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RKG is a digital marketing agency providing data-driven solutions to online marketing challenges.



 



Google Addresses One of the Flaws in Its Paid & Organic Report, Others Remain

23 May 2017 10:01:16

Google announced yesterday that its paid and organic report can now be downloaded by device, a marked upgrade in allowing marketers to analyze ad and organic link performance by query more granularly. Both paid and organic ranking and peformance can vary by device type, making this segmentation crucial for understanding both channels’ performance as well as assessing results of tests such as brand ad holdouts. However, the report is still limited in a couple of critical ways in that it does not include data from Google Shopping campaigns and the data still cannot be segmented by geographic region. Here’s why those two points matter. Google Shopping Ads Are a Huge Source of Traffic for Retailers and Crucial to Understanding Ad Visibility Google Product Listing Ads (PLA) accounted for 52% of all retailer Google paid search clicks in Q1 2017 and 75% of all non-brand clicks, according to Merkle’s Q1 Digital Marketing Report. As such, leaving these ad units out of the paid and organic report greatly limits how much insight advertisers can draw from it. For example, having a PLA unit as well as a text ad and organic link for a particular search might impact expected performance compared to when just a text ad and organic link are present. At present, the report would deem these two situations as identical. Obviously moving forward, retailers would greatly appreciate an update to include Google Shopping in the paid and organic report. Global Organic Data Inhibits Valuable Analysis The other major limitation of the paid and organic report that has yet to be addressed is the lack of geographic segmentation. This is important for a couple of reasons. One is that even if a brand were completely global and relevant in every country that uses Google search, its competitive position is likely different for different regions. Aggregate global trends might hide valuable regional insights, and advertisers currently have no ability to account for this. Another big reason this is an issue is that paid search data is obviously limited to the regions targeted in AdWords, while organic performance represents the entire world. That means that while the ‘ad only’ and ‘both’ categories of query performance are limited to regions targeted by AdWords, the ‘organic only' performance is mixed between regions targeted in AdWords and any other regions which accounted for organic impressions. This isn’t an issue if AdWords campaigns target the entire world equally with ads, but that would be an incredibly rare if not non-existent scenario. At a basic level, this makes it nearly impossible to make comparisons of aggregate click-through-rate when an organic link is present by itself versus when an ad is shown alongside an organic link, since the global data makes for an apples-to-oranges scenario. This can be accounted for in holdout testing when ad impression share for a query is at or near 100%, but it’s a headache and marketers are out of luck for any query without near-100% ad impression share. Conclusion This is the first major update to the paid and organic report since its release in terms of real additional functionality, and represents a strong step forward in making the report more nimble for advertisers to actually use in analysis. Unfortunately, there are still a couple of other areas that need to be patched up in order to make the paid and organic report all it could be. If you’re reading this, Google, inclusion of Google Shopping ad performance and geographic segmentation are next on our wish list for this evolving report. [...]



Latest Google Ad Rank Changes Driving Up Minimum Bids for Non-Brand Keywords – Brand Minimums Down

19 May 2017 8:50:52

Google recently announced that, beginning in early May, two changes are being rolled out to Ad Rank: Minimum Ad Ranks to appear on the first page or at the top of the page can be calculated based on the meaning of the query. Depending on query meaning, bids may be weighted more heavily in determining Ad Rank. The first change appears to be focused on better incorporating the context of a query into determining the required Ad Rank, and thus bid needed,to receive an ad impressions at the top of the page or on the first page of results. The second point indicates that ad quality factors such as expected click-through rate might be weighed less heavily in determining an advertiser’s Ad Rank depending on query meaning. Google has said that these changes are expected to roll out through the end of May. However, taking a look at top-of-page and first-page bid minimums as well as CPC trends, it’s clear that the effects of this change are already starting to take form. Non-Brand Minimum Bid Estimates Up, Brand Down For the median Merkle Google searchadvertiser, non-brand first-page minimum bid estimates began increasing at the same time that brand first page minimums began decreasing in early May.  While first-page minimum bids can fluctuate greatly for any given keyword, viewed across an entire program they are generally a good indicator of when significant changes are occurring in the Google auction, either announced or unannounced. We find similar trends with regards to top-of-page minimum bid estimates, with brand keyword minimums going down and non-brand minimums going up. With these changes, we might expect a corresponding increase in CPC for non-brand keywords and a decrease for brand terms. However, we find just half of that is true. CPC Trending Down for Brand and Non-Brand Keywords Since the trends in first-page and top-of-page minimums began taking hold, brand CPC has declined more significantly Y/Y than what was observed between March and May. With the vast majority of brand clicks occurring at the top of the page, top-of-page minimum bids are much more important than first-page minimums in determining CPC for most advertisers. While Ad Rank thresholds are increasing for non-brand keywords, CPC has not gone up, and Y/Y change has recently been relatively low within the range of what we’ve seen since the beginning of March. With so few days since the change, it’s totally possible that the effects of these updates aren’t fully accounted for in these figures. However, there are two points to make on this front. For non-brand keywords, most advertisers are shooting for specific return on ad spend goal of some type. This means that if the cost of traffic were to go up as a result of these changes without driving any more value for advertisers, some share of keyword bids would have to necessarily come down in order to maintain the same return on investment observed prior to the update. As such, aggregate non-brand CPC wouldn’t necessarily go up with the increases in Ad Rank thresholds that we’ve seen. Brand keywords are often not held to strict return on ad spend goals. This is usually because these terms convert at a very strong rate, and brands also want to have an ad present in order to get as much brand traffic as possible and control messaging. As such, advertisers are more likely to eat any increases in CPC for brand terms, to a point. Google can still cross the line, as evidenced by steep increases in Google brand CPC in Q2 2015 resulting in advertisers taking active measures to mitigate the impact on spend. Additionally, Google’s move to update both how Ad Rank thresholds and Ad Rank for specific queries are calculated makes it difficult to formulate expectations for how these updates will impact performance. That said, announcing that bids will be more heavily weighted in some auctions sure sounds like a change that will put upward pressure on CPCs by not factoring in quality score advantages as much. Looking at how traffic breaks down by page[...]



Nonprofits Investing in Digital Channel Experience Growth

17 May 2017 12:19:22

As more organizations are turning their fundraising focus to digital channels and media, one of the questions I hear frequently is, “How much of our budget should we allocate to digital versus our more traditional offline channels? And what return can we expect from that investment?”

To help nonprofit marketers answer those questions, Merkle conducted a digital benchmark survey with 79 nonprofit organizations, each with $10 million or more in annual revenue, to assess their commitment to online fundraising and explore related trends.  This post includes some of the most poignant findings from that study, as described in the Digital Roundup: 2017 Online Fundraising Benchmark Report.

According to the report, the average organization dedicated about 16.2 percent of its overall budget to online fundraising efforts. This investment resulted in about 15 percent of their total direct response revenue. In recent years, other industry benchmark studies have reported online revenue making up about 5-10 percent of overall revenue. So for nonprofit organizations, online investment steadily produces more revenue as their constituent base increasingly responds to email and web-based interactions.

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For most of these organizations, online marketing efforts include email, mobile, and digital advertising. Email continues to be a cornerstone, with the average nonprofit generating about $3.0 million in annual gross revenue from an average list of about 389,000 subscribers. For digital advertising, most organizations are utilizing about 15% of their total media spend to fund their own unique mix of paid search, display, paid social, and video advertising.

Organizations investing new funds or reallocating budget from other channels into digital advertising are seeing a cost per dollar raised (CPDR) of about $0.36 for acquisition and renewal. Most groups are focusing spend on top of the funnel (awareness and consideration), with the mid and lower funnel spend a secondary priority.

To learn more about nonprofit trends and results of investing online in email, mobile, digital advertising, channel integration and more, view our on-demand webinar, Embracing the Next Generation of Fundraising or view the Benchmark Report.

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What to Know About Facebook's 2017 Ad Updates

16 May 2017 10:39:02

Facebook continues to see explosive growth in its advertising business, as the Merkle Digital Marketing Report showed 71% Y/Y Facebook ad spend increase and eMarketer projected that the platform will account for nearly 40 percent of U.S. display ad revenue in 2017. But with rising competition from platforms like Snapchat, the rollout of new tactics to advertisers is crucial to continued growth. Let’s take a look at some of the new advertising options available in Facebook so far in 2017. Expanding the Reach of Dynamic Product Ads In January, Facebook launched a beta program giving advertisers the ability to target Dynamic Product Ads (DPAs) to broader audiences than just the users who have viewed the products in a brand’s catalog. Advertisers now have the option to use Facebook targeting options such as interests and demographics to seek out potential new customers based on intent demonstrated on Facebook and around the web. A retailer selling shoes, for example, would be able to serve DPAs to users who have looked at Facebook pages or other websites related to shoes. Those ads would display products from the retailer’s product feed to match the user’s demonstrated intent. Then, once that user visits the retailer’s site or app, they would become eligible for retargeting based on the products they browsed on the site. This beta also allows brands to use CRM data to both re-engage existing customers not included in retargeting audiences and build prospecting models that will expand reach on Facebook in a smart, targeted way. A Merkle retail client using DPAs to retarget product viewers has used this beta to additionally re-engage a purchaser list and target a lookalike model with great success over the last several months. The purchaser list converts at a 46 percent higher rate than product retargeting audiences, while the lookalike ad groups have seen outstanding engagement, with a click-through rate 36 percent higher than retargeting audiences and 92 percent higher than the average CTR across Facebook and Instagram, according to eMarketer. The ability to target new users with dynamic ads also eases the burden on creative teams, with a brand’s product catalog serving as the creative engine. Rather than needing to develop unique ads for each product in a catalog, the relative simplicity of dynamic ads makes the process of acquiring new customers a more turn-key solution. The beta is currently closed to new advertisers, but we’re keeping our fingers crossed that it will re-surface later this year. New Collection Ad Format In the meantime, advertisers who want to promote products from a catalog have a new option available to them: the Collection ad format. The new format is not dynamic, but it pairs a “hero” image or video with related products (chosen by the advertiser) to help drive product discovery on mobile. Four products from a product set will display below the main creative, but when a user clicks on the ad, they will be able to browse the extended product set without leaving Facebook—from there, they can click through to your site or app and purchase. Even once the broader audience program is released to more advertisers, Collection ads should be a strong component of advertisers’ social plans; they bring together the best parts of both video ads (engaging creative that tells a story) and DPAs (keeping the focus on the products). But in the meantime, they offer the added benefit of being one of the best ways for brands to promote their products to new users. Ad Breaks Coming to Facebook videos At the end of February, Facebook announced the expansion of ad breaks to its on-demand and live video offerings. After long banning pre-roll ads and restricting video ads to standalone units, these ad breaks represent a clear attempt to compete with video advertising rivals Snapchat and YouTube. Pages and profiles in the U.S. that have at least 2,000 followers and have reached at least 300 concurrent viewe[...]



Merkle Q1 2017 Digital Marketing Report Released

25 Apr 2017 10:04:07

Today we are pleased to announce the release of the Q1 2017 Merkle Digital Marketing Report for download. The DMR is a long-standing barometer of key digital marketing channels that includes in-depth stats and analyses on paid search, SEO, display advertising, paid social, and more. In this edition of the report, we explore the rise of Google Local Inventory Ads for brick-and-mortar retailers and nclude updates on the performance of recent changes such as Google Expanded Text Ads and the growing presence of ad on Google Maps. Download the Q1 2017 Digital Marketing Report today. In addition to the report, we’ll be hosting a webinar on Wednesday, April 26th at 12:00pm ET to discuss the major storylines included in the report and to field listener questions. This event will be recorded and those unable to attend can sign up to receive a copy at the end of the week by registering for the webinar. Here are a few brief descriptions of some of the data included in the report. Paid Search Google spend growth accelerated from Q4 to Q1, as Google made several updates which have allowed advertisers to invest more in paid search overall. One such update was the decoupling of desktop and tablet bids in mid-2016, which has allowed brands to bid less for tablet traffic and more for desktop traffic, in line with the value derived from each. As such, desktop spend increased while tablet spend decreased Y/Y. Google Shopping (also known as Product Listing Ads - PLAs) spend grew the fastest of any search engine ad format. In addition to the growth of traditional PLAs, Google’s Local Inventory Ads are also becoming a larger part of Google Shopping spend for brick-and-mortar retailers. Organic Search & Social While overall organic visit growth declined Y/Y, Q1 marked the smallest such decline in the past five quarters. Visits decreased significantly on desktop and tablet devices, but mobile organic site visits were up 15%. Social media still accounts for only a small share of all website visits, but traffic share continues to steadily increase. In Q1, social media networks accounted for 3.8% of all mobile site visits, stronger than the share of overall visits. Display, Paid Social, and Video Advertising The strong mobile share of social media visits is also clear looking at Facebook’s mobile device spend share, as phones and tablets combined to account for 76% of all Facebook spend in Q1. This far outpaces the share of paid search spend from mobile devices. Paid social is steadily growing in importance, and the gap between advertisers' investment in social platforms vs traditional display advertising shrunk significantly Y/Y. Comparison Shopping Engines Amazon eliminated its Product Ads format in late-2015, but advertisers are increasingly taking advantage of other advertising opportunities on Amazon such as Sponsored Products ads. In Q1, Sponsored Products spend declined similarly to Google Shopping spend Q/Q. Among traditional CSEs, the eBay Commerce Network accounts for the vast majority of advertiser spend. However, Connexity is more competitive for some product categories. For more information on these and other trends across digital marketing channels, download the Q1 2017 Merkle Digital Marketing Report and sign up for our webinar on Wednesday, April 26th at 12:00pm ET. [...]



Why Google Shopping Yields Smaller Orders, and Why That Might Be Okay

10 Apr 2017 10:40:57

This article appears in the Merkle Dossier 8.1, which includes actionable insights on paid search, SEO, loyalty services, co-op marketing, and more. Download Dossier 8.1 here. Online retailers should know well by now the importance of Google Shopping, also known as Product Listing Ads (PLAs), in paid search. As of Q4 2016, these image-based ad units accounted for 48 percent of all Google paid search traffic for retailers, according to the Merkle Digital Marketing Report. With text ads and PLAs now accounting for roughly equal shares of their total Google search ad traffic, many retailers look to compare metrics between these two formats to find opportunities for optimizations. One key difference that advertisers have consistently seen over the years is that the average order value (AOV) tends to be smaller for PLAs. Here we’ll examine the potential causes for such a difference, and explain why it might not make sense for advertisers to try to force higher AOVs from their PLAs. Google Shopping AOV Lower than Text Ads across Device Types Comparing AOV for PLAs vs text ads by device type for January 2017, PLA average order value was 12 percent lower than that of text ads on desktop and tablets and 17 percent lower on phones. These differences can also be much larger, as about 20 percent of the advertisers studied find PLA average order value more than 30 percent below that of text ads for any given device type. Only about 15 percent of advertisers had a higher AOV for Google Shopping than text ads for any given device type. Importantly, AOV is lower for PLAs because of differences in both the average number of items purchased per order and the average price of the items purchased. Do Product Listing Ad Clickers Buy Fewer Items? While PLAs have steadily expanded to show for a wide range of queries, including very general searches for broad product categories such as “men’s shoes,” PLAs are still more likely to show for queries that indicate the intent to purchase a specific product (for example, “Nike free 5.0 men’s”). For these specific searches, the query indicates that the searcher is looking for a single item, and logically it makes sense that searchers are likely to click on a PLA that displays an image of the precise product they’re looking for. This is to say that searchers looking for a specific product might be more likely to be presented with and then click on a PLA unit, while searchers conducting more general inquiries might be more likely to be presented with and end up clicking on a text ad. Very specific searches in turn probably yield smaller shopping carts than more general searches, since these queries show the intent to find a single product rather than to browse through multiple products. Looking at basket size for PLAs versus text ads in January 2017, this theory appears to hold up as the median PLA advertiser (Merkle clients) found that PLA-driven orders had fewer total items per conversion than text ads for every device type. The difference in the number of items per order is greatest on phones, which also produce the largest gap in AOV overall. However, the difference in AOV is greater for desktop and phone than the difference in the number of items purchased. So this data doesn’t quite tell the whole story. Do Product Listing Ad Orders Include Cheaper Products? Looking at the median price per item purchased of PLA orders versus text ad orders, we find that items in PLA orders are slightly cheaper across every device type. Product price is clearly displayed in each PLA unit, and searchers can deliberately choose to click on the cheapest possible option from among the products listed. Text ads, on the other hand, are not required to include price in ad copy, and very few searches return text ads that all have price clearly listed. Further, searchers have the option to click into Google Shopping and sort all relevant products by[...]



AdWords Price Extensions Might Not Be as Awesome as You Think

5 Apr 2017 8:35:49

Price extensions, released out of beta testing in mid-2016, feature products or services along with pricing information below traditional text ad copy, significantly expanding the size of text ad units. Along with the additional real estate, these extensions also provide users with more information about product/service pricing, which might help lead to more informed clicks and thus higher conversion rates. While several price extension case studies published show that ads with price extensions have higher click-through-rate than those that don’t, it’s important to account for variables such as keyword mix, device, and the fact that price extensions tend to show in higher average positions than ads that don’t trigger these extensions. Here we assess the performance impact for one advertiser currently using price extensions, and also highlight that Google appears to be showing these extensions in unexpected places on the SERP. Price Extensions tied to Higher CTR and CPC With such a substantial addition to the area taken up by a text ad, price extensions should naturally draw more clicks than ads that don’t feature this additional real estate. Indeed, looking at relative performance for the median exact match keyword when price extensions are featured versus when they are not featured, CTR is higher across all three device types when price extensions are triggered. Relative CTR is highest on phones, which also produce the vast majority of price extension impressions. For the keywords studied, phones accounted for 69% of all impressions when price extensions were triggered, compared to just 34% when price extensions were not triggered. This might speak to how likely Google is to feature these extensions on different device types. It also highlights the need to segment by device when comparing performance since device traffic share isn’t the same for ads that feature price extensions as for those that do not. As you can also see in the above chart, average cost-per-click is also higher for the median keyword in situations when price extensions show versus when they don’t. Are the extensions forcing advertisers to pay more? Probably not, and the difference likely has to do with Google’s propensity to show price extensions for ads in higher positions on the page. Price Extensions Triggered When Ads Appear Higher on the Page Looking at the same set of exact match keywords, we find that ads that feature price extensions have a higher average position than when the same ads are featured without price extensions. In average position, a lower value means an ad is featured higher on the page – hence the flipped axis in this chart. As you can see, while average position was just 0.1 positions higher on the page for desktop computers, that figure is 0.4 for both phones and tablets. Higher position likely explains why CPC is higher, given that clicks in higher positions typically cost more than those in lower positions as they require more competitive bids. While a 0.4 position difference might not seem like a lot, it can have a significant impact on the likelihood of searchers clicking on an ad. Particularly on phones, where the top ad listing might take up the entire screen above the fold, moving up a single position can have massive effects on CTR. As such, it’s fair to attribute at least some of the increase in CTR observed for ads that feature price extensions to the simple fact that these ads are typically in higher positions than those that do not feature price extensions for the same keywords. But what about the value of these extensions in driving more orders for advertisers? Users are getting more information about potential pricing, which should lead to more informed clicks and potentially higher conversion rate. However, the data shows no such effect. Conversion Rate Lower When Price Extensions Show Across all three device type[...]



Baidu Adds New Spider with Rendering Job

28 Mar 2017 14:37:27

About a month ago, I was informed by Baidu that they would be releasing a game-changer to rebuild the eco-system of the web in China. On March 24, in alignment with their previously published Web Ads Guideline (guidelines are in Chinese) Baidu Webmaster Tools announced that they have added a new crawling spider.

This new spider will not only crawl the HTML of the web pages but also render the page with other elements including CSS, JS, and images to help Baidu better understand the content of the page and provide more meaningful results. Baidu started the test on the 23rd and they are rolling it out now. The user agent of spider is marked as:

Mozilla/5.0 (compatible; Baiduspider-render/2.0; +http://www.baidu.com/search/spider.html) (Desktop)

Mozilla/5.0 (iPhone; CPU iPhone OS 9_1 like Mac OS X) AppleWebKit/601.1.46 (KHTML, like Gecko) Version/9.0 Mobile/13B143 Safari/601.1 (compatible; Baiduspider-render/2.0; +http://www.baidu.com/search/spider.html) (Mobile)

Baidu said this change is adding some pressure for sites, as it costs extra resources, but is advising webmasters not to block those spiders.

This change makes Baidu more like other advanced search engines and signals an elevated investment on the user experience and safety of the web. During the rollout, we expect the results rankings on Baidu to experience increased fluctuation. For technical SEO, Merkle is updating its Fetch & Render Tool to reflect this major change.

In 2015, Merkle became Baidu’s first US-headquartered reseller. For more on our partnership with Baidu and how this can benefit your China program, visit our Baidu page.

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3 Tips for Effective Paid Search Audience Management

9 Mar 2017 16:12:56

Audience targeting is one of the most powerful levers paid search marketers have at their disposal. With limited budgets, complicated service/product offerings, and aggressive goals, harnessing the power to hone in on subsets of searchers is a must for a successful program. The challenge with audience targeting is that paid search advertisers can fall prey to pitfalls such as over-complication: too many segments can quickly become hard to manage and make remarketing efforts messy. By following a few guidelines, you can avoid common pitfalls and set your program up for success. 1) Ensure there is a business reason behind each specific audience you're targeting. There are two main reasons to isolate audiences from the rest of your traffic: to serve a unique experience or to bid differently based on performance. If your use case doesn't fall into one of these two scenarios, consider that it may be more work to tactically break out the subset of people than it is worth in reward. However, there are exceptions. For instance, you may need the ability to report on an audience separately using metrics not available in the user interface (i.e. 3rd party conversions). But if that's not the case, plan carefully so you don't inadvertently overcomplicate your account. 2) Prioritize audiences based on client objective. In most cases, it's possible for searchers to meet the criteria of multiple AdWords remarketing and Customer Match audiences. Because users can fit criteria for multiple lists, it's important to develop an audience hierarchy to prioritize them. For example, if shopping cart abandoners of high value products are worth more to an advertiser than page visitors of those high value products, the more important audience should be prioritized and trump other audiences. An audience hierarchy can be enforced either via audience negatives (if using AdWords' Target & Bid setting for audiences) or by bid strategy (if using the Bid Only setting). In the example below, if using the Target & Bid setting, campaigns targeting the “Cart Abandoners: High Value Product” audience wouldn’t have any negative audiences. This ensures that any searcher falling into that audience (regardless of what other audiences he/she falls into) is served the experience for the highest value product. For campaigns targeting the lowest priority audience, (“Page Visitors: Low Value Product” in this example), add all higher priority audiences as negatives to the lower priority campaigns. If using the Bid Only setting, simply bid most aggressively for top priority audiences and less for lower priority audiences, as search engines respect the audience with the highest modifier. Be methodical about which buckets searchers can fall into and ensure you're using audience negatives, which prevent ads from showing to members of a particular audience, to properly shepherd traffic to the correct audience. Keep in mind that if you are targeting Customer Match & remarketing audiences separately, overlap must be taken care of at the campaign or ad group negative list level but cannot be addressed within custom combination lists. Keep up with this! Negative audiences should be evaluated and possibly updated every time you update your lists, add new lists or update targeting in campaigns and ad groups. Do yourself a favor and save a running document to keep track of changes. It's difficult to audit and clean up later if you aren't diligent, so keep current and make this an ongoing effort. If you let it slip, you could jeopardize the efficacy of your program! 3) Always keep your focus on the areas of greatest return. It's easy to get bogged down by all of the possible segments! Keep your focus on what moves the needle for your account and don't let the tiny audience that doesn't perform cause distractions. Prioritize testing [...]



Creating a Local Paid Search Strategy to Drive Customers to Stores

8 Mar 2017 17:13:04

Hi, I'm Laura Stiles. I'm a senior analyst here at Merkle, and today I want to talk about how to create a paid search strategy to drive customers into stores.

Now, more than ever, we're seeing that customers are blurring the lines between online and offline. So they're researching new brands and products on their phones before going in to stores to make a purchase. For paid search, we want to create a strategy that follows a similar line of thought.

So, the first thing that we want to think about is how we're going to measure our in-store campaigns. We need a way to capture the user's store visits or their in-store transactions. Google offers several tools to help measure both of these things. This part is really important because it's going to help us to discover parts of our current program that are really effective at driving customers into stores.

The next step is going to be creating local campaigns. We want to target keywords that capture the user's intent as they go into stores. Think of keywords like, "shoes near me," or, "rain boots in Charlottesville, Virginia," as examples of the queries they might use. 

Next we want to geo-target these campaigns so that we're only serving ads to users that fall within a reasonable distance of the store. That way, we're not wasting ad spend on users that couldn't reasonably drive to your physical store. We want to have ad copy that reinforces the user search. We also want to make sure that we're focused on in-store value propositions as opposed to online value props. As an example, where you would normally focus on free shipping, maybe instead you want to focus on something instead like door busters.

Next we need to figure out what landing page to send the users to. Typically the store locator page is going to be your best bet. Ideally, have the store locator already targeted towards your user's immediate area.

Finally, let's talk about the bidding piece. We want to be more aggressive on mobile devices. In this case, we want to capture users that are on the go, so mobile is going to be a great place for you to aggressively bid. We want to set different goals for our offline campaigns compared to our online campaigns. We want to make sure that we're judging these campaigns by their ability to drive users into stores as opposed to drive online conversions.

From all of this, there's a lot that can be gained. We're going to be able to drive users in to the store more effectively than we ever were before. Overall, that's how we can capture users searching online before making purchases in stores.

Thanks.

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