Posted by
Bill Piel on Tue, May 15, 2012 @ 02:32 PM
Hoverboards probably won't be on the shelves until 2015, or possibly 2014, but alpha versions of amazing, bleeding-edge web development frameworks are available today!
Recently, there have been some exciting developments in this space. Several teams are working on their own solutions with the goal of drastically simplifying the process of developing a web application.
Derby
Meteor
Firebase
SocketStream
Capsule & Thoonk
Space Magic
These frameworks boast a few common features I am very excited about:
Sharing code between client and server
I feel terrible every time I have to duplicate model validation logic in both a server-side language and javascript. These new frameworks are based on javascript, or languages that compile to javascript (like coffeescript), which means everything you write can be run on the server or in the browser.
Notably, clojure, with the invention of clojurescript, also has the capability to compile to javascript, although I am not aware of anyone working to leverage the concept of real-time model syncing and live binding into a framework. I would love to see this.
Automatic real-time model syncing and view rendering
Every web app I've written has had semi-specialized code dedicated to translating UI interactions into changes to a data model, and then communicating those changes to and from the server. These frameworks allow you to define UI-model bindings declaritively and then handle propagation between UI, model and server automatically and in real time. And, if one client makes a change to a model that is also powering another client's UI, the second client receives the updated model data and has their UI re-rendered automatically as well. These are powerful ideas and will simplify or eliminate many of the typical complications that currently hinder web development.
What's the catch?
The catch is that these technologies are still very alpha. They are either missing important features, very buggy, or regularly making breaking changes to their APIs. I've spent some time with Derby in particular, and it's definitely bleeding-edge (because I got cut, bad). But, that hasn't lessened my strong belief that the fantastic ideas implemented in these solutions will be part of mainstream web development in the near future. I'm rooting for all of these guys.
Google CEO Larry Page recently announced that Google Plus crossed over the 100 million user mark and continues to see strong user growth.
Despite these strong numbers, however, the service continues to be pummeled in the press. Many outlets have claimed that engagement is poor and that growth is only fueled by Google forcing membership upon users of its other products.
Rather than rely on third-party reports, we decided to pull publicly available data on a random population into an RJMetrics online dashboard and see for ourselves.
Here are some of our most interesting findings:
- The average post has less than one +1, less than one reply, and less than one re-share.
- 30% of users who make a public post never make a second one. Even after making five public posts, there is a 15% chance that a user will not post publicly again.
- Among users who make publicly-viewable posts, there is an average of 12 days between each post
- A cohort analysis reveals that, after a member makes a public post, the average number of public posts they make in each subsequent month declines steadily. This trend is not improving in newer cohorts.
How We Did It
We began by selecting a population of 40,000 random Google Plus users. For each user, we downloaded their entire public timelines (which consist of all publicly-visible activities for that user). Only one third of the users in our population had any public activity, so this sub-set of the population is the main focus of many of our statistics.
Once we had the data, it was a snap to upload it to RJMetrics and pull the insights seen here with just a few clicks.
Since we are looking at public data exclusively, we want to point out that this data is not necessarily reflective of the entire population of users. These are simply insights into the public-facing actions of Google Plus users based on a population that is known to post publicly.
Repeat Posters
Once a user has made one public post, the chances that they will make a second post are quite strong: around 70%. After that, however, Google Plus does not perform as well as other social services that have analyzed. In charts like these, we typically expect to see the probability of repeat posts shoot up to well north of 90% by the time the user has made several posts. This is basically the "once you're using it you're hooked" principle.
With Google Plus, however, this number never crosses the 90% mark. Even after having made five such posts, the chance of making a sixth is only 85%. The means that 15% of people who have made five posts never came back to make a sixth.
Cohort Analysis
The cohort analysis below shows the rate at which new publicly-viewable posts are created by users who made their first post in different months throughout time.
This is a cumulative chart, so we're basically showing the "average number of total posts made" as it grows over time for users in each cohort.
The decay rate here is very concerning. Users are less and less likely to make additional posts even a few months after initially joining. While it may not be an apples-to-apples comparison, it's interesting to contrast this with the same chart from our Pinterest Data Analysis, which shows no decay whatsoever.
Time Between Posts
We were surprised at the by the length of time between public posts among users. On average, a user waits 15 days between making their first public post and making their second. This number declines with each subsequent post, but not drastically. There is an average of 10 days between a user's fifth and sixth public posts.
The overall average time between any two public posts by the same user is 12 days.
Remember that, since we are only looking at public posts, it is very possible that users are making non-public posts in between the ones that we were able to see. Despite this, however, we were still quite surprised by the large amount of time between public posts.
+1s, Replies, and Sharing
Of all the categories, we feel that this is the least likely to be biased by the fact that we only studied public posts. These public posts will still be visible to each member's private networks, and actually could attract +1s, shares, and replies from external users as well. If anything, we would expect our numbers here to be higher than in the general population.
Despite that, our population of nearly 70,000 posts yielded the following properties:
- An average of 0.77 "+1s" per post
- An average of 0.54 replies per post
- An average of 0.17 re-shares per post
Conclusion
From what we can see from the outside looking in, Google Plus has a long way to go before it becomes a real threat to the social networking landscape. While user growth is strong, it is unclear how much of that is driven by tie-ins with other Google products.
At the end of the day, Google Plus simply does not show the same level of ravenous user adoption and engagement that we've seen in other social networks (see our reports on Pinterest Data and Twitter Data for examples).
This week, at RJMetrics...
Product News:
- We've rolled out improvements to our dashboards that will allow for greater compatibility with Webkit-based browsers and a generally better-looking dashboard experience.
- Our data syncing process has received new functionality that allows it to more intelligently identify changed data on our clients' remote systems. This will lead to faster update cycles for many of our clients.
- Rollout of our improved charting system continues. More details here.
- New clients will now experience a smoother on-boarding process thanks to the release of a new guided implementation process.
Company News:
- Drexel grad Tara Carlin joined our team last week as a Support and Implementation Analyst.
- Francis Ryan, a developer and recent Drexel grad, will be starting with us this week.
- Ted Bockius has joined our team as our new Director of Marketing. Ted has held numerous senior roles at high-growth technology companies.
- The Broad Street Run was held in Philadelphia last weekend and we were proud to have several team members participate.
- Our CEO Robert J. Moore delivered a keynote address at the Symantec Vision 2012 Conference in Las Vegas on the topic of "The Data Explosion."
You might have heard or seen by now that we are in the middle of releasing major changes to your RJMetrics dashboards. The most obvious changes were made on chart visualizations, but this is just the tip of the iceberg. We will also be introducing numerous enhancements that aim to improve your overall user experience. At the time of writing this blog post, we have rolled out the new features to 35% of our clients, and we continue to migrate new clients every day. So if you haven't yet been transitioned, rest assured that it is just a matter of time for the new charts to reach your dashboard.
In this blog post I will explain what the changes are, and most importantly their benefits to you.
New Dashboard Visualizations
The new charts will now look much more vibrant. They will be rendered using the HTML5 standard which will allow faster rendering, and multi-platform support. The library that we are using also supports a plethora of other types of chart visualizations, which will allow us to extend our chart type offerings in the future.
All new charts will also be using the Scalar Vector Graphics (SVG) format which will allow you to download a graph and resize it without any loss of image quality. Another cool feature included in the new HTML5 charts is the ability to directly click on the name of a series in the chart's legend to remove or add the series from a multi-series chart.
Transitioning away from Flash means that you can now actively view your dashboards on your iPad/iPhone. Note however that chart editing is not yet fully supported on your mobile devices.
Faster Chart Loading
Chart loading times are dramatically faster with the new chart system. This is partly due to HTML5 rendering, but it is also due to the introduction of a redesigned caching framework. For non-technical folks, caching is a method of saving data in memory so that future access of the same data is faster. More specifically, we use caching to store chart data for faster retrieval. Our live production testing revealed a 10-fold loading time reduction for new charts compared to old charts. The benefit can be even more pronounced if you have charts with a very high number of data points, such as our advanced cohort analysis charts.
Faster Updates
The new caching system will not only reduce chart loading times, but also reduce the time taken to complete a data update cycles (syncing your RJMetrics data warehouse with your own database). This is a result of speeding up the chart pre-caching section of an update cycle.
Another indirect performance enhancement will come from the fact that we will no longer need to make certain calculations during an update cycle. These calculation processes were integral to the proper functioning of the old chart engine, but we have eliminated this requirement in the new charts.
Conclusion
We are all very excited about these changes, and we all believe that this is a major step in the right direction for user experience. The most noticeable change will be chart rendering, but under the hood, these changes will enable us to iterate faster with new features and improvements.
As always we really value your opinion, so let us know what you think about the changes by dropping us an email at support@rjmetrics.com.
Here's a quick update on what's been going on around RJMetrics' headquarters.
Product News:
- Speed and visualization improvements continue with the rollout of our new HTML5 charting system to several dozen more clients.
- New users will now be greeted by a guided tour after logging in for the first time.
- Our product now supports the Indonesian Rupiah.
Company News:
- We participated in a number of Philly Tech Week events, including Philly Start Up Weekend, The Indy Hall Blood Drive, the "Tales of a Philly Entrepreneur" panel at Woodcock Washburn, the "eCommerce Secrets Exposed" panel at Seer Interactive, and the Philly Tech Week Signature Event.
- The Philadelphia Building, which houses our headquarters, completed a window replacement project that will make it a much more energy efficient building (and finally allow them to remove some unsightly scaffolding).
- The company kegerator is finally operational, just in time for summer weather. On tap are Yards Philadelphia Pale Ale and Dogfish Head 60 Minute IPA.
What's Next:
- At current, we are actively interviewing candidates for several open positions, which can be found here on our jobs page. Look for more additions to our dedicated team in the near future.
- You can catch our CEO Robert J. Moore presenting live to 3,000 attendees as the Symantec Vision 2012 Conference in Las Vegas on Tuesday, May 5th.
Check back with us in two weeks for more product updates, office news and info.
Airbnb is one of the hottest sites on the internet. The Y Combinator graduate has raised $120 Million of funding to change the way people find places to stay around the globe.
As fans of Airbnb with a passion for startup data, we decided to try and learn more about the site's user base by looking at the publicly-available profiles of its members. We sampled just over 60,000 users and were able to draw some interesting insights using an RJMetrics business intelligence dashboard.
Some highlights include:
- Airbnb has over 2.1 million registered users and is growing about 250% year-over-year. At this rate, they'll have 3 million users by the end of June and 4 million by the end of August.
- Almost 85% of Airbnb's userbase has never received a review as a host or a guest. Our sample suggests that there may be as few as 350,000 reviewed users among the userbase of over 2 million.
- Usage is addictive -- with each additional stay booked through Airbnb, users become increasingly likely to book again.
User Growth
Since Airbnb uses auto-incrementing IDs for its users and does not appear to have skipped any range of ID values, it is quite easy to track user growth over time.
Airbnb has very seasonal growth patterns, with most new users signing up in the summer (peaking in August) and significantly fewer signing up in the winter months (reaching a low point in December). These user analytics were easily extracted using RJMetrics.
The current user count is approximately 2.1 million.
For the past several months, the year-over-year growth rate has been steady at around 250%. Extrapolating this out for the rest of the year puts the site's user count at over 3 million by the end of June and over 4 million by the end of August. At its current growth rate, the site will approach 6 million registered users by the end of 2012.
Usage
Since we didn't have direct access to data on actual stays, we used reviews as a proxy for activity. Reviews are the lifeblood of the Airbnb community, so we think it's fair to assume that the number of reviews is a good proxy for the number of stays.
Most sites we study show signs of the "80/20 rule," which suggests that 80% of the activity comes from 20% of the users. In Airbnb's case, it's more like the "100/20" rule -- only 16% of the user base has been reviewed as a host or a guest.
Here are some other usage statistics:
Only about 14% of users (or about 300,000 users) have been reviewed as guests.
Only about 2.3% of users (or about 50,000 users) have been reviewed as hosts.
A mere 0.5% of the userbase has been reviewed as both guest and host.
5% of users (or about 100,000 users) have active listings, but only 2% (or about 40,000 users) have received reviews from guests. This suggests that more than half of the people listing properties have yet to host a guest.
Repeat Activity
By relying on the same techniques we use to track repeat purchase probability in RJMetrics, we were able to profile the average user's likelihood of using Airbnb with each additional stay.
As you can see, while only about 14% of the userbase ever books a stay (as indicated by a first review from a host), 22% of those users who book once go on book a second stay via Airbnb. By the time a user has booked five stays, the likelihood that they will book another stay on Airbnb is over 50%.
Note that these percentages are based on the behavior of the existing user population, the majority of which has been registered for less than a year. Since so many users have a limited history on the site, it's quite likely that these numbers will increase over time.
Conclusion
Airbnb continues to explode in popularity and experience tremendous user growth as a result. As with most consumer sites, however, the population of active users is much smaller than the total registered user count.
Airbnb's key to continued success will be to both grow its user base and convert more of its registered users into paying customers. As we've seen, with each additional booking users become more likely to book again.
Click here to use RJMetrics to draw actionable insights from your company's data.
So, as you've heard, Facebook has acquired Instagram for $1 Billion worth of cash, stock and PBR. That's more than the New York Times is worth.
Since the announcement, the general conversation is this:
- Instagram isn't worth $1 Billion since it has no revenue.
- Instagram is worth $1 Billion because it's so much better than Facebook at photo sharing. See Robert Scoble's arguments.
- I should start a company that Facebook would want to buy.
Let's focus on that last one. I've ranted about this before, but to put it frankly, we've got bigger fish to fry. I mean that as a society.
I think it's relatively safe to say that the photo-sharing problem has been solved. There's 1001 real problems on this planet that have no solution.
So, I'm proposing something different. Before starting a business or joining a startup, ask yourself if that startup is solving a problem. And I don't mean a "this photo could use more filters" problem. I mean a real, "this will actually make people's lives better" problem.
Start the next Dollar Shave Club, not the next Instagram.
I'll be at Startup Weekend Philadelphia on April 20th. I'll help you start something real.
It's been a busy two weeks here at RJMetrics.
Product News:
- We added support for the Swiss Franc, providing more options and capabilities for a global market.
- Users can now have a better understanding of how fresh their data is by looking at the "data updated through" time in the connections section of the settings page. This shows the last time that we went and checked for new data from your database.
- Bug fix: the default lable in the dashboards menu can now correctly handle the syndicated dashboards.
- We added resources to the server that hosts our dashboard, in an effort to keep the time it takes to load pages down.
- Forward progress continues on our new chart builder and HTML5 charts. We are in the process of migrating dozens of clients over to the new system and will continue to push forward with the migration in the coming weeks.
Company News:
- We're ordering and assembling furniture and workstations, in preparation for the arrival of our five exceptional summer interns, who start in early June.
- We're in the process of setting up individual phone lines, to better handle and streamline our customer service and communication.
- Every two weeks, we now have a company happy hour.
- Our newly arrived kegerator is a work in progress. After much debate, we've settled on what kind of beer should be in the office. Now, all that's left is figuring out how to put the whole thing together.
What's Next:
- At current, we are actively interviewing candidates for several open positions, which can be found here on our jobs page. Look for more additions to our dedicated team in the near future.
- Come out and see RJMetrics at Philly Tech Week! Bob is speaking here and here.
- Later this week, Bob and Jake head out to San Francisco to meet with investors and customers. Brace yourself, west coast.
Check back with us in two weeks for more product updates, office news and info.
Posted by
Owen Jones on Thu, Apr 12, 2012 @ 03:29 PM
I recently left a job at a large company to join Philadelphia startup RJMetrics as a Software Developer. While I knew it would be very different here, I wasn't completely sure what to expect. Now that I've had a chance to get the full experience, I thought I would share some of the pleasant surprises I've encountered.
While a few of these are RJMetrics-specific, I think many of them would be true at most startups. As such, I would encourage everyone out there who is considering a move to a smaller company to read closely and strongly consider taking the plunge. Here are 9 unexpected perks of working at a startup:
1. Values
Many of the items on this list are what I would call "perks," but they all exist because of the compelling core values of our company. Two of the values that struck me earliest were trust and fairness. These could seem like ephemeral ideas, but can have very benefical results when put in practice at a company. I saw them in action in my first few days.
RJMetrics gives away a free iPad to all of its developer applicants who make it to the in-person interview stage. I must have glossed over this when reading the job description, because I was completely unaware of the program. Shortly after I started, however, our CEO realized that I had never been given an iPad and immediately ordered me a shiny new iPad 3. I would have never asked for it or begrudged them for not getting me one -- they did it anyway because it was the right thing to do. They keep their promises.
Understanding and agreeing with values like these makes it easy to feel proud of what I do and grow as a person while I do it.
2. Ownership
Every single person at the company participates in the Employee Stock Option Plan. This aligns all of our incentives for creating long-term value and makes us proud and excited by each other's accomplishments.
3. Amazing People
Being surrounded by people who you respect intellectually is one of the most valuable parts of a job. When you're at a large company, it's inevitable that some people have slipped through the cracks who just aren't up-to-par. In some companies, those people end up being the majority. Startups, however, have smaller teams and are able to exercise a much higher level of control over who is brought on-board.
It is extremely clear that every single member of the RJMetrics team was hand-picked and rigerously vetted before being brought on-board. There isn't a person in this office who I couldn't learn something new from, and based on the interview process I went through, I can tell that I was hired because I will teach a few lessons myself.
4. Frequent Feedback
Every six weeks, the founders of the company sit down privately with every single member of the team to provide job performance feedback, solicit feedback on their own performance, and listen to opinions and ideas about the direction of the company.
This simple process is extremely valuable, so it's surprising to me that most larger companies have infrequent reviews that don't involve bi-directional feedback.
For me, this process provides a clear sense of how I'm doing and what I can expect as a member of this team. It also gives me a chance to help steer the business side of the company, which is not always a perk that a developer receives.
5. 10% Time
We are each given one day every 2 weeks to pursue a project of our choosing. This is a fairly new program at RJMetrics, but it has already generated a bunch of really useful internal tools and some great user experience improvements.
In addition to yielding great output, this program also allows everyone to exercise their creative side and be an end-to-end product manager on something that genuinely interests them.
6. Agility
Older, larger companies often have layers of bureaucratic scar tissue that can discourage employees and even make it seem impossible to innovate. Startups have to get stuff done to stay alive, and their teams are motivated to do so quickly.
As a result, I get to look back at "where we were" even a month ago and see real, meaningful changes that I've helped bring to life.
7. Transparency
Every day at 5PM, we have a stand-up meeting where each team member briefly reports on his or her progress that day and plans for the next day. This keeps me in the loop about company-wide projects and confirms that what I'm working on really matters.
We also have flat-screens throughout the office showing metrics about customers, revenue, system usage, and other indicators of company value. Sometimes these figures raise questions that are completely unrelated to my job. Thanks to our culture of transparency, I'm not afraid to ask them.
8. Trust
Employees are a startup's most valuable asset. Team members are trusted to contribute everything they've got. They are offered tremendous perks as a result of that trust.
Besides more common employee benefits like health insurance and stock options, RJMetrics provides a suite of benefits to promote a healthy, efficient and fun work environment. Little things like the fully stocked kitchen, freedom to design your workspace (including the awesome Geekdesk), and flexible working hours go a long way towards helping us contribute our best possible work. We even have a nap room for those days when a power nap at lunchtime will lead to a more effective afternoon.
9. Fun
There are no shortage of jokes in this office. We go out for company events on a regular basis. Our conference room table doubles as a ping pong table. I can't recall a stand-up meeting where everyone hasn't laughed at least once.
When everyone is excited about what they're doing and proud of the output, it's easy to have fun at work. Nowhere is this more possible than at a startup.
Conclusion
As I read through this list, it strikes me that these "perks" mirror our company's core values very closely. Everything on this list is a reflection of the culture of RJMetrics.
When looking for your startup job, try to make note of the culture of the company. It's a much bigger deal than you might think.
Posted by
Jake Stein on Mon, Apr 09, 2012 @ 12:35 PM
Almost every company we work with is interested in running cohort analysis on their data. This comes as no surprise to us because cohort analysis is an extremely powerful tool with many potential applications.
Many companies understand that cohort analysis can be a valuable tool, but they ask an important, fundamental question:
How can I use cohort analysis to improve my business today?
Here, we step through an example of how a fictional company uses cohort analysis to make smarter business decisions. This example was compiled based on observations of how real companies are using the cohort analysis functionality in our online dashboards.
A Cohort Analysis Example
Let's use our Vandelay Industries demo data set. There are a few important things to know about this business.
- Ecommerce site
- Actively spending on acquiring new users
- Some users buy immediately upon signing up, others only after a while, and others not at all
- Cost per acquisition for paid search is $80
- All-in acquisition cost (including discounts and revenue splits) is $60 for a group buying site
Based on this information alone, it makes sense to double down on group buying, because it has a significantly lower cost. The missing information is what these users do after they are acquired. That's where the cohort analysis comes in.
Below, we have two weekly cohort analysis charts. One is for customers acquired through paid search, and the other is for a group buying site. The average incremental revenue from customers acquired through group buying sites is significantly smaller than other customers. Once the data is presented in this way, it's easy to see that our strategy of focusing on group buying rather than paid search is shortsighted.
Three months in, users acquired from paid search generate $140 and group buying generate $75, almost 50% less.
- Paid search 3 month net revenue per user is $140 - $80 = $60
- Group buying 3 month net revenue per user is $75 - $60 = $15
We could look at the data for different cohort time periods, or in different segments, but the underlying message is the same. Without the benefit of cohort analysis, the folks at Vandelay would be acquiring drastically less profitable customers.
For a real life example of how one of our customers uses this analysis to make smarter customer acquisition decisions, see the Jackthreads case study.
You can also test drive the Vandelay Industries demo to run this analysis yourself, or start your free trial of RJMetrics to run cohort anlayses on your business's data.