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Let Data Take the Wheel – Using API-Integrated Reporting Dashboards

Posted by IanWatson

Some say the only constant thing in this world is change — and that seems to go double for the online marketing and SEO industry. At times this can seem daunting and sometimes insurmountable, but some have found ways to embrace the ambiguity and even thrive on it. Their paths and techniques may all differ slightly, but a commonality exists among them.

That commonality is the utilization of data, mainly via API-driven custom tools and dashboards. APIs like Salesforce’s Chatter, Facebook’s Graph, and our very own Mozscape all allow for massive amounts of useful data to be integrated into your systems.

So, what do you do with all that data?

The use cases are limitless and really depend on your goals, business model, and available resources. Many in our industry, including myself, still rely heavily upon spreadsheets to manage large data sets.

However, the amount of native data and data within reach has grown drastically, and can quickly become unwieldy.

An example of a live reporting dashboard from Klipfolio.

Technology to the rescue!

Business intelligence (BI) is a necessary cog in the machine when it comes to running a successful business. The first step to incorporating BI into your business strategy is to adopt real-time reporting. Much like using Google Maps (yet another API!) on your phone to find your way to a new destination, data visualization companies like Klipfolio, Domo, and Tableau have built live reporting dashboards to help you navigate the wild world of online marketing. These interactive dashboards allow you in integrate data from several sources to better assist you in making real-time decisions.

A basic advertising dashboard.

For example, you could bring your ad campaign, social, and web analytics data into one place and track key metrics and overall performance in real-time. This would allow you to delegate extra resources towards what's performing best, pulling resources from lagging activities in the funnel as they are occurring. Or perhaps you want to be ahead of the curve and integrate some deep learning into your analysis? Bringing in an API like Alchemy or a custom set-up from Algorithmia could help determine what the next trends are before they even happen. This is where the business world is heading; you don’t want to fall behind.

Resistance is futile.

The possibilities of real-time data analysis are numerous, and the first step towards embracing this new-age necessity is to get your first, simple dashboard set up. We're here to help. In fact, our friends at Klipfolio were nice enough to give us step-by-step instructions on integrating our Mozscape data, Hubspot data, and social media metrics into their live reporting dashboard — even providing a live demo reporting dashboard. This type of dash allows you to easily create reports, visualize changes in your metrics, and make educated decisions based on hard data.

Create a live reporting dashboard featuring Moz, Hubspot and social data

1. First, you'll need to create your Mozscape API key. You'll need to be logged into your existing Moz account, or create a free community or pro Moz account. Once you're logged in and on the API key page, press "Generate Key."

2. This is the key you'll use to access the API and is essentially your password. This is also the key you'll use for step 6, when you're integrating this data into Klipfolio.

3. Create a free 14-day Klipfolio trial. Then select "Add a Klip."

4. The Klip Gallery contains pre-built widgets for your whatever your favorite services might be. You can find Klips for Facebook, Instagram, Alexa, Adobe, Google Adwords and Analytics, and a bunch of other useful integrations. They're constantly adding more. Plus, in Klipfolio, you can build your own widgets from scratch.

For now, let’s keep it simple. Select "Moz" in the Klip Gallery.

5. Pick the Klip you'd like to add first, then click "Add to Dashboard."

6. Enter your API key and secret key. If you don’t have one already, you can get your API key and secret ID here.

7. Enter your company URL, followed by your competitors' URLs.

8. Voilà — it’s that easy! Just like that, you have a live look at backlinks on your own dash.

9. From here, you can add any other Moz widgets you want by repeating steps 5–8. I chose to add in MozRank and Domain Authority Klips.

10. Now let’s add some social data streams onto our dash. I'm going to use Facebook and Twitter, but each of the main social media sites have similar setup processes.

11. Adding in other data sources like Hubspot, Searchmetrics, or Google Analytics simply requires you to bet set up with those parties and to allow Klipfolio access.

12. Now that we have our Klips set up, the only thing left to do is arrange the layout to your liking.

After you have your preferred layout, you're all set! You've now entered the world of business intelligence with your first real-time reporting dashboard. After the free Klipfolio trial is complete, it's only $20/month to continue reporting like the pros. I haven't found many free tools in this arena, but this plan is about as close as you’ll come.

Take a look at a live demo reporting dash, featuring all of the sources we just went over:

Click to see a larger version.


Just like that, you've joined the ranks of Big SEO, reporting like the big industry players. In future posts we'll bring you more tutorials on building simple tools, utilizing data, and mashing it up with outside sources to better help you navigate the ever-changing world of online business. There's no denying that, as SEO and marketing professionals, you're always looking for that next great innovation to give you and your customers a competitive advantage.

From Netflix transitioning into an API-centric business to Amazon diving into the API management industry, the largest and most influential companies out there realize that utilizing large data sets via APIs is the future. Follow suit: Let big data and business intelligence be your guiding light!

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Google Keyword Planner's Dirty Secrets

Posted by rjonesx.

Sometimes our best data sources aren't exactly up to par. While nearly every search marketer will rely on Google Keyword Planner data at one point or another, especially while doing keyword research, the reality is that the data is often untrustworthy and should be viewed with great skepticism. Whether you plan to use it to help build a paid search campaign or determine which content to write, there are huge caveats to the numbers presented as Average Search Volume. Today, I want to walk through a number of the "gotchas" in Google Keyword Planner data so you can do better keyword research and make smarter decisions for you or your clients' sites.

Dirty secret #1: Rounded averages

By far, the most-used piece of data from Google Keyword Planner is the "Average Monthly Search Volume" metric. This key data point is used in everything from basic decisions on what keywords to use in an ad campaign to complex traffic prediction curves. But can we trust it?

Suppose you run a sports website and two keywords pop up in the recommendations: baseball scores and basketball games. Google Keyword Planner lets us know that each of these keywords has an Average Monthly Search Volume of 201,000. At first glance, you should be able to choose either of these keywords and expect similar traffic results, right?

Wrong. The "Average Monthly Search Volume" is more than just an average; it's rounded to the nearest-volume-bucket (which I will describe later). We know this is the case because Google Keyword Planner also exposes the last 12 months of traffic data. If we average that data, we will see that baseball scores receives 217,275 visits per month, while basketball games averages only 205,750! That is a difference of over 10,000 searches per month, which is obscured by Google KWP's rounding algorithm.

When we took a sample of keywords at the 201,000 Average Monthly Search volume, the standard deviation was 14,621 in the "actual average." In some cases, it was off by over 40,000 monthly searches per month! If you don't look at the last 12 months of data, your annual traffic estimates will likely be off by tens of thousands of visits. What causes this anomaly?

Dirty secret #2: Traffic buckets

Google Keyword Planner uses "buckets" to group keywords by traffic volume. When a keyword returns a traffic volume of 201,000, it isn't because the keyword was actually visited that many times, or really that it was particularly close to the number 201,000, but just that it was closer to 201,000 than the next biggest bucket of 246,000. The next lower bucket is 165,000, which gives us a nice 80,000-searches-per-month wiggle room — within which a keyword might actually fall and still be categorized as 201,000 by Keyword Planner.

After analyzing a massive data set, we found that Google has around 85 different "buckets" for traffic, which are logarithmically proportioned. This means that long tail keywords might fall into buckets which only differ by 10–20 searches at a time, while head tail keywords might see gaps of hundreds of thousands of searches per month. The bigger the search volume, the less certain you can be about the accuracy of the Average Monthly Searches, especially relative to other terms that fall in the same group. In fact, the largest buckets have variances of of nearly a quarter million searches per month!

Google uses this rounding procedure for convenience and, likely, to take into account the real month-to-month variance which can be huge for these very popular terms.

Dirty secret #3: Hidden keywords

Rand had an excellent write up on this issue a while back if you want to read the full details or want a more in-depth look at the problem. However, I thought I'd just throw out some stats here to show you just how ridiculous the recommendation system can be relative to the reality of related words and phrases. Let's start with the phrase "football." In this example, we will start with using GrepWords data to find the most valuable words that contain "football" in them. Then, we simply ask Google what they recommend. How close do they match? What is missed?

The top 3 most-trafficked football-based keywords weren't recommended to us, and only 4 of Google's recommended made it into the top 10. In fact, when we analyzed dozens of Google keyword recommendation reports, we found that only 35% of the keywords were among the most trafficked terms.

It appears that Google Keyword Planner is simply trying to provide a diverse cross-section of terms, but for marketers it means you potentially miss out on huge opportunities unless you dig much deeper. You can battle back against this "feature" by choosing more short-tail terms to seed your searches and setting volume and CPC limits, as the recommendations get stronger and stronger the more specific you get. In the end, though, you're going to miss out on some great terms if you've restricted your research to only Google Keyword Planner.

Dirty secret #4: Combination inconsistencies

If you're like me and spelling isn't your forte, you have certainly seen Google give you the "showing results for {correct spelling}." This is very useful for the searcher, but throws a pretty big wrench into keyword volume metrics. What does Google do in these situations? Does it count all the traffic towards correctly spelled keyword (which is actually showing in the search results) or does it count the traffic toward the misspelling or variation? Well, it turns out it's a mixed bag. Let's take a look at a fairly popular term Texas A&M Football.

In the above picture we see several variations of how one might search for the concept Texas A&M Football.

Keyword Corrected? Distinct Volume Texas A&M Football No Yes Texas A and M Football No Yes Texas AM Football Yes Yes Texas A & M Football No Yes Texas A& M Football Yes Yes

Notice that whether or not the keyword is mapped to the canonical spelling makes no difference, in this case, for the total search volume. Even though many keywords will show you Texas A&M results, Google's volume count is only for the correct spelling of the term.

Now here's where it starts to matter. Let's say that you run a site that sells football attire and you're deciding which schools to include. You look up Google's Keyword Planner data and see that "Texas A&M Football" and "FSU Football" are both searched 201,000 times a month. These keywords seem equal in terms of volume but, in reality, there are many more keywords that are mapped organically to the phrase "Texas A&M Football," which makes its combined search volume much higher. In this particular case, there are several thousand visitors a year that you might miss out on by choosing "FSU Football" over "Texas A&M Football" simply because Google doesn't combine the keywords in Keyword Planner despite doing so in organic search.

This might seem like a reasonable compromise. The Keyword Planner is giving you back the search counts for the keywords, regardless of whether those searches are redirected to a different phrase. This would be appropriate if it was consistent, but with certain punctuation in terms we see Google treat the case completely differently. Take the search terms and facebook com. Google reports that both of these terms are searched 7.8 million times a month. Clearly these two variants are not searched an identical number of times; Google has simply mapped the keywords together BOTH in organic search results AND in volume. This forces keyword researchers to build huge keyword lists and go line-by-line removing the edge cases.

Here's a quick tip for you Excel experts out there: Look into using Jaro Winkler distance to find very similar terms that have identical search volume. Often these terms are mapped both in organic and in volume, and you can find those exclusions easily.

Dirty secret #5: Strange recommendations

Sometimes Google Keyword Planner gets the keyword recommendations completely wrong. Here are a couple of the examples that I was able to pull in just a few minutes of brainstorming:

Starting Keyword Recommended Keyword baseball glove boxing glove pigeon cabins calamari pork chops rap country music

Because Google Keyword Planner uses more than just phrase matching to build their recommended keywords, you will regularly find some truly strange entries in your recommended keyword list, or connections that a computer might make but a human never would. Unfortunately, this means you have to be very careful about what you get back, going keyword by keyword if you want to start a paid search campaign based on what's been returned. You simply can't be confident in the relevancy of the results. Can you imagine how many webmasters just blindly added Google's recommendations to their advertising campaigns?

All is not lost

Luckily, there is more than one way to get at and improve the Keyword Planner data using clickstream data sources. For example, we know of two keyword data sources — and SimilarWeb — which correlate nicely with Google Keyword Planner volumes.

While this data from SimilarWeb is very useful, building a more accurate prediction of search volume for a term requires that you build a regression model comparing the user data to Google's estimates. Moreover, demographic differences between the whole Google user base and those included in the user panels of SimilarWeb and mean that building a ubiquitous regression model across all the keyword data might not be the best, as the users tracked by SimilarWeb and might be biased towards different topics. The solution is to build models around topically-related keywords.

For example, instead of modeling all the keywords against one another, if Google Keyword Planner gave you 2 keywords on the same topic with the same keyword bucket (like 201,000 searches per month), you could build a regression model on the fly comparing a sample of topically-related keywords, using that to predict with greater granularity the performance of the two seemingly identical keywords.

While this user data helps you defeat issues of granularity, getting better (both more thorough and more accurate) recommendations for keywords can be a little more difficult. Your best bet here is to use keyword data aggregators like GREPWords,, or the upcoming Moz Keyword Explorer.

Keyword Planner is dead. Long live Keyword Planner

Unfortunately, despite all of the strange quirks and outright deceptions of Google Keyword Planner, it's the best thing we really have going for us in terms of getting search volume data out of Google. We can potentially refine some of the data with clickstream data, or get estimates by running Google Adwords campaigns and watching impression counts, or even looking in Google Search Console. But none of these are strong replacements for the Google Keyword Planner.

Instead of letting Google Keyword Planner's problems get in the way of your keyword research, use it to your advantage. Look for the edge cases where a keyword has a ton of misspellings mapped to the correct version, but not combined into the volume score. This could be a great win that your competitors are overlooking because the head term looks smaller than it really is. Wherever there's bad data, there's also money to be made in sweating the details. So, put your gloves on and get to scrubbing your Keyword Planner data. Somewhere beneath the rough is a diamond.

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Persona Research in Under 5 Minutes

Posted by CraigBradford

Well-researched personas can be a useful tool for marketers, but to do it correctly takes time. But what if you don’t have extra time? Using a mix of Followerwonk, Twitter, and the AIchemy language API, it’s possible to do top-level persona research very quickly. I’ve built a Python script that can help you answer two important questions about your target audience:

What are the most common domains that my audience visits and spend time on? (Where should I be trying to get mentions/links/PR)What topics are they interested in or reading on those sites? (What content should I potentially create for these people)

You can get the script on Github: Twitter persona research

Once the script runs, the output is two CSV files. One is a list of the most commonly-shared domains by the group, the other is a list of the topics that the audience is interested in.

A quick introduction to Watson and the Alchemy API

The Alchemy API has been around a while, and they were recently acquired by the IBM Watson group. The language tool has 15 functions. I've used it in the past for language detection, sentiment analysis, and topic analysis. For this personas tool, I’ve used the Concepts feature. You can upload a block of text or ask it to fetch a URL for analysis. The output is then a list of concepts that are relevant to the page. For example, if I put the Distilled homepage into the tool, the concepts are:

Notice there are some strange things like Arianna Huffington listed, but running this tool over thousands of URLs and counting the occurrences takes care of any strange results. This highlights one of the interesting features of the tool: Alchemy isn’t just doing a keyword extraction task. Arianna Huffington isn’t mentioned anywhere on the Distilled homepage.

Alchemy has found the mention of Huffington Post and expanded on that concept. Notice that neither search engine optimization or Internet marketing are mentioned on the homepage, but have been listed as the two most relevant concepts. Pretty clever. The Alchemy site sums it up nicely:

"AlchemyAPI employs sophisticated text analysis techniques to concept tag documents in a manner similar to how humans would identify concepts. The concept tagging API is capable of making high-level abstractions by understanding how concepts relate, and can identify concepts that aren't necessarily directly referenced in the text.”

My thinking for this script is simple: If I get a list of all the links that certain people share and pass the URLs through the Alchemy tool, I should be able to extract the main concepts that the audience is interested in.

To use an example, let’s assume I want to know what topics the SEO community is interested in and what sites are most important in that community. My process is this:

Find people that mention “SEO” in their Twitter bio using FollowerwonkGet a sample of their most recent tweets using the Twitter APIPull out the most common domains that those people shareUse the Alchemy Concepts API to summarize what the pages they share are about Output all of the above to a spreadsheet

Follow the steps below. Sorry, but the instructions below are for Mac only; the script will work for PCs, but I’m not sure of the terminal set up.

How to use the scriptStep 1 – Finding people interested in SEO

Searching Followerwonk is the only manual part of the process. I might build it into the the script in future, but honestly, it’s too easy to just download the usernames from the interface.

Go into the "Search Bios" tab and enter the job title in quotes. In this case, that's "SEO." More common jobs will return a lot of results; I recommend setting some filters to avoid bots. For example, you might want to only include accounts with a certain number of followers, or accounts with less than a reasonable number of tweets. You can download these users in a CSV as shown in the bottom-right of the image below:

Everything else can be done automatically using the script.

Step 2 – Downloading the script from GitHub

Download the script from Github here: Twitter API using Python. Use the Download Zip link on the right hand side as shown below:

Step 3 – Sign up for Twitter and Alchemy API keys:

It’s easy to sign up using the links below:

Get a Twitter API key Get a free API key for Alchemy

Once you have the API keys, you need to install a couple of extra requirements for the script to work.

The easiest way to do that is to download Pip here: — save the page as “". Create a folder on your desktop and save the Git download and the “” file in it. You then need to open your terminal and navigate into that folder. You can read my previous post on how to use the command line here: The Beginner's Guide to the Command Line.

The steps below should get you there:

Open up the terminal and type:

“cd Desktop/”

“cd [foldername]”

You should now be in the folder with the file and the folder you downloaded from Github. Go back to the terminal and type:

“sudo python”

“sudo pip install -r requirements.txt”

Create two more files:

usernames.txt – This is where you will add all of the Twitter handles you want to – The file with your API keys for Alchemy and Twitter

In the api_keys file, paste the following and add the respective details:

watson_api_key = "[INSERT ALCHEMY KEY]"

twitter_ckey = "[INSERT TWITTER CKEY]"

twitter_csecret = "[INSERT CSECRET]"

twitter_atoken = "[INSERT TOKEN]"

twitter_asecret = "[INSERT ASECRET]"

Save and close the file.

Step 4 – Run the script

At this stage you should:

Have a username.txt file with the Twitter handles you want to researchHave downloaded the script from GithubHave a file named with your details for Alchemy and TwitterInstalled Pip and the requirements file

The main code of the script can be found in the “” file.

To run the script, go into your terminal, navigate to the folder that you saved the script to (you should still be in the correct directory if you followed the steps above. Use “pwd” to print the directory you’re in). Once you are in the folder, run the script by going to the terminal and typing: “python”. Depending on the number of usernames you entered, it should take a couple of minutes to run. I recommend starting with one or two to check that everything is working.

Once the script finishes running, it will have created two csv files in the folder you created:

“domain + timestamp” – This includes all the domains that people tweeted and the count of each“concepts + timestamp” – This includes all the concepts that were extracted from the links that were shared

I did this process using “SEO” as the search term in Followerwonk. I used 50 or so profiles, which created the following results:

Top 30 domains shared:

Top 40 concepts

For the most part, I think the domains and topics are representative of the SEO community. The output above seems obvious to us, but try it for a topic that you’re not familiar with and it’s really helpful. The bigger the sample size, the better the results should be, but this is restricted by the API limitations.

Although it looks like a lot of steps, once you have this set up, it’s very easy to repeat — all you need to change is the usernames file. Using this tool can get you some top-level persona information in a very short amount of time.

Give it a try and let me know what you think.

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Mobile Web vs Mobile Apps: Where Should You Invest Your Marketing? - Whiteboard Friday

Posted by randfish

Mobile's been a hot topic for a while now. We know it's not something to be ignored, but when it comes to different mobile mediums, it can be tricky to determine where to focus your efforts. In this week's Whiteboard Friday, Rand goes over the differences between marketing via mobile apps and mobile web, examines some criteria that can help guide your decision, and speculates about the future of the mobile world in general.

Click on the whiteboard image above to open a high resolution version in a new tab!

Video Transcription

Howdy, Moz fans, and welcome to another edition of Whiteboard Friday. This week we're going to chat a little bit about the mobile world and specifically whether we should be investing our mobile marketing efforts into the mobile web — meaning a website that is responsive and adaptive or just specifically designed for mobile browsers — or whether we should be worried about building a mobile app to help draw in traffic and gain customers and users. I think these two worlds are actually quite different.

So I spent a bunch of time recently here internally at Moz going through a huge number of statistics, trying to gather as much data as I could to understand these two worlds, and I thought I'd share that with you. I'll give a bunch of links in this presentation, probably a good dozen of them that I'll make sure are in there.


Pew Internet: Smartphone Use in 2015 Comscore & MarketingLand: Apps Eat Digital Media Time Morgan Stanley & MarketingLand: No, Apps Aren't Winning, the Mobile Browser Is IAB Study & MarketingLand: Despite Time Spent, Mobile Web Just as Important as Apps Fred Wilson [AVC]: Mobile Web is Top of Funnel, Mobile Web is Bottom of Funnel MarketingLand: Search is Number One Content Discovery Tool for Mobile Users SimilarWeb & Clickz: Why Mobile Web Still Matters in 2015 Andrew Chen: Mobile App Retention Rates Smart Insights: Mobile Marketing Statistics Think with Google: Mobile Path to Purchase Comscore: 2015 Mobile App Report Forrester: Mobile Users Spend 80% of Time in Just 5 Apps Nielsen: So Many Apps, So Much More Time for Entertainment TechCrunch & Nielsen: An Upper Limit for Apps TechCrunch & Forrester: Only 5 Apps See Heavy Use VentureBeat: Mobile Browser Traffic is 2X Bigger than App Traffic Quartz and Comscore: Most Smartphone Users Download 0 Apps per Month Mobile web qualities

Just to give you a broad overview, basically the mobile web kind of looks like this.

There's a lot less time spent in the mobile web, meaning on mobile websites on a mobile device, than there is in the world of apps — far, far less time spent. But weirdly, and this is very strange but confirmed by several different sources, there's more traffic overall, meaning more unique people making more different visits, which makes a little bit of sense when you think about how those things are done. Remember that a visit to a web page is a much less intense activity than loading up a mobile app and then spending time in it. So sure that can make some sense.

It's also growing faster. So the mobile web is about two times bigger in terms of raw traffic, and it is growing faster than the mobile app world, which will also make sense in a sec when we talk about apps.

This is Morgan Stanley data. I think they're using comScore as one of their sources, and there's another one that backs this up as well.

Mobile traffic is also highly distributed, and you can see that in everyone's numbers, everyone from SimilarWeb to comScore to Nielsen. They're all reporting this. It's a lot like desktop, which again makes sense.

It's not that we spend all our time on just a few websites. In fact, because so much of the time that we spend on the web in desktop is on Facebook's website and on YouTube's website, and that is mostly app traffic in the mobile web, the long tail looks really long when it comes to the mobile web. There's essentially tons of people visiting tons and tons of different websites all across there, I think on average visiting a few hundred to a few thousand unique websites in a month across mobile browsing.

For the mobile web, search, social, and word of mouth or type in or bookmarking, those are the big sources of mobile referrals, which isn't surprising. Those are pretty big on desktop as well.

So pretty distributed broad system here. A lot of similarities to the desktop web. We're pretty familiar with this world.

Mobile app world

Mobile app world qualities, kind of different though. Apps dominate. I mean dominate like they crush the times that we spend on mobile devices. So you might have seen Mary Meeker's State the Internet Report for this year showing that mobile traffic in 2014 eclipsed desktop traffic.

Desktop traffic is weird. It basically kept growing, growing, growing from 1990 to 2010, and then it's basically today almost exactly where it is in 2010. Weirdly, I think a good trivia question would be, "Do people spend more or less time on desktops today than they did five years ago?" Of course, we would all say, "Well, they spend less." But actually we spend a teensy, tinsy bit more than we did then.

It's just that mobile has gone crazy. Mobile has eaten up all of the rest of the time in our lives. We don't see our friends or family any more. We don't eat meals. We just browse our mobile devices.

So mobile is about 85% to 90% depending on the source of time spent on mobile. It's your YouTubes and your Facebooks and all those kinds of things.

It sends and receives far fewer referrals. So basically, most of the ways that people are getting to apps is not from another app or from a website. It's directly from the launcher. They're going to their home screen. They're clicking on that app. That makes pretty good sense.

But they're also not sending out as much traffic. So if you're browsing Facebook on a mobile device, it seems like, on average, you're less likely to click on to a mobile web link and then load up a web page versus maybe if you're browsing Facebook on the desktop web, which also makes sense. You want to stay in the app that you're in. Mobile speeds are slow or especially outside of countries where 4G and LTE are common.

The top 25 to 50 apps in mobile — and it depends on who you ask — some sources are showing that just the top 5 apps are responsible for 80% to 90% of all app usage. This is data from Forrester and data from comScore. Marketing Land did some work on this.

So what we're essentially saying here is if you're not in the top 25 to 50 apps on a platform, you're probably getting very little mobile app activity, because it turns out that the long tail is nowhere near like it is on the mobile web. People don't visit hundreds and thousands of apps. They visit just a few.

In fact, the average mobile owner uses about 24 apps per month, 24 unique apps per month and visits between 10 and 30 times as many unique websites in a given month.

Seven percent of heavy app users (so the people who download the most apps, who use the most apps), they're responsible actually for 50%, a full half of all download activities.

So it's sort of a small subset of app users who just go crazy. They download every app that they can. They treat apps like websites. They have this huge long tail. But for the 93% of the rest of us, a little bit different.

Most new discovery for mobile apps comes from three sources -- mobile web, word of mouth, or app store top lists. That tends to be how we get to the app world.

So these two are very, very different. They're different in usage. They're different in how they operate. They're different in how you would need to do marketing around them.

Things every business needs to optimize for mobile web

It's my general opinion, based on what I've seen about the mobile web, that every business needs to optimize for the mobile web, and you have to optimize in a few ways. That means you must have responsive or adaptive design. It's not just an option any more.

You've got to have a mobile search-friendly experience, so being able to get the mobile search-friendly tag, which means you can rank better.

But it also means that you're delivering a better user experience from search because search is so big to the mobile web world.

You should be SEO-aware and optimize your site for search engines. That's critical. If you're watching Whiteboard Friday, you're probably doing a fine job with that.

You need to load fast, even on slow connections.

I think one of the challenges is that a lot of us assume that everybody is on 4G or everybody is on LTE. That is not the case, especially in a lot of the developing world. But even in the United States and in Europe and in other countries like Japan, there are plenty of connection speeds that are slow or limited due to where people are, particularly when they travel or are inside buildings or are having connectivity issues. I'm sure you've all experienced that.

Finally, you've got to provide that great user experience and a great content experience that delivers answers quickly.

So I don't mean just loads fast. I mean gives people the answers they're looking for quickly, because as we know, Google is using click-through rate and pogo-sticking and all those kinds of things. If you have a bad experience where you're not delivering, even if your page loads fast, you're not delivering the answers someone was seeking when they performed a mobile search, they land on your mobile web page, they're going to click the "Back" button and choose somebody else. They're less likely to choose you in the future, and Google is less likely to rank you in the future. Very frustrating.

My take on mobile app development

But mobile app development — again, this is my opinion — I think that there are plenty of folks out there who have reasonable disagreements about the way that I think about this. But based on what I've seen, I would generally recommend that mobile app development is only right for your organization if you fit a few criteria.

(A) You need to have a great strategy around what your mobile app will do and that there need to be features and value that your app provides that you could not provide well or could not provide at all in a mobile web experience. Apps can do things like push notifications, even when the app is dormant. That's very, very tough for a website to do, although Google has talked about potentially making that available in Chrome someday. So maybe.

Integration with contacts or integration with other apps. Integration with the phone features itself, the calling and the device system or the root functions of the phone. Those types of things, if you can provide value off of that that you could not do through a mobile website, okay.

By the way, the mobile web provides a lot more features and functionality than many folks often think it does. I'll link you to another great piece (What the Web Can Do Today) that was on Hacker News the other day that has just a great chart of all the things that you might want to be able to do and whether they're supported on mobile web or app or both.

(B) You've got to be able to convince not only yourself but convince your team, convince your audience that you can be among the top few — let's say hundred — apps in the world, or you only need a small handful, maybe a few hundred to a few thousand people that install your app in order for it to be successful.

If you can't make one of those claims — either we're going to be one of the top few hundred apps in the world, or we only need a few hundred to a few thousand people on our app — well, the way apps work is the rich, the dominant apps get all the traffic, all the activity.

I think it can be very frustrating to say, "Hey, we're going to build a great app that sits somewhere in the middle of the pack just like our website sits somewhere in the middle of the pack." That's not how it works. All the attention goes to the most popular apps.

(C) Your app can beat the retention curve odds.

So again, in my research what I found time and time again is that mobile app retention, it's just awful, terrible. Basically, the overwhelming majority of apps, I think more than 9 out of 10 apps will never be opened again after 90 days. So you've got to find a way to make your app retain users and keep their interest, keep them coming back to you again and again, and that is no small feat.

(D) You've got an amazing team of app developers or an incredible one or two people who can do great app development and make a world-class product.

Because if you're not going to be best in class, app world just doesn't feel like it's worth it.

This could all change if...

All right. Now let me add a quick caveat at the end of this. So what I want to say is that this world of apps versus mobile web could change.

In fact, I think there's a lot of people in the SEO world who believe that it's on the verge of changing because of what Google is doing with mobile app integration into mobile web search.

So if I do a search today for "best pasta Portland" on my mobile device, I am going to get pretty much exclusively mobile web content. That's true until and unless I perform a search that really is very app-focused or app-centric. So if I were to perform a search like "find best local restaurants near me," it might come up with Yelp or a travel destination app. Google will pull up in my results probably TripAdvisor and stuff like that. That is happening a little bit today, and we do see it. I think there's folks who are going, "Hey, this is an opportunity." It is an opportunity.

But Google has also made another change where they are now indexing content inside of apps, including in Facebook, which was a big announcement a few weeks ago, and potentially will be placing those inside of the mobile search results, potentially even if you don't have that app installed. That's the game changer. If it turns out that mobile search, which is now more than 50% of all search, becomes a place where Google does sort of what they did with Google+, remember where they were giving highly biased, preferential treatment to posts that had been Google Plussed, even from people who were barely in your network or connected to another person and they made Google+ like this center of the local ecosystem and all those kinds of things.

If they do the same thing in the app world and they give this biased, preferential treatment across the board to apps rather than to mobile web content, we could see this equation start to change. Then it might make sense to say, "Hey, even if I can't attract and keep people and build the best app in the world, maybe I should build an app anyway just to be able to expose my content and get the benefit to Google."

I think it would be a little bit of an odd move from Google, but it's not impossible, and I think in 6 to 12 months we're going to know a lot more. There'll be plenty of studies and data about the clickstream patterns on mobile search and how often the results appear and how often they're clicked and how often that leads to a mobile app download. All those kinds of metrics should be available in the next 6 to 12 months. Then we'll be able to report back to you with a lot more about whether this equation has changed.

All right, everyone. Look forward to your comments and we will see you again next week for another edition of Whiteboard Friday. Take care.

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Celebrate #GivingTuesday, the global day of giving

Today we’re joining people across the globe in celebrating #GivingTuesday (@GivingTues), a day dedicated to giving, and a movement that challenges us to ask ourselves, “How can I give back?”

Created on Twitter and founded by New York’s 92nd Street Y (@92Y) in partnership with the UN Foundation (@UNFoundation), #GivingTuesday has propelled into a global movement fueled by the power of millions of people uniting on Twitter for good. Now in its fourth year, #GivingTuesday has more than 30,000 organizations on board and raised more than $100 million in donations in just one day last year. In 2014 alone, #GivingTuesday Tweets received over 32.7M impressions and 750K hashtag mentions.

To learn more about how this inspiring movement began and how anyone can get involved on Twitter today, we spoke with movement founder Henry Timms (@htimms), Executive Director of 92nd Street Y.

Where did the idea for #GivingTuesday come from?
After Thanksgiving, there was Black Friday and Cyber Monday — two days for getting deals — and we thought, what about a day for giving back? That’s how we got to #GivingTuesday. We also wanted to find a way to bring people together around giving back, to share their passions and their favorite causes on #GivingTuesday, and create connections on social media that would translate into people connecting more with each other in real life.

How has Twitter been instrumental in building awareness about the #GivingTuesday movement?
Obviously, the hashtag was critical from the start, and it served as a kind of shorthand to people on social media that this movement was talking to them, and looking to be in their space.

Twitter was the tool that connected the movement. As the initiative has rolled out, spreading the word through Twitter chats and memes like the #unselfie have been a huge part of #GivingTuesday’s evolution and growth.

What are some unique ways you’ve seen charities leverage Twitter to connect with donors, and vice versa?
The Michael J. Fox Foundation encouraged people to share “a picture of someone or something that represents your reason for giving” to support the foundation. They wound up with tremendously moving portraits of people’s moms and dads and grandparents and partners, and it really brought that cause to life and inspired donors. Badass Brooklyn Animal Rescue also used Twitter to tell their story — posting photos and Tweets of how they rescued dogs from a “high-kill” animal shelter — with lots of pictures of adorable dogs that told a story of hope rather than despair.

How can people, businesses, and charities get involved with #GivingTuesday?
There are so many ways to get involved in #GivingTuesday — in addition to making monetary donations, give blood, give a coat, give your time. There is even a campaign this year to encourage organ donation.

Any great success stories from #GivingTuesday that you can share?
There are many different kinds of success we’ve seen in the #GivingTuesday movement. Here are just two: the University of Michigan created #GivingBlueDay last year, and reached out to alumni and students to raise awareness and drive donations; they exceeded their goal of $1 million by more than double, raising over $3.2 million. And then there is World Bicycle Relief, which organized a campaign to raise funds to buy 500 bikes for students in Africa, and they used fun graphics and social media to spread the word effectively enough to raise enough money for 754 bikes.

What has surprised you most about #GivingTuesday?
I wouldn’t say “surprised” as much as “inspired.” And that’s the growth of the movement in places where Black Friday and Cyber Monday don’t exist; the huge creative capacity of the social sector, and the growth of the local and regional campaigns across the country.

How do you see #GivingTuesday evolving over the new few years?
Our hope is that whatever the details look like, #GivingTuesday will continue to provide an opportunity for people around the world to take a break from the news of the day, which can often be so painful, to think about the power we all have to make a positive difference, especially when we step across boundaries to come together to give. We want this to truly become the opening day of the giving season.

Start giving
We’re inspired by Henry and proud to be part of the #GivingTuesday movement. To research and donate to charities on Twitter, browse our collection of #GivingTuesday Tweets below. And, make sure to follow @GivingTues to stay up to date with the movement year round.

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