marketerium

Wednesday, December 2, 2015

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

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.

Conclusion

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!

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

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 facebook.com 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 — ClickStre.am 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 ClickStre.am mean that building a ubiquitous regression model across all the keyword data might not be the best, as the users tracked by SimilarWeb and ClickStre.am 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, KeywordTool.io, 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.

Catch these ‘must have’ links with Majestic

If you run a business that is very typical, for example an online store, or if you simply run a firm that has a lot of competition, it might be tough for you to break through Google’s rankings without the links. No doubt that good content helps, however good links can easily win the case.…

The post Catch these ‘must have’ links with Majestic appeared first on Majestic Blog.

Tuesday, December 1, 2015

Easily get back to the images you’ve found on Google

The perfect image of your next big adventure, knitting project or style-changing haircut is bound to exist somewhere out there. But what happens once you find the image? Take a screenshot? Maybe try to save the webpage? Starting today there is an easier option: you can now star and bookmark images directly from Google’s image search in your mobile browser.

Let’s say you’re searching for “bob hairstyles” on Google and an image catches your eye. Simply select it and tap the star. Next time you’re at the stylist, you can easily access the picture without having to dig around or do another search.

Once you’ve starred a few images, you can keep them organized in folders: to add an image to a folder of similar items, tap the pencil shaped edit icon. Create a grouping such as “haircuts for the winter” or “snowman ideas” and your image will be added to a folder with similar ones.

This feature is currently available in the US when you search for images on mobile, across all major browsers on both Android and iOS. To try it out, make sure you’re logged into your browser with your Google Account; then you can start image searching and planning that next adventure.

Posted by Diego Accame, Software Engineer

It's Here! The MozCon Local 2016 Agenda

Posted by EricaMcGillivray

*drumroll* The MozCon Local 2016 agenda is here! For all your local marketing and SEO needs, we're pleased to present a fabulous lineup of speakers and topics for your enjoyment. MozCon Local is Thursday and Friday, February 18–19 2016 in Seattle. On Thursday, our friends LocalU will present a half-day of intensive workshops, and on Friday we'll be having an entire day of keynote-style conference fun. (You do need to purchase the workshop ticket separately from the conference ticket.)

If you've just remembered that you need to purchase your ticket, do so now:

Buy your MozCon Local 2016 ticket!

Otherwise, let's dig into that agenda!

MozCon Local 2016

Thursday workshops

12:00–12:30pm
Registration

12:30–12:35pm
Introduction and Housekeeping

12:35–12:55pm
The State of Local Search with David Mihm

Already one of the most complex areas in all of search marketing, local has never been more fragmented than it is today. Following a brief summary of the Local Search Ranking Factors, David will give you his perspective on which strategies and tactics are worth paying attention to, and which ones are simply "nice to have."

David Mihm is one of the world’s leading practitioners of local search engine marketing. He has created and promoted search-friendly websites for clients of all sizes since the early 2000s. David co-founded GetListed.org, which he sold to Moz in November 2012.

12:55–1:35pm
Local Search Processes with Aaron Weiche, Darren Shaw, Mike Ramsey, and Paula Keller

Panel discussion and Q&A on the best processes to use in marketing local businesses online.

1:35–2:35pm
How to do Competitive Analysis for Local Search with Aaron Weiche, Darren Shaw, David Mihm, Ed Reese, Mary Bowling, Mike Ramsey

Each panelist will demonstrate their methods and the tools they use to audit a specific area of the online presence of a single local business. The end result will be a complete picture of how a thorough competitive analysis for a local business can be done.

2:35–2:50pm
Break

During this time period, each attendee will choose any three 30-minute workshops to attend. Some workshops are offered in all time slots, while others are only offered at specific times. Present your challenges, discuss solutions, and get your burning questions answered in these small groups.

LocalU Workshops

2:50–3:20pm

Tracking and Conversions with Ed Reese
Solving Problems at Google My Business with Willys DeVoll and Mary Bowling
Ask Me Anything About Local Search with David Mihm
Local Targeting of Paid Advertising with Paula Keller
Using Reviews to Build Your Business with Aaron Weiche
Local Links with Mike Ramsey
Citations: Everything You Need to Know with Darren Shaw

3:20–3:50pm

Tracking and Conversions with Ed Reese
Solving Problems at Google My Business with Willys DeVoll and Mary Bowling
Ask Me Anything About Local Search with David Mihm
Local Targeting of Paid Advertising with Paula Keller
Using Reviews to Build Your Business with Aaron Weiche
Agency Issues with Mike Ramsey
Local Links with Darren Shaw

3:50–4:20pm

Tracking and Conversions with Ed Reese
Solving Problems at Google My Business with Willys DeVoll and Mary Bowling
Ask Me Anything About Local Search with David Mihm
Local Targeting of Paid Advertising with Paula Keller
Using Reviews to Build Your Business with Aaron Weiche
Local Links with Mike Ramsey
Citations: Everything You Need to Know with Darren Shaw

4:20–5:00pm
Live Site Reviews

The group will come back together for live site reviews!

5:00–6:00pm
Happy Hour!

Friday conference

Mary Bowling talks to the local crowd

8:00–9:00am

Breakfast

9:00–9:05am
Welcome to MozCon Local 2016! with David Mihm

David Mihm is one of the world’s leading practitioners of Local search engine marketing. He has created and promoted search-friendly websites for clients of all sizes since the early 2000s. David co-founded GetListed.org, which he sold to Moz in November 2012.

9:05–9:35am
Feeding the Beast: Local Content for RankBrain with Mary Bowling

We now know searcher behavior and continual testing via machine learning indeed affects Google rankings and algorithm refinements. Learn how to create local content to satisfy both Google and our human visitors.

Mary Bowling's been in SEO since 2003 and has specialized in local SEO since 2006. When she's not writing about, teaching, consulting, and doing internet marketing, you'll find her rafting, biking, and skiing/snowboarding in the mountains and deserts of Colorado and Utah.

9:35–10:05am
Local Links: Tests, Tools, and Tactics with Mike Ramsey

Going beyond the map pack, links can bring you qualified traffic, organic rankings, penalties, or filters. Mike will walk through lessons, examples, and ideas for you to utilize to your heart's content.

Mike Ramsey is the president of Nifty Marketing and a founding faculty member of Local University. He is a lover of search and social with a heavy focus in local marketing and enjoys the chess game of entrepreneurship and business management. Mike loves to travel and loves his home state of Idaho.

10:05–10:35am
Citation Investigation! with Darren Shaw

Darren investigates how citations travel across the web and shares new insights into how to better utilize the local search ecosystem for your brands.

Darren Shaw is the president and founder of Whitespark, a company that builds software and provides services to help businesses with local search. He's widely regarded in the local SEO community as an innovator, one whose years of experience working with massive local data sets have given him uncommon insights into the inner workings of the world of citation-building and local search marketing. Darren has been working on the web for over 16 years and loves everything about local SEO.

10:35–10:55am
AM Break

10:55–11:20am
Technical Site Audits for Local SEO with Lindsay Wassell

Onsite SEO success lies in the technical details, but extensive SEO audits can be too expensive and impractical. Lindsay shows you the most important onsite elements for local search optimization and outlines an efficient path for improved performance.

Lindsay Wassell's been herding bots and wrangling SERPs since 2001. She has a zeal for helping small businesses grow with improved digital presence. Lindsay is the CEO and founder of Keyphraseology.

11:20–11:45am
Optimizing and Hacking Email for Mobile with Justine Jordan

Email may be an old dog, but it has learned some new mobile tricks. From device-a-palooza and preview text to tables and triggers, Justine will break down the subscriber experience so you (and your audience) get the most from your next campaign.

In addition to being an email critic, cat lover, and explain-a-holic, Justine Jordan also heads up marketing for Litmus, an email testing and analytics platform. She’s strangely passionate about email, hates being called a spammer, and still codes like it's 1999.

11:45am–12:10pm
Understanding App-Web Convergence and the Impending App Tsunami with Emily Grossman

People no longer distinguish between app and web content; both compete for the same space in local search results. Learn how to keep your local brand presence afloat as apps and deep links flood into the top of search results.

Emily Grossman is a Mobile Marketing Specialist at MobileMoxie, and she has been working with mobile apps since the early days of the app stores in 2010. She specializes in app search marketing, with a focus on strategic deep linking, app indexing, app launch strategy, and app store optimization (ASO).

12:10–12:35pm
Building Customer Love and Loyalty in a Mobile World with Robi Ganguly

How the best companies in the world relate to customers, create a personal touch, and foster customer loyalty at scale.

Robi Ganguly is the co-founder and CEO of Apptentive, the easiest way for every company to communicate with their mobile app customers. A native Seattleite, Robi enjoys building relationships, running, reading, and cooking.

12:35–1:35pm
Lunch

1:35–2:05pm
The Past, Present, and Future of Local Listings with Luther Lowe and Willys Devol

Two of the biggest kids on the local search block, Google and Yelp, share their views on the changing world of local listings, their place in the broader world of local search, and what you can do to keep up, in this Q&A moderated by David Mihm.

Luther Lowe is VP of Public Policy at Yelp.

Willys Devol is the content strategist for Google My Business, and he spends his time designing and writing online content to help business owners enhance their presence online. He's also a major proponent of broccoli and gorillas.

2:05–2:35pm
Fake It Til You Make It: Brand Building for Local Businesses with Paula Keller

Explore real-world examples of how your local business can establish a brand that both customers and Google will recognize and reward.

As Director of Account Management at Search Influence, Paula Keller strategizes with businesses on improving their search, social, and online ads results, and she works to scale those tactics for her team's 800+ local business clients. Paula views online marketing the same way she views cooking (her favorite way to spend her free time): trends come and go, but classic tactics are always the foundation of success!

2:35–3:05pm
Your Marketing Team is Larger Than You Think with Dana DiTomaso

Imagine doing such a great job with your branding that you become a part of your customer's life. They trust your brand as part of their community. This magic doesn't happen by dictating the corporate voice from a head office, but from empowering your locations to build customer community.

Whether at a conference, on the radio, or in a meeting, Dana DiTomaso likes to impart wisdom to help you turn a lot of marketing bullshit into real strategies to grow your business. After 10+ years, she's (almost) seen it all. It's true, Dana will meet with you and teach you the ways of the digital world, but she is also a fan of the random fact. Kick Point often celebrates "Watershed Wednesday" because of Dana's diverse work and education background. In her spare time, Dana drinks tea and yells at the Hamilton Tiger-Cats.

3:05–3:25pm
PM Break

3:25–3:55pm
Mo' Listings, Mo' Problems: Managing Enterprise-Level Local Search with Cori Shirk

Listings are everyone's favorite local search task...not. Cori takes you through how to tackle them at large scale, keep up, and not burn out.

Cori Shirk is a member of the SEO team at Seer Interactive, where she specializes in managing enterprise local search accounts and guiding strategy across all of Seer's local search clients. When she's not sitting in front of a computer, you can usually find her out at a concert enjoying a local craft beer.

3:55–4:10pm
The Enterprise Perspective on Local Search with Matthew Moore

Learn how the person responsible for local visibility across a portfolio of nearly 1,000 locations tackles this space on a daily basis. Matthew from Sears Home Services shares his experiences and advice in this Q&A moderated by David Mihm.

Matthew Moore is Senior Director, Marketing Analytics at Sears Holdings Corporation.

4:10–4:40pm
How to Approach Social Media Like Big Brands with Adria Saracino

Facebook, Twitter, LinkedIn, Instagram, Pinterest, YouTube, Snapchat, Periscope...the seemingly never-ending world of social media can leave even the most seasoned marketer flailing among too many tasks and not enough results. Adria will help you cut through the noise and share actionable secrets that big brands use to succeed with social media.

Adria Saracino is a digital strategist whose marketing experience spans mid-stage startups, agency life, and speaking engagements at conferences like SearchLove and Lavacon. When not marketing things, you can see her cooking elaborate meals and posting them on her Instagram, @emeraldpalate.

4:40–5:10pm
Analytics for Local Marketers: The Big Picture and the Right Details with Rand Fishkin

Are your marketing efforts taking your organization where it needs to go, or are they just boosting your vanity metrics? Rand explains how to avoid being misled by the wrong metrics and how to focus on the ones that will keep you moving forward. Learn how to determine what to measure, as well as how to tie it to objectives with clear, concise, and useful data points.

Rand Fishkin uses the ludicrous title "Wizard of Moz." He’s the founder and former CEO of Moz, co-author of a pair of books on SEO, and co-founder of Inbound.org.

6:00–10:00pm
MozCon Local Networking Afterparty, location TBA

Join your fellow attendees and Moz and LocalU staff for a networking party after the conference. Light appetizers and drinks included. See you there!

Buy your MozCon Local 2016 ticket!

Amazing New Data Visualisation of backlink growth

Occasionally, one stumbles upon a thing of beauty. We were stunned to see a new visualisation of Majestic Data, a beautifully animated dataviz created by fusing the power of the Majestic API with the wonderful visual capability of the software version control vizualisation tool, “Gource.” The visualization uses the generation of nodes within a linked graph to…

The post Amazing New Data Visualisation of backlink growth appeared first on Majestic Blog.

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 Followerwonk
Get a sample of their most recent tweets using the Twitter API
Pull out the most common domains that those people share
Use 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 script

Step 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:

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: https://bootstrap.pypa.io/get-pip.py — save the page as “get-pip.py". Create a folder on your desktop and save the Git download and the “get-pip.py” 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 get-pip.py file and the folder you downloaded from Github. Go back to the terminal and type:

“sudo python get-pip.py”

“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 research
api_keys.py – 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 research
Have downloaded the script from Github
Have a file named api_keys.py with your details for Alchemy and Twitter
Installed Pip and the requirements file

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