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Sift Science team.

The 8-person San Francisco startup uses machine learning to analyze user interaction with web sites and create a digital profile of who will likely perpetrate online fraud, said company co-founder Brandon Ballinger, an ex-Google software engineer.

Companies can use the service — built on Hadoop, HBase, Avro and MongoDB —  by adding some Javascript code to their sites and then using JSON (JavaScript Object Notation) APIs “to track transactions, bans, chargebacks, or custom event types,” according to the company.

Here are some early findings based on the private beta of the service:

1: Fraudsters tend to be nightowls. Most fake accounts are created late at night local time: 3:00 a.m is apparently the witching hour.

2: Bad guys stick with old technology.  People using Chrome on Windows XP are four times more likely to create a fake ID than the average user. (Firefox users are 50 percent more likely than average to create a faux account.)

On the other side of the same coin:

3: Fakers don’t update.  An account created on Safari running on Mac OS X is about 30 percent less likely to be fake. Those running IE9 on Windows 7 are 33 percent less likely than average to be fake.

4: Yahoo email is big. Folks with Yahoo.com email accounts are five times more likely to create a fake account than someone using Gmail.com or Comcast.com addresses.

5: Geography is key. Most traffic coming from Nigeria is fraudulent but also goes through a proxy to disguise its point of origin.

“Based on user actions, we build a model of what a normal user would do on a site versus what a fradulent user would do. We look at the time of account creation, the sequence of pages viewed. If they’re browsing around, they’re probably normal. If they set up an account and jump straight to a transaction, probably not,” Ballinger told me by phone. But then again, they’re tricky. Sift Science found that someone who opens an account, then waits an hour before transacting is 7 times more likely to be fraudulent than the average user.

The proess is similar to Google Analytics in that Sift Science creates a history of user events and comes up with a score for each user that rates the likelihood that he or she is involved in fraud, he said.

Sift Science is heavy on former Googlers:  6 employees are ex-Google engineers. Jason Tan was former CTO of BuzzLabs and Fred Sadaghiani was CTO of Teachstreet.

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Once Hiptype’s plugin is added to an ebook, it provides insights like reader demographics, reading behavior (where people start or stop reading; what they skip), conversion patterns (who buys an ebook after reading a free sample); and sharing and highlighting behavior (which passages readers highlight or take notes on). Publishers then log into their Hiptype accounts to see a dashboard with visualizations of the data. Hiptype also helps publishers run Facebook campaigns and target readers with personalized recommendations.

Hiptype launches in beta this week and is working with a limited number of publishers, whom 26-year-old founder and CEO James Levy (cofounder is 19-year-old Sohail Prasad) would not name — though a sample book profile for 50 Shades of Grey suggests Random House might be one early client. Other publishers — as well as self-published authors — can request access on Hiptype’s website and will be invited to join in waves. The first book is free. After that, Hiptype will charge $19 per month per book for a basic package (including data from up to 1,000 readers and basic insights and trends) or $99 per month per book for a pro package (including data from up to 500,000 readers, detailed insights and trends, ad management and personalized backlist recommendations for readers).

One possible concern is privacy. “We don’t want to discourage the conversation about privacy,” Levy said, noting that while all of the data Hiptype collects is anonymous, users can opt out completely. The company is also looking for ways it can improve its service for readers. In beta, end users have requested that Hiptype make its data available to them. For example, Levy said, a teacher could track how students are interacting with the books they’ve been assigned to read.

It doesn’t work everywhere yet

Hiptype’s largest limitation is that it doesn’t work on every platform. The plugin only works on platforms that support HTML5 and allow Javascript to be embedded within a book. Apple, which supports EPUB3 and HTML5, is in. But e-ink devices, like Kindle and Nook e-readers, web-based readers like Kindle Cloud, and desktop e-reading platforms are out.

Apple is estimated to have about 10 percent of the ebook market, with Kindle at 55 to 60 percent and Nook around 25 percent. In the case of Kindle and Nook, we don’t know how much of their usage comes from devices versus mobile apps, but for now Hiptype is missing a large portion of the ebook market.

Levy says Hiptype works on most iOS and Android e-reading apps, but wouldn’t clarify what those are beyond “some of the most popular e-reader apps on the most popular operating systems.” He says Hiptype is in discussions with ebook retailers and it’s “paramount to our success that we have an open line of communication.”

When publishers do see the data on their books, “it can be a little bit depressing,” Levy said. Publishers testing Hiptype in beta, for instance, were surprised by “how low conversion rates are” — early data suggests that only three to four percent of people who download a free ebook sample go on to buy the book — and how few people who do buy a book finish reading it. “It can be a bit of a bummer,” Levy said. “But as soon as you start measuring, you can do tests and see what moves the needle. We’re already doing research on the data we’re collecting. As data hackers, we think there are underlying patterns here even if they’re not apparent at first.”

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In reality, though, the fact is that almost everyone is looking for something else: a way out that changes their life. Whether it’s going public or getting acquired, everybody wants a return on their investment and the big exit. The life-changing sum of money is, ultimately, the pot of gold that drives startup culture.

But how do you make your dream exit a reality?

I spent yesterday at an event in London run by Seedcamp, the pan-European seed investment program, where an interesting discussion emerged about the nature of acquisitions, and how to achieve them. It started with a to-and-fro between insiders at two of the biggest potential buyers for most web startups, Facebook and Google. The question: how do they decide which companies to buy? What is it that they are looking for?

Christian Hernandez, Facebook’s head of international business development, pointed out that although Mark Zuckerberg’s company has made more than its share of purchases over the last couple of years, most of them were not obvious purchases.

“We think about either acquiring talent or actually looking at technologies that we can bring in and build products on,” he said. “We don’t usually acquire products.”

“There’s very few,” he pointed out, referring to a couple of recent transactions. “There’s Beluga, which we launched as Messenger recently; there’s Snaptu in Israel, which is a simplified low-end phone application. All the rest have been talent acquisitions. Expensive acquisitions, but…”

This is a tricky situation to navigate. In fact, perhaps it’s impossible. After all, you need to be successful to get interest from acquirers — but looking at what he said, there’s a subtext: that if you’re too successful, you may end up pricing yourself out of the market.

Even most product purchases are small

Conversely, Google has bought in a lot of products — Maps came from buying Australian company Where2; Analytics was built on the work of acquisitions like Measure Map; Android, meanwhile, was an eight-person outfit when Andy Rubin (pictured) sold it to Google in 2005. But Anil Hansjee, who ran Google’s acquisitions team across Europe, Africa and the Middle East for five years, pointed out that the vast majority of its purchases actually fell into a similar category to Facebook’s: talent.

“Eighty five percent of all Google’s deals since day one have been sub-$50 million transactions,” he said. What did that mean? “You have to think about what kind of company you are, and what kind of money you take on board.”

This, he suggested, meant understanding the way your incentives change over time. It’s easy to imagine that there is one easy answer for getting acquired: build a prototype, raise money, scale, profit, exit. But, in fact, there are two paths for entrepreneurs to follow, he suggested.

On one side there’s a track followed by those who are either early in their lifecycle or who have not taken large rounds of funding. This leaves the door open to a talent acquisition (but probably means your product dies). On the other side, there’s a route followed by those who take — or need to take — some sort of significant investment. The size of the acquisition that investors require to make their money back means that many companies will have probably already reached the point where they need a big exit. And that means they have to be one of those uncommonly large acquisitions that fall into the 15 percent category.

In some ways this may sound crazy — that raising money reduces your chances — but Hansjee was circumspect.

Misaligned incentives

He pointed out that it was simply that more entrepreneurs needed to understand the consequences of their actions; that they needed to think about how the incentives for founders and investors changed as money comes in. Bottom line: take significant venture capital — $5 million or above, say — and your board is much more unlikely to get the deal they want from an acquirer like Google or Facebook.

In some extreme cases, this is obvious. Look at the famous example of Color, which raised so much money it immediately priced itself out of the acquisition market.

The discussion also turned to Path, which rejected a reported offer of $100 million despite the fact that the service has not got a lot of traction. In both cases, the founders and investors had different incentives which meant that most of them had already decided to play the long game. But not everybody is in that position, or has the luxury of personal wealth.

So is it possible to be too successful? The answer — thankfully — seems to be no, at least if you measure success by the size of the business you build, not the amount of venture funding that you raise.

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It’s free and easy to get started with Analytics, but there are also a lot of advanced features that can make it even more useful. I’m sometimes surprised by how many people only look at their dashboard page and never really drill down into some of the more interesting details and features. I thought it might be time to do post with a few quick tips for getting more out of Google Analytics.

1. Alerts. If you want to keep on top of your sites and know when something out of the ordinary is happening, you should visit the “Intelligence” section and set up a few alerts. You can configure the service to email or text you when something specific happens. For example, on one of my websites, I have it set to alert me when the number of visitors goes over a certain threshold on any one day. Alerts can be set using most of the many different metrics available in the various reports. You can also apply your alerts to multiple profiles and use them on several different websites.
2. Custom Reports. Don’t just use the built-in reports; create your own custom reports (available in the “My Customizations” menu). Spend a few minutes thinking about what you really want to know, and create a custom report that you can view every time you log in. For example, I have a custom report that shows the unique visitors, new visits, time on page and pageviews for each blog post, and when I drill down into a single blog post, I can see which keywords people used to arrive at the page from search engines. The best thing about these custom reports is that you can share them across your Analytics accounts and use them on multiple blogs.
3. Export. Most of us would probably think about exporting our data as a CSV or XML file that we could use to crunch the numbers in some other application, and Google Analytics can certainly do that. However, it can also be used to create some nicely formatted PDFs of your data that you can send to your manager or your clients. This is a great way to quickly give someone who isn’t familiar with Google Analytics an overview of some specific event or a monthly analytics report with little extra work on your part. My favorite is to create a report by exporting from the dashboard, which gives you a multiple page file with overview numbers and graphs for visitors, traffic sources, maps, content and anything else you’ve added to your dashboard. You can get PDF exports by using the “Export” drop-down menu of any report; you can even export your custom reports.
4. Customize Your Dashboard. You should also take the time to customize your dashboard. First, add any frequently-used reports to your dashboard using the “Add to Dashboard’ button at the top of any report. You can even add your custom reports to the dashboard. Each box on your dashboard also has a very faint and tiny “x” in the upper-right corner that you can use to remove any unwanted information. Now that you have the right information on your dashboard, you can use the upper-left corner of each box to drag the components around to put the ones you want to see first near the top of the page. and less frequently-used items further down the page.
5. In-Page Analytics. I saved the best for last. In-page Analytics is one of my favorite features, since it lets you see where people actually click on your pages. You can find In-Page Analytics under the “Content” section in the left-hand navigation. You can navigate to various pages on your website to get a different view of where people are clicking on your subpages. You can also use the drop-down filter at the top to hide any clicks below a certain percentage to focus on where most people are clicking, or you can create your own filters to only see clicks from new or returning visitors, certain geographies, or based on almost any other available metric.

What are your favorite tips and tricks for squeezing more out of Google Analytics?

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Polaris is free for the single-account version, while a multi-user account will cost $15 per year. It’s based on Adobe AIR, so you’ll have to download that first if you don’t already have it. Once you have Polaris installed, you just use your sign-in for Google Analytics to start tracking site metrics from within the Polaris widget. It automatically creates an icon on your desktop that you can use to pop it up at any time.

RefreshingApps has posted a good video showing how Polaris works. You can view both graphs and numerical data in Polaris, and you can view several types of metrics concurrently, such as site visits, page views, pages viewed per visit and more.

If you’re interested in going beyond what both Polaris and the Google Analytics site do in terms of customization, there is an open-source site analytics application called Piwik that is worth trying (I wrote about it here). The great thing about Piwik is that an open community of users creates plug-ins for it, so you can get access to all kinds of widgets for analyzing site traffic data. It’s essentially like customizing your own dashboard for looking at site metrics, and is worth trying in addition to Polaris.

What do you use for analyzing site traffic metrics?

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I run product development at Xobni, maker of an email application that helps you organize your Outlook inbox. My co-founders and I were fortunate to get seed funding from Y Combinator in the summer of 2006, and I now often speak with entrepreneurs that are applying to the incubator. And when I do, I give them this advice: The most important decisions are the ones you make in the beginning of the process, such as what product to build, and what market to serve. These will determine whether you’re headed for failure or a multimillion-dollar exit.

Xobni was extremely lucky in that even though we initially built the wrong product, we were always focused on our product-market fit. This helped us quickly correct our course, and eventually produce a product that is making Microsoft drool. I’ll explain how we turned it around.

The Wrong Product
Our initial product offering was a program called Xobni Analytics, an Outlook plug-in that analyzed email traffic in the same way that Google Analytics analyzes traffic on your web site. The plan was to sell this software to corporations, enabling managers to remotely monitor employee email productivity. We soon discovered why this model was a bad idea, however: Employees might feel like they were being spied upon.

But Xobni Analytics was the wrong product to build for another, more important, reason: It wasn’t a sticky application, one that tempted users to come back again and again. But when we presented the data in a sidebar it was completely different; it allowed us to display numerous features beyond just the analytics, like users’ contacts and current communication threads, or documents they’ve recently exchanged with one other. This added even more value for the user. Plus, the sidebar sits right next to the inbox, so users are exposed to it for the two hours they spend (on average) in Outlook every day.

So we incorporated what we learned into the product we have today. Xobni is successful now because it provides focused information about people, (see second graphic, below), not just statistics.

The founders’ lesson: Remember that you are serving an audience of individuals who need simple solutions to their everyday problems.

The Right Market
Unlike the initial problems with product development, Xobni made the right decision early on to target the Outlook market. There are 350 million to 400 million Outlook users out there and yet there is also major dissatisfaction with the program.

After Outlook, people most often requested that we build Xobni for Gmail and Apple’s Mail.app. However, both of those clients have much lower “pain points” than Outlook, and Outlook users are more likely to have business credit cards they can use to buy software.

Good Looks
Here are some mockups of how we originally wanted Xobni to look. The mockup on the right was our original choice. It blends nicely into Outlook, almost as if Xobni was built into it from the start. We created the third one almost as a joke, to show how the sidebar would look if we used a funky color palate.

We decided to go with the bright, saturated colors on the left, because we believed it would have the following effect: Jack would walk by Jane’s desk, and see a bright blob on the right side of her Outlook screen, and he would blurt out: “What the heck is that?” Jane would have to explain Xobni and what it does, and Jack would probably install it once back at his desk.

Architecture
Xobni’s major differentiator is our software architecture. We don’t do the easy thing, but the right thing. For example, the data layer in Xobni is a platform for communications data in general, not just emails in Outlook. We can easily build new applications and build integrations into other email clients, as these leaked screenshots illustrate.

The Launch
How do you know when you’re ready to launch? That’s what I asked Gmail creator Paul Buchheit two months before our launch date. At the time, Paul was pretty skeptical, but he inspired us with an idea he later repeated:

“…find 100 happy users and then go for it.”
–Paul Buchheit, at Y Combinator’s Startup School 2008.

So we added the Are You Happy? box to the sidebar, and listened closely to customers via our support team.

The result? Let’s just say that since we launched on May 5, we’ve built a very popular product that we think users truly love.

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