to our site based on interest in a specific product, but returned again because of interest in what the site has to offer.

Those non-branded campaigns that appeared in this report continued to receive a portion of our monthly budgets with an emphasis on those that created direct traffic; those that failed to contribute to total sales were our opportunities for reducing inefficiencies.

Tale 2: A Tale Of The Stolen Credit

In this story, the client was concerned that their non-branded campaigns were losing credit for sales, as they may have been misattributed to branded ads in their reporting platform.

Q: How many sales are initiated through non-branded searches that end in branded purchases?

A: 18% of total sales for this time period.

Simple, right?

But how did we demonstrate this clearly and concisely?

We began this analysis by examining the data in which the initial click and final sale both came from a PPC campaign. From here, the data was segmented into the categories based on the following questions:

  • Did the initial click come from branded or non-branded searches?
  • Did the final sale come from branded or non-branded PPC?
  • Were other marketing channels present in the path to conversion?

From this list, a pivot table was created that breaks down the data into these characteristics, with the golden cells pinpointing the sales originating with a non-branded clicks and ending with a purchase through a branded click.

This data is now prepared for comparison to back-end performance. For this timeframe, approximately 18% of sales initiated with non-branded but closed with brand, 15% of sales were strictly non-branded, and 67% of sales began with a branded search.


The Magical World Of Multi-Channel Funnel Reports

These two reports are simply stepping stones into the deep dive available through Multi-Channel Funnels and the attribution modeling available in Google Analytics. Once you’ve identified the channels that have the strongest impact, you can optimize your investment based on these insights.

For those of you focusing on multiple marketing channels, these reports are just a scratch in the surface of what you might find. While this article focuses on segments of PPC traffic, another obvious direction loops in your other marketing channels. How does your revenue change when visitors are both email referrals and direct visitors? Do display buys assist in customer acquisition, such as email list signups?

These relationships can be parsed out through your Analytics data and through the reporting found within your Multi-Channel Funnel tab. There is an eternity of insights awaiting you, it’s simply your task to begin gathering your data and assessing what it’s telling you. For as Sir Arthur Conan Doyle said:

Data! Data! Data! I can’t make bricks without clay!

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