Here’s a rundown of my work setup. I’ve tested all of these products extensively and consider them indispensable.
Computer: Macbook Air-13 inch 256GB
Monitor: Thunderbolt. For a long time I thought that this was an overpriced monitor. I was very wrong. It makes every other monitor I’ve used look broken in comparison. It definitely reduces eye strain at the end of the day.
Sizeup: SizeUp allows you to quickly resize and position your windows with keyboard shortcuts. They call it the missing window manager and I have to agree. I mainly use it to resize windows to the left and right half of the screen. This allows me to take advantage of all the screen real-estate on a cinema display monitor. For keyboard mappings I have option-q = Left, option-w = Fullscreen, option-E = Right.
Jumpcut: Shows the last 10 things I copied to the clipboard.
Quicksilver: It’s similar to spotlight, but I find that it does a much better job at launching applications. I also use it to control iTunes from the keyboard while I’m working in other apps. I have keyboard shortcuts setup to rate tracks and display the currently playing song on the screen.
Dropbox: I save all my created documents in Dropbox so it’s always backend up and available on other computers.
Notational Velocity Alt: I use it to take all my notes. I find Evernote to be really heavy and it’s footprint is much too big. Notational velocity takes up a tiny amount of screen real-estate so I can use it in conjunction with other apps while I’m working. The Alt version adds the ability for theming. I use a black background with white text, which reduces eyestrain.
Simplenote: I use this on my iPhone for note taking. It works perfectly with Notational Velocity so text is always synced between my desktop and phone.
Afloat: I use afloat on Notational Velocity to keep that window on top of other windows. I often have an app open full screen, but I need to take notes or refer to them. I hate having to switch windows, so Afloat just keeps that windows on top of all the others.
F.lux: Looking at a screen late at night when the surrounding environment is dark, increases eyestrain. Flux gradually adds a tint to the screen at night to make it easier on the eyes.
Streambox: Having a music service like Pandora in the browser just doesn’t work. I accidentally close it all the time, and it’s hard to find the right tab to see what’s playing. Streambox is a Pandora app that sits in the menu bar.
Airfoil: I love this app. It allows you to beam music from your desktop to another desktop, iPhone, or Airport.
Adobe Creative Suite: Pretty standard. I haven’t tried Cloud yet, but I really skeptical. I’m still on CS6 desktop version.
JMP: I use this for statistical data analysis. It’s similar to R but with a usable graphic interface. It’s ability to quickly clean data sets is unparalleled. I use it to quickly run distributions, get rid of outliers, and look for correlations in data. There is way more in there than I know how to use. If you’re reading this you’ll probably be interested in it’s ability to do logistic regressions, and partition analysis.
Tableau: I just started using Tableau but so far I’m really impressed. I would describe it as Excel PivotTables on crack. It makes manipulating and visualizing data very easy. I can almost always do the work in Excel, but Tableau does it in minutes instead of hours. Also, when I’m dealing a very large data set, Excel chokes and Tableau handles it like a pro. Tableau is Windows only so I run it in Windows with Parallels.
Rubymine: I’ve just started to get better at programming. Rubymine is a full featured editor and it makes it a lot easier for a beginner.
Chrome Canary: I recently discovered Google’s beta version of Chrome, which they call Canary. It’s a completely separate browser from Chrome, so I can be signed into my work account. I use regular Chrome to sign into my personal gmail.
Skitch: I use Skitch for screen-capture and annotation. It was a lot better before Evernote acquired it, but it’s still decent.
Pinboard: I bookmark all my web findings in Pinboard. It’s a Delicious clone which I signed up for when it looked like Delicous was going to be shut down.
Mailbox: I use Mailbox for work email on my phone. Their ability to snooze an email until later is perfect for work email.
37 Signals Backpack: I used Backpack to write all my technical specs. They unfortunately stopped supporting it and new users can’t sign up. I am in the process of building a new version for writing specs.
When I’m working on a user acquisition project, I use Optmizely to A/B test the email capture landing page. I always create a custom event that triggers when the user successfully submits an email. Unfortunately, Optmizely doesn’t have a proper API which makes doing this difficult without redirecting to a new page.
First create a regex function to validate an email
Next, create a function that fires when the user clicks the submit button
Put the entered email into a variable
Write an if statement that uses our ValidEmail function to test if the email is valid
If the email is valid, send the event to Optimizely
In the last line we are calling our event ‘email_submit’. You can change this to any event name that you want.
All together it looks like this:
In Optimizely create a new custom event goal. Set “Custom Event to track” to email_submit.
Next week we’ll be releasing an app called Matchbook. Signup to be notified when it’s out. We’re a proponent of the lean startup methodology, so we wanted to share the process we used to get this app out the door.
We like to build software that mimics real life. The goal of software should be to make already occurring behavior easier, not to create new behavior. So, if you’ve ever taken a matchbook from a restaurant to remember it later, then you have an understanding of what this app does. Matchbook is a dead simple bookmarking application for places. When someone gives you a recommendation about a bar, restaurant, or shop you can bookmark it. The app will organize those places so you can make a fast decision about where to go out. We’ve heard it described as Delicious or Instapaper for places.
I called up a buddy I often discuss tech with and said, “Something is nagging me about the location based space. It doesn’t feel like mainstream America is quite ready for the check-in.” The question became, “What type of location based activities are normal people ready for?”
Mobile location research should be preformed in real locations, outside of the office. To answer our question we sought out feedback from normal people instead of from the tech industry.
To achieve this we planted ourselves at a bar, approached groups of people, told them we were about to build an app, and asked some questions. We also used the dating site HowAboutWe.com to go on dates so we had the undivided attention of a female for market research. No judgment; we paid for dinner. This turned out to be a great place to do market research because:
This is what we found:
We started wireframing the app in Omnigraffle. We spent most of our time removing features until we had what we thought might be the minimum viable product.We went back out to the bars and tested them. We rigged up a clickable prototype with a great app called Interface that allowed us to do our user testing. We would get a nights worth of feedback, re-do our wireframes, and then go back out. We iterated through this process about 30 times.
We kept going until:
When we began, we thought that Matchbook would be a social app. We envisioned it helping people make plans, share tips, or share bookmarked places. As we talked to more women, we found th
at they were a little burned out on social and a more then a little concerned about sharing their location. The number of women that perfectly articulated the
social circles problem was amazing. As a result, our wireframes pivoted away from social and became a personal app. We will probably add in social in the future, but we need to rethink exactly how that should work for this market.
The MVP is a bookmarking application for places. The user can:
Once we had our MVP, we moved onto the development phase. We outsourced the entire thing, which involved a good chunk of time spent iterating through developers instead of code. That will be the subject of another post, but in the end we found a great team. My co-founder and I developed the entire thing for about $10,000, paid for out of our savings.
A key problem with building an iPhone app is that Apple only allows 100 slots for beta testers. This was rough as we tried to test our assumptions. We needed to ASK all of our users to download it, which skews the data.
After some brainstorming we came up with an alternative. We are going to launch in the Canadian app store first. Since we can’t do a private beta, this will be our beta test. People in the US can’t see the Canadian app store so we will localize things there. We’ll use our Canadian launch to get feedback and gather metrics.
Once we’ve iterated based on that feedback we’ll launch a more polished product in the US app store. The idea is to couple the download traffic from launch PR, with the iTunes Recently Released app list. This concentration of downloads will hopefully bump us onto a Top Downloads list in our category.
These are the assumptions our lean process has yielded. We will be testing these in Canada next week:
We started with this step at the same time as Step 3. We decided that offering local deals is the best bet for monetizing a location based startup. Since we don’t have the money for a sales force we began our customer development process by speaking with group buying sites. We found out that they:
To better understand the group buying market, we offered to help out a NY based group buying site with their metrics. This gave us enormous insight into the types of challenges our customers face, and we learned great tactics for optimizing daily deal sales.
That’s it for now. The app will be out in Canada in a week, and out in the US shortly after.
Thank for reading,
Cross-posted from Business Insider
“Love ‘em or hate ‘em, you have to admit GoDaddy’s Super Bowl ads are effective.”
That’s how Mashable opened their recent blog post on GoDaddy’s biggest sales day in the company’s history. What’s perplexing is that the numbers don’t add up to a profitable campaign. In fact, they seem to suggest that GoDaddy lost up to $7 million dollars. Despite this, I applaud GoDaddy for releasing these numbers. This type of transparency keeps the cost of advertising in check by allowing us to calculate its value.
Here are the stats from Mashable:
- Hosting sales jumped 45%.
- Dot-com domain sales rose 40%.
- New mobile customers increased by 35%.
- The company added 10,000 customers in total.
We need a few more stats to calculate GoDaddy’s ROI:
That makes their customer conversation rate .009% (10,000 customers/108.41 million viewers).
The Cost Per Acquisition for GoDaddy is $750 ($7.5 million / 10,000 customers).
A campaign is only considered successful if it acquires a customer for a cost less than the customer’s lifetime value. In this case the lifetime value of a GoDaddy customer would need to be greater than $750 for this campaign to be considered successful.
Let’s gather a few more data points from GoDaddy’s website to calculate LTV (lifetime value):
Let’s assume that the average hosting customer stays with GoDaddy for 1.5 years, making them worth $89.82 ($4.99 hosting cost x 18 months). Some customers will cancel after a month or two, and some will stick around for a long time; 1.5 years is an educated guess on the average.
Let’s also assume that the average domain renews at least once since that happens automatically, making it worth $18.78 ($9.39 x 2).
Assuming that there was a 50/50 split in the products purchased, the lifetime value of an acquired GoDaddy user is $54.30 ($89.92 hosting + $18.78 domain / 2). That means that GoDaddy lost $660 per user ($750 CPA – $54.30 LTV) or $7 million dollars ($7.5 million – $54.30 LTV X 10,000 customers).
To be fair, GoDaddy was only reporting the number of customers they received on Monday, the day after the Super Bowl. They will likely continue to gain new customers for a longer period of time. Let’s assume that each day they acquire 20% fewer customers, as a result of the Super Bowl ad, than they did the day before. This should account for the ripple effect of media attention. That would mean that the Super Bowl ad would have a one-month effect, and GoDaddy would end up with 50,000 new customers. If we re-do our calculations:
Cost per acquisition: $150
Lifetime Value is still: $54.39
That means they lost $95.61 per user, or $4.7 million total.
I hear a lot of talk from marketers about intangible benefits. Maybe the intangible benefits of running a Super Bowl ad is equal to $4.7 million, but I have a hard time wrapping my head around that. An often-cited explanation is that the media buzz from running a Super Bowl ad exceeds the cost of the ad. According to the Wall Street Journal, companies value the media coverage at an additional $10-20 million dollars in equivalent advertising. Measuring the return on investment by calculating the value of the additional advertising they receive seems circular. Why aren’t they measuring their return on investment in sales?
This isn’t a condemnation of GoDaddy. It seems that the ad industry is significantly overcharging for their Super Bowl slots, and not delivering on their promise of customers. Companies are willing to pay, so you could argue that they are valued appropriately for demand. However, as we move away from traditional marketing and towards measurable user acquisition, I imagine that will change.