PostRank™

We’re constantly working on making PostRank Analytics even better, based on your feedback and our own technology research. (Ok, we take breaks from time to time to play foosball, too…)

We’ve already posted about our first round of upgrades and fixes, and we’ll be telling you about Analytics improvements weekly.

This week, we’ve got a really cool addition to the Analytics functionality to tell you about: Trends! Thanks to you for asking for this and for telling us what you wanted to see in it. We already have some ideas for version two, so stay tuned!

Analytics customers may already have noticed the new Trends tab when they login to Analytics. This page features information on:

• engagement events and their relation to engagement points
• where your content is being picked up geographically
• your engagement breakdown by social site.

So what does that all mean?

Engagement Events / Engagement Points

What is the composition of your posts’ engagement scores? Do you get a wide variety of engagement types (clicks, comments, tweets, diggs, etc.)? Or does your content tend to mostly garner a few specific types of engagement (e.g. you’re regularly the king or queen of Delicious)? Tracking this graph’s engagement profile over time to shows how audience sharing of your content is evolving.

A more in-depth explanation of engagement: Engagement Explained.

Geographic Distribution

View the top 8 countries where your engagement is coming from (by percentage). Also displays the total number of visitors to your site, and you can expand the list to see every country where engagement has come from.

Engagement by Social Site

Week by week this graph breaks down where your engagement came from on the social web. It also shows by percentage how much of your total engagement each source represents. You can customize the graph by adding or removing sources for comparisons.

You asked us for more trending information, and we listened. Take your Analytics Trends for a spin and let us know what you think!

ReadWriteWeb’s Real-Time Web Summit last week was a hit and PostRank was glad to be a sponsor. 

It’s often a gamble to run with an unconference style, but with that room and the excellent facilitation the board filled up quick. It was great to connect with so many great people in one place. 

The discussions were many and engaging and it was great to meet folks in person and put real faces to names (or avatars).

Highlights for us were the update on Pubsubhubub, critiquing Echo, the latest in comment systems from js-kit, and getting glimpses of new moves from Pheedo.

PostRank ramped up to the event with a pair of blog posts, the first: Architecting the Real-Time Web, followed up by: Filtering the Real-Time Web.

We’re excited to participate in this conversation and look forward to talking about filtering with social engagement data. If you have thoughts or ideas in this area we’d love to hear about it!

We’ve just made a PDF version of Architecture & Filtering Technologies for the Real-Time Web, so check it out and let us know what you think.

As we recently reported, Red Canary launched a feature spotlighting a number of startups in the KW area (Guelph included).

Sure, there’s plenty of info and opinion out there about local 800lb gorillas like RIM and OpenText, but what are things like among some of the smaller companies? Who are the 800lb gorillas of tomorrow? Votes were cast in 5 categories:

• Most Likely to Win BIG
• Best Tech Team
• Best Leadership
• Best Product
• Best Place to Work

and the results are in! we’re pretty chuffed to be able to report that PostRank was the only company to place in the top 5 in every category. Sure, coming in first in every category would have been awesome, but we actually like the competition a lot, so we’re cool with the results.

Big congratulations to our friends at Well.ca, who came in tops in the overall rankings (most points). They deserve every bit of the kudos (though we’ll totally kick your well-exfoliated butts next year!)

The commentary on the voting and rankings at the bottom of the page is interesting, too. I’d love to know specifics like where people who voted live and work, but I think it does point to the tech community in the KW area needing to do a bit more to market our companies, our skills, and ourselves to the world. Fortunately, given the cool products and tech, brilliant people, and great culture we have going on around here, this should not prove difficult.

Photo source.

It’s been three weeks since we launched PostRank Analytics, and man, have we been busy!

The reception has been great, and we’re thrilled about all the sign-ups. We’re also, of course, grateful for all the feedback, questions, and kudos we’ve received, too. Keep ‘em coming!

Now, launching something as big as Analytics is no excuse to rest on our laurels. (Good thing, since laurels are kind of pointy and uncomfortable.) The team has been really busy in the succeeding weeks, fixing bugs, tweaking the UI, and making things work even better.

Like what?

New metrics layout: We’ve changed the Analyze view to better show what engagement is and how it’s calculated. We added “Engagement Events”, which represent the number of distinct audience activities for each story. We’ve more clearly visually tied “Events” to the PostRank score for each story, and introduced average amount of engagement per activity, which is a useful metric to judge the types of activity each post is attracting (e.g. lots of low engagement activities — like views, a few high engagement activities — like comments, etc.)

Updated login UI: A number of folks alerted us to the fact that it was a bit confusing to tell whether you were logged in or logged out from the Analytics site. We’ve changed how things look so it should be pretty obvious now if you’re logged in, and, for those with more than one account, who is logged in.

Google Integration is now industrial strength: We replaced the Google Analytics integration code with a much faster engine. This has improved loading time and performance by leaps and bounds.

Bug fixes: We do our best, but we can’t catch everything… We’ve fixed some things the community has reported, as well as things we noticed when sign-ups started. Some fixes affect the whole system; some are user-specific. This will be an ongoing project, of course.

Improved Daily Engagement Reports: Mostly on the back end, we upgraded how they’re built and sent out, so they should be more reliable now.

Upgraded social profiles: We added more sources to enable you to better connect with your audience (e.g. GitHub and LinkedIn).

Revamped Account page: It was a bit scroll-y before, so we’ve separated out the functions in a sidebar on the left, which should make it easier to navigate to what you want to do.

Even though we’ve made a lot of improvements, PostRank Analytics is by no means a static product at this point. Even as we speak we’re working on some very cool enhancements that we can’t wait to share with you! Stay tuned…

With the emergence and spread of a variety of real-time communications protocols and channels – from IM clients to RSS and enterprise applications – the useful half-life of information has shrunk significantly, in many cases to mere seconds. PubSubHubbub, RSSCloud, ping servers, and a dozen of other technologies are also transforming RSS into a near real-time medium. However, content and information are not one and the same. Looking at our overflowing inboxes, it is clear that instant delivery is but one of many applicable filters. Having dozens or hundreds of stories delivered to you in real-time is not terribly useful if the context is wrong or irrelevant. Which raises a great question: how do we filter the real-time web?

Information vs. Attention Scarcity

Delivering highly personalized, context aware and timely information should be the goal of any publisher and application. There is simply so much information online that it’s impossible to be competitive without those deliverables. The push towards real-time technologies addresses the factor of time, but also places an even higher value on context and relevance. If the breaking story requires immediate attention, should the application interrupt your current task or pull you out of a meeting? Herbert Simon identified this problem decades ago:

Many designers of information systems incorrectly represent their design problems as information scarcity rather than attention scarcity, and as a result they built systems that excel at providing more and more information to people, when what is really needed are systems that excel at filtering out unimportant or irrelevant information.

Or, as Clay Shirky put it, “It’s not information overload. It’s filter failure.”

Context, Relevance and Rich Metadata

Context and relevance are subjective and require explicit knowledge about the user. Personalized news, targeted content and recommendations systems can now be found in most applications as they try to help the user navigate the continuously expanding media landscape. Metadata about the user is a scarce and a valuable resource: if the application knows your preferences, it can deliver useful information. But in order to know your preferences, you first have to go through an often painful training phase where it knows often laughably little about you. In machine learning parlance, this is known as the “cold start” problem.

However, user metadata is only one part of the equation. Having a rich description of the content itself can be an enormous help in helping determine the context and relevance to the user. For example: what is the content about, who is the author, how was it classified, how big is the audience? At PostRank, we’re trying to answer all of those questions and more. We leverage the real-time web to guarantee timely delivery, but as each story passes through the PostRank stack, it is also enriched with as much metadata as possible:

• Language Analysis: Each story is run through a machine learning algorithm to determine the language. As it turns out, most publishers either forget to provide this data or have it set incorrectly.
• Semantic Analysis: Each story is a categorized for general sentiment (positive, neutral, or negative), the overall emotional score, and a detailed score for each of Paul Ekman’s categories (anger, disgust, fear, happiness, sadness, surprise).
• Real-time Feed Engagement Score: How has this feed performed within the last 30 days? A real-time engagement score is injected into every feed, allowing you to easily gauge the size of the engaged audience.
• Topic & Category: Leveraging the PostRank index and topic classification, each feed is enriched with data about areas of coverage and their popularity.
• And more…

Attention is scarce and as designers of these applications we have to leverage every bit of information available to help the user make the best use of their time and attention. At PostRank our goal is to help the user “Find and Read What Matters”. As the real-time protocols gain wider adoption, we believe that having rich metadata will be crucial to good user experience, and the next evolution in the better, faster dissemination of content and news.

Building or thinking of a Real-Time web application? Come by and talk to us at the ReadWriteWeb Real-Time Summit this week (October 15th) in Mountain View, or ping us directly at anytime.