Hashtag Filter

Last month, we released SocialRank for Instagram. One of the most popular new features has been the ability to filter your followers by the hashtags they have used in their posts.

The Hashtag filter also shows you your followers most popular hashtags. As the saying goes, you are who you’re friends are. So if you’re a marketer, the most popular hashtags may give you some insight on what your brand is all about.

Or if you’re like us, perhaps this looks more like a personality test (we love New York, SXSW, and the beach):


Either way, popular hashtags gives context to your social graph. Go ahead and check out the new feature here.

Introducing SocialRank for Instagram

At SocialRank we’re always thinking about where our industry is headed and what role we play in that future. Three things constantly turn up when we talk about the trajectory of social media and marketing:

First: there’s not one, but multiple social networks now with 100mm+ users — Facebook, Twitter, Instagram, Pinterest, Snapchat, and the rest of the gang.

Second: hundreds of millions of people are using these social platforms as integral parts of their daily lives.

Third: despite painstakingly building audiences on these social networks, brands don’t spend enough time understanding who exactly their existing followers are.

This blind spot is what we’re trying to address. We believe that over the next few years it’s going to become as important to understand who your existing followers are before running off to gain new ones. Our goal is to build a central location for anyone to be able to manage all of their followers across multiple social networks. We’re working to put the “people” piece of the puzzle back into the marketing stack.

Over the past year, these thoughts has guided many of our product decisions. Up until now we’ve focused solely on our Twitter product. Today, however, that changes with the launch of SocialRank for Instagram.

Launching SocialRank for Instagram

New Homepage
New Homepage

SocialRank for Instagram will have a lot of the same segmentation features as our Twitter product. You will be able to log in for free, load up your Instagram account, and quickly filter and sort through your Instagram followers based on engagement, bio keywords, location, and a few new ones like filtering by followers that use certain hashtags.

When your Instagram report loads after you log in, you will be directed to your Followers List. Here is where you will be able to do all your filtering and sorting through your Instagram followers.

SocialRank for Instagram
SocialRank for Instagram

One new feature we’ve added is the ability to see each follower’s top three Instagram posts. When you hover over each post, you will be able to see any captions that accompany the image, as well as how many likes and comments the post got. This should be an interesting way to get a quick look at what your followers are sharing on IG:

SocialRank for Instagram Card
SocialRank for Instagram Card

But what if you want to switch over and look at your Twitter followers? Simple. Just toggle over to Twitter via the switch located above the green Save List icon:


We’ve seen people use our Twitter product in extremely inspiring ways. From finding your biggest follower in a city to help promote a blood drive, to rewarding your most engaged fan with a physical or digital product – SocialRank helps brands find their people.

For the past two weeks we’ve been seeding brands and organizations with an early version of the product. We’d like to highlight a few great brands and organizations that are doing cool things with the people they find via SocialRank.

Big shout out to this weeks MVGs (most valuable grammers) @trentshafer @kellycalamas @jaymanny123 — found via @socialrank A photo posted by American Red Cross (@americanredcross) on

If you’re interested in what we’re building, have any feedback for us, or otherwise want to drop us a note to say hello, you can reach us at Instagram@SocialRank.com.

Number Of Followers Filter

Today, we are introducing a new feature on SocialRank to soup up your segmentation and filtering game. You can now filter your followers based on how many followers they have. This is all part of our goal to help you better fine-tune your searches and find the people you want to find. This filter can be accessed by clicking “More Filters.”

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Example use case: find your Most Engaged followers who have more than 2,000 followers (using “Filter by Number of Followers”). This will surface your more popular accounts who have actually engaged with you recently. This query might help identify future partnerships for everyone ranging from big brands to freelance bloggers. Knowledge is power.

New Look for Market Intel

Our Market Intel product (still in private beta) allows users to run reports on any Twitter account. Because we know this product will be extremely useful to entities ranging from big brands and record labels to agencies and universities, we are still slow to onboard new users to test it.

However, for those beta testing it (or those still interested in beta testing), we have added a new look to Market Intel. In addition to being able to segment and parse through someone else’s followers list, you will now be able to see their dashboard:


The dashboard gives a higher level view of what’s going on for someone else’s Twitter account (in this case, Pepsi’s). You’ll be able to see trends in follower counts and engagement, as well as other more specific stats. This capability builds upon all the segmenting and filtering you could do previously, which is still accessible via the Followers tab in the side navbar:


Just like with your own personal account, you can save searches for your future reference. Below is what the “Save History” tab would look like if I saved my search for Pepsi’s followers in New York City:


If you’ve had enough and want to return to your own personal Twitter account, all you have to do is follow the directions on the green bar that’s perpetually at the top of the screen:


If you’re interested in becoming a beta user for Market Intel, sign up here! We’ll make note of your information as we start granting Market Intel access to more people.

Lessons from Launching a Data Product

Over one month ago, we launched a product called the SocialRank Index. The Index tracks the Twitter activity of the world’s biggest brands, and our goal with it is to build a tool that monitors the “pulse” of how people are engaging with brands online.

Since the Index has launched, we’ve learned myriad lessons on what makes for a truly compelling and useful data product (hint: it’s a lot harder than just pulling some graphs together).

Here are three big things we’ve learned after getting feedback from users, marketers, and data scientists/statisticians.

1. Tweet Annotations: There’s a story to uncover in the data


When we got the first working version of the Index up and running, we were really excited to see the Engagement graph in action. This graph showed a particular industry’s hourly flow of retweets, mentions, and replies. Our first “Wow, this is really interesting” moment happened the morning after Obama’s State of the Union address. We took a look at the Tech Media Index (which consists of big hitters like the New York Times, Wall Street Journal, and BuzzFeed, among others):


Around 9pm on Tuesday night, there was an unexpected spike in activity in the Tech Media Index. After some deep deliberation, we concluded the spike was due to the State of the Union, which had begun … at 9pm.


But what about situations where there is no immediately recognizable reason for a spike in Twitter activity? Why leave this kind of “aha!” to guesswork and inference? The data clearly is telling a story, and so we should do our best to uncover what that story is.

Thanks to some technical wizardry by our co-founder Michael, the Index now automatically locates and annotates the largest peaks in the engagement graph. Can you guess when the Oscars were?


If you hover over these annotations, you can see the “highest velocity Tweet” at that particular hour. This is our best guess at the Tweet that got shared/retweeted/faved most frequently within that given hour.

According to the Tech Media Index, BuzzFeed and Lady Gaga won the Oscars. This is the Tweet that we captured at the peak of the graph:


Data isn’t very useful without context (see Jen Lowe’s great talk “Data Needs Memory”). Being able to correctly identify which events contributed to an anomalous piece of the data is crucial. Continually looking deeper at the data and trying to articulate which stories are being told (or not told) makes the data itself more insightful and valuable.

We still have a lot more work to do in this regard: our current system isn’t foolproof, doesn’t identify every single peak, and doesn’t answer every relevant question we might have.

For example: looking at the graph above, I notice that the mini-peaks throughout the week tend to fall at around the same time (around 11am). What’s the insight from that? I could deduce from anecdotal evidence that this is the time many tech media outlets push out new stories in order to maximize attention time (when people are about to break for lunch or take a mid-morning break). But of course, that is me just guessing– I would love to have something more to support this inkling.

Lesson learned: keep asking what the data is really telling or not telling us.

2. List View: Most “Big Data problems” are actually “Display problems”


One of the first things you learn the hard way when shipping product is that not everything is as obvious as you think it is. One common piece of feedback we get on the Index is “Wait, what exactly am I looking at?” To us, that is obvious — the graphs and charts show you what the average company in an index looks like on Twitter. But it became very clear after early rounds of feedback that this wasn’t crystal.

We’ve focused a lot of our efforts on the specific metrics to track, the specific types of graphs to plot, and the specific brands and industries to monitor. But the overarching issue of usability remains a sore spot. Our “Big Data” problem is a display problem. It isn’t that we aren’t pulling in enough data. Rather, we aren’t being as clear as we should be with how we show all of this data.

While this is still a major work in progress for us, our feedback from users told us something important about display problems: they happen when people are required to jump through too many cognitive hoops to figure out what’s going on. Our friends would first ask us “What exactly am I looking at?” and then follow up with “Wait, so which companies are in this index? Why can’t I just see how Adidas is doing?”

So today we’re unveiling List View, which breaks down the stats for each and every brand in an index. Here is the List View for the Tech Startups Index, sorted by Total Daily Engagement:


Now you can not only see which companies are in an index, but also what their specific stats are. We still need to tweak and retool the rest of the Index from a UX/UI standpoint to make everything more obvious. But we feel the “List View” will go a long way in helping people get a more intuitive understanding of what’s going on.

Lesson learned: it’s not that you don’t have enough data, it’s that you’re showing it all wrong.

3. Mean vs. Median: Hunt for a less misleading way to show data

A quick look at the two numbers above should raise some eyebrows. The mean (or average) number of followers for companies in the Tech Media Index is over 1 million. The median number of followers for companies in this index is just under 245,000. The difference between the mean and the median is over 700,000 followers — that is a lot of followers.

When we first began building the Index, the way we processed data made it much more practical to calculate averages (or means), and in the spirit of shipping things fast, we settled on the mean for all of our stats.

But the Index is supposed to display data for the “average company” in an index. And the average company in the Tech Media Index definitely doesn’t have over a million followers. In fact, only 24 out of the 95 brands in this index have over 1 million followers. Due to outliers such as the New York Times and the Wall Street Journal, using the mean to represent what an average company looks like was terribly misleading.

Here is the distribution of followers for brands in the Tech Media Index:

@Medium has 1.09mm followers, which is right around what the mean was that we calculated. There are only 23 other companies in this index that have more followers than Medium. Meanwhile, @PCWorld has some 244,000 followers, which also happens to be the median here. Notice how much more representative PCWorld is of the companies in the Tech Media Index than Medium is.

There’s too much misleading and lazy data out there that goes viral and gets morphed into “truth.” And when certain numbers get repeated enough, the desire to check if they actually represent reality grows stale.

We don’t want to contribute to that.

So we’ve switched all of the numbers in the Index to median measurements. We could’ve opted for more advanced statistical maneuvers, but we highly value simplicity, and we also recognize the difference between accuracy and precision.

Obviously this “mean vs. median” discussion is very basic compared to some of the more challenging problems other analytics products might be struggling with. But the lesson holds all the way through, regardless of the type of data problem.

Things to further consider: the size of each index. Right now, each index has about 100 members, but maybe this arbitrarily determined total is skewing the data (example: does the Tech Media Index need 100 members? Or is looking at just the top 50 or top 25 most useful?)

Lesson learned: Be simple, be useful, don’t mislead.

4. Retail & Music Index Launch: You’re building this for customers, not yourself.


At first, our process for determining which indexes to launch was internally determined — which ones did we think were cool and awesome and completely relevant to marketers?

And so we launched with indexes for Global Brands, Tech Media, Tech Companies, and Tech Startups. Each of these have a high amount of pop culture value, and journalists for the most part loved seeing them.

But when we started showing these indexes to existing customers, they kept asking whether there would be an index coming out for music or for retail or for their specific industry. Which is when we realized that we should’ve asked the market before building the product in the first place. While our initial indexes displayed data on the world’s “hottest brands,” marketers and strategists are more interested in relevant brands in their own specific industries.


Today, we are listening to our users and launching the Retail Index and the Music Index. The Retail Index consists of companies in the National Retail Federation’s annual top 100 list (think Amazon, Apple, Walmart, and the rest of the gang). The Music Index is comprised of artists from the Billboard 200. These indexes are equipped with all the updates listed above (List View, Median, and Annotations).

All of the lessons we’ve learned so far are some version of DJ Patil’s advice to “put the human back in the equation.” We’re excited to keep developing the Index into a place where marketers, brand strategists, and community managers can get real with data and start using it more meaningfully. If you are interested in what we are building, please don’t hesitate to shoot us an email at index@socialrank.com.

Early Access to SocialRank for Instagram

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At SocialRank we are building a place where you can log in with your various social accounts and pull all your followers into one central location. So far, we’ve been improving on our Twitter product before expanding to other platforms.

In a few short weeks, we will be launching SocialRank for Instagram. It will look very similar to what we’ve already been doing — you will be able to sort and filter your Instagram followers by location, keywords, most engaged, most valuable and more.

Instagram and Twitter are home to some of the most vibrant online communities imaginable. This upcoming launch aligns with our mission to allow brands and individuals alike to continue building strong relationships within these communities.

If you would like to request early access to SocialRank for Instagram, please head over to SocialRank.com/Instagram. If you want to get in touch with the team that is building SocialRank for Instagram feel free to email us at Instagram@SocialRank.com.

P.S. We are lining up brands and public figures to be part of the launch like we did when we launched our Twitter product (see: GoPro, Spotify, Muhammad Ali, Uber, Juicy Couture, and more). If interested, get in touch with us at hi@socialrank.com and we will talk.


The Startup T-Shirt Phenomenon: Branding and Conway’s Law

In 1967, programmer Mel Conway wrote a paper called “How Do Committees Invent?” and submitted it to the Harvard Business Review, who promptly rejected it. Luckily for us, the paper eventually ended up getting published the following year in a tech magazine that was popular at the time.

Hidden in this paper was a pretty big idea that gained a lot of fame in the engineering community. This big idea is called Conway’s Law, which goes like this:

“Any organization that designs a system (defined broadly) will produce a design whose structure is a copy of the organization’s communication structure.”

Put in other words, a product will mirror the communications structure in which it arose. To reduce it even further: product and culture end up looking a lot like each other. In 2007, research by management theorists at Harvard Business School found strong evidence in support of this.

GitHub: A Case Study

Source: http://www.wired.com/2013/09/github-office/
Source: WIRED

One classic illustration of Conway’s Law resides in the very fabric of tech startup GitHub. In a series of posts, longtime employee Zach Holman summed up GitHub’s culture in three guidelines (paraphrased below):

1. Set your own hours.

2. Avoid meetings.

3. To get creative, get in the zone.

At GitHub, a $100mm+ company, this means that much of the non-essential communication takes place in chat rooms so as to keep distractions minimal. It means that the company hosts happy hours, sponsors gym memberships, and organizes teaching workshops. In fact, for its first two years, GitHub didn’t even have an office — employees worked remotely (and many still do).

Why is this important, and what type of culture, exactly, is GitHub trying to build? Holman puts it this way:

“We want employees to be in the zone as often as possible. Mandating specific times they need to be in the office hurts the chances of that. Forcing me in the office at 9am will never, ever get me in the zone, but half of GitHub may very well work best in the morning.”

Or, in the words of Ryan Tomayko, another early GitHub employee, “Your team should work like an open-source project.” Funny, because a lot of open source projects are powered by GitHub. GitHub is a lightweight, cloud-based tool that programmers use to work on code together. Software for collaboration and open-source projects. Just like the culture and communications structure it has built, GitHub the product is asynchronous and distributed — that is, teamwork anywhere, anytime. 

If you want a slightly more tongue-in-cheek exploration of Conway’s Law in action, observe the sketch below, courtesy of Manuel Cornet: 

Source: http://www.bonkersworld.net/organizational-charts/

According to Cornet’s very data-driven graphs above, Amazon the company is culturally as hierarchical as the product (which is essentially a hierarchy of categories and subcategories containing things you totally need to buy). Google the company is culturally just as structured yet cross-dependent and cross-referencing as Google’s products. And Microsoft, well, yeah.

However, while Conway’s Law explains in some ways the relationship between culture and product, it’s missing a crucial piece: How does this alignment between product and culture get cemented? How does it become formalized, reinforced, and calcified?

Through branding. Namely, through monopolizing language and imagery.

The Startup T-Shirt Phenomenon


A couple years ago, Owen Thomas wrote a profile on Palo Alto, the “small California town where billion-dollar dreams are made.” This is the prototypical startup town, where companies like Google, PayPal, and Facebook got their start, and where many notable tech bigwigs call home. In what is pretty typical of the tech scene these days, you’ll see a lot of branded t-shirts. Thomas makes special note of this fact:

“You’ll often see Palantir employees walking around in polo shirts with the company logo.”

But startup t-shirts on their own aren’t evidence of any reinforcement of Conway’s Law. They are just the tip of the iceberg. In his essay The Anthropology of Mid-Sized Startups, Kevin Simler points to the t-shirts as a small piece of “the many rituals I’ve seen startups use to reinforce trust, solidarity, and company (or team) pride.” He lists out a handful of other ways in which this team-building ritualization happens: team sports, themed dress-up days, wall art, shared meals, and other activities.

We can break these reinforcing rituals down into two categories: images and language. Many successful businesses use these two levers to reinforce both internally and externally their culture as well as their product. One company in particular does a great job of this: Dropbox.

Dropbox and Freedom


Dropbox allows you to save, store, and access your files from anywhere you want. Wherever you go, all your documents, files, songs, and videos are with you. When Dropbox first came out back in 2007, this was freedom for people who had previously been tethered to their floppy disks, CDs, USB drives, and other easily-lost and easily-damaged storage devices.

The images Dropbox uses to represent itself entirely embody this idea of freedom. The company is renowned for its artful, humanistic use of illustrations, instead of the pseudo-industrial aesthetic common with other startups. Even their Error 404 page keeps with the “freedom” branding — you land on the design team’s interpretation of MC Escher’s impossible cube.

The language and copy the startup employs also reinforces the idea of freedom: from the landing page’s “Your Stuff, Anywhere” to the “Keep your stuff safe and accessible wherever you are” located in various locations on the website.

(If you want to nerd out further, more examples here, here, and here).


This “freedom” ethic definitely extends down into the culture of the company. The organizational structure is largely flat and engineering-driven. Dropbox is renowned for its “You’re smart, figure it out” mentality, its wildly creative hack weeks, and its recruitment videos starring muppets with MacBooks.

To some extent, CEO Drew Houston seems to have deliberately designed for this:

“One of the biggest challenges to growth has been something banal– inter-office communication. When the team was small enough to fit in one room, information just spreads naturally. But as we grew larger we had to start deliberately trying to figure out how to get the right info in the right people’s’ hands.” 

Dropbox’s product is all about freeing users; Dropbox’s communications structure is all about freeing employees; and Dropbox’s branding simply reinforces all of this to employees, users, investors, and journalists through imagery and language.

Branding Blind Spots


But all cohesive systems have blind spots; the very strengths they are designed to highlight can create glaring weaknesses. Organizations are no exception.

For example, Uber has gotten itself in trouble countless times in the past year. Perhaps by necessity, a company challenging a highly entrenched incumbent (taxi industry) has a highly efficiency-oriented product, a by-any-means-necessary culture, and sleek corporate branding. The blind side of this product and organizational design might be the reports of sabotaging competitors and naysayers. GitHub and Dropbox have also recently had to respond to their own cultural “blind spots” (GitHub’s institutionalized hostility towards women; Dropbox’s fortification of “frat boy culture”).

The lesson for businesses? Be very deliberate and rigorous about the culture you want to build, because it will show in the product. Then reinforce through authentic branding. In the oft-quoted words of Tony Hsieh, CEO of Zappos, “Your culture is your brand.” In this case, your culture might be your product, too.

We now leave you with an illustration of what SocialRank is all about — feel free to overanalyze it in the comments section:



Activity Filter Changes

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We’ve made an important change to our Activity Filter this past month. Previously, you could filter your followers based on whether they were Active, Inactive, or Fake. However, these categories weren’t fully accurate. We had come up with decent approximations for them, but honestly, only Twitter can display this information correctly.

For example, we might call a user Inactive because he hasn’t tweeted anything in a while. But he might be logging in on a daily basis and clicking on links, but choosing not to ever tweet, favorite, @reply, or RT. So calling him Inactive wouldn’t be exactly true.

So we scrapped these categories and replaced them with what we believe might end up being more useful for you. The Activity Filter now breaks down to Recently Tweeted, Previously Tweeted, and Never Tweeted.

Recently Tweeted: Tweeted in the last 90 days
Previously Tweeted: Haven’t tweeted in the last 90 days, but have tweeted at least
once in their Twitter history
Never Tweeted: Self-explanatory

Noticeably missing from these three is the popular Fake Followers filter. We trust in Twitter to work out this definition themselves as time goes on — currently, only they have access to the type of data that could accurately determine this. In the meanwhile, our update to the Activity Filter will allow you to more clearly see which of your followers are talking the most on Twitter.

Make sure to check out the new and improved Activity Filter!

Tech Startups Index

We recently launched a product we’ve been working on for several months — the SocialRank Index. The Index is a tool that tracks the Twitter activity of the world’s biggest brands. Anyone can log in and, without paying a dime, look at how the average company in a particular industry is performing. So far, we have released three industry-specific indexes: the Global Brands Index, Tech Companies Index, and Tech Media Index.


Today, we’re releasing one a lot of people will be interested to look at: the Tech Startups Index. The types of companies that populate this index? Uber, Airbnb, Dropbox, Slack, and more.

This index is based on a list of the world’s most valuable startups, published by Fred Wilson, William Mougayar, and the Wall Street Journal. For simplicity’s sake, we filtered based on three criteria: 1) founded after 2006, 2) founded in the USA, and 3) still privately-owned (hasn’t been acquired or gone public yet).


The companies listed in this index were born into an era where there’s an assumption that building and maintaining a highly engaged online audience is crucial to business.

Time will tell whether a strong social presence is a good predictor of the long-term success of a startup.


We will continue to release more industry-specific indexes to add to the four we now have publicly available. If you are interested in what we are building, please reach out to us (index@socialrank.com) or me (ammar@socialrank.com) with any ideas of metrics to track or indexes to build.

Tech Media Index

Tech Media Index

Last week, we debuted the SocialRank Index, which tracks the Twitter activity of the world’s biggest brands. So far, we have released the Global Brands Index (Nike, Pepsi, etc) and the Tech Companies Index (Microsoft, IBM, etc). Our plan is to continue to release new industry-specific indexes over the following weeks and months.


Today, we’re releasing a particularly saucy one: the Tech Media Index. This index includes the likes of TechCrunch, WSJ, the New York Times, Buzzfeed, and every other major outlet that covers tech news. The Tech Media Index was inspired by Techmeme’s Leaderboard, which lists the 100 most frequently posted outlets on Techmeme.


These media outlets play a significant role in shaping the landscape of conversations online. So of course the data this index yields will be very interesting.

In a nutshell, tech media rules Twitter.

A few interesting highlights:

  • An American Bias: The average company in the Tech Media Index has over 60% of its followers in the U.S.
  • Tweet-Happy Followers: It is no surprise that the Tech Media Index is dominant on the engagement side. Tech media bests the Tech Companies and Global Brands Indexes from overall Engagement all the way down to each specific type of engagement (RT, @Replies, and Mentions). Nearly 60% of the average tech media outlet’s followers have tweeted something in the past 90 days. This is higher than the Tech Companies Index (53%) and Global Brands Index (54%).
  • High-Profile Fans: The average company in the Tech Media Index has more than 3x the amount of verified followers (2,869) than the average company in the Global Brands Index (941). Moreover, they are beating the other indexes by far in terms of number of followers who have 1k+ followers. The average tech media outlet has over 45,000 followers with over 1,000 followers (Global Brands: 32,000; Tech Companies: 8,400).


We won’t ruin all the fun for you. Log in, check out the Tech Media Index, and if you’re a blogger feeling especially daring, compare yourself to this Index via the Dashboard.

Next Steps

The SocialRank Index is part of our larger mission to build a more sophisticated analytics tool for marketers and brand managers. Instead of looking at wonky numbers like total followers and total “reach” (whatever that means), we want you to be able to really drill down to a granular level, as well as pull back up and view things at a high level.

If you are interested in what we are building, please reach out to us (index@socialrank.com or ammar@socialrank.com) with any ideas of metrics to track or indexes to build.