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Google Marketing Live: An Advertiser’s Take on the Highlights

Updates from the Google Marketing Live keynote

For advertisers, the Google Marketing keynote is a hotly anticipated annual event where we get to hear about all of the new features coming up in Google’s suite of marketing tools. It’s also a great indicator of what’s top of mind for Google, and what betas you can expect to roll out (or bug your Google rep to let you into early).

Yesterday’s presentation kicked off with consumer trends, then covered improvements and launches across a range of Google ad platforms. Throughout the event we heard data control and privacy come up often, reminding us that privacy is still a major theme of 2018. And while professional paid media managers may have found the keynote a bit of a bore, there were some decent things to get excited about too.

If you don’t have an hour to watch the full recording, read on for our key highlights (or skim ‘em, if that’s more your thing).

AdWords is no more

Whoah whoah, don’t panic. The ad platform that you know and love (and rely on for your business) is still intact. In fact, if you follow PPC news or read the Google Ads blog, you probably already heard about the shift from Google AdWords to Google Ads that’s coming at the end of this month. Like the old Google Ads interface, you’ve probably already forgotten about ‘AdWords’, right?

the new Google Ads rebrand takes effect July 24th

What’s actually changed?
Here’s a breakdown of what this rebrand means, and what terms to use so you sound smart in front of your boss and clients:

  • AdWords will become Google Ads.
  • DoubleClick and Google Analytics 360 will now be combined into Google Marketing Platform.
  • DoubleClick Search is now Search Ads 360.
  • The rebrand becomes official July 24th, 2018.

Page speed is critical (and more visibility means more control)

We recently shared that we’re close to launching a beta program for Accelerated Mobile Pages at Unbounce, and that page speed is a top priority for us as a leading landing page builder—so naturally we were nodding along yesterday morning as Anthony Chavez, Product Management Director at Google Ads, explained the impact that page speed can have on conversion rates.

Chavez opened his speed segment by reminding us that:

“even the best ads may not perform if your landing pages aren’t up to par, especially on mobile.”

Chavez admitted that landing page speed is often a lower priority for advertisers, who are focused on optimizing keywords, bids, and ad copy. When that’s not enough, “one of the best ways to get better performance on mobile is to improve the speed of your landing pages,” says Chavez. And we couldn’t agree more.

This is why we were giddy when he announced that Mobile Speed Score is now available in Google Ads. Mobile Speed Score is a new score telling you how fast your ad’s resulting landing pages are. This score is on a ten-point scale (ten being the fastest) and includes secret-sauce factors visible to Google—like the relationship between your mobile landing page speed and conversion rates. Plus, it’s updated daily, so you won’t have to wait weeks to figure out if your speed optimizations are working for you.

New from the Google Marketing Keynote: Landing page speed score

Since it’s a column built into your Google Ads account, you’ll be able to sort and filter the landing pages that could use some love. You can find this new column in the Landing Pages tab of your Google Ads account:

Access your landing page speed score in a new column

Chavez went on to suggest using AMP landing pages as a “powerful and easy way to supercharge your site speed,” something we can definitely agree with. By using AMP landing pages together with Mobile Speed Score, you’ll be leaps and bounds ahead of your competition.

Want to get even further ahead of your competition? Sign up for early access to Unbounce’s AMP beta program right here.

Search ads are going responsive

For a while now Google has been integrating machine learning and automation into its ad platform, and it looks like the future is no different. Much like last year’s launch of Smart Display campaigns, Google dedicated quite a bit of time to explaining Responsive Search Ads. However, this may not come as news to you as the Responsive Search Ads beta has been available to many advertisers for months already.

Similar to how Smart Display campaigns combine images with text on the fly, Responsive Search Ads combine headlines and descriptions from variations you’ve inputted to create an ad that’s deemed “most relevant to the searcher.” Ideally this means your ads will be more catered to each user and query, instead of serving up a rotation of generic ads.

This is a step forward in more personalized search results, but also means less control for advertisers, and makes it complicated to test ad copy. One big benefit, however, is that these ads can show up to 90% more copy than Expanded Text Ads, meaning you take over more real estate on the SERP. If this is the future of search ads, SEOs should be worried.

Your ad could show up to three 30-character headlines (vs. just one) and two 90-character description lines (compared to one 80-character description line). And PPC-er’s seem to be on board with this extra space, with the reaction mostly positive, if not a little hesitant:

Not seeing Responsive Search Ads as an option in your account? The beta is still rolling out to English-language advertisers and will be rolling out to more advertisers and languages throughout 2018.

Also, if you still prefer man over machine, you can continue to use Expanded Text Ads in your campaigns.

Even more assorted product updates & improvements

Better cross-device tracking

Tracking users across devices has always been a pain for paid advertisers, but this has been improving over the years. Google reaffirmed its commitment to solving this pain by announcing cross-device reporting and remarketing in Google Analytics (to what sounded like the largest applause of the keynote).

Google Shopping updates

If you’ve ever launched Product Listing Ads (PLAs) on Google Shopping, you know that it can be a whole other beast. Starting this year, Google will be rolling out Automated Feeds which create a feed by crawling your website (no more troubleshooting feeds). Keeping with the theme, Google also talked about the recently launched Smart Shopping campaigns that automatically optimize around a goal.

These changes will make PLAs a lot more accessible to advertisers, but oppositely could increase competition for those of us already advertising on Google Shopping. In fact, Smart Campaigns will soon be integrated with Shopify, meaning Shopify merchants will be able to manage their Smart Shopping campaigns without leaving the platform. This reduces barriers for the 600,000+ Shopify users that may have been previously intimidated by the Google Merchant Center.

Updates to YouTube

On the video side of things, Google announced that later this year they will be bringing a new option to TrueView for Reach ads. In addition to a call to action button, the new Form Ads will allow you to collect leads through a form directly on the ad. Because we didn’t see any examples of how these would look in the wild, I’ll say it sounds like this feature won’t be released very soon. For now though, I can guess it will be something similar to Facebook’s Lead Ads, maybe even more simple.

They also kept YouTube on the machine learning bandwagon, announcing Maximize Lift Bidding. They describe this as a bidding strategy to help you “reach people who are more likely to consider your brand after exposure to an ad.” Google added a bit more context to this feature—currently in beta—on its blog, saying, “it automatically adjusts bids at auction time to maximize the impact your video ads have on brand perception throughout the consumer journey.”

We’ll have to wait until it rolls out officially later this year to learn even more.

Machine learning for small business

If you run a small business, Google used a small slice of the keynote to remind you that you’re still an important customer. They announced the upcoming launch of something called Smart Campaigns, and—you guessed it—it involves machine learning. Google Ads is a sophisticated platform, but can still be intimidating for a small business, or a non-marketer.

Using information scanned from the company’s website and their Google My Business listing, the Smart Display campaign automatically generates ads on both search and display. The goal is to get small business owners up and running with ads as quickly as possible and to help them overcome the learning curve that can come with online advertising (or the cost of hiring an agency). After launch, the campaigns automatically optimize themselves.

Going further, the campaigns automatically generate quick and simple landing pages for small businesses, for when you’re running without a website. While these landing pages include super basic information like your location and phone number, you don’t get any control over brand messaging or even the images that get selected.

As a paid advertiser by trade myself, I’m wary of handing this much control over my ads to Google’s machine learning, but that doesn’t mean this can’t work for a small business customer. The audience for Smart Campaigns is an advertiser starting from scratch (as in, no website-from-scratch) so there would be no historical performance to compare to.

What all these updates mean

While not everything was technically fresh news at this year’s Google Marketing Live, we still had some interesting key takeaways.

What stood out the most to us at Unbounce was the critical need for fast landing pages, especially on mobile. Undeniably though, the strong thread throughout the keynote was the shift toward machine learning.

My prediction is that—over the coming months and years—Google will shift to more and more “Smart” features and campaigns until eventually machine learning becomes so intertwined that we drop the “Smart.” I’m not quite ready to give Google the wheel on all of my ad copy, bids, and optimization just yet, but I’m curious to see the data and hear the results as we move into this new era of online advertising.

Excerpt from:

Google Marketing Live: An Advertiser’s Take on the Highlights

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CRO Hero: Sam Clarke, Director of Growth Marketing at Placester

CRO Heroes

Admittedly, Conversion Rate Optimization is not the most sexy term in the marketing world – but if you’ve ever run an A/B test where the variant won by a landslide, or made a website design change that led to a significant increase in product purchases, you know firsthand how exciting and powerful CRO can be in action. Marketers who specialize in conversion rate optimization are often a rare mix of analytical and creative; tactical, and intuitive. They need to get inside a customer’s head, but they also need to dive deep into data. Often, CRO professionals are tasked with: Reducing…

The post CRO Hero: Sam Clarke, Director of Growth Marketing at Placester appeared first on The Daily Egg.

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CRO Hero: Sam Clarke, Director of Growth Marketing at Placester

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Evangelizing experimentation: A strategy for scaling your organization’s test and learn culture

Communications—like experimentation—is an iterative process. You’ll need to revisit each part of the communications framework (inspiring, informing, involving, and iterating)…Read blog postabout:Evangelizing experimentation: A strategy for scaling your organization’s test and learn culture

The post Evangelizing experimentation: A strategy for scaling your organization’s test and learn culture appeared first on WiderFunnel Conversion Optimization.

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Evangelizing experimentation: A strategy for scaling your organization’s test and learn culture

Table Setting Guides for Great Design

Designing at your desk with Photoshop or HTML and CSS is easy, but getting your bosses and clients to give your work their stamp of approval is often quite a feat. In this webinar, Dan will share some stories of tools, methodologies, and non-traditional deliverables that can help you get the buy-in you need. Follow along to learn how to make everyone you work with say “please” and “thank you!”

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Table Setting Guides for Great Design

How Just One Ecommerce Popup Offer Helped Canvas Factory Generate 1.1 Million in Revenue

Canvas Factory's Popup Success

When you hear ‘website popup’ in a marketing context, my bet is—as a discerning marketer—you all but cringe. Surely these boxes that jump up in the middle of a screen are for low-level marketers. They’re scammy, make you lose your train of thought, nobody likes them,…you’d never use ‘em.

But can you really hate popups if they’re found to drive results?

As heated as the debate can get, Richard Lazazzera, an ecommerce entrepreneur and Content Strategist at Shopify has a fair point in this reply to a comment on his blog post:

Image via the Shopify blog.

And drive sales they can.

By experimenting with popup overlays, Auckland-based Canvas Factory (an ecommerce shop providing high-quality canvas prints) has found a ton of success engaging prospects at exactly the right time.

Using just one popup that appears across several of their domains, Canvas Factory discovered the targeting that worked best for them, and—most importantly—brought in 1.1 million USD in revenue(!) via their offer.

In today’s post, we’ll share Canvas Factory’s story, along with some lessons learned, so that—if you’re tempted—you too can convert more site visitors.

Canvas Factory’s approach to ecommerce popups

Similar to many ecommerce brands, Canvas Factory wanted to convert more of the visitors leaving their site empty handed. They’d realized some prospects only needed a moderate incentive to get over any purchase anxiety, so they had started offering a small discount via a coupon.

Eventually they wondered if the coupon would perform even better if delivered via a popup at the right moment.

Experimenting, they created this popup overlay in Unbounce for their site:

One of Canvas Factory’s domains outfitted with their popup.

They duplicated this one design eight times for running across different domains on certain URLs. The copy was the same for each, offering $10 off someone’s first order in exchange for an email, and only appeared as someone was actively trying to leave the site, once per visitor.

The main difference was location. The brand ran four of these overlays across their product pages on their Australian and New Zealand domains, while another four appeared on the Canvas Factory blog across the same domains.

How’d the experiment go?

The Unbounce popup overlay has now been running from November 2016 to present and in comparing the period before using the popups to promote this same coupon code to now:

  • Canvas Factory has seen a 6% to 9% increase in use of the coupon, and
  • Subscription to their mailing list has grown by over 14.3%.

Now the brand’s marketers can do a better job actively nurturing prospects claiming the coupon, and re-marketing to successful first-time customers.

But in terms of the bottom line? Managing Director Tim Daley says it best:
Tim from Canvas Factory

“Unbounce played a key part in Canvas Factory’s conversion rate optimization activity for our subscriber campaign. This has contributed to over $1.1 million dollars in purchases.”

$1.1 million the brand may not have otherwise seen had they not tried the overlay? If that’s not making you reconsider whether or not your personal distaste for popups should stop you from trying one out, I’m not sure what will.

That said…

How’d the brand track success?

Tim tells us the coupon use was measured by integrating Unbounce popup overlays with their mail platform and their payment gateway CS-Cart:

“This [integration] allows us, per country level, to collect new subscribers, partition [them] to relevant country and then track their individual and group purchase application of the coupon acquired through the popup.”

Ultimately the integration lets Canvas Factory see:

  • How many customers are using coupons + how many discounts are being used total
  • Total revenue before and after coupons are applied
  • Average order value before and after coupons are applied
  • What kind of customers the brand’s attracting with coupons

All very useful factors in understanding how long a campaign like this is feasible for, and experimenting with different discounts.

Want to push your lead data collected via landing pages, sticky bars, and popup overlays through to your mail platforms and other tools? See our Integrations Powered by Zapier and all the connections available right in Unbounce.

It’s all about location: A lesson on why popups in the wrong place are a big mistake

Your gut feeling that popups can be scammy? It’s not far off. If used incorrectly at the wrong time or on the wrong URL of your site, they certainly can be. We’ve all seen these types of popups and they’re maddening.

In Canvas Factory’s case, it wasn’t as simple as create the popup, set it and forget it. In running their Unbounce popup overlay in several locations, they’ve learned placement and timing is critical.

In Tim’s case, he discovered that the blog wasn’t the proper placement for this particular offer, it was simply too soon in the buyer journey to be offering someone a discount. With posts on the brand’s blog aimed to help you take better photos of your kids and other photography tips, this level of awareness doesn’t really align with wanting to purchase right away.

Overall, Canvas Factory’s blog popup conversion rate was 0.18% versus the up to 11% conversion rate they’d seen on product pages where the purchase intent was likely higher.

As outlined above, aim to align your offers with buyer intent.

The lesson:

If you choose the right place for your offer (pricing pages and high commitment URLs in Canvas Factory’s case), you’ll see results because you offered a timely and relevant incentive. In the wrong place, however, you simply won’t see the results you want, and worse, you’ll irritate and annoy your visitors.

Get actionable tips on where to place your popups, and which types of messages perform best in our Best Practice Guide.

So you shouldn’t use popups on your blog?

No—Canvas Factory’s unique experience isn’t to say that popups on your blog won’t work, because they definitely can. You just have to choose the right kind of offer and perfect targeting. Because your blog readers may not be product aware yet, you need to align your offer with the level of awareness readers do have about your company (i.e. they might be open to a free in-depth ebook about the exact topic they’re already reading about).

You might also try directing your blog traffic to an even higher-converting area of your site.

Here’s a super relevant clickthrough popup Seer’s Wil Reynolds uses to offer up more relevant content on his site:

By proactively serving up what prospects might want next, Seer becomes more trustworthy and keeps people engaged on their site longer (which is a great sign in Google’s eyes). You can make traffic shaping like this the goal of some of your popups in locations where a higher-commitment ask doesn’t make sense.

Try an Experiment Yourself

Overall, popups can definitely be annoying when used aggressively or poorly (there’s no arguing that) but, as we’ve seen with Canvas Factory, proper targeting and relevant offers can make all the difference to both marketers and site visitors who can be receptive to proper incentives at the right time.

If you’ve got a great campaign or offer running, a well-timed and targeted popup could ensure all the right people see it and that you don’t leave opportunities on the table.

Try an Ecommerce popup from Unbounce today

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How Just One Ecommerce Popup Offer Helped Canvas Factory Generate 1.1 Million in Revenue

Data-Backed Advice for High-Converting Real Estate Landing Page Design [+ FREE TEMPLATE]

You’re designing a landing page for your Real Estate client, and you turn to “best practice” advice articles to help guide the way.

But there’s a nagging voice at the back of your mind:

Does this “best practice” advice apply indiscriminately to my industry? Does this author really know anything about my audience at all?

“Best practices” become “better practices” when they are industry-specific.

When our design team was recently wireframing new landing page templates for the Unbounce builder, they set out to create industry-specific templates that addressed this truth: different audiences belonging to different industries behave differently. They have different pains, different motivators and different disincentives.

Firm believers that data needs to inform design, our design team sourced their research in two key areas:

  1. Data from the Unbounce Conversion Benchmark Report: The report includes average conversion rates for 10 popular industries, as well as Machine Learning-powered recommendations around reading ease, page length, emotion and sentiment.
  2. High-converting customer landing pages: Our designers looked at the top 10 highest-converting Unbounce landing pages in those industries, and analyzed common design and copy elements across the pages.

Our design team then combined insight from these two key areas of research to build out content and design requirements for the best possible landing page template for each of the 10 industries.

One of these industries was Real Estate, and now we want to share their findings with you.

See a breakdown of their process for designing the Real Estate page template at the bottom of this post, or read on for their key findings about what converts in the Real Estate industry.

Which copy elements convert best in the Real Estate industry?

Word count

The data scientists and conversion rate optimizers who put together the Unbounce Conversion Benchmark Report found that for Real Estate lead capture landing pages, short n’ sweet is better: overall, they saw 33% lower conversion rates for longer landing pages.

This chart shows how the word count relates to conversion rates for the Real Estate vertical. On the x-axis we have word count — on the y-axis, conversion rate.

This was consistent with what the design team saw across high-converting Unbounce customer landing pages in Real Estate: pages were relatively short with concise, to-the-point copy.

Reading ease

The Unbounce Convert Benchmark Report also revealed that in the Real Estate vertical, prospects want simple and accessible language. The predicted conversion rate for a landing page written with 6th grade level language was nearly double that of a page written at the university level.

This chart shows how conversion rates trend with changes to reading ease for the Real Estate Industry. On the x-axis we have the Flesch Reading Ease score — on the y-axis, conversion rate.
According to the Unbounce Conversion Benchmark Report, 41.6% of marketers in the Real Estate industry have at least one page that converts at less than 1.3% (in the 25th percentile for this industry). Download the report here to see the full data story on Real Estate and get recommendations for copy, sentiment, page length and more for nine additional industries.

Fear-inducing language

The Unbounce Conversion Benchmark Report used an Emotion Lexicon and Machine Learning to determine whether words associated with eight basic emotions (anger, anticipation, disgust, fear, joy, sadness, surprise and trust) affected overall conversion rates.

While these emotions did not seem to dramatically correlate with conversion rate in the Real Estate vertical, fear-based language was the exception. We saw a slight negative trend for pages using more fear-inducing terms:

This chart shows how the percentage of copy that evokes fear is related to conversion rates for the Real Estate vertical. On the x-axis we have the percentage of copy that uses words related to fear — on the y-axis, conversion rate.

If more than half a percent of your copy evokes feelings of fear, you could be hurting your conversion rates.

Here are some words commonly associated with fear on Real Estate lead capture landing pages: highest, fire, problem, watch, change, confidence, mortgage, eviction, cash, risk…

See the full list in the Unbounce Conversion Benchmark Report.

Calls to action

When our designers looked at the top 10 highest-converting Unbounce customer landing pages in the Real Estate vertical, they took a close look at the calls to action and found that:

  • Every page provided a detailed description of the offer
  • Almost all had a “request a call back” or “call us” option (other CTAs included “get more info,” “apply now” and “get the pricelist”)
  • Most did an excellent job of including button copy that reinforces what prospects get by submitting the form
If you use a “call us” CTA on your landing pages, make sure you try out our CallRail integration. This will help you track which calls are a result of your paid spend and landing pages!

Here are some examples of the forms and calls to action on some of our highest-converting Real Estate lead capture landing pages:

The usual suspects (benefits, social proof, UVP…)

Without much exception, the pages featured a lot of the copywriting elements that one would expect to see on any high-converting landing page (regardless of vertical):

  • Detailed benefits listed as bullet points
  • A tagline that reinforces the unique value proposition or speaks to a pain point:
  • And not surprisingly, testimonials. One page went above and beyond with a video testimonial:

Which design elements convert best in the Real Estate industry?

The highest-converting Real Estate landing pages included lots of imagery:

  • Beautiful hero shots of the interior and exterior of properties
  • Maps
  • Full-width photography backgrounds
  • Floor plans

Some examples:

Our designers also studied other design features as basic guidelines for the template they were then going to create.

While these specifics are meant to be taken with a grain of salt (you may already have brand colors and fonts!) they could serve as a good starting point if you’re starting completely from scratch and want to know what others are up to.

Many of the high-converting pages had:

  • San-serif fonts
  • Palettes of deep navy and forest green
  • Orange (contrasting) call to action buttons
The highest-converting landing pages in the Real Estate industry sit at 11.2%. If your Real Estate page converts at over 8.7%, you’re beating 90% of your competitors’ pages. See the breakdown of median and top conversion rates (and where you stand!) via the Unbounce Conversion Benchmark Report.

Behold, the template our designers created

After synthesizing all that research, our Senior Art Director Cesar Martínez took to his studio (okay, his desk), and drafted up this beautiful Real Estate landing page template:

Not only is the template beautiful, it was created by analyzing actual data: what makes for a high-performing landing page in the Real Estate industry via the Unbounce Benchmark Report and high-converting customer pages.

Footnote: The design process

Curious about the process our designers used to develop this data-backed Real Estate landing page template? Here are the steps they followed:

  1. For the 10 highest-converting customer landing pages, they analyzed all common elements (such as form, what type of information is collected, what type of offer, if there are any testimonials, etc). This allowed them to build their content requirements.
  2. They referred to the word count recommendations in the Unbounce Conversion Benchmark Report and designed for that word count limit.
  3. They referred to reading ease level recommendations for that specific industry from the Benchmark Report and shared the information with their copywriter.
  4. They sketched out a rough idea of their potential landing page template.
  5. They selected typography and colors relevant to the industry based on what was popular in the 10 examples.
  6. They named their imaginary company in the industry and sketched out some potential logos. They picked photography built out a moodboard.
  7. That helped them gather all the information they needed to build out their template!

See the article here: 

Data-Backed Advice for High-Converting Real Estate Landing Page Design [+ FREE TEMPLATE]

How Your PPC Strategy Should Differ on the AdWords Search VS Display Network

As we ramp up for Unbounce’s upcoming PPC week, we thought we’d revisit some of our favorite PPC posts from the archives. This post was originally published in June 2015 but still rings true. Enjoy!

Have you ever been kicking so much AdWords Search Network butt that it made you raise your chest and gave you instant super powers?

You know, the type of confidence that makes you walk with a pep in your step and hair bouncing around?

Confidence
Kinda like this mini-horse. Image source.

Feels AMAZING.

But sometimes you hit a ceiling with the keywords you’re bidding on, and there’s literally no more Search Network traffic out there (since your impression shares are all around 98%).

You immediately think of using the AdWords Display Network, simply because you know there’s more traffic, cheaper clicks and much more potential ROI just waiting to be grabbed.

dog-pee-to-claim-land-FACE-Low-Cost-SpayNeuter-Clinic-FB
Actually, don’t do that. It won’t get you conversions. Image source.

As you may already know, the AdWords Display Network (also known as the Google Display Network/GDN) is the biggest digital ad network in the world. It allows you to advertise on publisher properties like websites, mobile apps, Gmail, YouTube and more.

Compared to the AdWords Search Network, the Display Network also houses the largest viewership of any online platform. YouTube itself has a monthly viewership equivalent to 10 Super Bowls – so it shouldn’t come as a surprise that display advertising is said to capture 34% of all online ad spend and about 10% of all marketing budgets.

But with new channels come different strategies.

What you’re doing on the AdWords Search Network will not perform the same way on the Display Network.

If the Display Network is uncharted territory for you, here’s how you need to adjust your current PPC strategy to get the results you want.

Different user behavior calls for a different strategy

The biggest difference between the AdWords Search Network and Display Network can be seen in the sweet visual I had my designer custom-make below.

unbounce-_chuck_norris

In the “Chuck Norris” action cycle above, you can see how the power of keyword intent in the Search Network can put people really close to taking action (AKA converting), but the Display Network typically has visitors who are a few steps behind.

This is because people who are on the Display Network aren’t actively searching for what you offer. As Erin Sagin puts it, they’re rarely in “shopping mode.”

Instead, Display Network visitors are most likely in the research phase when your display ads are hitting them. They’re on forums, blog posts, or watching that YouTube vid trying to gather enough information to make a decision. They don’t know what they need yet, so your job is create awareness.

If you’re selling more of an “emergency” service like being a locksmith or roadside assistance, then you’ll have a hard time using the Display Network to your advantage.

This is simply because ads on the Display Network are not triggered from a search engine like text ads on the Search Network are. The Search Network works as a demand harvester (your ads are grabbing the intent), while the Display Network works as a demand generator (your ads are creating awareness).

So how do you change your strategy from the Search Network to also make the AdWords Display Network a money making machine?

Create trust and deliver value

As I mentioned, your Display Network ads could be interrupting someone who’s reading the news, reading a blog or watching a video.

Because of that, the level of commitment it takes for someone to stop what they’re doing, click your ad, then call you or fill out your landing page form is high and much more unlikely compared to the Search Network. In other words, you can’t expect to have the same campaign conversion rates on the Display Network as you do on the Search Network.

If you’re offering “Free Quotes” on the search network because people are actively searching for someone who can relieve their problem, it might actually be better for you to lead with valuable educational material (i.e. your content) on the Display Network.

A perfect example of this is my crush of an email marketing company, Emma.

Emma uses the AdWords Search Network to drive sign ups, but they use the Display Network to give you great, fun and actionable value. Here’s what some of their Display Ads look like (click on them to go to the accompanying landing page):

emma-gif-1

emma-gif-2

emma-gif-3

I reached out to Cynthia Price (the Director of Marketing at Emma) and she gave me this golden nugget about how they use the AdWords Display Network:

We get that someone seeing a display ad isn’t necessarily interested in learning more about our product just yet. It’s all about brand awareness, and more importantly for us, trust-building.

So we offer content that we think will be valuable and helpful to our audience’s marketing efforts. It starts our brand relationship off on the right foot, helps them understand the strength of our expertise and paves the way for us to nurture or retarget them in the future.

You already know that content marketing’s core foundation is about adding true value.

Your display ads should be no different.

On the Display Network, your first goal is to establish trust by giving value, and then nurture the visitors down the road to become paying customers.

Revisit your targeting options

Once you have a great piece of content that delivers value and educates your audience, it’s time to figure out how to target it to people who actually want it.

Let’s have a look at the five targeting options that’ve been found to drive the biggest impact on the Display Network.

To illustrate how each one works, let’s pretend you’re a dog walker. Your name is Lori and you live in Huntington Beach, CA. You’ve been advertising on the AdWords search network and this is your landing page:

lori-the-dog-walker

What are your best targeting options?

Placement targeting

Placement targeting allows you to advertise directly on certain publisher sites. This means you could have your ad show up on Forbes or CNN if you’d like.

Best practice advice: Make sure the website or page’s audience is relevant to what you’re offering. Don’t shotgun approach all of CNN – sniper shot individual placements within CNN if you can.

Contextual/Keyword targeting

Contextual/Keyword targeting allows you to give Google your keywords and have it automatically find relevant placements for your ads.

Best practice advice: Mix this with placement targeting to be even more laser focused with your targeting.

Topic targeting

Topic targeting allows you to go more broad than regular placement targeting.

For this, you could target the topic of Pets & Animals directly and cast a wider net, with the possibility of your ads showing up on FerretLovers.com (yes, that’s a real site).

Best practice advice: See what Topic targeting gives you, then exclude unwanted placements from your campaign once things are running and data is coming in.

Interest targeting

Interest targeting is kind of similar to topic targeting, but instead of judging the context of websites, interest targeting tracks behaviors of web users. This targeting method can be even more vague than topic targeting.

Best practice advice: Every industry is different, so always test things out and see the performance. Be quick to pause and exclude irrelevant placements once data comes in.

Combining targeting methods

This is where you’ll have a lot of fun and potentially get better results.

You’re not locked into using just one targeting method with the AdWords Display Network. In fact, Alistair Dent over at Search Engine Watch and many others highly recommend never going with just one targeting option, but combining multiple together.

You can target certain placements with the addition of contextual/keyword targeting to tell Google that you only want your ads to show when a visitor is on CNN and reading an article about dog walking.

Or you can target different interests with contextual/keyword targeting as well.

Create multiple ad groups, each with their own targeting specifications, and see how they perform against each other. Once you’ve hit your stride and conversions are coming in, pause the other ad groups that aren’t working, and make variations of the ad group targetings that are working for you, so that you can squeeze more out of your PPC dollars.

Wrapping up

Wow! Quite a bit of info huh?

Now that you clearly know why your Display Network strategy has to be different from your Search Network strategy, what do you have to lose? Get started now. Try different targeting combinations, and never forget to offer true value.

What have you found to be the best driver of conversions on the AdWords Display Network? How different are your strategies compared to the ones we talked about?

Read More: 

How Your PPC Strategy Should Differ on the AdWords Search VS Display Network

How to Make Facebook Ads Work for Your B2B Company With a Simple Google Form Survey

Google Survey

Facebook is still primarily a leisure social network: people browse it to connect with their friends, find interesting news and, of course, check out cat pictures. Therefore, most marketers believe that advertising on Facebook is useless for B2B. They’ll point to lower click-through rates for B2B Facebook ads, and higher costs per click, and go back to focusing on Google Adwords. Facebook is a great tool for B2C promotions, where marketers can offer discounts, promote sales and retarget buyers. But these tactics are not always suitable for the B2B crowd. That’s fair. But guess what? Companies are made of people….

The post How to Make Facebook Ads Work for Your B2B Company With a Simple Google Form Survey appeared first on The Daily Egg.

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How to Make Facebook Ads Work for Your B2B Company With a Simple Google Form Survey

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Google AdWords Launches Greater Visibility Into Quality Score Components (And What This Means For You)

A recent update to Google AdWords is changing the way performance marketers understand their landing pages’ Quality Scores. Image via Shutterstock.

While Quality Score is a critical factor in your ad performance, it’s always been a bit of a mystery wrapped in an enigma. Marketers have never been able to natively view changes to Quality Score components in AdWords directly. That is — even though expected click through rate, ad relevance and landing page experience scores are the elements contributing to your Quality Score, you haven’t been able to see these individual scores at scale (or for given timeframes) within your AdWords account, or export them into Excel.

Which is why, up until now, some especially savvy marketers have had to improvise workarounds, using third-party scripts to take daily snapshots of Quality Score to have some semblance of historical record — and a better-informed idea as to changes in performance.

Fortunately, an AdWords reporting improvement has brought new visibility into Quality Score components that could help you diagnose some real wins with your ads and corresponding landing pages.

What’s different now?

As you may have already noticed, there are now seven new columns added to your menu of Quality Score metrics including three optional status columns:

  • Expected CTR
  • Ad Relevance and
  • Landing Page Experience

And four revealing historical keyword quality:

  • Quality Score (hist.)
  • Landing Page Experience (hist.)
  • Ad Relevance (hist.)
  • Expected Click Through Rate (hist.)
what's new
Image courtesy of Google’s Inside AdWords blog

This is not new data per se (it’s been around in a different, less accessible form), but as of this month you can now see everything in one spot and understand when certain changes to Quality Score have occurred.

So how can you take advantage?

There are two main ways you can use this AdWords improvement to your advantage as a performance marketer:

1. Now you can see whether your landing page changes are positively influencing Quality Score

Now, after you make changes to a landing page — you can use AdWords’ newest reporting improvement to see if you have affected the landing page experience portion of your Quality Score over time.

This gives you a chance to prove certain things are true about the performance of your landing pages, whereas before you may have had to use gut instinct about whether a given change to a landing page was affecting overall Quality Score (or whether it was a change to the ad, for example).

As Blaize Bolton, Team Strategist at Performance Marketing Agency Thrive Digital told me:

As agency marketers, we don’t like to assume things based on the nature of our jobs. We can now pinpoint changes to Quality Score to a certain day, which is actual proof of improvement. To show this to a client is a big deal.

Overall, if your CPC drops, now you can better understand whether it may be because of changes made to a landing page.

2. You can identify which keywords can benefit most from an updated landing page

Prior to this AdWords update, ad relevancy, expected click through rate and landing page relevancy data existed, but you had to mouse over each keyword to get this data to pop up on a keyword-by-keyword basis. Because you couldn’t analyze the data at scale, you couldn’t prioritize your biggest opportunities for improvement.

Hovering over individual keywords
Image courtesy of Brad Geddes and Search Engine Land

However, now that you can export this data historically (for dates later than January 22, 2016), you can do a deep dive into your campaigns and identify where a better, more relevant landing page could really help.

You can now pull every keyword in your AdWords account — broken out by campaign — and identify any underperforming landing pages.

An Excel Quality Score Deep Dive
Now, an Excel deep dive into your AdWords campaigns can help you reveal landing page weaknesses.

Specifically, here’s what Thrive Digital’s Managing Director Ross McGowan recommends:

You can break down which of your landing pages are above average, or those that require tweaking. For example, you might index your campaigns by the status AdWords provides, assigning anything “Above Average” as 3, “Average” as 2 and “Below Average” as 1. You can then find a weighted average for each campaign or ad group and make a call on what to focus on from there.

What should you do when you notice a low landing page experience score?

As Google states, landing page experience score is an indication of how useful the search engine believes your landing page is to those who click on your ad. They recommend to, “make sure your landing page is clear and useful… and that it is related to your keyword and what customers are searching for.”

In short, it’s very important that your landing pages are highly relevant to your ad. Sending traffic to generic pages on your website may not cut it. Moreover, once you are noticing low landing page engagement scores, it’s time to try optimizing these pages with some quick wins.

In the words of Thrive’s Ross McGowan:

Figure out what a user wants, and do everything you can to tailor the on-page experience to them. Whether that be [using] Dynamic Text Replacement, A/B testing elements to get the best user experience, or spending less time on technical issues and more on writing great content.

Finally, for more on AdWords’ latest improvements, AdAlysis founder Brad Geddes has written a great article on Search Engine Land. His company had enough data on hand to attempt a reverse-engineer of the formula for Quality Score to get a sense of how changes to one of the QS components would impact overall score. His recommendation is much the same as Ross’, in that, if a landing page’s score is particularly low, your best bet is to focus on increasing user’s interaction with the page.

Want to optimize your landing pages?

Read more: 

Google AdWords Launches Greater Visibility Into Quality Score Components (And What This Means For You)

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Marketing Machines: Is Machine Learning Helping Marketers or Making Us Obsolete?

Hollywood paints a grim picture of a future populated by intelligent machines. Terminator, 2001: A Space Odyssey, The Matrix and countless other films show us that machines are angry, they’re evil and — if given the opportunity — they will not hesitate to overthrow the human race.

Films like these serve as cautionary tales about what could happen if machines gain consciousness (or some semblance of). But in order for that to happen humans need to teach machines to think for themselves. This may sound like science fiction but it’s an actual discipline known as machine learning.

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The machines are coming. But fear not — they could help you become a better marketer. Image via Shutterstock.

Still in its infancy, machine learning systems are being applied to everything from filtering spam emails, to suggesting the next series to binge-watch and even matching up folks looking for love.

For digital marketers, machine learning may be especially helpful in getting products or services in front of the right prospects, rather than blanket-marketing to everyone and adding to the constant noise that is modern advertising. Machine learning will also be key to predicting customer churn and attribution: two thorns in many digital marketers’ sides.

Despite machine learning’s positive impact on the digital marketing field, there are questions about job security and ethics that cannot be swept under the rug. Will marketing become so automated that professional marketers become obsolete? Is there potential for machine learning systems to do harm, whether by targeting vulnerable prospects or manipulating people’s emotions?

These aren’t just rhetorical questions. They get to the heart of what the future of marketing will look like — and what role marketers will play in it.

What is Machine Learning?

Machine learning is a complicated subject, involving advanced math, code and overwhelming amounts of data. Luckily, Tommy Levi, Director of Data Science at Unbounce, has a PhD in Theoretical Physics. He distills machine learning down to its simplest definition:

You can think of machine learning as using a computer or mathematics to make predictions or see patterns in data. At the end of the day, you’re really just trying to either predict something or see patterns, and then you’re just using the fact that a computer is really fast at calculating.

You may not know it, but you likely interact with machine learning systems on a daily basis. Have you ever been sucked into a Netflix wormhole prompted by recommended titles? Or used Facebook’s facial recognition tool when uploading and tagging an image? These are both examples of machine learning in action. They use the data you input (by rating shows, tagging friends, etc.) to produce better and more accurate suggestions over time.

Other examples of machine learning include spell check, spam filtering… even internet dating — yes, machine learning has made its way into the love lives of many, matching up singles using complicated algorithms that take into consideration personality traits and interests.


Machine learning may be helpful in getting products or services in front of the right prospects.
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How Machine Learning Works

While it may seem like witchcraft to the layperson, running in the background of every machine learning system we encounter is a human-built machine that would have gone through countless iterations to develop.

Facebook’s facial recognition tool, which can recognize your face with 98% accuracy, took several years of research and development to produce what is regarded as cutting-edge machine learning.

So how exactly does machine learning work? Spoiler alert: it’s complicated. So without going into too much detail, here’s an introduction to machine learning, starting with the two basic techniques.

Supervised learning

Supervised learning systems rely upon humans to label the incoming data — at least to begin with — in order for the systems to better predict how to classify future input data.

Gmail’s spam filter is a great example of this. When you label incoming mail as either spam or not spam, you’re not only cleaning up your inbox, you’re also training Gmail’s filter (a machine learning system) to identify what you consider to be spam (or not spam) in the future.

Unsupervised learning

Unsupervised learning systems use unlabeled incoming data, which is then organized into clusters based on similarities and differences in the data. Whereas supervised learning relies upon environmental feedback, unsupervised learning has no environmental feedback. Instead, data scientists will often use a reward/punishment system to indicate success or failure.

According to Tommy, this type of machine learning can be likened to the relationship between a parent and a young child. When a child does something positive they’re rewarded. Likewise, when “[a machine] gets it right — like it makes a good prediction — you kind of give it a little pat on the back and you say good job.”

Like any child (or person for that matter), the system ends up trying to maximize the positive reinforcement, thus getting better and better at predicting.

The Power of Machine Learning

A lot of what machine learning can do is yet to be explored, but the main benefit is its ability to wade through and sort data far more quickly and efficiently than any human could, no matter how clever.

Tommy is currently experimenting with an unsupervised learning system that clusters landing pages with similar features. Whereas one person could go through a few hundred pages in a day, this model can run through 300,000 pages in 20 minutes.

How do your landing page conversion rates compare against your industry competitors?

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The advantage is not just speed, it’s also retention and pattern recognition. Tommy explains:

To go through that many pages and see those patterns and hold it all in memory and be able to balance that — that’s where the power is.

For some marketers, this raises a troubling question: If machine learning systems solve problems by finding patterns that we can’t see, does this mean that marketers should be worried about job security?

The answer is more nuanced than a simple yes or no.

Machine Learning and the Digital Marketer

As data becomes the foundation for more and more marketing decisions, digital marketers have been tasked with sorting through an unprecedented amount of data.

This process usually involves hours of digging through analytics, collecting data points from marketing campaigns that span several months. And while focusing on data analysis and post-mortems is incredibly valuable, doing so takes a significant amount of time and resources away from future marketing initiatives.

As advancements in technology scale exponentially, the divide between teams that do and those that don’t will become more apparent. Those that don’t evolve will stumble and those that embrace data will grow — this is where machine learning can help.


Marketers that don’t embrace data will fumble. Those that do will grow — ML can help.
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That being said, machine learning isn’t something digital marketers can implement themselves after reading a quick tutorial. It’s more comparable to having a Ferrari in your driveway when you don’t know how to drive standard… or maybe you can’t even drive at all.

Until the day when implementing a machine learning system is just a YouTube video away, digital marketers could benefit from keeping a close eye on the companies that are incorporating machine learning into their products, and assessing whether they can help with their department’s pain points.

So how are marketers currently implementing machine learning to make decisions based on data rather than gut instinct? There are many niches in marketing that are becoming more automated. Here are a few that stand out.

Lead scoring and machine learning

Lead scoring is a system that allows marketers to gauge whether a prospect is a qualified lead and thus worth pursuing. Once marketing and sales teams agree on the definition of a “qualified lead,” they can begin assigning values to different qualified lead indicators, such as job title, company size and even interaction with specific content.

These indicators paint a more holistic picture of a lead’s level of interest, beyond just a form submission typically associated with lead generation content like ebooks. And automating lead scoring takes the pressure off marketers having to qualify prospects via long forms, freeing them up to work on other marketing initiatives.

Once the leads have reached the “qualified” threshold, sales associates can then focus their efforts on those prospects — ultimately spending their time and money where it matters most.

Content marketing and copywriting

Machine learning models can analyze data points beyond just numbers — including words on your website, landing page or PPC ads. Machine learning systems can find patterns in language and detect words that elicit the most clicks or engagement.

Is emotional copywriting on your landing page effective in your industry?

We used machine learning to help create the Unbounce Conversion Benchmark Report, which shares insights on how different aspects of page copy correspond to conversion rates across 10 industries.
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But can a machine write persuasive copy? Maybe, actually.

A New York-based startup called Persado offers a “cognitive content platform” that uses math, data, natural language processing, emotional language data and machine learning systems to serve the best copy and images to spur prospects into action. It does this by analyzing all the language data each client has ever interacted with and serving future prospects with the best possible words or phrases. An A/B test could never achieve this at the same scale.

Think this is a joke? With over $65 million in venture capital and a reported average conversion rate uplift of 49.5% across 4,000 campaigns, Persado’s business model is no laughing matter.

Still, there is no replacement for a supremely personalized piece of content delivered straight to your client’s inbox — an honest call to action from one human to another.

Recently Unbounce’s Director of Campaign Strategy, Corey Dilley, sent an email to our customers. It had no sales pitch, no call to action button. It was just Corey reaching out and saying, “Hey.”

corey-dilley-marketing-email-1

Corey’s email had an open rate of 41.42%, and he received around 80 personal responses. Not bad for an email written by a human!

Sometimes it’s actions — like clicks and conversions — you want to elicit from customers. Other times the goal is to build rapport. In some cases we should let the machines do the work, but it’s up to the humans to keep the content, well, human.


There is no replacement for personalized content and an honest ask from one human to another.
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Machine learning for churn prediction

In the SaaS industry, churn is a measure of the percentage of customers who cancel their recurring revenue subscriptions. According to Tommy, churn tells a story about “how your customers behave and feel. It’s giving a voice to the customers that we don’t have time or the ability to talk to.”

Self-reporting methods such as polls and surveys are another good way to give a voice to these customers. But they’re not always scalable — large data sets can be hard for humans to analyze and derive meaning from.

Self-reporting methods can also skew your results. Tommy explains:

The problem with things like surveys and popups is that they’re only going to tell you what you’ve asked about, and the type of people that answer surveys are already a biased set.

Machine learning systems, on the other hand, can digest a larger number of data points, and with far less bias. Ideally the data is going to reveal what marketing efforts are working, thus leading to reduced churn and helping to move customers down the funnel.

This is highly relevant for SaaS companies, whose customers often sign up for trials before purchasing the product. Once someone starts a trial, the marketing department will start sending them content in order to nurture them into adopting the service and become engaged.

Churn models can help a marketing team determine which pieces of content lead to negative or positive encounters — information that can inform and guide the optimization process.

Ethical Implications of Machine Learning in Marketing

We hinted at the ethical implications of machine learning in marketing, but it deserves its own discussion (heck, it deserves its own book). The truth is, machine learning systems have the potential to cause legitimate harm.

According to Carl Schmidt, Co-Founder and Chief Technology Officer at Unbounce:

Where we are really going to run into ethical issues is with extreme personalization. We’re going to teach machines how to be the ultimate salespeople, and they’re not going to care about whether you have a compulsive personality… They’re just going to care about success.

This could mean targeting someone in rehab with alcohol ads, or someone with a gambling problem with a trip to Las Vegas. The machine learning system will make the correlation, based on the person’s internet activity, and it’s going to exploit that.

Another dilemma we run into is with marketing aimed at affecting people’s emotions. Sure copywriters often tap into emotions in order to get a desired response, but there’s a fine line between making people feel things and emotional manipulation, as Facebook discovered in an infamous experiment.

If you aren’t familiar with the experiment, here’s the abridged version: Facebook researchers adapted word count software to manipulate the News Feeds of 689,003 users to determine whether their emotional state could be altered if they saw fewer positive posts or fewer negative posts in their feeds.

Posts were deemed either positive or negative if they contained at least one positive or negative word. Because researchers never saw the status updates (the machine learning system did the filtering) technically it fell within Facebook’s Data Use Policy.

However, public reaction to the Facebook experiment was generally pretty scathing. While some came to the defense of Facebook, many criticized the company for breaching ethical guidelines for informed consent.

In the end, Facebook admitted they could have done better. And one good thing did come out of the experiment: It now serves as a benchmark for when machine learning goes too far, and as a reminder for marketers to continually gut-check themselves.

For Carl, it comes down to intent:

If I’m Facebook, I might be worried that if we don’t do anything about the pacing and style of content, and we’re inadvertently presenting content that could be reacted to negatively, especially to vulnerable people, then we would want to actively understand that mechanism and do something about it.

While we may not yet have a concrete code of conduct around machine learning, moving forward with good intentions and a commitment to do no harm is a good place to start.

The Human Side of Machine Learning

Ethical issues aside, the rise of machines often implies the fall of humans. But it doesn’t have to be one or the other.

“You want machines to do the mundane stuff and the humans to do the creative stuff,” Carl says. He continues:

Computers are still not creative. They can’t think on their own, and they generally can’t delight you very much. We are going to get to a point where you could probably generate highly personal onboarding content by a machine. But it [will have] no soul.

That’s where the human aspect comes in. With creativity and wordsmithing. With live customer support. Heck, it takes some pretty creative data people to come up with an algorithm that recognizes faces with 98% accuracy.

Imagine a world where rather than getting 15 spam emails a day, you get just one with exactly the content you would otherwise be searching for — content written by a human, but served to you by a machine learning system.

While pop culture may say otherwise, the future of marketing isn’t about humans (or rather, marketers) versus machines. It’s about marketers using machines to get amazing results — for their customers and their company.

Machine learning systems may have an edge when it comes to data sorting, but they’re missing many of the things that make exceptional marketing experiences: empathy, compassion and a true understanding of the human experience.

Editor’s note: This article originally appeared in The Split, a digital magazine by Unbounce.

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Marketing Machines: Is Machine Learning Helping Marketers or Making Us Obsolete?