A mobile operating system for smartphones and mobile devices from Microsoft based on the Windows CE kernel and designed to look and operate similar to desktop versions of Microsoft Windows.
A mobile operating system for smartphones and mobile devices from Microsoft based on the Windows CE kernel and designed to look and operate similar to desktop versions of Microsoft Windows.
At its Build conference, Microsoft unveiled its new browser, Edge, as a follow-up to the recently defunct Internet Explorer. The new browser boasts faster speeds and better features, which could enhance the search experience for users.
A look at seven areas you must review in the kickoff of a well-oiled SEO campaign.
With Google’s recent mobile algorithm update, businesses of all sizes are clamoring to remain relevant in Google mobile search. The Mobile Search Survival Guide will not only help you survive the mobilepocalypse, but dominate it.
Today, YP rolled out its Audience Extension tool, which helps brands to both target campaigns across users' Web searches and find new customers based on first-party search data.
Beyond the site and landing page adjustments of a post-Mobilegeddon world, marketers should also be mindful of how to format and align their content for maximum mobile impact and consumption.
Block-level storage is a type of storage commonly deployed by larger businesses and enterprises in SANs and similar large-scale storage systems.
Google reported a 4 percent increase in profits for Q1, driven by a steady growth in ad revenues. The company was hurt by the recent strength of the U.S. dollar, however.
Cloud management means the software and technologies designed for operating and monitoring applications, data and services residing in the cloud.
With Google rolling out its latest algorithm change earlier this week, many business owners may be scrambling to make necessary adjustments after seeing themselves take a plunge in mobile search results.
Posted by randfish
Many SEOs are frustrated by the ever-expanding repertoire of answer boxes and results from the Knowledge Graph on Google's SERPs. One thing we can be sure of is that they're not going away anytime soon, so in today's Whiteboard Friday, Rand offers some strategic advice (as well as several tactics) for getting SEO value from those SERPs, and even from those boxes.
For reference, here's a still of this week's whiteboard. Click on it to open a high-resolution image in a new tab!
...and welcome to another edition of Whiteboard Friday. This week we're talking about the rich answers, instant answers, direct answers, whatever you want to call them, that Google and Bing are providing in search results, that are taking away a lot of clicks from those search results that people look for.
I think the big four that SEOs are concerned about are what I'm going to walk through first, and then we'll talk about some tactical ways that marketers can actually work around them or even take advantage of them.
So the first one here is what I'm calling the "customized instant answer." This is where Google has essentially said, "Hey, we're going to custom-build something for this type of a query that shows this kind of an answer box." You can see these for math equations, for weather kinds of searches.
The one I'm showing here is specifically around sports and schedules. So I search for Seattle Mariners, the local baseball team here in Seattle, who today, as of filming, it is their opening day, April 7. So Seattle Mariners' schedule is actually showing. Well, it's actually showing the score in real time, since the game's going on as I'm filming, but below that it shows scores and schedules. It says, "4-6 versus the Angels, live at the bottom of the 6th, 4-7 versus the Angels 7:10 p.m." etc., etc.
Then, it actually goes all the way down here, and if you click on any of these, you'll get more detail about where the game's being hosted and where you can watch it on television. Google's essentially said, "Hey, you know what? No one should ever have to click on any results to get all of the key information about the schedule." If you're looking for far-out scheduling stuff or very specific kinds of things, maybe you might go to there, but they even have links in here directly to buy tickets online. So really, they're taking away a lot of the clicks here.
Second, the Knowledge Graph answer. This is where Google essentially is using their Knowledge Graph to provide a specific answer. You can think of this as connecting up with entities or concepts, brands, those kinds of things. I search for "Mariners mascot," Google will give me this little box from their Knowledge Graph that says, "Mariner Moose, the Seattle Mariners, mascot," and they have a little logo there. They don't actually show a picture. I have to scroll down if I want to get images. But the next link there, of course, is the Mariner Moose webpage on Seattle.Mariners.mlb.com, that's a lot of sub-domains, Major League Baseball, but we'll deal with that later.
Then the third one, Knowledge Graph sidebar, this is probably what we're most accustomed to when it comes to the Knowledge Graph, where I search, I get a list of results, but then there's also a Knowledge Graph piece on the right-hand side. This one is showing Seattle Mariners baseball team. There's the logo, arena, location, our manager, some details about the team, where some of this data is extracted from, etc. Typical Knowledge Graph kind of result off to the side.
Then fourth, and potentially most perturbing, I think for many SEOs, many marketers, is the extracted instant answer. This is an answer that Google has pulled from a website, potentially your website, and they're showing right in the results that full answer, without a searcher needing to visit the page. Most of the time they will cite the page. Some of the time they don't even cite where the page, where the answer came from, which means you don't even have an opportunity to earn that click. Even more insanely frustrating.
But in this case I've searched for baseball, how many players on a baseball team. You can phrase this query in a bunch of different ways, and you will get Major League Baseball rosters, a roster of players able to play, blah, blah, blah, blah, the 25-man roster, and the 40-man roster. Do there are two different kinds of rosters in baseball, and Google is building a big, long answer to try and explain this and then sending you to the Wikipedia page if you need more detail.
So these four kinds of things are causing a ton of consternation in our field. There was a study from Stone Temple Consulting, out in Boston, that Eric Enge and Mark Traphagen put together, where they looked and saw that over a large quantity of search results, I believe it was 800,000 search results set, almost 20%, 19% of those had rich answers in some format, direct answers in the SERPS, like one of these, and I think that even excluded number three here, the Knowledge Graph. So that's a lot of queries where Google is taking away, potentially, a ton of traffic.
You might say "Hey, well, in the long tail and in the chunky middle, it's probably not as bad as it is in the fat head of query demand." But this is still very significant for a lot of folks. So there are two ways to think about this. One is strategically, and one is tactically.
My first advice is on the strategy side of SEO. So when you're thinking about Knowledge Graph and instant answers and these kinds of things, how they affect your results, I'd ask;
"Is the branding of extracted answers a worthwhile SEO investment?" If you get this, like Wikipedia has here, is that actually worthwhile for you? Or is that something where you say, "You know what? We're not going to concentrate on it?" Therefore from saying, "Hey, that's not an investment for us, any time we start to see these types of results, we're no longer going to make a considerable SEO investment there. We don't really care if our competition gets it. We'd rather focus our energy, attention, dollars, people, time on the organic results, where we think we can earn a higher click-through rate and actual traffic, rather than just the brand association." Or you might say, "Brand association matters hugely. We want very much to be associated with baseball. We're trying to build this up. It would be great if we could replace Wikipedia here. We'd be thrilled even if we didn't get the traffic."
Then, you need to go through the step of actually building some analytics. We need to say, "Hey, how are we going to measure, when we get these kinds of results, the potential volume that's going on there, and then how are we going to record that as a success?" You won't be able to see it in your visitor analytics or in any metric that is directly associated with your website.
What kinds of content investments could Google replace with instant answers? Content investments that we are making or that we are planning to make. If they could replace them, how likely do we think that is, and does that change our strategy around what we want to invest in from a content perspective, from an SEO perspective, for the future?
If we say "Hey, you know what? We are in the online printing business, and we think that Google will soon have a price comparison, in-search, direct answer kind of a thing, like they have for flight search, in our field. You know what? Maybe we want to shy away from that, and we want to go down a different avenue for the content that we're going to create." That could be something that goes into your calculus around decision-making. I would urge you to at least consider the possibility and know where your threat vectors are from a "Google taking us over in the SERPS" perspective.
Do we want more customized answers? If you're Major League Baseball or the Seattle Mariners, this is actually probably a godsend. This is a wonderful thing, reason being it helps folks directly find, so fast, where they can watch it on television, where to buy tickets online. This is actually probably wonderful for the Seattle Mariners. They don't actually care that much, at least from a strategic perspective and overall perspective, whether this is costing them a lot of traffic to their website, because it's bringing great value to the brand. Google is sending folks directly to the authoritative site. So this means, from an SEO perspective, you don't get spammers or manipulators or ticket resellers, who are taking over this search space for them.
So depending on the kind of brand you are, the kind of organization you are, instant answers might be a great thing, in which case you might want to think about, "How can we partner more deeply with Google? What can we provide in a structured format? How do we get that information to them in that kind of way, where they will, hopefully, replace a lot of these fat-head queries with exactly what we're hoping they do in a fast, efficient manner for searchers?"
Next up is tactical plans to consider, and I think the first one's most important here.
When you are doing your keyword research and your keyword evaluation, I think one of the things that many, many folks are still missing from this is a column that looks at keyword opportunity. So historically, we've had a bunch of things when we do keyword research. Here's our keyword column. We look at difficulty. We might look at volume. We might look at potential value to the business. Maybe we're looking at how successful it was when we purchased that keyword and what the conversion rates were like, all those kinds of things, path to conversion, etc., etc.
But one of the things we have not historically focused on is keyword opportunity, meaning the click-through rate opportunity. You could do something like a bucket -- high, medium and low. I put HML here. You could say something like, "Hey, we think that this alters the click-through rate curve, random guess 30%, 40%, whatever it is," and use some numbers to classify those so that when you're actually doing keyword research and choosing which keywords to consider, you make the right kinds of decisions, because a lot of the time you might see, hey, this has high volume, the difficulty's not that bad, oh shoot, but Google has an instant extracted answer that is taking up 30% of the above-the-fold space or 40% of the above-the-fold space. SERP number one is probably getting 20% of the click-through rate that it would ordinarily get if that instant answer weren't there. So that needs to be a part of our calculations going forward.
What kinds of content and kinds of event are searchers who are not satisfied by the Knowledge Graph or instant answer listing, what are they searching for and how? That is an opportunity for us to get around this problem. If I search for "Seattle Mariners schedule," but what I'm actually looking for is I only want to see away games that are in three states that I'm going to be visiting, well, you know what? Actually, this isn't enough. I need to go directly to the page, and so that might be an intent that I'm going to try and serve very easily from a user experience perspective on the page that ranks first that's on seattle.mariners.mlb.com.
That question, if you can answer that effectively and find a bunch of those, you may, in fact, over time be able to get rid of those instant answers. You've probably seen, there have been examples, where Google had an instant answer, had a Knowledge Graph, got rid of it, and my perception is that a big reason for that is that searchers weren't clicking those. They weren't taking advantage of them and instead they were choosing results below the fold, below the instant answer, and so Google got rid of it. So nice thing there.
Should we be creating or avoiding structured data for Google to use, and will our competition do that? So you need to make a decision. Hey, should we create structured data that Google can easily pull into Knowledge Graph, easily pull into instant answers? If we don't do it, will our competition do it? Do we care if they do it, if we don't do it? It's a little bit of prisoner's dilemma sometimes, but you've got to make the call there, and I think that's something SEOs should do in their tactical plan around keywords.
Next, do we need to control for search traffic changes with Knowledge Graph and instant answers in our analytics or our forward-looking estimates? So if you say to yourself, "Hey, we started seeing some tests here. We expect Google's going to roll this out in our space, around our site. How is that going to impact us, and what does that mean for our year-over-year search estimates for SEO, traffic estimates for SEO? Or what does it mean for how much we think we can grow this year or in the future, that kind of thing?" Looking backwards, if this has been introduced, how much did that change our results sets and our traffic, and do we think that could happen more or less? Have we put that into our analytics so that we recognize, hey, our SEOs did great work. Google just took a lot of the traffic away from us, from an opportunity perspective?"
Then the last one I think we need to think about is very deep in the tactical trenches, but that is: Did the titles, descriptions, and even the keyword targets that were focused on, those need to focus on longer-tail or more specific types of questions and searcher intent. So we might say, "Hey, you know what? I'm willing to sacrifice ranking for 'Mariners mascot', but I really want to rank for 'Mariner Moose videos.' Or I really want to rank for 'Mariner Moose costumes.' I really want to rank for whatever those extra intents, those things deeper down the funnel, and those long-tail parts of the query might be." That could change the types of content and keywords that you invest in.
All right everyone, I know Knowledge Graph and instant answers can sometimes be very frustrating for us. But I hope you'll apply these tactics and recommend some more in the comments and that we'll see you again next week for another edition of Whiteboard Friday. Take care.
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When you're designing cover photos, graphics, and other social media assets, sometimes knowing the bare bones image dimensions isn't enough.
What if you wanted to place text or an arrow on your Facebook cover photo without it getting covered by the profile photo? And what about the shared link thumbnails on Facebook or in-stream photos on Twitter ... how big should those be?
Search led ad format spend, while mobile continued its steady growth.
A day after the alleged major update, I thought it would make sense to highlight where we are at in the cycle.
Yesterday Google suggested their fear messaging caused 4.7% of webmasters to move over to mobile friendly design since the update was originally announced a few months ago.
The 4.7% of the websites Google pushed to go mobile friendly likely include some sites which would have been mobile friendly anyhow by virtue of being new sites on hosted platforms with responsive designs. But for the rest of the sites, was the shift worth it?
That is a tough question.
It is too early to tell.
The problem with going early is you eat the expense upfront, while the rewards are still unknown.
If you are spending your own time & money and you believe in what you are doing and the longevity of a project then it doesn't matter too much if the rewards come slowly or never come. A sense of purpose & a sense of pride in your work is a form of payment.
However, if you are spending a client's money & you ring a 5 alarm fire to rush to make some technical change & then see no upside after the much hyped announcement, that erodes client trust. If there is no upside and a huge drop in revenue, then the consultant looks like a clueless idiot burning money for the sake of it doing various make work projects.
A few years ago a Google rep stated Panda would be folded into the regular algorithms. Then recently we were told it was a near realtime. Then we were told it was something where updates needed to be manually pushed out & it is something Google hasn't done in 4 months. If we trusted Google & conveyed any of these messages to clients, once again we looked like idiots. If we choose to invest client money based on the cycles and advice we are given, quite often that is a money incinerator.
Imagine dropping $30,000 on a link cleanup project where you remove links which were helping your Bing rankings but the Google update "coming soon" takes over a year to show up.
Invest money to lower your current income while you're waiting for Godat.
So after Google made a big show of this pending mobile update by pre-announcing it, speaking about it at multiple conferences, comparing it to Panda and Penguin & stating it would have a bigger impact, sending out millions of warning messages via Webmaster Tools, etc etc etc .. when the big day came, did Google make the people who trusted them & invested in their advice look good?
Not so much.
Ayima recently launched a SERP flux pulse tracker tool which shows desktop and mobile flux side-by-side.
As you can see, nothing happened.
So far, no rewards. Maybe they will come. Though here is a hypothetical example where it could be very much NOT worth it for some publishers to go mobile friendly...
Any form of penalty (even a false positive) can become self-reinforcing. And many of the things which seem like they might help could cause harm.
Did you jump the gun or wait and see?
Attribution is a great tool to keep close by when optimizing and especially finding the hidden value in a PPC account.
Posted by SarahBird
Why do we do it? Moz gets it's strength from the community of marketers and entrepreneurs that support it. We celebrated 10 years of our community last October. In some ways, the purpose of this report is to give you an inside look into our company. It's one of many lenses that tell the story of Moz.
Yep. I know. It's April. I'm not proud. Better late than never, right?
I had a very long and extensive version of this post planned, something closer to last year's extravaganza. I finally had to admit to myself that I was letting the perfect become the enemy of the good (or at least the done). There was no way I could capture an entire year's worth of ups and downs—along with supporting data—in a single blog post.
Without further ado, here's the meat-and-potatoes 2014 Year In Review (and here's an infographic with more statistics for your viewing pleasure!):
Moz ended 2014 with $31.3 million in revenue. About $30 million was recurring revenue (mostly from subscriptions to Moz Pro and the API).
Here's a breakdown of all our major revenue sources:
Compared to previous years, 2014 was a much slower growth year. We knew very early that it was going to be a tough year because we started Q1 with negative growth. We worked very hard and successfully shifted the momentum back to increasingly positive quarterly growth rates. I'm proud of what we've accomplished so far. We still have a long ways to go to meet our potential, but we're on the path.
In subscription businesses, If you start the year with negative or even slow growth it is very hard to have meaningful annual growth. All things being equal, you're better off having a bad quarter in Q4 than Q1. If you get a new customer in Q1, you usually earn revenue from that customer all year. If you get a new customer in Q4, it will barely make a dent in that year, although it should set you up nicely for the following year.
We exited 2014 on a good flight path, which bodes well for 2015. We slammed right into some nasty billing system challenges in Q1 2015, but still managed to grow revenue 6.5%. Mad props to the team for shifting momentum last year and for digging into the billing system challenges we're experiencing now.
We were very successful in becoming more efficient and managing costs in 2014. Our Cost of Revenue (COR), the cost of producing what we sell, fell by 30% to $8.2 million. These savings drove our gross profit margin up from 63% in 2013 to 74%.
Our operating profit increased by 30%. Here's a breakdown of our major expenses (both operating expenses and COR):
Total operating expenses (which don't include COR) clocked in at about $29.9 million this year.
The efficiency gains positively impacted EBITDA (Earnings Before Interest, Taxes, Depreciation, and Amortization) by pushing it up 50% year over year. In 2013, EBITDA was -$4.5 million. We improved it to -$2.1 million in 2014. We're a VC-backed startup, so this was a planned loss.
One of the most dramatic indicators of our improved efficiency in 2014 is the substantial decline in our consumption of cash.
In 2014, we spent $1.5 million in cash. This was a planned burn, and is actually very impressive for a startup. In fact, we are intentionally increasing our burn, so we don't expect EBITDA and cash burn to look as good in 2015! Hopefully, though, you will see that revenue growth rate increase.
Let's check in on some other Moz KPIs:
At the end of 2014, we reported a little over 27,000 Pro users. When billing system issues hit in Q1 2015, we discovered some weird under- and over-reporting, so the number of subscribers was adjusted down by about ~450 after we scrubbed a bunch of inactive accounts out of the database. We expect accounts to stabilize and be more reliable now that we've fixed those issues.
We launched Moz Local about a year ago. I'm amazed and thrilled that we were able to end the year managing 27,000 locations for a range of customers. We just recently took our baby steps into the UK, and we've got a bunch of great additional features planned. What an incredible launch year!
We published over 300 posts combined on the Moz Blog and YouMoz. Nearly 20,000 people left comments. Well done, team!
We continue to see good growth across many of our off-site communities, too:
Our content and social efforts are paying off with a 26% year-over-year increase in organic traffic.
The team grew to 149 people last year. We're at ~37% women, which is nowhere near where I want it to be. We have a long way to go before the team reflects the diversity of the communities around us.
Our paid, paid vacation perk is very popular with Mozzers, and why wouldn't it be? Everyone gets $3,000/year to use toward their vacations. In 2014, we spent over $420,000 to help our Mozzers take a break and get connected with matters most.
Last, but certainly not least, Mozzers continue to be generous (the 'G' in TAGFEE) and donate to the charities of their choice. In 2014, Mozzers donated $48k, and Moz added another $72k to increase the impact of their gifts. Combining those two figures, we donated $120k to causes our team members are passionate about. That's an average of $805 per employee!
Mozzers are optimists with initiative. I think that's why they are so generous with their time and money to folks in need. They believe the world can be a better place if we act to change it.
That's a wrap on 2014! A year with many ups and downs. Fortunately, Mozzers don't quit when things get hard. They embrace TAGFEE and lean into the challenge.
Revenue is growing again. We're still operating very efficiently, and TAGFEE is strong. We're heads-down executing on some big projects that customers have been clamoring for. Thank you for sticking with us, and for inspiring us to make marketing better every day.
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Linux virtualization refers to running one or more virtual machines on a physical computer that's operated by the Linux open source operating system.
SEW, ClickZ, ClickZ Live, and SES have been bought by Blenheim Chalcot in a move that is guaranteed to create a stronger brand that is bigger and better than ever before.
SEW, ClickZ, and SES have been bought by Blenheim Chalcot in a move that is guaranteed to create a stronger brand that is bigger and better than ever before.
If you’re redesigning or moving a site and your URLs are changing, you will need redirects. So save your site’s search equity and be an SEO hero by following this redirects for SEO plan.
Retailers are jumping on board with Google's shopping ads. here's a look at accounts that have been running shopping ads consistently.
Posted by CraigBradford
In the near future, I think Google Now could tell you are pregnant or diagnose you with a medical condition before your doctor ever could. Humans are great at recognising patterns but only if we know we are creating them or where to look. Remember the Target story of how they knew a young girl was pregnant before she or her father did? Increases in technology like smart watches and the trend of "the quantified self" mean messages like being told you are pregnant aren't impossible in the near future. So how do we go from weather reports and traffic updates to a medical diagnosis?
When Google, Yahoo and Bing announced Schema.org in 2011, search engines were still in the strings-to-things phase. In my opinion, Google, in particular, are already moving on from that goal. The most recent addition to the Schema.org vocabulary is actions. See, the Schema site for more details or my SMX Munich deck for more details.
In my presentation, I made the point that the future of structured data isn't about understanding what a thing is, it's about understanding what a thing can do. If search engines can understand what your website, app or other interfaces can do, and they can understand user intent, they can match queries to the best place to do that action. How does Google know what we want to do?
Many people have said that Google wants to become the ultimate personal assistant. Things like Google Now and conversational search reinforce this standpoint. However, a prerequisite for that position is the concept of time. For a computerised personal assistant to be truly as useful as the real thing, they need to be aware of the past, the present and more importantly the future.
Historically, Google and other search engines have dealt with things from the past. Webpages by their nature are in the past, or at best, live. This makes the anticipation and initiative that you would expect from great personal assistant difficult for Google. They have very little data to predict what you might want to do or are going to do in the future. Gmail and Google calendar are the two most obvious ones that come to mind (if you use them).
Forgetting privacy or intellectual property for a second, imagine Google had access to every app on your phone and the data within it. What might they be able to know about you?
Just the apps above could give Google access to:
While I was in Munich, I saw an announcement that Google had opened the Google Now API to a selection of hand-picked, third-party apps.
This got me thinking. I do not know what the relationship will be or what data Google would have access to but one of the apps that have been accepted to work with Google Now is Lyft. The example Google gave in the article was a generic prompt to order a cab. For example, you arrive at an airport and Google Now might push you a notification to get a cab:
While the Lyft example above is interesting, it made me realise that allowing apps to talk to each other via Google Now would essentially turn your smartphone into an IFTTT for your life. So rather than a generic Lyft alert, what if they combined a few apps? They could use my British Airways app to see I have an upcoming flight, Google maps to know when I've arrived in Munich, and my Gmail account to see where I am staying. There are probably specific hotel apps they could use too. Using this, rather than getting a generic get a car card, I get one that's already personalised the quote to where I'm going.
The ultimate personal assistant would not only tell us what we expect, they would tell us things we never thought to consider. This would only be made possible by advanced pattern recognition, anticipation, and initiative beyond the possibility of a human.
What patterns do you already create but don't currently correlate? If you feel sluggish or tired on a Thursday, we do not necessarily correlate that to something that you may be allergic to that you ate on Monday. Many people spend years with conditions such as gluten or lactose intolerance but never make the connection between what they eat and how they feel. Humans cannot easily track and analyse lots of data like that, computers can.
So how can Google tell you are pregnant? I am not a doctor but I suspect like the Target example, there may be early signs of pregnancy that we do not think about at the moment (biological or otherwise). For a start, there could be a process of first increasing the priority that a particular pattern receives. For example, there may be lots of small things that people change before trying to get pregnant. If you're using a lot of different apps combined with hardware like heart rate monitors and blood pressure monitors, it wouldn't be too difficult for Google to take an educated guess. Just using the information in the Target article we know people do things like:
After all of the above, let's not forget Google knows everything you've searched for online and your browsing history if you use Chrome. I do not think it would take much to guess someone is thinking about having a family based on his or her search history alone.
Let's assume that based on the above, Google lowers the "pregnancy card" trigger threshold. This means they look closer at changes that might suggest your pregnant. I am not a doctor, so bear with me while I think out loud. Other than urine or blood samples, what other quantitative data is there that you might be pregnant?
For context, I recently learned that eating something that you have an intolerance to can show an elevated heart rate for two hours after eating. One test to check for allergies is to track your heart rate throughout the day. This was where this idea came from in the first place. Using a smartwatch with a heart rate monitor, plus My Fitness Pal, Google could make suggestions that you are allergic to foods you never thought of due to recognising patterns in elevated heart rate after your meals. This made me wonder what else could be possible. There's a ton of tech for tracking:
Could Google make a guess from this data alone? I cannot stress enough about my lack of medical qualifications, but I wonder if pregnancy impacts things like REM and deep sleep changes, significant blood pressure or heart rate changes at certain times of the day. Who knows, and maybe one of these things alone wouldn't be enough to know for sure, but combined, I think it will not be long before pregnancy prediction or similar could be done.
Enough about pregnancy, (Google probably thinks I am looking to start a family) what else? What things using heart rate alone could Google diagnose or push to us in Google Now? Could they push notifications to people who are diabetic to remember to take insulin? Could they diagnose diabetes? Could they flag heart problems before it is too late? I have no idea, but I'm excited to see where things go in the next few years.
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To grow organic rankings safely, links have to be earned on the basis of great content. But if the reality is that only 2 percent of followers share content — what hope do you truly have of earning links if your audience doesn’t share or amplify?
The problem is rarely attributed to Google, but as ecosystem diversity has declined (and entire segments of the ecosystem are unprofitable to service), more people are writing things like: "The market for helping small businesses maintain a home online isn’t one with growing profits – or, for the most part, any profits. It’s one that’s heading for a bloody period of consolidation."
If you don't think Google wants to disrupt you out of a job, you've been asleep at the wheel for the past decade— Michael Gray (@graywolf) March 13, 2015
As Google sucks up more data, aggregates intent, and scrapes-n-displaces the ecosystem they get air cover for some of their gray area behaviors by claiming things are driven by the data & putting the user first.
Those "data" and altruism claims from Google recently fell flat on their face when the Wall Street Journal published a number of articles about a leaked FTC document.
That PDF has all sorts of goodies in it about things like blocking competition, signing a low margin deal with AOL to keep monopoly marketshare (while also noting the general philosophy outside of a few key deals was to squeeze down on partners), scraping content and ratings from competing sites, Google force inserting itself in certain verticals anytime select competitors ranked in the organic result set, etc.
As damning as the above evidence is, more will soon be brought to light as the EU ramps up their formal statement of objection, as Google is less politically connected in Europe than they are in the United States:
"On Nov. 6, 2012, the night of Mr. Obama’s re-election, Mr. Schmidt was personally overseeing a voter-turnout software system for Mr. Obama. A few weeks later, Ms. Shelton and a senior antitrust lawyer at Google went to the White House to meet with one of Mr. Obama’s technology advisers. ... By the end of the month, the FTC had decided not to file an antitrust lawsuit against the company, according to the agency’s internal emails."
What is wild about the above leaked FTC document is it goes to great lengths to show an anti-competitive pattern of conduct toward the larger players in the ecosystem. Even if you ignore the distasteful political aspects of the FTC non-decision, the other potential out was:
"The distinction between harm to competitors and harm to competition is an important one: according to the modern interpretation of antitrust law, even if a business hurts individual competitors, it isn’t seen as breaking antitrust law unless it has also hurt the competitive process—that is, that it has taken actions that, for instance, raised prices or reduced choices, over all, for consumers." - Vauhini Vara
Part of the reason the data set was incomplete on that front was for the most part only larger ecosystem players were consulted. Google engineers have went on record stating they aim to break people's spirits in a game of psychological warfare. If that doesn't hinder consumer choice, what does?
When the EU published their statement of objections Google's response showed charts with the growth of Amazon and eBay as proof of a healthy ecosystem.
The market has been consolidated down into a few big winners which are still growing, but that in and of itself does not indicate a healthy nor neutral overall ecosystem.
The long tail of smaller e-commerce sites which have been scrubbed from the search results is nowhere to be seen in such charts / graphs / metrics.
The other obvious "untruth" hidden in the above Google chart is there is no way product searches on Google.com are included in Google's aggregate metrics. They are only counting some subset of them which click through a second vertical ad type while ignoring Google's broader impact via the combination of PLAs along with text-based AdWords ads and the knowledge graph, or even the recently rolled out rich product answer results.
Who could look at the following search result (during anti-trust competitive review no less) and say "yeah, that looks totally reasonable?"
Google has allegedly spent the last couple years removing "visual clutter" from the search results & yet they manage to product SERPs looking like that - so long as the eye candy leads to clicks monetized directly by Google or other Google hosted pages.
Search was an integral piece of the web which (in the past) put small companies on a level playing field with larger players. That it no longer is.
"What kind of a system do you have when existing, large players are given a head start and other advantages over insurgents? I don’t know. But I do know it’s not the Internet." - Dave Pell
The above quote was about app stores, but it certainly parallels a rater system which enforces the broken window fallacy against smaller players while looking the other way on larger players, unless they are in a specific vertical Google itself decides to enter.
"That actually proves my point that they use Raters to rate search results. aka: it *is* operated manually in many (how high?) cases. There is a growing body of consensus that a major portion of Googles current "algo" consists of thousands of raters that score results for ranking purposes. The "algorithm" by machine, on the majority of results seen by a high percentage of people, is almost non-existent." ... "what is being implied by the FTC is that Googles criteria was: GoogleBot +10 all Yelp content (strip mine all Yelp reviews to build their database). GoogleSerps -10 all yelp content (downgrade them in the rankings and claim they aren't showing serps in serps). That is anticompetitive criteria that was manually set." - Brett Tabke
About 3 years ago I wrote a blog post about how branding plays into SEO & why it might peak. As much as I have been accused of having a cynical view, the biggest problem with my post was it was naively optimistic. I presumed Google's consolidation of markets would end up leading Google to alter their ranking approach when they were unable to overcome the established consensus bias which was subsidizing their competitors. The problem with my presumption is Google's reliance on "data" was a chimera. When convenient (and profitable) data is discarded on an as need basis.
Or, put another way, the visual layout of the search result page trumps the underlying ranking algorithms.
Google has still highly disintermediated brand value, but they did it via vertical search, larger AdWords ad units & allowing competitive bidding on trademark terms.
Around this same time Google pushed through a black PR smear job of Bing for doing a similar, lesser offense to Google on rare, made-up longtail searches which were not used by the general public.
While Google was outright stealing third party content and putting it front & center on core keyword searches, they had to use "about 100 “synthetic queries”—queries that you would never expect a user to type" to smear Bing & even numerous of these queries did not show the alleged signal.
Here are some representative views of that incident:
What is so crazy about the above quotes is Google engineers knew at the time what Google was doing with Google's scraping. I mentioned that contrast shortly after the above PR fiasco happened:
when popular vertical websites (that have invested a decade and millions of Dollars into building a community) complain about Google disintermediating them by scraping their reviews, Google responds by telling those webmasters to go pound sand & that if they don't want Google scraping them then they should just block Googlebot & kill their search rankings
Google's justification for not being transparent is "spammer" would take advantage of transparency to put inferior results front and center - the exact same thing Google does when it benefits the bottom line!
The following types of websites are likely to merit low landing page quality scores and may be difficult to advertise affordably. In addition, it's important for advertisers of these types of websites to adhere to our landing page quality guidelines regarding unique content.
- eBook sites that show frequent ads
- 'Get rich quick' sites
- Comparison shopping sites
- Travel aggregators
- Affiliates that don't comply with our affiliate guidelines
The anti-competitive conspiracy theory is no longer conspiracy, nor theory.
Key points highlighted by the European Commission:
- Google systematically positions and prominently displays its comparison shopping service in its general search results pages, irrespective of its merits. This conduct started in 2008.
- Google does not apply to its own comparison shopping service the system of penalties, which it applies to other comparison shopping services on the basis of defined parameters, and which can lead to the lowering of the rank in which they appear in Google's general search results pages.
- Froogle, Google's first comparison shopping service, did not benefit from any favourable treatment, and performed poorly.
- As a result of Google's systematic favouring of its subsequent comparison shopping services "Google Product Search" and "Google Shopping", both experienced higher rates of growth, to the detriment of rival comparison shopping services.
- Google's conduct has a negative impact on consumers and innovation. It means that users do not necessarily see the most relevant comparison shopping results in response to their queries, and that incentives to innovate from rivals are lowered as they know that however good their product, they will not benefit from the same prominence as Google's product.
Consensus bias is set to an absurdly high level to block out competition, slow innovation, and make the search ecosystem easier to police. This acts as a tax on newer and lesser-known players and a subsidy toward larger players.
Eventually that subsidy would be a problem to Google if the algorithm was the only thing that matters, however if the entire result set itself can be displaced then that subsidy doesn't really matter, as it can be retracted overnight.
Whenever Google has a competing offering ready, they put it up top even if they are embarrassed by it and 100% certain it is a vastly inferior option to other options in the marketplace.
That is how Google reinforces, then manages to overcome consensus bias.
How do you overcome consensus bias?
Posted by EricEnge
It's time to look at your content differently—time to start understanding just how good it really is. I am not simply talking about titles, keyword usage, and meta descriptions. I am talking about the entire page experience. In today's post, I am going to introduce the general concept of content quality analysis, why it should matter to you, and how to use term frequency (TF) analysis to gather ideas on how to improve your content.
TF analysis is usually combined with inverse document frequency analysis (collectively TF-IDF analysis). TF-IDF analysis has been a staple concept for information retrieval science for a long time. You can read more about TF-IDF and other search science concepts in Cyrus Shepard's excellent article here.
For purposes of today's post, I am going to show you how you can use TF analysis to get clues as to what Google is valuing in the content of sites that currently outrank you. But first, let's get oriented.
Start by asking yourself if your page provides a quality experience to people who visit it. For example, if a search engine sends 100 people to your page, how many of them will be happy? Seventy percent? Thirty percent? Less? What if your competitor's page gets a higher percentage of happy users than yours does? Does that feel like an "uh-oh"?
Let's think about this with a specific example in mind. What if you ran a golf club site, and 100 people come to your page after searching on a phrase like "golf clubs." What are the kinds of things they may be looking for?
Here are some things they might want:
This is really only a partial list, and the specifics of your site can certainly vary for any number of reasons from what I laid out above. So how do you figure out what it is that people really want? You could pull in data from a number of sources. For example, using data from your site search box can be invaluable. You can do user testing on your site. You can conduct surveys. These are all good sources of data.
Whatever you do, it's worth using many of these methods to determine what users want from the pages of your site and then using the resulting information to improve your overall site experience.
At some level, they clearly are. Clearly Google and Bing have evolved far beyond the initial TF-IDF concepts, but we can still use them to better understand our own content.
The first major indication we had that Google was performing content quality analysis was with the release of the Panda algorithm in February of 2011. More recently, we know that on April 21 Google will release an algorithm that makes the mobile friendliness of a web site a ranking factor. Pure and simple, this algo is about the user experience with a page.
Exactly how Google is performing these measurements is not known, but what we do know is their intent. They want to make their search engine look good, largely because it helps them make more money. Sending users to pages that make them happy will do that. Google has every incentive to improve the quality of their search results in as many ways as they can.
Ultimately, we don't actually know what Google is measuring and using. It may be that the only SEO impact of providing pages that satisfy a very high percentage of users is an indirect one. I.e., so many people like your site that it gets written about more, linked to more, has tons of social shares, gets great engagement, that Google sees other signals that it uses as ranking factors, and this is why your rankings improve.
But, do I care if the impact is a direct one or an indirect one? Well, NO.
TF-IDF analysis is more about relevance than content quality, but we can still use various precepts from it to help us understand our own content quality. One way to do this is to compare the results of a TF analysis of all the keywords on your page with those pages that currently outrank you in the search results. In this section, I am going to outline the basic concepts for how you can do this. In the next section I will show you a process that you can use with publicly available tools and a spreadsheet.
The simplest form of TF analysis is to count the number of uses of each keyword on a page. However, the problem with that is that a page using a keyword 10 times will be seen as 10 times more valuable than a page that uses a keyword only once. For that reason, we dampen the calculations. I have seen two methods for doing this, as follows:
The first method relies on dividing the number of repetitions of a keyword by the count for the most popular word on the entire page. Basically, what this does is eliminate the inherent advantage that longer documents might otherwise have over shorter ones. The second method dampens the total impact in a different way, by taking the log base 10 for the actual keyword count. Both of these achieve the effect of still valuing incremental uses of a keyword, but dampening it substantially. I prefer to use method 1, but you can use either method for our purposes here.
Once you have the TF calculated for every different keyword found on your page, you can then start to do the same analysis for pages that outrank you for a given search term. If you were to do this for five competing pages, the result might look something like this:
I will show you how to set up the spreadsheet later, but for now, let's do the fun part, which is to figure out how to analyze the results. Here are some of the things to look for:
You can then tag these words for further analysis. Once you are done, your spreadsheet may now look like this:
In order to make this fit into this screen shot above and keep it legibly, I eliminated some columns you saw in my first spreadsheet. However, I did a sample analysis for the movie "Woman in Gold". You can see the full spreadsheet of calculations here. Note that we used an automated approach to marking some items at "Low Ratio," "High Ratio," or "All Competitors Have, Client Does Not."
None of these flags by themselves have meaning, so you now need to put all of this into context. In our example, the following words probably have no significance at all: "get", "you", "top", "see", "we", "all", "but", and other words of this type. These are just very basic English language words.
But, we can see other things of note relating to the target page (a.k.a. the client page):
Note that the last item is only visible if you open the spreadsheet. The issues above could well be significant, as the lead actors, reviews, and other indications that the page has in-depth content. We see that competing pages that rank have details of the story, so that's an indication that this is what Google (and users) are looking for. The fact that the main key phrase, and the word "billing", are used to a proportionally high degree also makes it seem a bit spammy.
In fact, if you look at the information closely, you can see that the target page is quite thin in overall content. So much so, that it almost looks like a doorway page. In fact, it looks like it was put together by the movie studio itself, just not very well, as it presents little in the way of a home page experience that would cause it to rank for the name of the movie!
In the many different times I have done an analysis using these methods, I've been able to make many different types of observations about pages. A few of the more interesting ones include:
These types of observations are interesting and valuable, but it's important to stress that you shouldn't be overly mechanical about this. The value in this type of analysis is that it gives you a technical way to compare the content on your page with that of your competitors. This type of analysis should be used in combination with other methods that you use for evaluating that same page. I'll address this some more in the summary section of this below.
The full spreadsheet contains all the formulas so all you need to do is link in the keyword count data. I have tried this with two different keyword density tools, the one from Searchmetrics, and this one from motoricerca.info.
I am not endorsing these tools, and I have no financial interest in either one—they just seemed to work fairly well for the process I outlined above. To provide the data in the right format, please do the following:
This may sound a bit tedious (and it is), but it has worked very well for us at STC.
You can also use usability groups and a number of other methods to figure out what users are really looking for on your site. However, what this does is give us a look at what Google has chosen to rank the highest in its search results. Don't treat this as some sort of magic formula where you mechanically tweak the content to get better metrics in this analysis.
Instead, use this as a method for slicing into your content to better see it the way a machine might see it. It can yield some surprising (and wonderful) insights!
Posted by Everett
If eCommerce businesses hope to remain competitive with Amazon, eBay, big box brands, and other online retail juggernauts, they'll need to learn how to conduct content marketing, lead generation, and contact nurturing as part of a comprehensive inbound marketing strategy.
First, I will discuss some of the ways most online retailers are approaching email from the bottom of the funnel upward, and why this needs to be turned around. Then we can explore how to go about doing this within the framework of "Inbound Marketing" for eCommerce businesses. Lastly, popular marketing automation and email marketing solutions are discussed in the context of inbound marketing for eCommerce.
Email acquisition sources differ greatly between lead gen. sites and online stores. The biggest driver of email acquisition for most eCommerce businesses are their shoppers, especially when the business doesn't collect an email address for their contact database until the shopper provides it during the check-out process—possibly, not until the very end.
With most B2B/B2C lead gen. websites, the entire purpose of every landing page is to get visitors to submit a contact form or pick up the phone. Often, the price tag for their products or services is much higher than those of an eCommerce site or involves recurring payments. In other words, what they're selling is more difficult to sell. People take longer to make those purchasing decisions. For this reason, leads—in the form of contact names and email addresses—are typically acquired and nurtured without having first become a customer.
Whether it is a B2B or B2C website, lead gen. contacts (called leads) are thought of as potential customers (clients, subscribers, patients) who need to be nurtured to the point of becoming "sales qualified," meaning they'll eventually get a sales call or email that attempts to convert them into a customer.
On the other hand, eCommerce contacts are often thought of primarily as existing customers to whom the marketing team can blast coupons and other offers by email.
Retail sites typically don't capture leads at the top or middle of the funnel. Only once a shopper has checked out do they get added to the list. Historically, the buying cycle has been short enough that eCommerce sites could move many first-time visitors directly to customers in a single visit. But this has changed.
Unless your brand is very strong—possibly a luxury brand or one with an offline retail presence—it is probably getting more difficult (i.e. expensive) to acquire new customers. At the same time, attrition rates are rising. Conversion optimization helps by converting more bottom of the funnel visitors. SEO helps drive more traffic into the site, but mostly for middle-of-funnel (category page) and bottom-of-funnel (product page) visitors who may not also be price/feature comparison shopping, or are unable to convert right away because of device or time limitations.
Even savvy retailers publishing content for shoppers higher up in the funnel, such as buyer guides and reviews, aren't getting an email address and are missing a lot of opportunities because of it.
Here's a thought. If your eCommerce site has a 10 percent conversion rate, you're doing pretty good by most standards. But what happened to the other 90 percent of those visitors? Will you have the opportunity to connect with them again? Even if you bump that up a few percentage points with retargeting, a lot of potential revenue has seeped out of your funnel without a trace.
I don't mean to bash the eCommerce marketing community with generalizations. Most lead gen. sites aren't doing anything spectacular either, and a lot of opportunity is missed all around.
There are many eCommerce brands doing great things marketing-wise. I'm a big fan of Crutchfield for their educational resources targeting early-funnel traffic, and Neman Tools, Saddleback Leather and Feltraiger for the stories they tell. Amazon is hard to beat when it comes to scalability, product suggestions and user-generated reviews.
Sadly, most eCommerce sites (including many of the major household brands) still approach marketing in this way...
Established eCommerce brands have gigantic mailing lists (compared with lead gen. counterparts), to whom they typically send out at least one email each week with "offers" like free shipping, $ off, buy-one-get-one, or % off their next purchase. The lists are minimally segmented, if at all. For example, there might be lists for repeat customers, best customers, unresponsive contacts, recent purchasers, shoppers with abandoned carts, purchases by category, etc.
The missing points of segmentation include which campaign resulted in the initial contact (sometimes referred to as a cohort) and—most importantly—the persona and buying cycle stage that best applies to each contact.
Online retailers often send frequent "blasts" to their entire list or to a few of the large segments mentioned above. Lack of segmentation means contacts aren't receiving emails based on their interests, problems, or buying cycle stage, but instead, are receiving what they perceive as "generic" emails.
The result of these missing segments and the lack of overarching strategy looks something like this:
My, What a Big LIST You Have!
TIME reported in 2012 on stats from Responsys that the average online retailer sent out between five and six emails the week after Thanksgiving. Around the same time, the Wall Street Journal reported that the top 100 online retailers sent an average of 177 emails apiece to each of their contacts in 2011. Averaged out, that's somewhere between three and four emails each week that the contact is receiving from these retailers.
The better to SPAM you with!
A 2014 whitepaper from SimpleRelevance titled Email Fail: An In-Depth Evaluation of Top 20 Internet Retailer's Email Personalization Capabilities ( PDF) found that, while 70 percent of marketing executives believed personalization was of "utmost importance" to their business...
"Only 17 percent of marketing leaders are going beyond basic transactional data to deliver personalized messages to consumers."
Speaking of email overload, the same report found that some major online retailers sent ten or more emails per week!
All too often, the eCommerce business will carry around big, dead lists of contacts who don't even bother reading their emails anymore. They end up scrambling toward other channels to "drive more demand," but because the real problems were never addressed, this ends up increasing new customer acquisition costs.
The cycle looks something like this:
It's like trying to fill your funnel with a bucket full of holes, some of them patched with band-aids.
Inbound marketing allows online retailers to stop competing with Amazon and other "price focused" competitors with leaky funnels, and to instead focus on:
Each of these areas will be covered in more detail below. First, let's take a quick step back and define what it is we're talking about here.
A lot of people think "inbound marketing" is just a way some SEO agencies are re-cloaking themselves to avoid negative associations with search engine optimization. Others think it's synonymous with "internet marketing." I think it goes more like this:
Inbound marketing is to Internet marketing as SEO is to inbound marketing: One piece of a larger whole.
There are many ways to define inbound marketing. A cursory review of definitions from several trusted sources reveals some fundamental similarities :
"Inbound Marketing is the practice of earning traffic and attention for your business on the web rather than buying it or interrupting people to get it. Inbound channels include organic search, social media, community-building content, opt-in email, word of mouth, and many others. Inbound marketing is particularly powerful because it appeals to what people are looking for and what they want, rather than trying to get between them and what they're trying to do with advertising. Inbound's also powerful due to the flywheel-effect it creates. The more you invest in Inbound and the more success you have, the less effort required to earn additional benefit."
"Inbound Marketing is a collection of marketing activities that leverage remarkable content to penetrate earned media channels such as Organic Search, Social Media, Email, News and the Blogosphere with the goal of engaging prospects when they are specifically interested in what the brand has to offer."
This quote is from 2012, and is still just as accurate today. It's from an Inbound.org comment thread where you can also see many other takes on it from the likes of Ian Lurie, Jonathon Colman, and Larry Kim.
"Inbound Marketing is a multi-channel, buyer-centric approach to online marketing that involves attracting, engaging, nurturing and converting potential customers from wherever they are in the buying cycle."
From Inflow's Inbound Services page.
"Inbound marketing refers to marketing activities that bring visitors in, rather than marketers having to go out to get prospects' attention. Inbound marketing earns the attention of customers, makes the company easy to be found, and draws customers to the website by producing interesting content."
"Inbound marketing" refers to marketing activities that bring leads and customers in when they're ready, rather than you having to go out and wave your arms to try to get people's attention."
"Instead of the old outbound marketing methods of buying ads, buying email lists, and praying for leads, inbound marketing focuses on creating quality content that pulls people toward your company and product, where they naturally want to be."
Via Hubspot, a marketing automation platform for inbound marketing.
When everyone has their own definition of something, it helps to think about what they have in common, as opposed to how they differ. In the case of inbound, this includes concepts such as:
The magic happens when retailers begin to hyper-segment their list based on buyer personas and other relevant information (i.e. what they've downloaded, what they've purchased, if they abandoned their cart...). This all starts with audience research to develop personas. If you need more information on persona development, try these resources:
Once personas are developed, retailers should choose one on which to focus. A complete campaign strategy should be developed around this persona, with the aim of providing the "right value" to them at the "right time" in their buyer's journey.
We've developed a quick-start guide in the form of a checklist for eCommerce marketers who want to get started with inbound marketing, which you can access below.
Hands-on experience running one campaign will teach you more about inbound marketing than a dozen articles. My advice: Just do one. You will make mistakes. Learn from them and get better each time.
Below is an example of how a hypothetical inbound marketing campaign might play out, assuming you have completed all of the steps in the checklist above. Imagine you handle marketing for an online retailer of high-end sporting goods.
When segmenting visitors and customers for a "high-end sporting goods / camping retailer" based on the East Coast, you identified a segment of "Trail Hikers." These are people with disposable income who care about high-quality gear, and will pay top dollar if they know it is tested and reliable. The top trail on their list of destinations is the Appalachian Trail (AT).
Tommy's first action is to do "top of the funnel" research from search engines (one reason why SEO is still so important to a complete inbound marketing strategy).
A search for "Hiking the Appalachian Trail" turns up your article titled "What NOT to Pack When Hiking the Appalachian Trail," which lists common items that are bulky/heavy, and highlights slimmer, lighter alternatives from your online catalog.
It also highlights the difference between cheap gear and the kind that won't let you down on your 2,181 mile journey through the wilderness of Appalachia, something you learned was important to Tommy when developing his persona. This allows you to get the company's value proposition of "tested, high-end, quality gear only" in front of readers very early in their buyer's journey—important if you want to differentiate your site from all of the retailers racing Amazon to the bottom of their profit margins.
So far you have yet to make "contact" with AT Hiker Tommy. The key to "acquiring" a contact before the potential customer is ready to make a purchase is to provide something of value to that specific type of person (i.e. their persona) at that specific point in time (i.e. their buying cycle stage).
In this case, we need to provide value to AT Hiker Tommy while he is getting started on his research about hiking the Appalachian Trail. He has an idea of what gear not to bring, as well as some lighter, higher-end options sold on your site. At this point, however, he is not ready to buy anything without researching the trail more. This is where retailers lose most of their potential customers. But not you. Not this time...
On the "What NOT to Pack When Hiking the Appalachian Trail" article (and probably several others), you have placed a call-to-action (CTA) in the form of a button that offers something like:
Download our Free 122-page Guide to Hiking the Appalachian Trail
This takes Tommy to a landing page showcasing some of the quotes from the book, and highlighting things like:
"We interviewed over 50 'thru-hikers' who completed the AT and have curated and organized the best first-hand tips, along with our own significant research to develop a free eBook that should answer most of your questions about the trail."
By entering their email address potential customers agree to allow you to send them the free PDF downloadable guide to hiking the AT, and other relevant information about hiking.
An automated email is sent with a link to the downloadable PDF guide, and several other useful content links, such as "The AT Hiker's Guide to Gear for the Appalachian Trail"—content designed to move Tommy further toward the purchase of hiking gear.
If Tommy still has not made a purchase within the next two weeks, another automated email is sent asking for feedback about the PDF guide (providing the link again), and to again provide the link to the "AT Hiker's Guide to Gear..." along with a compelling offer just for him, perhaps "Get 20% off your first hiking gear purchase, and a free wall map of the AT!"
Having Tommy's email address also allows you to hyper-target him on social channels, while also leveraging his initial visit to initiate retargeting efforts.
Eventually Tommy makes a purchase, and he may or may not receive further emails related to this campaign, such as post-purchase emails for reviews, up-sells and cross-sells.
Upon checkout, Tommy checked the box to opt-in to weekly promotional emails. He is now on multiple lists. Your marketing automation system will automatically update Tommy's status from "Contact" or lead, to "Customer" and potentially remove or deactivate him from the marketing automation system database. This is accomplished either by default integration features, or with the help of integration tools like Zapier and IFTTT.
You have now nurtured Tommy from his initial research on Google all the way to his first purchase without ever having sent a spammy newsletter email full of irrelevant coupons and other offers. However, now that he is a loyal customer, Tommy finds value in these bottom-of-funnel email offers.
Every inbound marketing campaign will have its own mix of appropriate channels. This post has focused mostly on email because acquiring the initial permission to contact the person is what fuels most of the other features offered by marketing automation systems, including:
Inbound has, for the the most part, been applied to businesses in which the website objective is to generate leads for a sales team to follow-up with and close the deal. An examination of various marketing automation platforms—a key component of scalable inbound marketing programs—highlights this issue.
Most of the major marketing automation systems can be be used very effectively as the backbone of an inbound marketing program for eCommerce businesses. However, only one of them (Silverpop) has made significant efforts to court the eCommerce market with content and out-of-box features. The next closest thing is Hubspot, so let's start with those two:
Unlike the other platforms below, right out of the box Silverpop allows marketers to tap into very specific behaviors, including the items purchased or left in the cart.
You can easily segment based on metrics like the Recency, Frequency and Monetary Value (RFM) of purchases:
You can automate personalized shopping cart abandonment recovery emails:
You can integrate with many leading brands offering complementary services, including: couponing, CRM, analytics, email deliverability enhancement, social and most major eCommerce platforms.
What you can't do with Silverpop is blog, find pricing info on their website, get a free trial on their website or have a modern-looking user experience. Sounds like an IBMⓇ company, doesn't it?
Out of all the marketing automation platforms on this list, HubSpot is the most capable of handling "inbound marketing" campaigns from start to finish. This should come as no surprise, given the phrase is credited to Brian Halligan, HubSpot's co-founder and CEO.
While they don't specifically cater to eCommerce marketing needs with the same gusto they give to lead gen. marketing, HubSpot does have an eCommerce landing page and a demo landing page for eCommerce leads, which suggests that their own personas include eCommerce marketers. Additionally, there is some good content on their blog written specifically for eCommerce.
HubSpot has allowed some key partners to develop plug-ins that integrate with leading eCommerce platforms. This approach works well with curation, and is not dissimilar to how Google handles Android or Apple handles their approved apps.
The Magento Connector for HubSpot, which costs $80 per month, was developed by EYEMAGiNE, a creative design firm for eCommerce websites. A similar HubSpot-approved third-party integration is on the way for Bigcommerce.
You can also use HubSpot's native integration capabilities with Zapier to sync data between HubSpot and most major eCommerce SaaS vendors, including the ones above, as well as WooCommerce, Shopify, PayPal, Infusionsoft and more. However, the same could be said of some of the other marketing automation platforms, and using these third-party solutions can sometimes feel like fitting a square peg into a round hole.
HubSpot can and does handle inbound marketing for eCommerce websites. All of the features are there, or easy enough to integrate. But let's put some pressure on them to up their eCommerce game even more. The least they can do is put an eCommerce link in the footer:
Despite the lack of clear navigation to their eCommerce content, HubSpot seems to be paying more attention to the needs of eCommerce businesses than the rest of the platforms below.
Nothing about Marketo's in-house marketing strategy suggests "Ecommerce Director Bob" might be one of their personas. The description for each of their marketing automation packages (from Spark to Enterprise) mentions that it is "for B2B" websites.
Driving Sales could apply to a retail business so I clicked on the link. Nope. Clearly, this is for lead generation.
Passing "purchase-ready leads" over to your "sales reps" is a good example of the type of language used throughout the site.
Make no mistake, Marketo is a top-notch marketing automation platform. Powerful and clean, it's a shame they don't launch a full-scale eCommerce version of their core product. In the meantime, there's the Magento Integration for Marketo Plug-in developed by an agency out of Australia called Hoosh Marketing.
I've never used this integration, but it's part of Marketo's LaunchPoint directory, which I imagine is vetted, and Hoosh seems like a reputable agency.
Their pricing page is blurred and gated, which is annoying, but perhaps they'll come on here and tell everyone how much they charge.
As with all others except Silverpop, the Marketo navigation provides no easy paths to landing pages that would appeal to "Ecommerce Director Bob."
This option is a SalesForce product, so—though I've never had the opportunity to use it—I can imagine Pardot is heavy on B2B/Sales and very light on B2C marketing for retail sites.
The hero image on their homepage says as much.
Again, no mention of eCommerce or retail, but clear navigation to lead gen and sales.
Eloqua, now part of the Oracle Marketing Cloud (OMC), has a landing page for the retail industry, on which they proclaim:
"Retail marketers know that the path to lifelong loyalty and increased revenue goes through building and growing deep client relationships."
Since when did retail marketers start calling customers clients?
The Integration tab on OMC's "...Retail.html" page helpfully informs eCommerce marketers that their sales teams can continue using CRM systems like SalesForce and Microsoft Dynamics but doesn't mention anything about eCommerce platforms and other SaaS solutions for eCommerce businesses.
There are many other players in this arena. Though I haven't used them yet, three I would love to try out are SharpSpring, Hatchbuck and Act-On. But none of them appear to be any better suited to handle the concerns of eCommerce websites.
The purpose of the section above wasn't to highlight deficiencies in the tools themselves, but to illustrate a gap in who they are being marketed to and developed for.
So far, most of your eCommerce competitors probably aren't using tools like these because they are not marketed to by the platforms, and don't know how to apply the technology to online retail in a way that would justify the expense.
The key concepts behind inbound marketing apply just as much to online retail as they do to lead generation.
In order to "do inbound marketing," a marketing automation system isn't even strictly necessary (in theory). They just help make the activities scalable for most businesses.
They also bring a lot of different marketing activities under one roof, which saves time and allows data to be moved and utilized between channels and systems. For example, what a customer is doing on social could influence the emails they receive, or content they see on your site. Here are some potential uses for most of the platforms above:
Assuming you don't have the budget for a marketing automation system, but already have a good email marketing platform, you can still get started with inbound marketing. Eventually, however, you may want to graduate to a dedicated marketing automation solution to reap the full benefits.
Most of the marketing automation systems claim to replace your email marketing platform, while many email marketing platforms claim to be marketing automation systems. Neither statement is completely accurate.
Marketing automation systems, especially those created specifically for the type of "inbound" campaigns described above, provide a powerful suite of tools all in one place. On the other hand, dedicated email platforms tend to offer "email marketing" features that are better, and more robust, than those offered by marketing automation systems. Some of them are also considerably cheaper—such as MailChimp—but those are often light on even the email-specific features for eCommerce.
Email "blasts" in the form of B.O.G.O., $10 off or free shipping offers can still be very successful in generating incremental revenue boosts — especially for existing customers and seasonal campaigns.
The conversion rate on a 20% off coupon sent to existing customers, for instance, would likely pulverize the conversion rate of an email going out to middle-of-funnel contacts with a link to content (at least with how CR is currently being calculated by email platforms).
Inbound marketing campaigns can also offer quick wins, but they tend to focus mostly on non-customers after the first segmentation campaign (a campaign for the purpose of segmenting your list, such as an incentivised survey). This means lower initial conversion rates, but long-term success with the growth of new customers.
Here's a good bet if works with your budget: Rely on a marketing automation system for inbound marketing to drive new customer acquisition from initial visit to first purchase, while using a good email marketing platform to run your "promotional email" campaigns to existing customers.
If you have to choose one or the other, I'd go with a robust marketing automation system.
Some of the most popular email platforms used by eCommerce businesses, with a focus on how they handle various Inbound Marketing activities, include:
This platform builds in features like abandoned cart recovery, advanced email list segmentation and automated email workflows that nurture contacts over time.
They also offer a host of eCommerce-related features that you just don't get with marketing automation systems like Hubspot and Marketo. This includes easy integration with a variety of eCommerce platforms like ATG, Demandware, Magento, Miva Merchant, Mozu and MarketLive, not to mention apps for coupons, product recommendations, social shopping and more. Integration with enterprise eCommerce platforms is one reason why Bronto is seen over and over again when browsing the Internet Retailer Top 500 reports.
On the other hand, Bronto—like the rest of these email platforms—doesn't have many of the features that assist with content marketing outside of emails. As an "inbound" marketing automation system, it is incomplete because it focuses almost solely on one channel: email.
Another juggernaut in eCommerce email marketing platforms, Vertical Response, has even fewer inbound-related features than Bronto, though it is a good email platform with a free version that includes up to 1,000 contacts and 4,000 emails per month (i.e. 4 emails to a full list of 1,000).
Responsys (the email platform), like Eloqua (the marketing automation system) was gobbled up by Oracle and is now part of their "Marketing Cloud."
It has been my experience that when a big technology firm like IBM or Oracle buys a great product, it isn't "great" for the users. Time will tell.
Out of the established email platforms for eCommerce, Listrak may do the best job at positioning themselves as a full inbound marketing platform.
Listrak's value proposition is that they're an "Omnichannel" solution. Everything is all in one "Single, Integrated Digital Marketing Platform for Retailers." The homepage image promises solutions for Email, Mobile, Social, Web and In-Store channels.
I haven't had the opportunity to work with Listrak yet, but would love to hear feedback in the comments on whether they could handle the kind of persona-based content marketing and automated email nurturing campaigns described in the example campaign above.
Congratulations for making this far! Here are a few things I hope you'll take away from this post:
There is a lot of great content on the topic of Inbound marketing, some of which has greatly informed my own understanding and approach. Here are a few resources you may find useful as well.