Andy Taylor, Author at Search Engine Land News On Search Engines, Search Engine Optimization (SEO) & Search Engine Marketing (SEM) Thu, 03 Mar 2022 19:36:39 +0000 en-US hourly 1 https://wordpress.org/?v=5.9.2 How DuckDuckGo (and Microsoft) benefit from Google’s sprawling advertising business /how-duckduckgo-and-microsoft-benefit-from-googles-sprawling-advertising-business-344079 Mon, 23 Nov 2020 17:49:55 +0000 /?p=344079 Smaller search engines are able to monetize their results with Google’s advertiser base to reach searchers on those properties with as few obstacles as possible.

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DuckDuckGo is a search engine that was founded in 2008 with a focus on protecting searchers’ privacy, notably showing all searchers the same search results and refraining from building profiles of its users. Its search volume has risen steadily over the years, and in October 2020 was up to nearly 60 million queries daily.

This rise could be evidence that Google’s dominance is not prohibitive to the rise of competitors, and that a search engine focused on user privacy can succeed in building a real business. However, smaller search engines like DuckDuckGo benefit from the expansive network of advertisers bidding on Google search ads. Here’s how.

Smaller engines rely on ease of campaign duplication to pull Google advertisers

The second-largest search business in the US, Microsoft Advertising, is built on query volume coming from Yahoo and Bing as well as other search partners, including DuckDuckGo. Bing and Yahoo account for about 3.5x and 5x as much organic search traffic as DuckDuckGo, respectively, according to Statista.

The benefit to using a platform like Microsoft Advertising to DuckDuckGo is that Microsoft can attract many more advertisers with its aggregate volume than DuckDuckGo could hope to at this stage in its business. This is because, in addition to the cost of actual paid search clicks, there is a cost to managing campaigns on different platforms in the form of additional time and effort to launch those campaigns and optimize them correctly. By joining Microsoft Advertising’s network, then, DuckDuckGo is able to garner ad dollars from advertisers that wouldn’t be able to profitably launch ads on DuckDuckGo if it required entirely separate management.

However, the same is also true of Microsoft Advertising, which leans into its own tools developed specifically with the aim of making it as easy as possible to duplicate Google campaigns to its platforms. To quote Microsoft’s own literature on Google Import:

‘If you’re already using Google Ads, you can save a lot of time by importing your campaigns directly into Microsoft Advertising…The less time you spend managing your ads, the more you can focus on serving your customers.’

No such capability exists when it comes to importing Microsoft Advertising campaigns into Google, because Google, as the dominant search engine, is able to attract the largest pool of advertisers in the US. 

Microsoft Advertising knows that, while the aggregate volume of the properties in its network is absolutely meaningful, many businesses would not be as active on its platform if there were significant differences in how campaigns were launched and managed relative to Google. Again, campaign launches and management take time, and if advertisers are able to tap into 90% of the paid search opportunity by focusing on just Google, many would only launch on Google were it not very easy to port those campaigns and settings over to Microsoft Advertising. Microsoft understands this, which is why a tool like Google Import exists.

DuckDuckGo, by way of being a part of the Microsoft Advertising network, also benefits from Microsoft making it as easy as possible for Google advertisers to duplicate campaigns into its platform. Were DuckDuckGo to launch its own platform, it would likely also have to create a similar import tool to either port over campaigns from Microsoft Ads or Google itself in order to maintain the pool of advertisers it has benefitted from in its business so far.

Conclusion

The purpose of this column is not to take sides on the question of searcher privacy or the pros/cons of Google’s dominant search position. It is merely to unpack the economics of how smaller search engines are able to monetize their results, and how that has largely relied on making it easy for Google advertisers to reach searchers on those properties with as few obstacles as possible.

Google itself also ostensibly benefits from this arrangement in a sense that it can point to legitimately viable competitors that are able to make money in search even without Google’s expansive volume. This is potentially even more important to Google now that it faces a DOJ investigation into its search dominance.

For better or worse, Google’s dominant search volume gives it more data to use in producing search results and attract more advertisers to its platform with bigger opportunity. Yahoo itself, now a part of Microsoft Advertising, indirectly acknowledged how powerful that flywheel can be when it decided to reenter a deal with Google in 2015 to power some of its ads that lasted until early 2019.

Whether Google has abused its position to further diminish competition is a more complicated question for another day. For now, it seems clear, to me at least, that other search engines have relied to an extent on Google’s advertiser base to help propel their own advertising businesses. That’s true even of DuckDuckGo.

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2020 Google paid search trends that have nothing to do with the pandemic /2020-google-paid-search-trends-that-have-nothing-to-do-with-the-pandemic-339705 Tue, 25 Aug 2020 12:00:00 +0000 /?p=339705 With close variant taking the place of broad match, limiting keywords isn't enough for keeping query-to-keyword matches tight.

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It’s no secret to paid search marketers that COVID-19 has hugely impacted performance and advertisers’ ability to spend on paid search marketing in ways varied across industries and business situations. There have been plenty of articles written on some of these shifts.

Here I’d like to talk about the 2020 trends affecting paid search marketers that have nothing to do with the pandemic, and how to think about them moving forward.

The death of the tablet

Looking across a collection of long-standing Tinuiti advertisers, tablet spend growth for Google US paid search started to take a dive in Q4 2019, going from 5% growth last Q3 to 22% decline in the final quarter of the year. The trend has only gotten more pronounced in 2020, with spend declining at least 45% each of the first two quarters of the year.

While device trends can certainly be a result of advertisers shifting strategies, the magnitude of the decline makes it clear this is more than just advertisers pulling back on tablets.

Indeed, global tablet shipments have declined steadily since a high observed in Q4 2014, according to data from Statista. In Q4 2019, shipments were the lowest they’d been since Q3 2012.

With larger smartphones packing better functionality steadily eroding the value proposition of tablet devices, tablets just don’t seem to carry the same demand as in the early goings of the device type. In turn, the volume of searches happening on these devices just isn’t what it used to be, and paid search advertisers are seeing a corresponding decline.

For paid search managers, this really just means it’s becoming less and less important for many to focus as much attention on traffic coming from these devices. While it’s still useful to check in and make sure there’s not a significant volume of inefficient spend coming from tablets, the likelihood of that being the case continues to decline over time, with tablets now accounting for just 4% of Google search clicks for Tinuiti advertisers.

This is also true of spend coming from the search partner network, which is now minimal after years of decline.

2019 updates put the fork in Google search partner share

Google announced in March 2019 that Shopping ads featured on Google image search would be grouped with the core search network as opposed to the Search Partner Network. This followed a decision by Yahoo to turn to Microsoft Ads for its search ads, severing a relationship that saw some Google search partner traffic coming from Yahoo.

These changes led to a steep decline in the click share coming from search partners for Shopping in particular, and by the end of Q2 click share for both text ads and Shopping was below 1%. 

While the Search Partner Network been a divisive source of paid search traffic over the years given the lack of control advertisers have overbidding and placements, I’ve long found that the efficiency of this traffic is typically in line with that of traffic that comes from google.com. This is because of an inherent discount for search partner clicks that usually roughly lines up with how much lower conversion rate is for search partner traffic relative to the core network.

Alas, after years of decline the search partner network is now so small that the debate on whether to target these sites isn’t very important these days.

2020 has also seen the decline of another contentious source of paid search traffic in broad match.

Broad matches now account for just 10% of nonbrand Google paid search clicks

Back in the first half of 2016, the share of nonbrand paid search clicks attributed as broad matches in Google search query reports was up above 25% for the median advertiser. Fast forward to Q2 2020, and that share is now just 10%.

So what happened? Did advertisers pack up their keywords and say no thank you to broad match?

While advertisers can choose to deploy different keyword strategies over time, particularly when transferring management from one agency/consultant to another, the decline observed over the last four years appears to be the result of Google’s ever-changing definition of close variants over time.

Indeed, looking over at the share of total exact match traffic (including close variants) which come from close variants, we find that share has gone from 12% in Q1 2016 to over 40% in Q2 2020 for the median advertiser.

With the current definition of close variant restricted to anything Google deems to have the “same meaning” as the keyword, it’s hard to imagine the definition getting any broader from here.

The infusion of so much traffic that would formerly have been considered broad match into close variants means advertisers need to stay vigilant in evaluating search query reports to identify situations which warrant keyword negatives. Not all close variants are poor matches, but many do see meaningfully different performance than true exact and phrase matches on the non-brand side.

Many marketers have long limited the keywords deployed on broad match in order to limit how many poor matches might be pulled into the queries driving ad impressions. With close variants now more or less taking the place of broad match, strategies like avoiding broad match keywords won’t suffice for keeping query-to-keyword matches tight.

Advertisers will have to remain vigilant regardless of what match type a keyword is set to.

Conclusion

There are a lot of moving parts going on in the world right now, with different regions moving through different stages of restricted movement in waves across the United States, sometimes having to revert to prior stages of safety precautions. This scattered reality will likely continue for the foreseeable future and have significant impacts on paid search performance that varies by locale and industry.

That said, some underlying trends have been taking shape for years and aren’t very much the result of current events. Understanding current performance necessitates an understanding of these shifts as well as those springing up due to COVID-19.

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The importance of valuing latent orders to successful Amazon Sponsored Products management /the-importance-of-valuing-latent-orders-to-successful-amazon-sponsored-products-management-338045 Fri, 24 Jul 2020 12:00:00 +0000 /?p=338045 Advertisers must consider the lag time between ad click and conversion as well as historic performance around key days to estimate shift.

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Sponsored Products is the most widely adopted Amazon search ad format, and typically accounts for more than six times as much ad spend as Sponsored Brands ads for the average Tinuiti (my employer) advertiser. As such, it’s incredibly important for advertisers to understand the full value that these ads drive.

Part of this is understanding the click-to-order period between when a user clicks on an ad and when that user ends up converting. Given how Amazon attributes orders and sales, it’s crucial that advertisers have an idea of how quickly users convert in order to value traffic effectively in real time.

Amazon attributes conversions and sales to the date of the last ad click

When assessing performance reports for Sponsored Products, advertisers should know that the orders and sales attributed to a particular day are those that are tied to an ad click that happened on that day. This is to say, the orders and sales reported are not just those that occurred on a particular day.

Advertisers viewing Sponsored Products conversions and sales in the UI are limited to only seeing those orders and sales attributed to the seven days following an ad click. However, marketers pulling performance through the API have greater flexibility and can choose different conversion windows from one to thirty days, which is how the data included in this post was assembled.

In the case of Sponsored Display and Sponsored Brands campaigns, performance can only be viewed using a 14-day conversion window, regardless of whether it is being viewed through the UI or through an API connection.

For marketers who wish to use a thirty-day conversion window in measuring Sponsored Products sales and conversions attributed to advertising, this means that it would take thirty days after the day in question in order to get a full picture of all conversions. Taking a look across Tinuiti advertisers, the first 24 hours after an ad click accounted for 77% of conversions and 78% of sales of all those that occurred within 30 days of the ad click in Q2 2020.

Unsurprisingly, the share of same-SKU conversions that happen in the first 24 hours is even higher, as shoppers are more likely to consider other products the further removed they become from an ad click.

For the average Amazon advertiser, we find that more than 20% of the value that might be attributed to ads happens more than one day after the ad click, meaning advertisers must bake the expected value of latent orders and sales into evaluating the most recent campaign performance. The math of what that latent value looks like varies from advertiser to advertiser.

Factors like price impact the length of consideration cycles

The time it takes for consumers to consider a purchase is naturally tied to the type of product being considered, and price is a huge factor. Taking a look at the share of 30-day conversions that occur more than one day after the click by the average order value (AOV) of the advertiser, this share goes up as AOV goes up. Advertisers with AOV over $50 saw 25% of orders occur more than 24 hours after the ad click in Q2 2020, whereas advertisers with AOV less than $50 saw 22% of orders occur more than 24 hours after the ad click.

Put simply, consumers usually take longer to consider pricier products before purchasing than they take to consider cheaper products, generally speaking. Other factors can also affect how long the average click-to-order cycle is for a particular advertiser.

In addition to latent order value varying by advertiser, there can also be meaningful swings in what latent order value looks like during seasonal shifts in consumer behavior, such as during the winter holiday season and around Prime Day.

Key shopping days speed up conversion process

The chart below depicts the daily share of all conversions attributed within seven days of an ad click that occurred during the first 24 hours. As you can see, one-day order share rose significantly on Black Friday and Cyber Monday as users launched into holiday shopping (and dropped in the days leading into Black Friday).

After these key days, one-day share returned to normal levels before rising in the weeks leading up to Christmas Day before peaking on December 21 at a level surpassing even what was observed on Cyber Monday. December 21 the last day many shoppers could feel confident in placing an order in time to receive it for the Christmas holiday, and it showed in how quickly the click-to-purchase path was for many advertisers.

Of course, Amazon created its own July version of Cyber Monday in the form of Prime Day, and we see a similar trend around one-day conversion share around the summer event as well.

This year’s Prime Day has been postponed, but reports indicate that the new event might take place in October.

As we head into Q4, advertisers should look at how the click-to-order window shifts throughout key times of the year in order to identify periods in which latent order value might meaningfully differ from the average.

Conclusion

Like any platform, advertisers are often interested in recent performance for Amazon Ads to understand how profitable specific days are. This is certainly important in determining shifts and situations in which budgets should be rearranged or optimization efforts undertaken, and that’s even more true now given how quickly performance and life are changing for many advertisers as well as the population at large.

However, in order to do so effectively, advertisers must take into consideration the lag that often occurs between ad click and conversion. Even for a platform widely regarded as the final stop for shoppers such as Amazon, more than 20% of 30-day conversions occur after the first 24 hours of the click, and this share can be much higher for advertisers that sell products with longer consideration cycles.

Further, advertisers should look to historic performance around key days like Cyber Monday and Prime Day to understand how these estimates might shift. Depending on product category, other holidays like Valentine’s Day or Mother’s Day might also cause shifts in latent order value.

Not all advertisers necessarily want to value all orders attributed to an ad over a month-long (or even week-long) attribution window equally, and particularly for products with very quick purchase cycles, it might make sense to use a shorter window. That said, many advertisers do find incremental value from orders that occur days or weeks removed from ad clicks, and putting thought into how these sales should be valued will help ensure your Amazon program is being optimized using the most meaningful performance metrics.

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How Google close variants brought broad match to every match type /how-google-close-variants-brought-broad-match-to-every-match-type-331035 Fri, 20 Mar 2020 12:00:00 +0000 /?p=331035 Most of us won’t weep about the death of broad match but we will miss the days of total match type control.

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The last couple of years have seen Google make sweeping changes to the definition of search queries which might be deemed close variants. In late 2018, Google announced that any query it deemed to have the same meaning as a keyword would now be considered an exact match close variant regardless of the actual words the query is comprised of. It then followed up on that update by expanding close variants for phrase match and broad match modifier keywords to also include same-meaning queries.

This has meant a meaningful shift in the control advertisers have over the relationship between the queries driving traffic to keywords, and over time broad match is fading in importance as close variants swallow up traffic.

Share of Google search ad traffic attributed as broad match down 50%

The chart below depicts the share of Google paid search clicks attributed to broad match in the match type column available in search term reports. This is the share of total clicks attributed to queries that had a broad match relationship with the keyword being targeted, regardless of the match type the keyword is set to.

As you can see, broad match share of non-brand clicks went from 28% in Q1 2016 all the way down to 14% in Q1 2020 so far. While shifts in advertiser strategy can certainly affect the share of traffic coming from a particular match type, the evidence suggests that the steady expansion to the definition of close variants is the more likely culprit.

Close variant share on the rise for both exact and phrase match

The chart below shows the close variant share of total exact match and phrase match traffic based on the relationship assigned between query and keyword in search term reports.

As you can see, close variant share went from 11% in the first quarter of 2016 to 40% in Q1 2020 so far. While close variant share of all phrase match clicks started at a much higher share of 38% in Q1 2016, this has also increased with the change rolled out in late 2019 and now stands at 55%.

All in all, Google’s updates seem to have significantly reduced the share of traffic that is considered broad match, pushing much of this traffic into close variants where keywords set to match types other than broad can now trigger ads for these terms.

As always, the problem with this has been the relevance of close variants to the keywords being matched. One way of measuring this is the relative conversion rate of close variants to that of true phrase and exact match.

In the case of exact match, close variants have a non-brand conversion rate between 10% and 20% lower than that of true exact for the median advertiser, though close variant and true exact conversion rates are nearly identical for brand keywords. For non-brand then, the inclusion of close variants in exact match traffic can reduce the efficiency of ad spend if poor-performing close variants aren’t weeded out via keyword negatives.

Conclusion

Paid search managers like control, and for years they had access to plenty of it in terms of keeping the search queries that triggered ads tight. Some advertisers chose to forego looser matches altogether by only launching exact match keywords.

But times have changed, and it’s now the case that essentially all match types can trigger ads for queries that might have once been considered broad matches. As such, the share of traffic that can only be triggered via broad match has declined.

There’s still a place for broad and broad match modified keywords to give advertisers a wider net to drag in showing ads for relevant queries which are either low volume or just haven’t been built out as exact match keywords yet. However, much of the traffic that was formerly assigned as broad match now falls under close variants.

In the big scheme of things, close variants are typically very relevant to the keywords they trigger. However, there are circumstances when the queries matched to keywords are clearly irrelevant, and for most advertisers close variants simply don’t convert at the same rate as true exact or phrase matches. Thus, the inclusion of close variants can result in less effective bid management.

Further, for advertisers operating under constrained budgets, they’d usually rather be able to spend all of it on the terms they’ve selected as opposed to being opted into additional auctions for variations which might require further effort to manage. Implementing scripts to automatically weed out close variants is one option to reduce workload, but does require additional effort that advertisers didn’t used to have to expend.

Most advertisers won’t weep for the death of broad match, the most commonly bemoaned match type among paid search managers because of the wider net it casts, which can sometimes lead to poor matches. But they do miss the days of total match type control, those wider nets now forced upon tighter match types which require extra care to manage.

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The importance of building brand awareness through Amazon advertising /the-importance-of-building-brand-awareness-through-amazon-advertising-328791 Thu, 06 Feb 2020 19:50:04 +0000 /?p=328791 Marketers should be looking at the brand-building potential across both display and search ads because Amazon is not just about direct response anymore.

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In the early goings of Amazon’s advertising platform, most advertisers looked to it as another source of ad inventory that should be focused on direct response. This is in large part due to Sponsored Products typically being the first format brands wade into, and that format produced a whopping 13% conversion rate for the median advertiser under Tinuiti (my employer) management in Q4 2019. As such, it’s safe to say that Amazon ads are certainly a strong avenue for driving orders and sales.

However, it’s no longer the case that Amazon advertisers are focused entirely on direct response goals, and marketers should be looking at the brand-building potential across both display and search ads in order to get the most out of the platform.

Amazon DSP advertisers increasingly focused on awareness and consideration

The Amazon Demand-side Platform (DSP) allows marketers to target display inventory both on and off Amazon. Across a sample of dozens of Amazon DSP advertisers, we found that the share of spend allocated to campaigns focused on building awareness and consideration grew from 26% in Q1 2019 to 60% in Q4.

As you can see from the chart above, advertisers began 2019 allocating nearly three quarters of all DSP spend to purchase-focused campaigns, but that share slipped to 40% by the end of the year. This increased willingness to invest in campaigns focused on more upper-funnel goals has enabled marketers to rapidly expand investment in the platform, and in Q4 ad spend grew 44% relative to Q3, the largest quarter-over-quarter growth of the year.

Investing in brand awareness campaigns also has the trickle-down effect of producing more customers that have not purchased from the brand previously or who are infrequent purchasers. Looking at new-to-brand metrics, which identify those customers which have not purchased from a brand on Amazon in the last twelve months, the share of total DSP purchases attributed as new to the brand advertising went from 71% in Q3 to 78% in Q4.

While some of this increase may be tied to seasonal shifts, it certainly makes logical sense that investing in campaigns aimed at building brand awareness would in turn spur on more new customers to purchase from a brand.

Much like any DSP, advertisers have the ability to choose different ad formats and dimensions to create different experiences. While advertisers generally use Dynamic Ecommerce Ads for use in purchase-focused campaigns, static banners give marketers the ability to inject brand and lifestyle images into the creative used for those campaigns that are more focused on building the brand.

Looking outside of the Amazon DSP, advertisers are also finding success in building brand awareness through the Sponsored Brands format.

Sponsored Brands new-to-brand share rises in Q4

New-to-brand metrics are also available for the Amazon Sponsored Brands ad format, which appears at the top of Amazon search results as well as additional placements rolled out in late 2018. Tinuiti advertisers saw the share of total Sponsored Brands conversions attributed as new-to-brand grow from 58% in Q3 to 60% in Q4.

Even more interesting is how new-to-brand share moved during the core weeks of the winter holiday shopping season between Thanksgiving and Christmas Day. During this roughly four-week period, daily new-to-brand conversion share averaged 64%, compared to the 60% figure observed for Q4 overall.

As such, it seems that customers are more willing to purchase from brands they haven’t bought from previously and/or those which they haven’t purchased from in at least a year during the holidays. This is an important consideration to keep in mind when allocating budget and placing bids throughout the crucial holiday shopping season.

As mentioned previously, these ads show at the top of search results as well as some other placements along the right rail, at the bottom of desktop results, and intermittently throughout mobile results. Taking a look at the share of conversions that placements at the top of search results account for, these slots produced 75% of all conversions in Q4 2019. Even more impressive, however, is that they produced 87% of all new-to-brand conversions.

Knowing this, brands looking to reach new customers should pay extra close attention to where their ads are showing on the page and adjust bids to ensure ads are reaching the competitive top of page placements.

Conclusion

What was once an opportunity that most advertisers used primarily for direct response, purchase-focused goals has quickly evolved over the last year. Marketers that are able to take advantage of the brand-building potential of both Amazon search and display formats and bake the expected value of these tactics into budget and bid planning will be able to maximize their output from Amazon advertising. Those that don’t will have a harder time competing moving forward.

Join us for two days packed with expert insights and tactics on all things digital commerce marketing — from Amazon to Google to Instagram and more — at SMX West in San Jose this month. Check out the agenda >>

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Paid search trends to watch for the 2019 holiday shopping season /paid-search-trends-to-watch-for-the-2019-holiday-shopping-season-325579 Fri, 22 Nov 2019 13:00:48 +0000 /?p=325579 Maps will play a larger role for retailers with physical stores and while Google Shopping will likely be the star, Amazon is poised to play the Grinch.

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The holidays are here! That means search marketers everywhere are putting the finishing touches on strategies to make the most out of the next few weeks, the most important stretch of sales for many businesses.

However, don’t go into the holiday shopping season without reading up on these key trends which might help wrap up your strategy a little bit tighter.

Google Shopping will likely be the star of retail

It should be absolutely no surprise to retailers that Google Shopping is incredibly important to paid search success, and I’ve written about its rise many times over the years. This continues to be the case today, as Google Shopping accounted for 48% of all Google search spend in Q3 2019 for Tinuiti (my employer) retail advertisers. Advertisers should once again prepare for Shopping to play a key role during the winter holidays this year.

However, this Q4 and the months that follow will be an important time for both Google and advertisers in determining just how long Google Shopping can continue its torrid pace of growth, as we’re beginning to lap some shifts that happened at the end of last year that significantly drove up Google Shopping traffic.

As you can see from the chart below, Google Shopping click growth jumped from 41% last Q3 to 49% in Q4, and while growth has remained strong since, there has been a steady deceleration.

As has long been the case, phones in particular are driving much of the Google Shopping growth, and in Q3 2019 clicks grew 36% on phones compared to 27% overall.

The leap last Q4 coincided with an explosion in Google Shopping impressions, as Google seemed to prioritize Google Shopping over text ads. The impression growth was most pronounced on phones, where impressions increased 127% Y/Y in Q4 compared to 81% in Q3.

Some of this increase can certainly be attributed to newer, growing Shopping variations such as Showcase Shopping Ads, which produce advertiser-specific listings for more general searches.

The queries that trigger these ads tend to be about 20% shorter in terms of character count than the queries triggering traditional Google Shopping listings. While character count is far from a decisive metric with regards to determining how general or focused a search is, it does indicate that Google is finding shorter queries which likely include less product-specific qualifiers that it’s now showing Showcase ads for.

However, the impressive Shopping growth that occurred at the end of 2018 wasn’t just a matter of Google finding additional spots to throw Showcase ads, as true traditional Shopping listings also saw an explosion in growth. Taken together, the evidence points to a significant expansion in the share of search queries producing Google Shopping results.

All of this is to say that it’s unclear if Google Shopping has another big push like the one we saw last Q4 in it, or if Google has more or less used up its powder with respect to expanding these ad units to the extent observed at the end of 2018. As such, advertisers shouldn’t be shocked if Shopping growth is slower during the holidays this year than last year.

Nor should we be surprised if Google once again finds a way to push growth back up as it has so many other times. After all, the surge last year was unexpected, and Google’s latest additions of image search and YouTube inventory as well as additional Showcase-eligible product categories may help in a potential rebound.

Regardless, a rather large player you might have heard of stands ready to steal some Shopping clicks from under the tree.

Amazon poised to play Grinch more so than in past years

Much like the importance of Google Shopping, it’s difficult for U.S. retailers to be unaware of the trillion-dollar website in the room – Amazon. Even still, many retailers might be surprised to know just how dominant the e-commerce giant has become in Shopping over the last year.

This is most apparent when looking at Amazon’s Shopping impression share in apparel through Auction Insights reports. As of last October, Amazon was only barely visible in Shopping results against apparel retailers in the U.S., but that has changed rapidly.

Amazon’s impression share is now more than double what apparel retailers saw last December and has held steady for the last three months. In addition to impression share gains over the last year in other categories such as home goods, furniture and electronics, all signs point to Amazon more fully flexing its might in Google Shopping this holiday season.

Of course, given Amazon’s choice to take a couple days off from Shopping during Prime Day, it’s probably unwise for anyone outside of its paid search team to espouse confident opinions on its likely Q4 strategy. But the foundation seems laid for a bigger holiday presence than ever before.

What’s a competitor to do? There’s not much in the way of Amazon-specific advice for competing in Shopping, as competing with Amazon looks a lot like competing with any Shopping advertiser.

Stay on top of the queries triggering ads and funnel traffic effectively using keyword negatives. Keep feeds up to date and out of trouble by responding quickly to any warnings from Google Merchant Center. Take advantage of Shopping variations like Showcase ads and Local Inventory Ads (for brick-and-mortar advertisers) to ensure ads are eligible to show in as many different types of relevant scenarios as possible.

On the last point, Local Inventory Ads (LIA) are a nice differentiator for retailers with physical stores, since Amazon can’t offer the same in-store options. However, Amazon’s impression share is just as strong against LIA campaigns as traditional Shopping for many brands, so don’t think it won’t be lurking for searches with local intent as well.

Speaking of local intent – it’s time for my favorite paid search trend of the year.

Searchers turn to Maps for the Turbo Man dash

When it’s down to the Christmas wire and shipping cutoffs have left the prospect of getting a gift delivered in time shaky, many shoppers are forced to physical stores to make sure Jamie gets the right action figure.

This is readily apparent when looking at the share of Google text ad clicks which are attributed to the “Get location details” (GLD) click type, which comes predominantly from Google Maps according to Google. The chart below shows daily share for one national apparel retailer from last holiday season, for which GLD clicks accounted for 14% of all text ad traffic on 12/23 – the biggest daily share observed between November and December. A close second was Christmas Eve, with 13%.

These figures can vary significantly by advertiser, but the general trend of GLD clicks spiking in the lead up to Christmas relative to other days of the year is very common among brands with a brick-and-mortar presence.

In terms of accounting for this, advertisers often look to results from last year to determine if they overspent or underinvested on particular days. If a brick-and-mortar brand were to only look at the online conversions attributed to ads in assessing the value of traffic on the last days leading up to Christmas, the picture may not provide a true representation of the value of that traffic given the huge offline intent on these days. This is true throughout the year for brands with physical stores, but made more glaring in situations like last-minute holiday shopping.

Given the way the calendar falls this year, last-minute shopping is likely to be hugely important.

Shortest holiday season since 2013 will make for a time crunch

The period between Thanksgiving and Christmas will be a full six days shorter this year than in 2018, and we haven’t had a Thanksgiving occur this late into November since 2013. As such, the race will be on for both consumers and brands alike.

History offers us a helpful test on the effects of a shorter holiday shopping period in the form of a 1939 decision by FDR to move the Thanksgiving holiday one week earlier at the request of retailers who hoped to drive more revenue from the holiday season. 23 states immediately adopted the new date (the third Thursday of November), while 23 others stuck to the original fourth Thursday of November. Two states chose to celebrate both.

After the holiday season, businesses reported that total consumer spending was similar across states that adopted the earlier date and those that stuck with the later date, indicating a longer period between the two holidays didn’t produce more spending. However, the distribution of sales revenue throughout the holiday season was different between the two, with the bulk of holiday shopping occurring in the last week before Christmas for states with the later date compared to evenly distributed throughout the holiday season for those celebrating the earlier date.

Using this as an indicator for how shopping might shake out this year (though there may have been one or two major developments in retail since 1939…), the shorter holiday season shouldn’t in and of itself reduce holiday-related sales for retailers. However, the last week ahead of Christmas might be especially important this year.

Most importantly, the U.S. settled on the fourth Thursday of November as Thanksgiving Day once and for all in 1941, meaning marketers will only have to deal with one Black Friday and Cyber Monday. And for that, I am thankful. Have a Happy Thanksgiving everyone.

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With loss of Yahoo and image search, Google Shopping search partner traffic nosedives /with-loss-of-yahoo-and-image-search-google-shopping-search-partner-traffic-nosedives-323121 Tue, 08 Oct 2019 17:21:18 +0000 /?p=323121 While it is a small fraction of Shopping traffic, the partner network can help advertisers currently excluding this traffic to grow moving forward, particularly in a competitive Q4 holiday season.

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Click traffic from the Google search partner network took two major blows in early 2019. The first was Yahoo’s move to begin showing only Microsoft Ads-powered sponsored listings following a more than three-year stint in which some of Yahoo’s listings were powered by Google. The second was Google’s update to bring ads featured in image search out from the partner network and into the core Google Search Network.

Here we evaluate a sample of long-standing Tinuiti (my employer) advertisers to assess the effects of these changes to the share of Google Shopping traffic coming from search partners, the relative value and cost of that traffic, and what it all means for advertisers.

Search partner click share falls dramatically across device types

As you can see from the chart below, search partner traffic once accounted for a significant share of Google Shopping clicks, and in August 2017 was at 16% for desktop. In August 2019, that figure was just 3%, with share on tablets and phones at 2% and 1%, respectively.

The timing of the dip seems a bit delayed from what we might have expected given the details of the two announcements ostensibly driving this trend.

In the case of Yahoo, it announced in January that it would only serve Microsoft Ads, but the change was said to have rolled out through March. For image search, Google announced that it would be integrated into the core Search Network in late March. As such, April would have presumably been when much of the decrease occurred.

However, our numbers show that traffic share really took the biggest month-to-month dip from June to July. It’s not entirely clear why there seems to have been a delay, but the decline is certainly what we expected in light of these two changes, and it’s possible Google’s change to image search took longer than expected to roll out. There may have also been other less publicized updates to the partner network affecting these trends.

Some advertisers choose not to allow Shopping ads to show on the search partner network, owing to the lack of controls available in terms of bidding and where ads are shown. However, our research shows that the Google Search Partner Network is usually an efficient way to extend the reach of Shopping campaigns.

Search partner clicks convert at a lower rate than core search, but cost less too

Looking at the conversion rate of search partner traffic relative to core search, partners clearly convert at a significantly lower rate.

In July and August, search partner conversion rate improved relative to core search across device types. This makes sense if the image search change really did take a few months to roll out, since the transition of image search clicks from the partner network to core search would likely put downward pressure on core search conversion rate.

Regardless, the disparity in conversion rate might be enough to send some advertisers running to Shopping campaign settings to shut down the partner network. However, looking at relative CPC, search partner traffic also consistently tracks well below core search in the price paid for clicks as well.

All told, the median advertiser saw no difference in the cost per conversion of search partners versus core search network in August 2019. As such, opting Shopping campaigns into the partner network garners incremental traffic without harming ROI for many advertisers.

Conclusion

These updates meaningfully reduced the importance of the partner network to Google Shopping campaigns, and it seems unlikely that we should ever expect partner click share to regain its former heights. There just aren’t many properties out there for Google to partner with that can produce the kind of click volume that Yahoo and Google image search provide.

Still, it remains the case that the partner network is typically a worthwhile investment for retailers looking to maximize the reach of their Google Shopping campaigns. While it may only be a small fraction of Shopping traffic, it can certainly help advertisers that are currently excluding this traffic to grow moving forward. Particularly in the competitive Q4 holiday season, it would be a shame for brands to leave this opportunity on the table.

Of course, Google didn’t actually lose image search ad traffic, and those impressions and clicks are now just a part of its core Search Network. Advertisers that were already targeting the Search Partner Network shouldn’t have seen much of a change to overall Shopping traffic as a result of this update specifically, though the change may have forced competitors that were formerly excluding partners into competing for these image search placements.

Yahoo’s move did give Microsoft Ads traffic a boost, and while Google will likely continue to account for the vast majority of paid search traffic in the U.S., Microsoft Ads is still a crucial part of reaching searchers who might not turn to Google with their queries.

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Search query reports show a huge increase in Google close variant traffic /search-query-reports-show-a-huge-increase-in-google-close-variant-traffic-322047 Tue, 17 Sep 2019 12:00:55 +0000 /?p=322047 Here's a look at research based on the past year and how advertisers should think about close variants moving forward.

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Google made its most sweeping change to the definition of close variants ever late last year when it announced that queries would now be considered exact match close variants if they were deemed by Google to have the same meaning as the keyword being bid on. While limitations in the past put hard constraints on the types of words that could constitute close variants, this change made it so that a query with any manner of relationship to the keyword could match in this way, so long as Google’s ad serving technology deemed it to have the same meaning.

As such, many marketers were rightfully concerned about potential harmful effects that this could have on performance. Here we dive into how close variant traffic has trended since the update was fully rolled out to English keywords last October, and how advertisers should think about it moving forward with a fresh close variant update now taking hold.

Close variants skyrocketed for both brand and non-brand keywords

Looking at the median share of exact match non-brand traffic coming from close variants in Google search query reports for a sample of long-standing Tinuiti (my employer) advertisers, close variant share clearly took off in Q4 of last year and has remained elevated ever since. Close variant click share went from 26% in Q3 2018 to 35% so far in Q3 2019.

This share is based on the match type assignment available in Google search query reports, which is populated based on the relationship of the query to the keyword triggered, rather than the match type a keyword is set to. As such, it gives a sense for how more traffic an advertiser with keywords set only to exact match might expect from close variants than if exact match were restricted to true exact matches.

The trend looks similar for brand keywords, where close variant share of exact match clicks went from 5% last Q3 to 8% this year.

The concern for marketers is that these close variants might not carry the same intent as true exact match queries, affecting their value and how much advertisers are willing to spend for the traffic. Looking at the relative conversion rate of close variants, such concern isn’t without merit.

Non-brand close variant conversion rate typically 10%-15% lower than true exact matches

For the median advertiser, close variant conversion rate is regularly at least 10% lower than that of true exact match for non-brand keywords. The additional close variant matches unleashed with the Google change last October do not appear to be meaningfully worse in terms of conversion rate relative to true exact match than previous close variant matches were, given relative conversion rate has been relatively steady since the update.

However, this comparison is heavily impacted by the efforts of our account managers, who are regularly weeding out any poor-performing queries through keyword negatives to reduce any negative effects of close variants on account performance. These efforts also slow the growth of close variant click share.

In Q3 2019, non-brand close variants are converting at a rate 13% lower than true exact matches for the median advertiser studied, but median non-brand close variant cost per click is 2% higher than that of true exact match. Naturally advertisers would like to bring the cost of close variant traffic in line with the relative value of that traffic, but Google’s changes have made it more difficult for advertisers to ensure the best possible bid is being placed for the queries now bundled into close variants.

Fortunately, brand close variant conversion rate is identical to true exact match conversion rate on average for the median advertiser over the last three years. This indicates that Google is usually very good at identifying close variants that do carry the same intent as brand searches.

However, that’s not the case for every advertiser. Brand close variants averaged a conversion rate 33% lower than that of true exact matches in the worst-case example of the advertisers studied, and some brand names are more susceptible to inappropriate matches through close variants.

Knowing this, someone might want to get Jason Fried to sit down before he checks Basecamp’s brand search query reports given the types of close variants I imagine might get pulled in to match for a term like ‘basecamp.’

Conclusion

Close variant performance can vary by advertiser, campaign, keyword and specific close variant match. While most advertisers see these matches convert at meaningfully lower rates than true exact matches for non-brand keywords, some actually see higher conversion rate from close variants looking at this comparison account-wide. However, there’s likely no account where close variants are so relevant and tightly related to all the keywords being triggered that advertisers should simply allow them to take their course.

As such, advertisers must continue to regularly evaluate search query reports to find close variants that should be weeded out via keyword negatives to minimize wasted spend from any inappropriate matches. Google reiterated as much in their most recent announcement that same-meaning close variants will now be applied to phrase match and broad match modifier keywords.

Taking a look at the share of phrase match traffic attributed to close variants, the share is already quite high compared to exact match, but had been trending lower over time.

It’s unclear to what extent the most recent change has been rolled out given Google’s stated timeline in its July announcement of “in the coming weeks,” but it’s likely we’ll see an uptick in phrase match close variant share in the quarter to come. I’ll certainly be keeping an eye on it as we head into the holiday season given how significant the increase in close variants was in the last Q4.

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Be smart, advertisers. Here’s how to approach rising Google brand CPC /be-smart-advertisers-heres-how-to-approach-rising-google-brand-cpc-317241 Mon, 20 May 2019 16:50:02 +0000 /?p=317241 While we are at the mercy of Google’s auction systems in determining CPC, we can install safeguards to ensure increases are controlled.

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Branded keywords, or keywords that include the name of the advertiser bidding on those keywords, have long been a source of controversy in the paid search industry. For years, many paid search managers grouped these keywords into reports that reflected total account performance.

This tends to overinflate the value of paid search campaigns since most brand queries are navigational and reflect a user that is already intent on buying from the brand searched for. As such, brand conversion rate is typically significantly higher than that of non-brand traffic and high brand return on ad spend (ROAS) can cover up underperforming non-brand campaigns.

These days, most advertisers are hip to the fact that they should be looking at brand and non-brand performance separately. However, there have been a lot of changes over time that might impact an advertiser’s brand keyword strategy, starting with a significant increase in the price of these keywords over the years.

The price of brand keywords ain’t what it used to be

Google has long given advertisers an advantage over competitors in bidding on their brand terms by way of quality score, which is generally very high for an advertiser bidding on its own terms and lower for competitors trying to show ads on those terms. This makes a lot of sense in terms of providing users with a quality experience since the query indicates that the user is probably most interested in going to the website for that particular brand and that Google should prioritize the brand’s listing as opposed to a competitor.

This quality score advantage plays a direct role in the price advertisers pay for brand keywords and has long suppressed average cost-per-click below what many advertisers might be willing to pay for brand traffic. However, that gap is becoming smaller over time.

Evaluating Merkle (my employer) advertiser data, average brand CPC rose more than 20% between Q4 2017 and Q3 2018 before final slowing over the last couple of quarters.

Google’s response to the increases that specific advertisers see typically references competitive forces encroaching on these auctions. That may well be true, but Google itself is responsible for the extent to which competitors can drive up brand CPC.

This goes back to the quality score advantage most advertisers have over competitors for their brand terms. Changes to advertisers’ relative quality score impact the ad ranks of those brands, which directly affects the CPC an advertiser must pay.

For example, say Google started giving competitors even worse quality scores for an advertiser’s brand keywords. If the advertiser were paying just enough to beat the ad rank of the closest competitor, this change should result in lower brand CPC, since competitors’ ad ranks would go down with worse quality score.

The opposite can certainly also happen, with Google giving competitors greater quality scores relative to an advertiser bidding on its brand terms. This would naturally increase an advertiser’s CPC.

Of course, Google’s response to unpalatable CPC increases is to call out the fact that advertisers have control over how much they pay for branded traffic.

Don’t like brand CPC? Just lower the bid of course!

Google is well within its rights to charge as much as it wants for brand clicks as long as advertisers are paying less than the max CPC assigned to those keywords. As such, shrinking the gap between the price paid for a keyword and the max CPC bid is one method of keeping CPC increases in a palatable range.

Advertisers that have already seen brand CPC go up significantly often combat the increase by testing out lower bids in a step-down approach to figure out how much traffic is lost at different levels. This can be useful in determining a bid that keeps the advertiser visible for as many brand searches as possible but also limits exposure to increases in CPC by reducing the gap between the bid and the average CPC.

However, the auction can change at any time with updates, either by competitors or Google, that throws a wrench into the conclusions reached from past test results, and a bid that gets an advertiser the vast majority of brand traffic today might not cut it tomorrow. Sometimes such increases can spawn from mistakes on Google’s end, but the search giant has become far less forgiving over time in making sure advertisers feel whole from such events.

Don’t ask for a refund

Back in 2016, brand CPC briefly spiked on phones before coming back down after an article of mine exposed the issue.

The increase was the result of an unintentional issue on Google’s end, and affected advertisers received a credit for the overspend from Google.

Fast-forward to 2019, and we recently saw a similar spike in brand CPC for some advertisers, attributed by Google to what it described as a ‘bug.’ CPC soon returned to normal, but there were no credits given out this go around, even for advertisers that saw dramatic increases in ad spend from the issue. Where keeping good relations with advertisers may have once led to a goodwill gesture to make good, Google now seems to favor the argument that as long as average CPC is below max CPC, spikes in spend are on the advertiser.

This transition in attitude only makes it more important for advertisers to control the gap between average CPC and bids to ensure there’s only so much wiggle room for a similar bug to ramp up costs since Google clearly won’t be saving anyone from itself. Setting logical budgets to cap brand spend based on campaign history and creating systems for intraday checks can also go a long way towards limiting the potential damage from surges in CPC.

I think it’s particularly true that advertisers need to be protective in these ways in light of Google’s recent decision to sunset average position.

Don’t let new metrics drive you to bid too much

Google announced in February that it would be eliminating the average position metric come this September. Instead of average position, it recommends that advertisers rely on impression and click share metrics in assessing how competitive a particular ad is in relevant auctions.

The announcement highlighted that average position is often a messy metric to use when assessing where an ad is falling on the page. However, as with most updates, it stands to reason that there might be some upside to Google in transitioning advertisers away from average position and towards metrics like absolute top impression share. This is particularly true for brand keywords, which are often judged based primarily on how well they take up the top possible placement in search results.

For example, some advertisers see a perfect average position of 1.0 for brand keywords but an absolute top impression share of just 75%. Once these brands no longer have average position to fly by, it’s possible that they’ll turn to bidding based on achieving as high an absolute top impression share as possible. Given 75% might not seem good enough, it’s quite possible this will lead to increased bids, which would, in turn, give Google more wiggle room in charging higher average CPC.

Knowing this, it might make sense for advertisers to assess brand traffic growth over time and make bid adjustments based on that. We find that Merkle advertisers typically see Y/Y click growth around 5%.

However, brand traffic growth is hugely dependent on efforts outside of paid search, such as print and television advertising. As such, it’s necessary to adjust expectations based on such efforts as well other big-picture factors such as shifts in overall market share and consumer demand for the specific offerings of an advertiser. This gets messy quickly but is at least one alternative data point to reference in assessing whether bids should get ramped up to maximize absolute top impression share.

Of course, none of this takes into account the role of organic listings in brand search.

Can I just not pay for brand listings? Maybe!

After years of debate, the answer to whether a brand can forego bidding on brand keywords altogether and still receive all the traffic from branded queries remains the same: it depends on the brand.

If the brand is big enough and the competition sparse enough that all or nearly all brand searchers end up making their way to the brand’s website without a paid ad, it should certainly consider turning off brand ads to save the money. However, most brands do see a dip in traffic and orders when turning off brand ads, and the only way to measure just how significant that dip might be is through testing – though again, changes to the SERP can render any past tests useless at a moment’s notice.

Advertisers’ appetite for bidding on brand keywords despite higher CPCs isn’t infinite, and there is a point at which brands should call it quits despite the potential for lost clicks and sales, though Google certainly doesn’t want to reach that point. While paid search marketers are somewhat at the mercy of Google’s auction systems in determining CPC, they can still take proactive steps to learn as much as possible about the incremental lift coming from brand ads and install safeguards to ensure increases in CPC are controlled.

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What the numbers tell us about the current voice search opportunity /what-the-numbers-tell-us-about-the-current-voice-search-opportunity-314810 Mon, 01 Apr 2019 18:19:32 +0000 /?p=314810 Since we can't segment voice from typed interactions in performance reports easily, it's helpful optimization for voice search overlaps with traditional search.

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Despite the rapid growth of voice and virtual assistant adoption, platforms like Google and Amazon have yet to provide businesses with the ability to segment voice interactions from typed interactions in performance reports. This makes it difficult to fully assess the role of voice search and virtual assistants at present, but there are some signals we can use to examine any changes in user behavior and the directional growth of voice interactions.

Since the early goings of voice search, a common belief has been that it would change the language used to interact with devices as searches would become more conversational. In reality, we’ve seen little change in the queries driving paid and organic impressions in many regards. Further, many recent reports indicate the commercial opportunity of voice interactions is still modest at present.

Queries haven’t changed much by some standards related to voice

In 2016  Microsoft research showed queries inputted by voice were typically longer than those inputted by text in terms of word count. As voice search grows, such research would indicate that the average length of queries would also grow.

However, looking at both the word count and character count of the queries triggering paid and organic Google results (using the paid and organic report) for longstanding Merkle advertisers predominantly in retail, we find little change over the last couple of years. This indicates that if voice interactions are growing in the share of paid and organic results they produce, these queries aren’t different enough in length from typed searches to impact average query length.

In support of this notion, Google data presented to agencies points to only small differences in query length between typed and spoken search.

The same article from Microsoft mentioned that searchers are more likely to include question words when using voice. However, looking at the share of queries triggering Google paid and organic results that include a question word, we’ve seen little change to indicate that voice search is increasing the number of queries framed as a question.

And yet, voice interactions are certainly growing, as myriad sources release data points on increased adoption (even if some of those data points are less than reliable). How can it be that the queries driving paid and organic search impressions aren’t changing in concert?

As mentioned, there may be so little difference in voice search compared to typed search in these regards that even if voice were to grow to account for most queries, we still wouldn’t see much movement in query length and question words. These differences could also change over time, given the early stage of voice interactions we find ourselves in, so that there aren’t consistent query attributes that are more likely to be voice search.

Additionally, the types of “searches” happening may not be very relevant for many types of businesses.

‘Voice’ is growing, ‘voice commerce’ less so

The term voice search is currently wielded very broadly, often used to indicate wide-ranging actions for everything from telling a device to call mom to plug in an address to navigational apps. Many of these actions that might be bundled as part of voice search would be more appropriately categorized as voice commands, in which the user isn’t searching for any information, service or product, but rather telling a device to do something.

As such, many data points on the growth of voice search reflect some interactions that wouldn’t be considered a search if they were completed by manual input using a keyboard or mouse. However, surveys are becoming more pointed in asking what types of queries voice searchers are using to assess better the commercial opportunity, which appears modest at present.

For example, a May 2018 shopper survey from RichRelevance showed that 70% of U.S. consumers have never used a voice assistant to search for a product, let alone purchase a product in this way

The Smart Audio Report from NPR and Edison showed that 16% of surveyed adults owned voice-activated smart speakers by the end of 2017, and that of those that did only 22% had purchased a new item using a speaker. This means that only about 4% of all those surveyed had purchased anything at all by smart speaker. This lines up with what internal Amazon sources told The Information in August 2018, pegging the share of Alexa users that have ordered something by voice at 2%.

Even estimates portrayed as bullish, such as OC&C Strategy Consultants prediction that voice shopping would grow to more than $40B by 2022, paint voice search as only a small slice of the total e-commerce pie. With $517B in e-commerce occurring in the U.S. alone in 2018, this prediction indicates that voice shopping is likely to account for less than 5% of e-commerce between the US and UK in 2022 given expected e-commerce growth rates.

Naturally, some product and service categories are more likely to be purchased by voice than others, so the opportunity is likely to be greater for some types of businesses than the estimated overall e-commerce share. However, even in the case of industries which might see a majority of purchases happening by voice shortly, it’s not clear at present that there are strategies specific to voice that brands should adopt to take advantage. Rather, it seems the best practices for voice search mostly overlap with existing best practices for search in general.

Clear eyes, full hearts, can’t lose

At this point optimizing for voice search looks a lot like lot optimizing for search in general. Marketers should be aware of what queries are growing in volume and cater to advertising and content strategies around that knowledge.

While the call-and-response nature of voice interactions has made it even more advantageous to be the number one organic result and Quick Answer, the advantage of such positioning extends beyond voice search. Optimizations made to get featured in prime locations for important queries are certainly valuable for voice, but don’t let voice search be the only determining factor in prioritizing such efforts.

That could certainly change quickly as Amazon and Google make potential updates to how results are served for these types of interactions, and certainly Google’s speakable schema markup is a step towards voice-specific optimizations. For now, however, the voice search opportunity appears modest and isn’t altogether unique in terms of how most marketers should approach it from an optimization standpoint.

With no clear reporting available, perhaps the biggest challenge regarding voice at present is quantifying the opportunity, and hyperbolic statistics showing incredible growth do little to show relative size vs. traditional search. In this sense, it’s good that optimization for voice search overlaps with that of traditional search since marketers have little to fly by in isolating for voice.

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