7 ways to use dynamic content and multiply your conversions

Ask marketers what their goals are, and one of the first things they will say is to deliver a more personalized experience to their customers. This isn’t a goal aimed solely at increasing conversions; it’s also about meeting customers’ growing expectations.

So, how can marketers meet the high demand for super-personalized communications? The answer lies in dynamic content.

In this free guide, see seven simple ways marketers can use dynamic content to connect with audiences in a more organic and personalized way.

Grab your copy to find out:

how top brands like Netflix and Amazon use dynamic content.the marketing automation features that enable you to deliver personalized experiences.ways to personalize your emails, landing pages, forms, pop-ups and more using dynamic content.

Visit Digital Marketing Depot to download “7 Easy Ways to Multiply Your Conversions.”

SearchCap: Google algorithmic update, SEO reviews & mobile apps

Below is what happened in search today, as reported on Search Engine Land and from other places across the web.

From Search Engine Land:

Google confirms mid-December search ranking algorithm update
Dec 20, 2017 by Michelle Robbins

As the update continues to roll out, early indications suggest disruptions in mobile SERPs, sites with no schema data & those relying on doorway pages being most impacted

7 ways to use dynamic content and multiply your conversions
Dec 20, 2017 by Digital Marketing Depot

Ask marketers what their goals are, and one of the first things they will say is to deliver a more personalized experience to their customers. This isn’t a goal aimed solely at increasing conversions; it’s also about meeting customers’ growing expectations. So, how can marketers meet the high demand for super-personalized communications? The answer lies […]

How independent reviews influence Google’s trust in your brand
Dec 20, 2017 by Pratik Dholakiya

Cultivating user reviews is an integral part of any search strategy, especially for local businesses. Columnist Pratik Dholakiya discusses the impact of reviews and provides tips for where to focus your efforts.

The upcoming mobile app Monday: Be prepared
Dec 20, 2017 by Bobby Lyons

Christmas Day and the day after are two of the biggest mobile download days of the year, and columnist Bobby Lyons shares some app store optimization (ASO) tips to help your app get found.

Search News From Around The Web:

Google Assistant on tablets is full width and unfortunately portrait only [Gallery], 9to5GoogleGoogle Maps’s Moat, Justin ObeirneGoogle’s SEO Starter Guide Downplays Speed & Security?, Search Engine RoundtableGoogle’s snippets and the length of your meta description, YoastHow To Select Prized Search Terms With Zippy Conversions, Ignite VisibilityTips for newsrooms to tell the local story when it matters most, Google Blog

Data bug with Google Search Console's Search Analytics report

Google has posted about a data anomalies bug with the Search Analytics report found in the Google Search Console. The specific issue shows up when you use the “AMP non-rich results” search appearance filter and look at the clicks and impressions between December 14, 2017, and December 18, 2017.

Google said there “was an error in counting AMP non-rich results impressions and clicks” between those dates and you “might see a drop in your data during this period.” It did not impact the actual search results; it was just an analytics bug.

Here is what the report might look like for you:

The data should return to normal on or after December 19, 2017, but those few days will have some inaccurate data.

Google launches new Rich Results testing tool with some rebranding

Google has announced it has launched a new version of a structured data testing tool for rich results at https://search.google.com/test/rich-results.

The company also said it will be calling rich snippets, rich cards or enriched results “Rich results” from now on and group them all together.

Google said the new testing tool “focuses on the structured data types that are eligible to be shown as rich results.” This new version enables you to test all data sources on your pages, including the recommended JSON-LD, Microdata or RDFa. Google said this new version is a “more accurate reflection of the page’s appearance on Search and includes improved handling for Structured Data found on dynamically loaded content.”

The tool currently only supports tests for Recipes, Jobs, Movies and Courses. Google said it will be adding support for other rich results over time.

Here is a screen shot of the tool. Note it works on desktop or mobile:

You can check out the new rich results testing tool over here.

PPC 2017: Epic review of the biggest trends & updates in paid search

As 2017 draws to a close, let’s take a moment to catch our breaths and look back at the whirlwind that was PPC in 2017.

There wasn’t a big change that dominated the landscape like enhanced campaigns of 2013 or expanded text ads of 2016, but multiple trends created an atmosphere of constant, incremental change this year. However, if we were to dub 2017 the year of something in search marketing, it would clearly be the year of the machine. While machine learning and other forms of artificial intelligence aren’t new to search marketing, their use became pervasive in 2017.

Here’s a look back at the big developments and key trends that happened in PPC in 2017 that will continue to inform and influence our work in 2018.

Finally past the year of mobile, this was the year of AI in search

Sure, there is still work to do in improving mobile experiences and conversion rates, and we’ll continue to see Google, in particular, push its initiatives in this area: AMP for ads and landing pages, Purchases on Google and more. This year, the big shift was the extent to which machine learning and other forms of artificial intelligence permeated all things search.

Here are eight highlights of ways the search engines ingrained machine learning into their products. They cover everything from keyword matching to ads to audiences to spend pacing to attribution:

In March, Google made putty of the meaning of ‘exact’ in exact match, stretching it to include close variants of a keyword with different word order and/or function words.Ad rank thresholds got a machine learning infusion to take the context of a query into consideration when setting the bid floor.Google’s Smart display campaigns are nearly entirely powered by machine learning.Google’s data-driven attribution methodology is entirely AI-powered. It’s been in AdWords for more than a year, but it gained new attention with the introduction to Google Attribution.Google and Bing released new automated bid strategies: Bing’s Maximize Clicks and Google’s Maximize Conversions.Google’s move to let daily spend exceed up to 2x the budget? Yep, that, too, relies on machine learning to try to predict spend trends throughout the month.One flavor of Google’s custom intent audiences on the GDN uses machine learning to automatically create audiences based in part on inferred characteristics of an advertiser’s target customers.Bing Ads is testing AI-powered chatbot extensions in search ads.Dynamic Search Ads in Bing Ads came to the US and the UK.

Forget A/B testing, because machine learning

Another big, if more subtle, shift was in ad testing methodology. All year, Google has pushed advertisers to move away from the A/B testing model of running two ads per ad group and manually assessing performance.

If there was any doubt Google was serious about this, the move to limit ad rotation options in August put that doubt to rest. The change makes the push for advertisers to choose “optimize,” letting the machines choose the best ad to serve, that much more forceful. Google’s Matt Lawson laid out in a column last month the argument for having at least three ads in an ad group: Overall impressions will increase as Google’s algorithms will serve up the best ad based on the specific query. Advertisers shouldn’t even be evaluating individual ad performance under this new rubric, but rather at the ad-group level of performance, says Google.

To this end, Google rebooted its Ads Added by AdWords pilot in September. The ads suggestions test automatically generates additional text ads (for approval) in some ad groups. Again, the goal is to get more advertisers running more ads in their ad groups, even if Google has to do the work for them.

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Identity & audience targeting

Dovetailing with the rise of machine learning is the steady advance in audience targeting capabilities. Keyword intent may still be the calling card of search marketing, but audience targeting options continued to expand. The popularity of Facebook’s audience-focused, people-based marketing approach largely precipitated this shift over the years as Google has loosened the reigns on its user data and shifted to signed-in data for audience development and targeting.

Some of the big moves in audience targeting this year:

Bing Ads began testing in-market and custom audiences at the beginning of the year. In September, it announced there are now more than 70 in-market audiences available to target.Google introduced in-market audiences and similar audiences to Search and Shopping campaigns in March, and consumer pattern targeting and life events targeting for YouTube and Gmail in May.Google’s custom intent audiences debuted in November for display campaigns.More offline data can now be used for first-party audience targeting as well. Earlier this month, Google expanded its Customer Match offering to include the ability to build retargeting lists based on customer phone numbers and addresses, not just email addresses.Microsoft has begun integrating the LinkedIn Graph with the Microsoft Audience Intelligence Graph. We should expect audience targeting to come out of this effort in 2018.

Attribution & 0nline-offline tracking

With more channels, more devices, more campaigns and more technology in play, attribution isn’t getting any easier.  The biggest news on this front was, of course, the beta launch of Google Attribution. Announced in May, the product could upend the way many search marketers approach attribution, but the real impact won’t be seen until next year when the product rolls out more fully. Google Attribution aims to give users a bigger picture of how their channels and campaigns — at all stages of the funnel — are contributing to the bottom line.

The Google beauty of it is that the data can automatically feed back into AdWords or DoubleClick to inform bidding strategies. That’s the real motivation here; it’s not going to be the silver-bullet answer to everyone’s attribution challenges. From a Google campaign perspective, it will provide more cross-channel insights than AdWords or Google Analytics does currently.

The other big news in attribution this year largely revolved around online-to-offline conversions.

Google’s in-store sales measurement news was the most notable. In one approach, retailers can upload their loyalty or other customer email lists into AdWords. The other approach is powered by Google partnerships with financial vendors. In-store sales conversions will automatically show up in AdWords when enough conversion data is available. Google has said its vendor-supported program gives it coverage of 70 percent of credit card transactions in the US.Google’s store visits measurement extended to YouTube campaigns as of May, giving retailers insights into how effective their videos are at driving viewers to stores.Bing’s support for uploading offline CRM conversion data with a new Offline Conversion Import tool in September.Bing’s integrations with call-tracking systems to enable call conversion imports rolled out this month.

Shopping keeps growing

Across the pond, Google got slapped with a giant antitrust fine by the EU for shutting competing comparison shopping engines (CSEs) out of Google Shopping. Google is contesting the fine, but in the meantime, Google Shopping is operating as a separate business unit and will compete in auctions against other CSEs for spots in the Shopping carousel in Google search results in the EU. (Crealytics’ Andreas Reifen and I each took issue with the ruling.)

Stateside, the influence of Shopping on retail search just continued to grow. At the year’s halfway mark, Merkle reported Google and Bing saw continued growth in shopping ad spend, outpacing that of text ads among retail clients. But there’s an elephant in the room, and its name is Amazon. Amazon loomed in terms of being a head-on competitor with its one-again-off-again presence in Google Shopping, in terms of the rapid and expanding build-out of ad offerings for merchants on its own site, as well as in the realm of product discovery and ordering via digital assistant.

For its part, Google continues to experiment with the way it displays shopping ads. Below is an example of an elusive Purchases on Google ad, but these ads also have a new “Quick view” feature that lets users learn more about the product and seller right from the search results.

Google continues to search for new places to extend Shopping ad inventory. At the end of May, it automatically opted advertisers into a test to show product ads on the Display Network.

Local, driven by mobile

Mobile, voice and digital assistants will continue to spur innovation next year, but perhaps in no area greater than local. Last year, Google said local searches are growing 50 percent faster than mobile search overall and account for one-third of mobile searches. Those habits are driving the development of search ad products aimed at connecting users to local businesses (thus the increase in online-to-offline attribution capabilities covered above). Merkle’s Andy Taylor covered the growing importance of local ad products for brick-and-mortar stores in his recent column.

Though not ad-related, Bing launched bots for local businesses in Bing Places in May that also work with Facebook Messenger and Cortana.Google rebranded and expanded its ad products for local service providers. Local Services by Google will be in 30 cities as of year-end.Google teamed with HomeAdvisor and Porch to offer local services discovery and lead generation through Google Assistant and Google Home.Location extensions and store visits measurement extended to YouTube in October.Text ads and Local inventory ads (LIA) began showing in local knowledge panels in Google search results.

Local inventory ads began showing in local knowledge panels in August.

Honorable mentions

We can’t close out a 2017 wrap-up without mentioning the new AdWords interface. There is a lot of grumbling about the new UI, which is expected to become the de facto interface at some point in 2018. Change isn’t easy, and there still isn’t enough parity or ease of use to have endeared it to many paid search managers who are in it on a daily basis managing campaigns. But every sign indicates Google is leaning into this new “experience,” not backing away. There are many, many features now that are only available in the new UI. That will only continue.

In further evidence that 2017 was one long year, some updates that feel much older than they actually are. Can you believe Google switched to the green outline Ad Label this year (February)? All Mac users got access to Bing Ads Editor in March. Google added historical Quality Score data in AdWords in May. Oh, and AdWords price extensions rolled out to all devices in March, and Bing merchant promotions in Shopping ads came out of pilot in the US in April.

That does it for 2017. After I wrote this piece, I looked back at how I concluded 2016’s year-end wrap-up: “Expect to see the trends we saw this year — audiences; attribution, including online-to-offline; mobile; and automation — continuing to influence change in the year ahead.”

Looking at that list of trends in terms of next year, I’d swap out mobile for local (mobile is foundational now) and add voice marketing to the mix. We are still in very early days with voice and digital assistants in terms of marketing potential, but I expect we’ll continue to see this area develop rapidly.

What you learn from talking with Google’s largest advertisers all day, every day

There’s a position at Google called “Chief Search Evangelist.” It’s evolved in the years since Fred Vallaeys filled that role, now focusing on meeting with our advertisers in person when they come to visit Google on-site. I think my job is pretty cool, but I must admit that the idea of talking search ads day-in, day-out with people at the cutting edge of their craft makes me more than a bit jealous. Nicolas Darveau-Garneau, who currently fills the role of Chief Search Evangelist, is the man whose job turns me a light shade of green with professional envy.

I learn so much every time I talk with Nick, so I thought it would be fun to sit him down and pick his brain about all of those meetings he gets to have. Here’s an edited transcript of the wide-ranging conversation we had recently about automation, growth, keywords and more.

Nicolas Darveau-Garneau, Chief Search Evangelist at Google

Lawson: What are the biggest trends that you’ve noticed when talking with top AdWords marketers?

Nick Darveau-Garneau (NDG): The best in the business have really figured out how to use automation and machine learning. Managing a search campaign should be partially automated these days, and there’s so much value you can unlock when you’re strategic about using automation. I’ve seen the most success here when people have a clear strategy, focusing on user experience and personalized marketing. Then they leave a lot of the detailed stuff to automation.

I consider this setup to be “semi-automated marketing.” Set the right KPIs, then let the machines do most of the work. You don’t need to worry about the results of individual tactics or specific keywords anymore. In fact, I see automated tools like Dynamic Search Campaigns and Smart Bidding largely outperforming manual optimizations.


Lawson: Semi-automated marketing. I like that. What does that look like in practice?

NDG: A lot of it is straightforward work that I already imagine people are doing. Smart Bidding (Target CPA and Target ROAS, in particular), Data-Driven Attribution, Dynamic Search Ads. And they work well together, so use them all.

I’ve also seen plenty of companies have success by buying into automation with their ads. The faster people realize that ad testing is a thing of the past, the better off they’ll be. Optimize your ad rotation, enable as many extensions as you can, and add a bunch of ads to your ad groups. Using optimized rotation uses the most appealing ad at the time of each auction, for each individual customer. I know you wrote about this recently on Search Engine Land, so just add that link and tell people to read it.

Bottom line: Use the entire search machine learning stack together.


Lawson: One of the more controversial things I’ve heard you talk about before is keyword selection. What’s your preferred method?

NDG: I don’t think my opinion should even be considered controversial. Once you believe in machine learning like I do, I think it’s easy to believe in this. And it’s simple, really: Buy all the relevant keywords.


Lawson: All of them?

NDG: Yep. All of them. Look, there’s no need to carefully select our keywords anymore. The machine will automatically figure out which of those work for us. I mean, when you’re using Smart Bidding, you’re already setting bids on a query-by-query basis. If that query sees OK performance, the algorithm will set OK bids. If that query works great, you’ll set very competitive bids. And if one query doesn’t work that often, the bids will be set accordingly. That even includes cases where your bids are so low as to effectively pause that keyword. If things change, think [about] your conversion rates or even the competition on that keyword/query, then you’re eligible to try out that auction again.

Some advertisers are also being more aggressive and use a lot more broad match because Smart Bidding sets bids at the query level, not the ad group level.


Lawson: And Smart Bidding isn’t the only tool to use with your keywords. You’re a big believer in audience targeting, too, right?

NDG: Oh, absolutely. It works really well. You want to power all of that bidding with your most important audience signals. Smart Bidding considers your audience lists, so feed those lists into your campaigns. You can stop worrying about bid modifiers, as Smart Bidding looks at audience along with a ton of other stuff. Just like ad testing is outdated, audience bid adjustments are irrelevant if you’re using Smart Bidding.


Lawson: There’s that semi-automated marketing again. As people get used to handing some control over to the machine, what are the things they should pay special attention to?

NDG: I mentioned the strategic stuff like customer experience already, and that’s incredibly important. Really focus on improving the customer experience. The most successful advertisers have high conversion rates relative to their competitors. Stay ahead of the pack by using tools like AMP for AdWords, parallel tracking, one-click signup and one-click buy. The better your conversion rate, the higher your ceiling as a marketer.

Something else I think is important is KPIs. One of the key issues that differentiates top advertisers is the KPIs they select. It’s almost like an evolutionary scale. You might start with doing what you can on a fixed budget, then you graduate to a CPA target, then you evolve to a sales ROAS and eventually a profit-margin ROAS. And the ideal final state is cash flow based on lifetime value.

Once you’ve got the right KPIs in place, and once you’re measuring those KPIs effectively, there’s really no limit to what you can do.


Lawson: You mentioned measuring KPIs effectively. What does that look like?

NDG: It’s about data. The best way to improve your account is to understand its performance as fully as possible, so share data with your agencies and platforms as much as possible. Smart Bidding gets better as it understands the value and life cycle of your conversions as completely as possible.

Many advertisers start with simple conversion data, and from there they evolve to revenue-based conversions. And that’s true even if you’re selling something with a long sales cycle. The next level up involves sharing your margin-per-conversion. Revenue is great, but revenue doesn’t consider your bottom line. You want to be as profitable as possible, which is why I love when advertisers talk to us about margin. Finally, the cream of the measurement crop has started forecasting lifetime value of their customers. With those forecasts, they can optimize toward profitability farther out in the future than that one short-term sale.


Lawson: I know you’ve talked about profitability with customers a whole lot in the past. What’s the focus of those conversations?

NDG: It’s growth. Focus on growth. Don’t obsess over a low CPA or a high ROAS. Look at your business as a whole and see if you’re more profitable today than you were yesterday. Think of it this way: You can get 10 conversions at a $10 CPA, or you can get 15 conversions at a $20 CPA. You might be making more money at the higher CPA. Can we add a chart to this interview? Is that possible? (Note: here’s a re-creation of what NDG drew on the board.)

CPAConversionsMarketing CostMargin (@$50/conv.)ProfitCPA goal$1010$100$500$400Profit goal$2015$300$750$450

This is a super simple example, but for me, I take the second option every time. It’s only $50 more profit. But if you’re not willing to take that $50, you need to change your approach. Because once you get that extra $50, you’ll get into the mentality of how to get the next $50. And the next and the next.


Lawson: That makes sense, but not every conversion is worth the same.  How do you think about that?

NDG: That’s when forecasting LTV (lifetime value) comes into play.  Companies who can forecast the LTV of each customer they acquire at or near the time of acquisition significantly outperform their peers. Imagine being able to forecast the three-to-five-year cash flow of every new customer you acquire with good accuracy and setting your marketing KPI for customer acquisition as a percentage of that profitability. You’ll be investing something like $100 to acquire a customer worth $1,000 and $300 for a customer worth $3,000. By bidding higher for better customers, these advertisers get a much higher percentage of these top customers.


Lawson: I know you’ve got to take off to a summit. Any parting words for anybody who reads this?

NDG: Relax. Once you get comfortable navigating the world of semi-automation, you have to resist the temptation to micromanage. Hundreds or even thousands of small decisions were just removed from your plate, so you now have more time to think about the big, important items. Strategy, user experience, how to focus on being a marketer.

Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.

SearchCap: Rich results testing tool, Google AdWords images & Search Console bug

Below is what happened in search today, as reported on Search Engine Land and from other places across the web.

From Search Engine Land:

Google launches new Rich Results testing tool with some rebranding
Dec 19, 2017 by Barry Schwartz

In addition to the new testing tool, Google is grouping all the names for these types of search results into the name “Rich Results.”

Data bug with Google Search Console’s Search Analytics report
Dec 19, 2017 by Barry Schwartz

The AMP filter, specifically for AMP non-rich results impressions and clicks, may show incorrect data for your site.

Google is testing images in search text ads
Dec 18, 2017 by Ginny Marvin

The test was spotted on mobile over the weekend.

What you learn from talking with Google’s largest advertisers all day, every day
Dec 19, 2017 by Matt Lawson

The world’s largest advertisers routinely visit the Google campus to talk strategy. Columnist Matt Lawson sits down with Google’s Chief Search Evangelist for some top insights from those meetings.

PPC 2017: Epic review of the biggest trends & updates in paid search
Dec 19, 2017 by Ginny Marvin

This year, artificial intelligence and machine learning underpinned nearly every paid search update.

Search News From Around The Web:

Your Guide to Getting Organized for PPC Success, PPC Hero#NoHacked 3.0: Fixing common hack cases, Official Google Webmaster Central BlogGoogle Makes 14 Changes to the Review Guidelines, Sterling Sky IncEU; Google’s Record Fine of $2.8 Billion Was a `Deterrent’, Ad AgeFull Guide To Using Google Search Console (2018 Edition), ignitevisibility.comGoogle Explains Trailing Slashes & How It Impacts SEO, Search Engine RoundtableGoogle User Satisfaction Score: Does It Exist (Gary Illyes Pubcon 2017), Stone TempleHow Long Should Your Meta Description Be? (2018 Edition), MozSEO Basics: How to Grow Traffic When You Know Nothing About SEO, ahrefs.com

3 inconsistencies in Yelp’s review solicitation crackdown

Last month, Yelp doubled down on its war on review solicitation. Yelp has long given mixed signals about whether you can ask customers for reviews on their platform, but they seem to now be unifying their message against review solicitation.

In November, they began sending messages like this to businesses and agencies:

Disclosure: We (Go Fish Digital) received the email above. However, they must not have really done a lot of research to compile this list, as we do help clients with reputation management, but we do not solicit Yelp reviews on their behalf. We don’t do any review solicitation.

This new crackdown is a little disturbing, and in many ways, quite misleading. Here are three ways in which I view this all as quite hypocritical.

1. They LITERALLY told us review solicitation was OK

I once emailed Yelp support and asked them directly if review solicitation was OK. The wording on their website was ambiguous, so I wanted a clear answer to the question.

I had just returned a rental car, and the rental car company (a household name brand) sent me an email asking for a review on Yelp. I screen-shotted the text of the email and sent it to support asking if this was acceptable. Below is a screen shot of their response, which I wrote about this last year in my post, “5 Yelp Facts Business Owners Should Know (But Most Don’t).”

You can see in the response that they discouraged it, but it wasn’t against their rules. But now, Yelp is saying that they’ll suppress you in their search results, and potentially add a consumer warning if they find you are systematically asking for reviews.

Interesting change of position, eh?

2.  They apparently speak for the whole internet

Much (but not all) of the communication talks about prohibiting requesting reviews from customers. And they aren’t just saying, “Don’t request Yelp reviews.” They are saying, “Don’t request reviews, period.”

From their site:

Asking for reviews at all, even if the business breaks norms and attempts to ask more than just their happy customers, can create a bias away from organically motivated reviews. And when some businesses ask for reviews and others don’t, it becomes difficult for users to compare reviews across businesses. Not only does solicitation lead to bias, it’s a bad experience for customers, too.

If there were only one review site in all of the land, I could see how a blanket declaration against review solicitation would be OK. But I think we could all rattle off at least five or 10 more review sites that exist besides Yelp. And most of them have not taken a hard stand against asking customers for reviews.

As a small business owner, I’d be very frustrated. Yelp is basically telling you how to run your business. In reality, reviews are just the “word of mouth” for the internet. Can you imagine an authority figure saying, “You can’t ask customers to tell their friends about your small business. You might bias the word of mouth.” It sounds ridiculous because it is.

3.  They misinterpreted (or misrepresented?) a study about reviews to justify their crackdown

Hat tip to my Go Fish Digital co-founder, Dan Hinckley, for catching Yelp red-handed with this one.

On July 31, 2017, Vince Sollitto, the senior vice president of corporate communications and public affairs at Yelp, published a post on the Yelp blog titled, “Why Yelp Doesn’t Condone Review Solicitation.” It is a short post that includes this:

Part of what makes content high quality is a lack of bias. That’s why Yelp’s automated software does not recommend reviews it believes to have been solicited by businesses, since solicitation leads to bias.

That “leads to bias” phrase links to a research study by researchers at Northwestern University on review solicitation, “Understanding and Overcoming Biases in Customer Reviews,” and it appears that Yelp is using this study to justify its position.

But here’s the thing: While the study did indeed find that solicited reviews tend to be higher than those of “self-motivated web reviewers,” the researchers actually concluded that this is because the latter group is biased. The study highlights that, over time, there is a naturally occurring negative bias if reviews are not solicited. (The study notes that their data supports the findings of two other studies on reviews that show the same thing.)

In other words, if a business doesn’t solicit reviews, their rating will trend downwards — even if they “provide great customer service to anyone that walks in the door,” as Yelp recommends. Existing reviews bias users toward what they should write in their own review; so, if you start with a couple bad reviews, improving your customer service may not ever be enough to improve your star rating. The study found that “even the decision of a user to submit a review can be influenced by the current state of the reviews.”

On the flip side, the study found that reviews solicited over email do not have the same negative bias that occurs over time when reviews are left to be posted naturally. The average star rating of reviews solicited via email remained consistent over time. They say:

The plot suggests that email reviews are stable over time (i.e., the 20th email review for a product is, on average, equal to the 1st email review for that product), while web reviews display a downward temporal trend.

In the study’s conclusion, it literally says businesses should solicit reviews, as it will lead to a larger, more representative population of reviewers:

Furthermore, the introduction of email prompts does not disturb in any way the existing reviewing population while it incentivizes an entirely new segment of the population to submit a review. We think that this finding should provide motivation to retailers to send email prompts to their verified buyers. The reviews overall will become more representative (since a larger segment of the population will be reviewing), more credible (since the new segment of the population that starts reviewing are all verified buyers) and the ratings overall will increase (since the email ratings are on average higher than web ratings).

A swing and a miss

Yelp has a long list of things not to do, but I think the main one they actually care about is, “Don’t run surveys that ask for reviews from customers reporting positive experiences.”

This is a common practice, and I think this is what they are trying to avoid. But instead of just pinpointing this, they are throwing the baby out with the bathwater by discouraging all review solicitation. This is in contrast to the study they cited, which literally says review solicitation brings about a more accurate rating.

Why does this matter?

Look, I rely on Yelp as a consumer, and we help brands navigate its confusing web of rules, filters and users. I actually like the product and think that it does a lot of things well.

However, I think Yelp really falls short in how they deal with businesses — from aggressive salespeople using high-pressure sales techniques to confusing and contradictory communication. After all, their revenue comes from these businesses’ advertising dollars, so you’d think they’d place a high priority on each touch point with their paying customers.

Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.

Supercharge your email marketing with Google AdWords

I have a confession to make.

The odds of my instantly deleting one of the many marketing emails I receive each day are about as good as Tom Brady and the Patriots making the playoffs — meaning it’s pretty likely to happen.

Unfortunately for all you email marketers out there, I’m not alone. According to email marketing service MailChimp, the average email open rate across industries is below 25 percent, with a click rate of 2 to 3 percent. That means that, on average, you’d need to send 100 emails to get two or three people to take any action. All that time and energy spent crafting the perfect email marketing campaign will be wasted if you don’t create a complementary strategy to get more sales from your hard-earned email list.

The good news is that you can use Google AdWords as your complementary strategy by simply leveraging the existing data you have on your email subscribers. Let’s dive into the best ways to make that happen.

Learn the ins and outs of Customer Match in AdWords

Customer Match in AdWords might be the greatest secret weapon for email marketers that Google has to offer. It allows you to target or exclude your existing customers on Google Search, Display and YouTube by simply uploading your customer email list to AdWords. Think of it as another way to nurture your sales leads besides sending them more emails.

The best thing about Customer Match is that it’s not that difficult to get up and running. Here’s what you need to do to get started:

Click on the “Wrench” icon in the top right corner of your AdWords Dashboard.Click on “Audience Manager” under the Shared Library section.Click on “Audience Lists” from the Page Menu on the left.Click on the blue “+” button to create a new audience list.Select “Customer List.”Choose the option to upload a plain text data file or a hashed data file.Choose your new file.Check the box that says “This data was collected and is being shared with Google in compliance with Google’s policies.”Set a membership duration (this should be determined by the types of customers that make up the list).Click “Upload and Create List.”

Please note that these instructions are for the “new” version of the AdWords dashboard. If you’re interested in Customer Match but are still using the “old” version of the AdWords dashboard, see here for more instructions.

Segment your email list

Now that you have a better understanding of Customer Match, let’s take a look at how you might want to slice and dice your email list to more effectively target your sales leads on AdWords.

Take a look at the following email audience segments we use at AdHawk (my company) for a moment:

New and engaged email subscribers who have not become customers.Email subscribers who have not opened an email recently.Email subscribers who are existing customers and would be a good fit for an upgraded product or service.

Each of these email audience segments has an entirely different relationship with our business and needs to be messaged to differently. If you have a similar breakdown of your marketing emails, you can repurpose your email list segmentation for your AdWords campaigns via Customer Match. This will allow you to tailor the messaging of your ads for each segment, and as a result, help to nudge your sales leads farther down your funnel.

Create a different AdWords strategy for each segment of your email list

Once you have your email audience segments in place, it’s time to develop a unique AdWords strategy for each segment.

I’m going to use the three email audience segments noted above as examples. Your approach might be different, and that’s okay. Just make sure you’re not using general ads for every email audience segment you have on your list.

Converting new and engaged email subscribers

When a new lead signs up to learn more about AdHawk, our team goes into “educate” mode. The goal is to get them to see the value of our product and services as quickly as possible so we can move them down the funnel.

Our “Welcome” email flow takes the first steps in educating our leads, and it performs pretty well compared to the industry average. But our secret weapon emerges when we take a list of our “new” sales leads and turn it into a Customer Match campaign in AdWords.

Here’s what a typical flow for this segment looks at AdHawk:

Step 1: Potential customer signs up to learn more about AdHawk.Step 2: After signing up, the potential customer receives the first email in the “Welcome” email flow, with a call to action to book a time with our sales team.Step 3: A Customer Match segment is created for all “new” prospective customers that didn’t take action on the first email in the “Welcome” email flow.

By using a Customer Match segment for all new and engaged AdHawk sales leads, we’re able to bid up on more generic keywords that would be too risky to bid up on for a general search campaign. We’re also able to create Gmail Ads with a similar look and feel to our “Welcome” emails series that prompt a strong customer recall.

Converting unengaged email subscribers

Converting unengaged email subscribers can be a huge pain in the butt. They’ve stopped engaging with your emails, so the worst thing you could do is continue to bash them over the head with more emails.

Here’s the flow we use to re-engage leads that have left us hanging:

Step 1: Potential customer signs up to learn more about AdHawk but does not engage with our emails for 30 days.Step 2: A Customer Match segment is created for all “unengaged” prospective customers.Step 3: A Remarketing campaign is created to target prospective customers that have not converted after 30 days.Step 4: We tailor the Customer Match and Remarketing ads to promote a special offer.

This group is the least likely to convert, so any new business scraped up is a huge win! It’s important to educate these stale leads on what we do and remind them why they signed up in the first place.

Upselling existing customers to a new product or service

Most marketers are so intent on attracting new business that they often forget that there is a wealth of opportunity under their noses. Don’t sleep on marketing to those that have bought something from you in the past! We use our existing customer segment to promote new features or products we feel they will be a good fit for.

Here’s the flow we use to target existing customers:

Step 1: A Customer Match segment is created for our “Existing Customers.”Step 2: We further segment this list by renewal date to ensure that customers see our ads when their contract is up.Step 3: Tailor the ads to promote additional services we offer that our customers are not leveraging.

We’ve structured our flow this way because our product runs on a subscription basis. If you’re selling physical goods that can be repurchased often, break down your segment by the products your customers have shown the most interest in. That way, you can tailor your ads to the specific products you believe would resonate most with them.

Final thoughts

Are you leveraging AdWords as part of your email marketing strategy? If you are, I’d love to learn more about what strategies you have used that have been successful.

Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.

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Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.