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Lean Analytics For Startups
 

Lean Analytics For Startups

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What do web startups need to watch? This deck looks at "lean analytics" for startups, showing what metrics you need to track for a web-based business and what details investors should demand from ...

What do web startups need to watch? This deck looks at "lean analytics" for startups, showing what metrics you need to track for a web-based business and what details investors should demand from companies they're considering.

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  • In july, we released a book with O&#x2019;Reilly called complete monitoring. <br /> It&#x2019;s different than other ORLY books in that it&#x2019;s not concentrated on a programming language <br /> but business outcomes instead.
  • Pirate Metrics, Four Steps to the Epiphany, and the Lean Startup
  • Imagine for a minute that you&#x2019;re the mayor of a sleepy little beach town. You track all kinds of things about the city (because you&#x2019;re an analyst.) You track tourism. And drowning rates. And hotel room vacancies. And ice cream consumption. And grains of sand. And all kinds of things.
  • You track tourism. And drowning rates. And hotel room vacancies. And ice cream consumption. And grains of sand. And all kinds of things.
  • You track tourism. And drowning rates. And hotel room vacancies. And ice cream consumption. And grains of sand. And all kinds of things.
  • You have a problem with drowning, and you&#x2019;ve ruled out the usual causes.
  • One day, someone is crunching ice cream numbers
  • They notice there&#x2019;s a correlation between ice cream and drowning.
  • They notice there&#x2019;s a correlation between ice cream and drowning.
  • They notice there&#x2019;s a correlation between ice cream and drowning.
  • This is useful: Knowing icecream consumption trends, you can predict demand for funeral homes
  • Or tell local merchants how much ice cream to stock based on drowning rates. You have CORRELATION, which can be used to make predictions.
  • But what&#x2019;s really going on? It turns out that both icecream and drowning are correlated to something else -- something causal: summertime.
  • One day, someone points out that there&#x2019;s a correlation between ice cream and drowning.
  • One day, someone points out that there&#x2019;s a correlation between ice cream and drowning.
  • One day, someone points out that there&#x2019;s a correlation between ice cream and drowning.
  • One day, someone points out that there&#x2019;s a correlation between ice cream and drowning.
  • Knowing this, you can minimize deaths (through CPR)
  • or lifeguards
  • And maximize ice cream sales (perhaps by locating them near lifeguard stands just to be sure.)
  • Every business has a goal hidden inside it.
  • Amazon: what do they want you to do?
  • Maximize your shopping cart size
  • They&#x2019;re a transactional site. They make money when people complete a process, usually involving a purchase or subscription.
  • But Amazon also wants you to leave reviews
  • And add something to a wishlist
  • These are forms of collaboration, where communities create content.
  • What about another kind of site. What does gmail want you to do?
  • GMail is first and foremost a SaaS site. It wants you to be productive, so you can get work done and keep using the system. A paid SaaS site is the same thing.
  • Of course, GMail is also another kind of site -- a media site. That&#x2019;s an ad up there.
  • Media sites want you to click on targeted advertising.
  • Analytics is about measuring.
  • Here&#x2019;s the simplest possible analytics model.
  • Here&#x2019;s the simplest possible analytics model.
  • Here&#x2019;s the simplest possible analytics model.
  • Here&#x2019;s the simplest possible analytics model.
  • Here&#x2019;s the simplest possible analytics model.
  • Here&#x2019;s the simplest possible analytics model.
  • Here&#x2019;s the simplest possible analytics model.
  • Here&#x2019;s the simplest possible analytics model.
  • Here&#x2019;s the simplest possible analytics model.
  • Here&#x2019;s the simplest possible analytics model.
  • Here&#x2019;s the simplest possible analytics model.
  • This is a &#x201C;funnel&#x201D; -- the usual way to visualize the conversion of web visitors to folks who do what you want them to.
  • For example, the number of people who come to a site, but then leave right away, is called the Bounce Rate.
  • For example, the number of people who come to a site, but then leave right away, is called the Bounce Rate.
  • For example, the number of people who come to a site, but then leave right away, is called the Bounce Rate.
  • For example, the number of people who come to a site, but then leave right away, is called the Bounce Rate.
  • For example, the number of people who come to a site, but then leave right away, is called the Bounce Rate.
  • For example, the number of people who come to a site, but then leave right away, is called the Bounce Rate.
  • For example, the number of people who come to a site, but then leave right away, is called the Bounce Rate.
  • For example, the number of people who come to a site, but then leave right away, is called the Bounce Rate.
  • For example, the number of people who come to a site, but then leave right away, is called the Bounce Rate.
  • For example, the number of people who come to a site, but then leave right away, is called the Bounce Rate.
  • For example, the number of people who come to a site, but then leave right away, is called the Bounce Rate.
  • In addition to bounce rate,
  • There are KPIs for shopping cart abandonment
  • Or traffic volumes
  • Or content creation rate
  • It&#x2019;s one thing to know what people did on your site. But often you want to know how they did it -- did they click on the red button or the blue text? Did they scroll all the way down?
  • Designers call things like buttons and doorknobs &#x201C;affordances.&#x201D; They worry about things like whether the user perceived the affordance, and whether it was in fact intended as one.
  • Designers call things like buttons and doorknobs &#x201C;affordances.&#x201D; They worry about things like whether the user perceived the affordance, and whether it was in fact intended as one.
  • Designers call things like buttons and doorknobs &#x201C;affordances.&#x201D; They worry about things like whether the user perceived the affordance, and whether it was in fact intended as one.
  • Designers call things like buttons and doorknobs &#x201C;affordances.&#x201D; They worry about things like whether the user perceived the affordance, and whether it was in fact intended as one.
  • for example, the &#x201C;Xiti Pro&#x201D; and &#x201C;Xiti Free&#x201D; links aren&#x2019;t actually URLs. They&#x2019;re text that people mistake for hyperlinks.
  • You can drill down to the individual form components
  • Companies like Expedia, Travelocity, and Priceline had problems with abandonment. <br /> Visitors would search for a hotel, find one they liked, check rates and availability&#x2014;and then leave. <br /> The sites tried offering discounts, changing layouts, modifying the text, and more. Nothing.
  • &#x201C;Why did you come to the site?&#x201D; <br /> Visitors weren&#x2019;t planning on booking a room, only checking availability. <br /> The reason they thought visitors were coming to their site was wrong. <br /> The site&#x2019;s operators had a different set of goals in mind than visitors did, and the symptom of this disconnect was the late abandonment.
  • With this new-found understanding of visitor motivations, travel sites took two important steps. <br /> First, they changed the pages of their sites, offering to watch a particular search for thecustomer and tell them when a deal came along, as shown in Figure 7-1. <br /> <br /> Second, they moved the purchasing or bidding to the front of the process, forcing the buyer to commit to payment or to name their price before they found out which hotel they&#x2019;d booked. This prevented window-shopping for a brand while allowing them to charge discounted rates. <br /> The results were tremendous, and changed how online hotel bookings happen. Today, most travel sites let users watch specific bookings, and many offer deeper discounts than the hotel chains themselves if customers are willing to commit to a purchase before they find out the brand of the hotel.
  • PMOG and Webwars. <br /> <br /> In these games, players install browser plug-ins that let them view websites in different ways than those intended by the site operator. <br /> <br /> In PMOG, a user can plant traps on your website that other players might trigger, or leave caches of game inventory for teammates to collect.
  • Other &#x201C;overlays&#x201D; to the web let people comment on a site using plug-ins like firef.ly&#x2014;shown in Figure 7-3&#x2014;or use site content for address books and phone directories as Skype does.
  • Sites still fail in lots of ways. It&#x2019;s scary how much things break. This is just a sample of pages for Canadians...
  • Sites still fail in lots of ways. It&#x2019;s scary how much things break. This is just a sample of pages for Canadians...
  • Sites still fail in lots of ways. It&#x2019;s scary how much things break. This is just a sample of pages for Canadians...
  • Sites still fail in lots of ways. It&#x2019;s scary how much things break. This is just a sample of pages for Canadians...
  • Sites still fail in lots of ways. It&#x2019;s scary how much things break. This is just a sample of pages for Canadians...
  • Sites still fail in lots of ways. It&#x2019;s scary how much things break. This is just a sample of pages for Canadians...
  • Sites still fail in lots of ways. It&#x2019;s scary how much things break. This is just a sample of pages for Canadians...
  • Sites still fail in lots of ways. It&#x2019;s scary how much things break. This is just a sample of pages for Canadians...
  • Sites still fail in lots of ways. It&#x2019;s scary how much things break. This is just a sample of pages for Canadians...
  • Sites still fail in lots of ways. It&#x2019;s scary how much things break. This is just a sample of pages for Canadians...
  • All of this analytics is good. But it&#x2019;s only half of the job of web monitoring. Because try as you might, websites have a problem.
  • for example . . . imagine that you decided to launch a kick ass survey. you&#x2019;ve bought the latest shiny tool <br /> you&#x2019;ve carefully crafted the questions <br /> you hired outside help to make sure they&#x2019;re worded properly <br /> you had them sent to a professional copy editor to get the final tone just right <br /> it went through legal <br /> you segmented your campaign according to the demographic whose voice you need to understand the most <br /> <br /> and as you sit precariously over the big red send button you can&#x2019;t help but feel that you&#x2019;ve covered all your bases. <br /> Satisfied, you press the button and out it goes into the world.
  • that was the case with paypal, recently. <br /> We don&#x2019;t have insight into their numbers, so we can&#x2019;t tell for sure what the particular conversion rate for this survey was, but we suspect that the pickup wasn&#x2019;t as good as anticipated. <br /> <br /> Their web analytics and VOC don&#x2019;t have the necessary functions built in to determine that their SSL cert was mismatched, cause safari and other browsers to come up with a nasty message saying &#x201C;we can&#x2019;t verify the identity of paypal-surveys.com&#x201D;. <br /> After all, think about it; if it&#x2019;s coming from paypal and the identity can&#x2019;t be verified, would you go on the site and fill anything out?
  • we know of a case of a marketing officer who&#x2019;se job was put in question because of a string of failed campaigns.The company jumped the gun on this one. Thanks to a friend in the web operations department, he was able to show that the network was at fault. Even though the company load tested diligently, they only did from their internal network. It turns out the problems were related to the last mile - something that was hidden until the company implemented synthetic monitoring. <br /> <br /> Even though overall sentiment was a little more negative than usual during the campaigns, the conversion rates skyrocketed once better transit was installed.
  • This is a scary one and a true. If you haven&#x2019;t heard, sitemeter took down every single website that were a client of theirs. If you were on IE and wanted to access sites like TechCrunch, Gizmodo and so on, you were out of luck in August, because the code crashed the browser. <br /> <br /> Think about it - your site isn&#x2019;t just vulnerable to whatever goofy code your development team throws at the Internet, it&#x2019;s also vulnerable to your very own web analytics tracking codes! <br /> <br /> This would take hours of troubleshooting to reveal without synthetic monitoring - or one simply alert would be triggered with the proper tools in place. <br /> <br /> I don&#x2019;t mean to pick on SiteMeter btw, I&#x2019;m sure they have a great service - but these types of errors can kill substantial amounts of revenue until you catch it.
  • Once upon a time, performance was a dark art. We struggled to deliver &#x201C;good enough&#x201D; without really knowing why.
  • We managed by anecdote. We were sure faster was better, but we couldn&#x2019;t tie it to specific business outcomes.
  • The notion that speed is good for users isn&#x2019;t new. The concept of &#x201C;Flow&#x201D; &#x2013; a state of heightened engagement that we experience when we&#x2019;re truly focused on something &#x2013; was first proposed by mihaly csikszentmihalyi
  • There&#x2019;s a study from IBM in 1981 that shows strong evidence of the relationship between performance and productivity. As systems get faster, users get EXPONENTIALLY more productive.
  • It turns out that attention and engagement drop off predictably. At ten milliseconds, we actually believe something is physically accessible &#x2013; think clicking a button and seeing it change color. At 100 milliseconds, we can have a conversation with someone without noticing the delay (remember old transatlantic calls?) At a second, we&#x2019;re still engaged, but aware of the delay. At ten seconds, we get bored and tune out, because other things come into our minds.
  • It turns out that attention and engagement drop off predictably. At ten milliseconds, we actually believe something is physically accessible &#x2013; think clicking a button and seeing it change color. At 100 milliseconds, we can have a conversation with someone without noticing the delay (remember old transatlantic calls?) At a second, we&#x2019;re still engaged, but aware of the delay. At ten seconds, we get bored and tune out, because other things come into our minds.
  • It turns out that attention and engagement drop off predictably. At ten milliseconds, we actually believe something is physically accessible &#x2013; think clicking a button and seeing it change color. At 100 milliseconds, we can have a conversation with someone without noticing the delay (remember old transatlantic calls?) At a second, we&#x2019;re still engaged, but aware of the delay. At ten seconds, we get bored and tune out, because other things come into our minds.
  • It turns out that attention and engagement drop off predictably. At ten milliseconds, we actually believe something is physically accessible &#x2013; think clicking a button and seeing it change color. At 100 milliseconds, we can have a conversation with someone without noticing the delay (remember old transatlantic calls?) At a second, we&#x2019;re still engaged, but aware of the delay. At ten seconds, we get bored and tune out, because other things come into our minds.
  • It turns out that attention and engagement drop off predictably. At ten milliseconds, we actually believe something is physically accessible &#x2013; think clicking a button and seeing it change color. At 100 milliseconds, we can have a conversation with someone without noticing the delay (remember old transatlantic calls?) At a second, we&#x2019;re still engaged, but aware of the delay. At ten seconds, we get bored and tune out, because other things come into our minds.
  • How much was fast enough? It was anybody&#x2019;s guess.
  • And guess they did. <br /> This is Zona&#x2019;s formula for patience, the basis for the &#x201C;eight second rule.&#x201D; Unfortunately, things like tenacity, importance, and natural patience aren&#x2019;t concrete enough for the no-nonsense folks that run web applications.
  • And guess they did. <br /> This is Zona&#x2019;s formula for patience, the basis for the &#x201C;eight second rule.&#x201D; Unfortunately, things like tenacity, importance, and natural patience aren&#x2019;t concrete enough for the no-nonsense folks that run web applications.
  • IT operators and marketers are completely different people. What convinces an IT person to fix performance doesn&#x2019;t convince a marketer. They want to know how it will impact the business fundamentals.
  • By now, we know that everything matters. Usability, page latency, visitor mindset, and even sentiment on social media platforms all contribute to the business results you get from a site.
  • Fortunately, we&#x2019;re getting better at linking performance to business outcomes.
  • One example of this is performance experimentation that Google&#x2019;s done. Google&#x2019;s a perfect lab. Not only do they have a lot of traffic, they also have computing resources to do back-end analysis of large data sets. Plus, they&#x2019;re not afraid of experimentation &#x2013; in fact, they insist on it. So they tried different levels of performance and watched what happened to visitors.
  • The results, which they presented at Velocity in May, were fascinating. There was a direct impact between delay and the number of searches a user did each day &#x2013; and to make matters worse, the numbers often didn&#x2019;t improve even when the delay was removed. You may think 0.7% drop isn&#x2019;t significant, but for Google this represents a tremendous amount of revenue.
  • Microsoft&#x2019;s Bing site is a good lab, too. They looked at key metrics, or KPIs, of their search site.
  • They showed that as performance got worse, all key metrics did, too. Not just the number of searches, but also the revenue (earned when someone clicks) and refinement of searches.
  • Shopzilla overhauled their entire site, dramatically reducing page load time, hardware requirements, and downtime.
  • They saw a significant increase in revenues
  • The site improvement increased the number of Google clicks that turned into actual visits
  • It also affected search engine scores. By improving load time, search engines (in this case Google UK) &#x201C;learned&#x201D; that this was a good destination. That&#x2019;s right &#x2013; Google actually penalizes sites that are slow by giving them a lower page ranking.
  • By tying performance and availability to Key Performance Indicators &#x2013; KPIs &#x2013; business and operations can finally have a conversation. <br /> But KPIs are different for different sites.
  • Strangeloop agreed to set up an experiment using their technology which would help measure this.
  • First, traffic. Despite splitting visitors to be optimized and unoptimized evenly, we had many more optimized sessions captured by the analytics. This may be a result of slower-loading pages failing to execute the analytics script, or abandoning the visit before the page had time to load.
  • Unoptimized visitors are roughly 1% more likely to leave the site immediately, without proceeding to other pages.
  • The unoptimized visits consisted of more new visitors than the optimized ones did. While this might seem counter-intuitive, remember that these are visits:
  • This likely means that optimized visitors came back more often.
  • Optimized visitors spent more time on the site
  • And looked at more pages during their visit &#x2013; if you&#x2019;re a media property, this means more impressions for your advertisers.
  • On a second e-commerce site running roughly the same experiment, conversions were 16 percent higher and orders were 5.5% higher.
  • Here comes Monsanto, and Big Agriculture
  • Or volume of comments
  • It&#x2019;s easy to craft a message. Getting genuine attention is the hard part. <br /> <br /> **GLOSS OVER** <br /> <br /> Online marketing made advertising accountable thanks to web analytics. <br /> <br /> Viral marketing approaches makes it easy to spread messages that have high returns. <br /> <br /> Community marketing now makes it possible for others to genuinely be interested in a product by not feeling like they&#x2019;re getting messages from a company with ulterior motives to sell.
  • Online advertising -- paid, affiliate, or SEO -- gives marketers better control. But you still have to pay for it; message strength grows with the money you spent on ads. <br /> <br /> Marketers retained control over the message, but less so over where it was shown and to whom.
  • Nothing was better at this than Hotmail, which gained millions of users in a short amount of time with a simple embedded message.
  • Hotmail&#x2019;s growth closely mirrored this. It had all the things needed to go viral: <br /> - A good story <br /> - Support from community leaders <br /> - A large end audience <br /> - A platform for distribution
  • Communities help facilitate a new kind of PR, but one in which you lose control of both the means and the audience in return for a genuine message and cheap distribution. Not all messages can survive this transparency, and all members of the organization are involved in the interaction.
  • Support communities can show the earliest form of ROI for many companies. They allow the customer to support themselves. Customers like it, and it costs less. Some companies have gone to great lengths to replace their traditional support sites with community platforms. <br /> <br /> Online communities offer specialized, rated, organized feedback mechanisms than generic communities such as a mailing list or Usenet can&#x2019;t provide.
  • Turns out that there are very good reasons to implement support communities. <br /> <br /> The cost of any other support is extremely high.
  • Turns out that there are very good reasons to implement support communities. <br /> <br /> The cost of any other support is extremely high.
  • Turns out that there are very good reasons to implement support communities. <br /> <br /> The cost of any other support is extremely high.
  • Turns out that there are very good reasons to implement support communities. <br /> <br /> The cost of any other support is extremely high.
  • Turns out that there are very good reasons to implement support communities. <br /> <br /> The cost of any other support is extremely high.
  • Even if you don&#x2019;t want to build one yourself, sites like Getsatisfaction can allow you to build quick self-service portals that can actually be seeded and moderated by non-employees.
  • Testing on visitors: you can crowdsource your product development, resulting in faster and more accurate iterations. In this case, backtype created a &#x2018;Trends&#x2019; tab without actually launching the feature, opting instead to let users share ideas about the feature before rolling it out (or perhaps even building it).
  • Another good reason to monitor communities is because what happens on them may put you at risk. Whether that&#x2019;s someone slandering you, stealing or leaking your content, or even using you as a platform for malicious attacks -- such as those linked to from President Obama&#x2019;s campaign sites. <br /> Libelous or slanderous content <br /> Intellectual property theft <br /> Your own liability
  • Referrals are another big reasons for joining or building a community. <br /> Whether your company is looking for new customers or for new employees, websites are quickly becoming the most efficient tool for establishing those relationships.
  • And there are many compelling reasons to have a presence on online communities. Consumers themselves have high expectations of traditional brands, often expecting them to be online for no other reason than &#x201C;having a presence&#x201D;.
  • Charlene Li of the Altimeter Group published this pyramid of engagement, showing several kinds of online participant. Some lurk; some go so far as to moderate and manage community.
  • Charlene Li of the Altimeter Group published this pyramid of engagement, showing several kinds of online participant. Some lurk; some go so far as to moderate and manage community.
  • Charlene Li of the Altimeter Group published this pyramid of engagement, showing several kinds of online participant. Some lurk; some go so far as to moderate and manage community.
  • Charlene Li of the Altimeter Group published this pyramid of engagement, showing several kinds of online participant. Some lurk; some go so far as to moderate and manage community.
  • Charlene Li of the Altimeter Group published this pyramid of engagement, showing several kinds of online participant. Some lurk; some go so far as to moderate and manage community.
  • Charlene Li of the Altimeter Group published this pyramid of engagement, showing several kinds of online participant. Some lurk; some go so far as to moderate and manage community.
  • Charlene Li of the Altimeter Group published this pyramid of engagement, showing several kinds of online participant. Some lurk; some go so far as to moderate and manage community.
  • Charlene Li of the Altimeter Group published this pyramid of engagement, showing several kinds of online participant. Some lurk; some go so far as to moderate and manage community.
  • Charlene Li of the Altimeter Group published this pyramid of engagement, showing several kinds of online participant. Some lurk; some go so far as to moderate and manage community.
  • Charlene Li of the Altimeter Group published this pyramid of engagement, showing several kinds of online participant. Some lurk; some go so far as to moderate and manage community.
  • The reality is that every kind of interaction is unique. Some are private, one-to-one; others are open to everyone. Some are brief snippets; others, detailed prose.
  • There are other things that happen before the visitors come to the site, we see that there are many other factors that form what we call a &#x201C;long funnel.&#x201D; They&#x2019;re all part of a campaign. <br /> For example... (clicks) <br /> What should we track for communities? That&#x2019;s communilytics.
  • There are other things that happen before the visitors come to the site, we see that there are many other factors that form what we call a &#x201C;long funnel.&#x201D; They&#x2019;re all part of a campaign. <br /> For example... (clicks) <br /> What should we track for communities? That&#x2019;s communilytics.
  • There are other things that happen before the visitors come to the site, we see that there are many other factors that form what we call a &#x201C;long funnel.&#x201D; They&#x2019;re all part of a campaign. <br /> For example... (clicks) <br /> What should we track for communities? That&#x2019;s communilytics.
  • There are other things that happen before the visitors come to the site, we see that there are many other factors that form what we call a &#x201C;long funnel.&#x201D; They&#x2019;re all part of a campaign. <br /> For example... (clicks) <br /> What should we track for communities? That&#x2019;s communilytics.
  • There are other things that happen before the visitors come to the site, we see that there are many other factors that form what we call a &#x201C;long funnel.&#x201D; They&#x2019;re all part of a campaign. <br /> For example... (clicks) <br /> What should we track for communities? That&#x2019;s communilytics.
  • ALISTAIR START <br /> Consider two key attributes of your community&#x2019;s members: Followers and reach. Followers is &#x201C;naive&#x201D; popularity; Reach is their ability to deliver the goods.
  • But it&#x2019;s not this simple. In addition to followers, we have to consider reach. In a Twitter model, for example, each community member may amplify things. I&#x2019;m much more likely to amplify certain people than others.
  • But it&#x2019;s not this simple. In addition to followers, we have to consider reach. In a Twitter model, for example, each community member may amplify things. I&#x2019;m much more likely to amplify certain people than others.
  • But it&#x2019;s not this simple. In addition to followers, we have to consider reach. In a Twitter model, for example, each community member may amplify things. I&#x2019;m much more likely to amplify certain people than others.
  • But it&#x2019;s not this simple. In addition to followers, we have to consider reach. In a Twitter model, for example, each community member may amplify things. I&#x2019;m much more likely to amplify certain people than others.
  • But it&#x2019;s not this simple. In addition to followers, we have to consider reach. In a Twitter model, for example, each community member may amplify things. I&#x2019;m much more likely to amplify certain people than others.
  • But it&#x2019;s not this simple. In addition to followers, we have to consider reach. In a Twitter model, for example, each community member may amplify things. I&#x2019;m much more likely to amplify certain people than others.
  • But it&#x2019;s not this simple. In addition to followers, we have to consider reach. In a Twitter model, for example, each community member may amplify things. I&#x2019;m much more likely to amplify certain people than others.
  • But it&#x2019;s not this simple. In addition to followers, we have to consider reach. In a Twitter model, for example, each community member may amplify things. I&#x2019;m much more likely to amplify certain people than others.
  • But it&#x2019;s not this simple. In addition to followers, we have to consider reach. In a Twitter model, for example, each community member may amplify things. I&#x2019;m much more likely to amplify certain people than others.
  • But it&#x2019;s not this simple. In addition to followers, we have to consider reach. In a Twitter model, for example, each community member may amplify things. I&#x2019;m much more likely to amplify certain people than others.
  • But it&#x2019;s not this simple. In addition to followers, we have to consider reach. In a Twitter model, for example, each community member may amplify things. I&#x2019;m much more likely to amplify certain people than others.
  • But it&#x2019;s not this simple. In addition to followers, we have to consider reach. In a Twitter model, for example, each community member may amplify things. I&#x2019;m much more likely to amplify certain people than others.
  • But it&#x2019;s not this simple. In addition to followers, we have to consider reach. In a Twitter model, for example, each community member may amplify things. I&#x2019;m much more likely to amplify certain people than others.
  • But it&#x2019;s not this simple. In addition to followers, we have to consider reach. In a Twitter model, for example, each community member may amplify things. I&#x2019;m much more likely to amplify certain people than others.
  • But it&#x2019;s not this simple. In addition to followers, we have to consider reach. In a Twitter model, for example, each community member may amplify things. I&#x2019;m much more likely to amplify certain people than others.
  • But it&#x2019;s not this simple. In addition to followers, we have to consider reach. In a Twitter model, for example, each community member may amplify things. I&#x2019;m much more likely to amplify certain people than others.
  • But it&#x2019;s not this simple. In addition to followers, we have to consider reach. In a Twitter model, for example, each community member may amplify things. I&#x2019;m much more likely to amplify certain people than others.
  • But it&#x2019;s not this simple. In addition to followers, we have to consider reach. In a Twitter model, for example, each community member may amplify things. I&#x2019;m much more likely to amplify certain people than others.
  • (If you think this isn&#x2019;t the case, then ask: Why is Twitter formalizing Retweets? Simple -- this is how you calculate Pagerank for people, which you can then monetize. And why )
  • Let&#x2019;s talk for a minute about what a community might do.
  • It might spread a message to others
  • If that message is popular and interesting, it will amplify itself
  • It might accomplish a goal you want it to achieve
  • It might accomplish a goal you want it to achieve
  • It might accomplish a goal you want it to achieve
  • It might accomplish a goal you want it to achieve
  • It might accomplish a goal you want it to achieve
  • It might accomplish a goal you want it to achieve
  • The goal might even be to help other people become community members (enrolling, subscribing, and so on)
  • The goal might even be to help other people become community members (enrolling, subscribing, and so on)
  • The goal might even be to help other people become community members (enrolling, subscribing, and so on)
  • The goal might even be to help other people become community members (enrolling, subscribing, and so on)
  • Well, each of those users has a chance of turning their impression into a goal conversion.
  • Putting all of this together, we can start to imagine a communilytics funnel that reaches far beyond traditional web funnels, and incorporates measures of spread, amplification, and reach.
  • Putting all of this together, we can start to imagine a communilytics funnel that reaches far beyond traditional web funnels, and incorporates measures of spread, amplification, and reach.
  • Putting all of this together, we can start to imagine a communilytics funnel that reaches far beyond traditional web funnels, and incorporates measures of spread, amplification, and reach.
  • Putting all of this together, we can start to imagine a communilytics funnel that reaches far beyond traditional web funnels, and incorporates measures of spread, amplification, and reach.
  • While you&#x2019;re watching communities to see what they say about you, you may as well see what they&#x2019;re saying about your competitors.
  • For example, a community you want to spread a message to virally means you have to focus on making it easy to amplify the message.
  • By contrast, a campaign like a fundraiser might involve a small, influential set of seeders who have considerable reach.
  • If you want a community to do something (like signing a petition) you care about the ratio of impressions to clicks a lot.
  • We built a simple website encouraging people to &#x201C;buy their country a beer&#x201D; on Canada Day
  • We launched the event by mentioning it, knowing others were ready to amplify and seed the message. But we (I) made a mistake -- anyone see it?
  • Over time, the message spread. We used tools like Streamgraph to understand what was being said, and join in with the conversation according to the sentiment.
  • We reached prominent online personalities -- though it was only around 20, they had hundreds of thousands of followers, giving us a 1:35,000 seed ratio. <br /> A few people mentioned it on other platforms or their blogs, but not many, so repurposing of the initial message wasn&#x2019;t high. <br /> The message was retweeted a modest amount, and those people&#x2019;s follower counts were small, meaning it only amplified by 2.9%. Remember, it needs to be >100% to be &#x201C;viral&#x201D;! <br /> We only saw 1,642 total visits, but that translated to about $1,000 in donations. Conversion rates were less than 0.2%, which we attribute in part to the passive message we used at first. In other words, the tone of the campaign emphasized attention (&#x201D;visit this page&#x201D;) over conversion (&#x201D;please donate&#x201D;).
  • We reached prominent online personalities -- though it was only around 20, they had hundreds of thousands of followers, giving us a 1:35,000 seed ratio. <br /> A few people mentioned it on other platforms or their blogs, but not many, so repurposing of the initial message wasn&#x2019;t high. <br /> The message was retweeted a modest amount, and those people&#x2019;s follower counts were small, meaning it only amplified by 2.9%. Remember, it needs to be >100% to be &#x201C;viral&#x201D;! <br /> We only saw 1,642 total visits, but that translated to about $1,000 in donations. Conversion rates were less than 0.2%, which we attribute in part to the passive message we used at first. In other words, the tone of the campaign emphasized attention (&#x201D;visit this page&#x201D;) over conversion (&#x201D;please donate&#x201D;).
  • We reached prominent online personalities -- though it was only around 20, they had hundreds of thousands of followers, giving us a 1:35,000 seed ratio. <br /> A few people mentioned it on other platforms or their blogs, but not many, so repurposing of the initial message wasn&#x2019;t high. <br /> The message was retweeted a modest amount, and those people&#x2019;s follower counts were small, meaning it only amplified by 2.9%. Remember, it needs to be >100% to be &#x201C;viral&#x201D;! <br /> We only saw 1,642 total visits, but that translated to about $1,000 in donations. Conversion rates were less than 0.2%, which we attribute in part to the passive message we used at first. In other words, the tone of the campaign emphasized attention (&#x201D;visit this page&#x201D;) over conversion (&#x201D;please donate&#x201D;).
  • We reached prominent online personalities -- though it was only around 20, they had hundreds of thousands of followers, giving us a 1:35,000 seed ratio. <br /> A few people mentioned it on other platforms or their blogs, but not many, so repurposing of the initial message wasn&#x2019;t high. <br /> The message was retweeted a modest amount, and those people&#x2019;s follower counts were small, meaning it only amplified by 2.9%. Remember, it needs to be >100% to be &#x201C;viral&#x201D;! <br /> We only saw 1,642 total visits, but that translated to about $1,000 in donations. Conversion rates were less than 0.2%, which we attribute in part to the passive message we used at first. In other words, the tone of the campaign emphasized attention (&#x201D;visit this page&#x201D;) over conversion (&#x201D;please donate&#x201D;).
  • We reached prominent online personalities -- though it was only around 20, they had hundreds of thousands of followers, giving us a 1:35,000 seed ratio. <br /> A few people mentioned it on other platforms or their blogs, but not many, so repurposing of the initial message wasn&#x2019;t high. <br /> The message was retweeted a modest amount, and those people&#x2019;s follower counts were small, meaning it only amplified by 2.9%. Remember, it needs to be >100% to be &#x201C;viral&#x201D;! <br /> We only saw 1,642 total visits, but that translated to about $1,000 in donations. Conversion rates were less than 0.2%, which we attribute in part to the passive message we used at first. In other words, the tone of the campaign emphasized attention (&#x201D;visit this page&#x201D;) over conversion (&#x201D;please donate&#x201D;).
  • We reached prominent online personalities -- though it was only around 20, they had hundreds of thousands of followers, giving us a 1:35,000 seed ratio. <br /> A few people mentioned it on other platforms or their blogs, but not many, so repurposing of the initial message wasn&#x2019;t high. <br /> The message was retweeted a modest amount, and those people&#x2019;s follower counts were small, meaning it only amplified by 2.9%. Remember, it needs to be >100% to be &#x201C;viral&#x201D;! <br /> We only saw 1,642 total visits, but that translated to about $1,000 in donations. Conversion rates were less than 0.2%, which we attribute in part to the passive message we used at first. In other words, the tone of the campaign emphasized attention (&#x201D;visit this page&#x201D;) over conversion (&#x201D;please donate&#x201D;).
  • We reached prominent online personalities -- though it was only around 20, they had hundreds of thousands of followers, giving us a 1:35,000 seed ratio. <br /> A few people mentioned it on other platforms or their blogs, but not many, so repurposing of the initial message wasn&#x2019;t high. <br /> The message was retweeted a modest amount, and those people&#x2019;s follower counts were small, meaning it only amplified by 2.9%. Remember, it needs to be >100% to be &#x201C;viral&#x201D;! <br /> We only saw 1,642 total visits, but that translated to about $1,000 in donations. Conversion rates were less than 0.2%, which we attribute in part to the passive message we used at first. In other words, the tone of the campaign emphasized attention (&#x201D;visit this page&#x201D;) over conversion (&#x201D;please donate&#x201D;).
  • We reached prominent online personalities -- though it was only around 20, they had hundreds of thousands of followers, giving us a 1:35,000 seed ratio. <br /> A few people mentioned it on other platforms or their blogs, but not many, so repurposing of the initial message wasn&#x2019;t high. <br /> The message was retweeted a modest amount, and those people&#x2019;s follower counts were small, meaning it only amplified by 2.9%. Remember, it needs to be >100% to be &#x201C;viral&#x201D;! <br /> We only saw 1,642 total visits, but that translated to about $1,000 in donations. Conversion rates were less than 0.2%, which we attribute in part to the passive message we used at first. In other words, the tone of the campaign emphasized attention (&#x201D;visit this page&#x201D;) over conversion (&#x201D;please donate&#x201D;).
  • We reached prominent online personalities -- though it was only around 20, they had hundreds of thousands of followers, giving us a 1:35,000 seed ratio. <br /> A few people mentioned it on other platforms or their blogs, but not many, so repurposing of the initial message wasn&#x2019;t high. <br /> The message was retweeted a modest amount, and those people&#x2019;s follower counts were small, meaning it only amplified by 2.9%. Remember, it needs to be >100% to be &#x201C;viral&#x201D;! <br /> We only saw 1,642 total visits, but that translated to about $1,000 in donations. Conversion rates were less than 0.2%, which we attribute in part to the passive message we used at first. In other words, the tone of the campaign emphasized attention (&#x201D;visit this page&#x201D;) over conversion (&#x201D;please donate&#x201D;).
  • We reached prominent online personalities -- though it was only around 20, they had hundreds of thousands of followers, giving us a 1:35,000 seed ratio. <br /> A few people mentioned it on other platforms or their blogs, but not many, so repurposing of the initial message wasn&#x2019;t high. <br /> The message was retweeted a modest amount, and those people&#x2019;s follower counts were small, meaning it only amplified by 2.9%. Remember, it needs to be >100% to be &#x201C;viral&#x201D;! <br /> We only saw 1,642 total visits, but that translated to about $1,000 in donations. Conversion rates were less than 0.2%, which we attribute in part to the passive message we used at first. In other words, the tone of the campaign emphasized attention (&#x201D;visit this page&#x201D;) over conversion (&#x201D;please donate&#x201D;).
  • We reached prominent online personalities -- though it was only around 20, they had hundreds of thousands of followers, giving us a 1:35,000 seed ratio. <br /> A few people mentioned it on other platforms or their blogs, but not many, so repurposing of the initial message wasn&#x2019;t high. <br /> The message was retweeted a modest amount, and those people&#x2019;s follower counts were small, meaning it only amplified by 2.9%. Remember, it needs to be >100% to be &#x201C;viral&#x201D;! <br /> We only saw 1,642 total visits, but that translated to about $1,000 in donations. Conversion rates were less than 0.2%, which we attribute in part to the passive message we used at first. In other words, the tone of the campaign emphasized attention (&#x201D;visit this page&#x201D;) over conversion (&#x201D;please donate&#x201D;).
  • We reached prominent online personalities -- though it was only around 20, they had hundreds of thousands of followers, giving us a 1:35,000 seed ratio. <br /> A few people mentioned it on other platforms or their blogs, but not many, so repurposing of the initial message wasn&#x2019;t high. <br /> The message was retweeted a modest amount, and those people&#x2019;s follower counts were small, meaning it only amplified by 2.9%. Remember, it needs to be >100% to be &#x201C;viral&#x201D;! <br /> We only saw 1,642 total visits, but that translated to about $1,000 in donations. Conversion rates were less than 0.2%, which we attribute in part to the passive message we used at first. In other words, the tone of the campaign emphasized attention (&#x201D;visit this page&#x201D;) over conversion (&#x201D;please donate&#x201D;).
  • We reached prominent online personalities -- though it was only around 20, they had hundreds of thousands of followers, giving us a 1:35,000 seed ratio. <br /> A few people mentioned it on other platforms or their blogs, but not many, so repurposing of the initial message wasn&#x2019;t high. <br /> The message was retweeted a modest amount, and those people&#x2019;s follower counts were small, meaning it only amplified by 2.9%. Remember, it needs to be >100% to be &#x201C;viral&#x201D;! <br /> We only saw 1,642 total visits, but that translated to about $1,000 in donations. Conversion rates were less than 0.2%, which we attribute in part to the passive message we used at first. In other words, the tone of the campaign emphasized attention (&#x201D;visit this page&#x201D;) over conversion (&#x201D;please donate&#x201D;).
  • We reached prominent online personalities -- though it was only around 20, they had hundreds of thousands of followers, giving us a 1:35,000 seed ratio. <br /> A few people mentioned it on other platforms or their blogs, but not many, so repurposing of the initial message wasn&#x2019;t high. <br /> The message was retweeted a modest amount, and those people&#x2019;s follower counts were small, meaning it only amplified by 2.9%. Remember, it needs to be >100% to be &#x201C;viral&#x201D;! <br /> We only saw 1,642 total visits, but that translated to about $1,000 in donations. Conversion rates were less than 0.2%, which we attribute in part to the passive message we used at first. In other words, the tone of the campaign emphasized attention (&#x201D;visit this page&#x201D;) over conversion (&#x201D;please donate&#x201D;).
  • We reached prominent online personalities -- though it was only around 20, they had hundreds of thousands of followers, giving us a 1:35,000 seed ratio. <br /> A few people mentioned it on other platforms or their blogs, but not many, so repurposing of the initial message wasn&#x2019;t high. <br /> The message was retweeted a modest amount, and those people&#x2019;s follower counts were small, meaning it only amplified by 2.9%. Remember, it needs to be >100% to be &#x201C;viral&#x201D;! <br /> We only saw 1,642 total visits, but that translated to about $1,000 in donations. Conversion rates were less than 0.2%, which we attribute in part to the passive message we used at first. In other words, the tone of the campaign emphasized attention (&#x201D;visit this page&#x201D;) over conversion (&#x201D;please donate&#x201D;).
  • We reached prominent online personalities -- though it was only around 20, they had hundreds of thousands of followers, giving us a 1:35,000 seed ratio. <br /> A few people mentioned it on other platforms or their blogs, but not many, so repurposing of the initial message wasn&#x2019;t high. <br /> The message was retweeted a modest amount, and those people&#x2019;s follower counts were small, meaning it only amplified by 2.9%. Remember, it needs to be >100% to be &#x201C;viral&#x201D;! <br /> We only saw 1,642 total visits, but that translated to about $1,000 in donations. Conversion rates were less than 0.2%, which we attribute in part to the passive message we used at first. In other words, the tone of the campaign emphasized attention (&#x201D;visit this page&#x201D;) over conversion (&#x201D;please donate&#x201D;).
  • We reached prominent online personalities -- though it was only around 20, they had hundreds of thousands of followers, giving us a 1:35,000 seed ratio. <br /> A few people mentioned it on other platforms or their blogs, but not many, so repurposing of the initial message wasn&#x2019;t high. <br /> The message was retweeted a modest amount, and those people&#x2019;s follower counts were small, meaning it only amplified by 2.9%. Remember, it needs to be >100% to be &#x201C;viral&#x201D;! <br /> We only saw 1,642 total visits, but that translated to about $1,000 in donations. Conversion rates were less than 0.2%, which we attribute in part to the passive message we used at first. In other words, the tone of the campaign emphasized attention (&#x201D;visit this page&#x201D;) over conversion (&#x201D;please donate&#x201D;).
  • Very spiky traffic profile reflects the short-lived campaign.
  • Most community management processes involve several stages, starting with the creation of something (a message, an offer, a destination.) Then, as you&#x2019;re engaging a community, or running a campaign, you&#x2019;re constantly adjusting, tweaking, amplifying, and mitigating what&#x2019;s happening. The message is out of your control, but you&#x2019;re shepherding it.
  • Most community management processes involve several stages, starting with the creation of something (a message, an offer, a destination.) Then, as you&#x2019;re engaging a community, or running a campaign, you&#x2019;re constantly adjusting, tweaking, amplifying, and mitigating what&#x2019;s happening. The message is out of your control, but you&#x2019;re shepherding it.
  • Most community management processes involve several stages, starting with the creation of something (a message, an offer, a destination.) Then, as you&#x2019;re engaging a community, or running a campaign, you&#x2019;re constantly adjusting, tweaking, amplifying, and mitigating what&#x2019;s happening. The message is out of your control, but you&#x2019;re shepherding it.
  • Most community management processes involve several stages, starting with the creation of something (a message, an offer, a destination.) Then, as you&#x2019;re engaging a community, or running a campaign, you&#x2019;re constantly adjusting, tweaking, amplifying, and mitigating what&#x2019;s happening. The message is out of your control, but you&#x2019;re shepherding it.
  • Most community management processes involve several stages, starting with the creation of something (a message, an offer, a destination.) Then, as you&#x2019;re engaging a community, or running a campaign, you&#x2019;re constantly adjusting, tweaking, amplifying, and mitigating what&#x2019;s happening. The message is out of your control, but you&#x2019;re shepherding it.
  • Most community management processes involve several stages, starting with the creation of something (a message, an offer, a destination.) Then, as you&#x2019;re engaging a community, or running a campaign, you&#x2019;re constantly adjusting, tweaking, amplifying, and mitigating what&#x2019;s happening. The message is out of your control, but you&#x2019;re shepherding it.
  • Most community management processes involve several stages, starting with the creation of something (a message, an offer, a destination.) Then, as you&#x2019;re engaging a community, or running a campaign, you&#x2019;re constantly adjusting, tweaking, amplifying, and mitigating what&#x2019;s happening. The message is out of your control, but you&#x2019;re shepherding it.
  • increase chance that messages will be amplified by the community <br /> Don&#x2019;t know which social platforms will dominate <br /> Last-minute announcement goes on Twitter; detailed list goes in a blog posting; question looking for responses goes to a mailing list <br /> Monitor broad range of sites in case conversations about you&#x2014;or your competitors&#x2014;emerge <br /> The accounting department may not use the same social networks as the executive team, who may work with different tools from the folks in support. Different audiences gravitate towards different platforms.
  • There are really 8 major types of communities today with four levels of engagements to each.
  • mailing lists, where users share mail with each other in a group setting
  • forums where users can talk with each other - but not in real time
  • irc communities, where users connect with each other in real time
  • social networks, where users can connect with each other and build their social graph
  • blogs where you state an opinion and can interact with your users through comment systems
  • wikis, where users share searchable information with each other
  • micromessaging platforms like twitter
  • and news aggregation sites where communities vote on popular content.
  • And there are four levels of engagement you can have with them. More engagement means more visibility, at the expense of anonymity.
  • And there are four levels of engagement you can have with them. More engagement means more visibility, at the expense of anonymity.
  • And there are four levels of engagement you can have with them. More engagement means more visibility, at the expense of anonymity.
  • And there are four levels of engagement you can have with them. More engagement means more visibility, at the expense of anonymity.
  • And there are four levels of engagement you can have with them. More engagement means more visibility, at the expense of anonymity.
  • by setting up google alerts
  • or by setting up page level alerts to tell you if a particular site has changed. This is especially useful if you want to be told of an update on a particular site that might not be indexed by google often and doesn&#x2019;t have an RSS feed for the area you want to follow.
  • you can also roll out your own search engine to find and be alerted on content on a particular group or type of site.
  • you can use forum crawlers like bigboards to forum mentions
  • and do the same on IRC using search engines like searchirc.
  • in walled gardens, you can get rudimentary aggregate keyword information through programs like Lexicon for Facebook.
  • twitter has a powerful search functionality
  • and you can compare your share of voice on different networks using tools like site volume.
  • And there are four levels of engagement you can have with them. More engagement means more visibility, at the expense of anonymity.
  • some mailing lists require you to join so that you can search them
  • and many forums won&#x2019;t allow you to read the content until you actually become a member as well.
  • walled gardens like facebook only gives you searchable information once you&#x2019;ve joined, and even then - will only give you information on your own social graph - not beyond it.
  • by joining certain blog comment communities, you can get more insight into the types of comments and blogs certain users visit.
  • And there are four levels of engagement you can have with them. More engagement means more visibility, at the expense of anonymity.
  • for example, moderating a mailing list might mean that you have the power to decide if a particular message can get published to the list or not.
  • and moderating a facebook group may mean that you can reach out to members, delete and invite them as well.
  • And there are four levels of engagement you can have with them. More engagement means more visibility, at the expense of anonymity.
  • you can run a social media platform
  • and take advantage of the built in stats that the platform offers you. This is the case for ones like Lithium, Jive, Teligent and so on.
  • you can run IRC servers which can give you a much broader set of metrics like channel names, user names and so on.
  • you can run your own blogs, which means that you&#x2019;re free to run any analytics service you want on it.
  • running a wiki means that you can track all sorts of information such as incipient links, number of posts per day and so on.
  • if you run your own micro-blogging platform, you&#x2019;re free to integrate it in whatever application you own, and run any analytics in the back end. This can give you powerful information such as social graphing information.
  • So -- what you monitor and what you get out of it depends on what approach you take and what platform you&#x2019;re engaging with. Here are some examples of the approaches and platforms.

Lean Analytics For Startups Lean Analytics For Startups Presentation Transcript

  • Ries, Mclure, and Blank are often misquoted.
  • They never said “fail faster”
  • Instead:
  • Learn and adapt.
  • Waterfall, agile, and lean Three approaches for three situations
  • Waterfall methodologies Know the problem and the solution
  • Known set of requirements
  • Known ways to Known set of satisfy them requirements
  • Known ways to Known set of satisfy them requirements Spec
  • Known ways to Known set of satisfy them requirements Spec Build
  • Known ways to Known set of satisfy them requirements Spec Build Test
  • Known ways to Known set of satisfy them requirements Spec Build Test Launch
  • Known ways to Known set of satisfy them requirements Spec Build Test Launch
  • Known ways to satisfy them Spec Build Test Launch Known set of requirements
  • Agile methodologies Know the problem, iterate on the solution
  • Known set of requirements
  • Unclear how Known set of to satisfy them requirements
  • Unclear how Known set of to satisfy them requirements Problem statement
  • Unclear how Known set of to satisfy them requirements Problem statement Build
  • Unclear how Known set of to satisfy them requirements Problem statement Build Test Sprints
  • Unclear how Known set of to satisfy them requirements Problem statement Build Test Viable? Sprints
  • Unclear how Known set of to satisfy them requirements Problem statement Build Test Viable? Sprints Adjust
  • Unclear how Known set of to satisfy them requirements Problem statement Build Test Viable? Launch Sprints Adjust
  • Unknown set of requirements
  • Unclear how to Unknown set satisfy them of requirements Problem statement Build Test Viable? Launch
  • Unclear how to Unknown set satisfy them of requirements Problem statement Build Test Viable? Launch Iterations & pivots Redefine problem, business
  • Most startups don’t know even know what problem they solve.
  • Possible problem space
  • You are here Possible problem space
  • You are here Possible Possible problem Trial startup viable space offering
  • You are here Possible Possible problem Trial startup viable space offering Trial startup Possible viable offering
  • You are here Possible Possible Possible viable Trial startup problem Trial startup viable offering space offering Trial startup Possible viable offering
  • Possible viable offering You are Trial startup here Possible Possible Possible viable Trial startup problem Trial startup viable offering space offering Trial startup Possible viable offering
  • Possible viable offering You are Trial startup t here vo Pi Possible Possible Possible viable Trial startup problem Trial startup viable offering space offering Trial startup Possible viable offering
  • As we become more agile, we need to be more aware.
  • (AARRR)
  • Complete Web Monitoring The big picture
  • The difference between accounting and optimization
  • http://www.flickr.com/photos/roryfinneren/65729247
  • Chair rentals per day 50 37.5 25 12.5 0 1 2 3 4 5 6 7 8 9 10 http://www.rvca.com/anp/wp-content/plugins/wp-o-matic/cache/57226_07+proof+1a+hb+beach+day.jpg
  • Chair rentals per day 50 37.5 25 12.5 0 1 2 3 4 5 6 7 8 9 10 http://www.rvca.com/anp/wp-content/plugins/wp-o-matic/cache/57226_07+proof+1a+hb+beach+day.jpg
  • http://www.imdb.com/media/rm3768753408/tt0073195
  • http://www.flickr.com/photos/kapungo/2287237966
  • Ice cream and drownings 10000 1000 100 10 1 Ice cream consumption Drownings
  • Ice cream and drownings 10000 1000 100 10 1 Ice cream consumption Drownings
  • Ice cream and drownings 10000 1000 100 10 1 Ice cream consumption Drownings
  • http://www.flickr.com/photos/25159787@N07/3766111564
  • http://www.flickr.com/photos/wheressteve/3284532080
  • http://www.flickr.com/photos/wtlphotos/1086968783
  • True causality 10000 1000 100 10 1 Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Ice cream consumption Drownings Temperature
  • True causality 10000 1000 100 10 1 Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Ice cream consumption Drownings Temperature
  • True causality 10000 1000 100 10 1 Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Ice cream consumption Drownings Temperature
  • True causality 10000 1000 100 10 1 Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Ice cream consumption Drownings Temperature
  • http://www.flickr.com/photos/stuttermonkey/57096884
  • http://www.flickr.com/photos/germanuncut77/3785152581
  • http://www.flickr.com/photos/fasteddie42/2421039207
  • “Hard” data Analytics Usability Performability (what did they (how did they (could they do do on the interact with what they site?) it?) wanted to?) Complete Web Monitoring Community VoC Competition (what were (what were (what are they they saying?) their up to?) motivations?) “Soft” data
  • “Hard” data Analytics Usability Performability (what did they (how did they (could they do do on the interact with what they site?) it?) wanted to?) Complete Web Monitoring Community VoC Competition (what were (what were (what are they they saying?) their up to?) motivations?) “Soft” data
  • Everybody has goals. http://www.flickr.com/photos/itsgreg/446061432/
  • Organic Ad Campaigns search network $ 1 1 1 Advertiser site Visitor 2 O er 3 $ 8 Upselling 4 Abandonment Reach 5 Purchase step $ Mailing, alerts, Purchase step $ 9 promotions $ Conversion $ Disengagement 7 Enrolment 6 Impact on site $ Positive $ Negative
  • Bad $ 4 content Social Search Invitation network link results 4 Good content 1 $ 1 1 Collaboration site 2 Visitor Content creation Moderation $ 3 Spam & trolls $ Engagement 5 Viral 6 Social graph spread 7 Disengagement $ Impact on site $ Positive $ Negative
  • Enterprise subscriber $ 1 End user (employee) $ Refund $ 2 Renewal, upsell, SLA reference SaaS site violation Performance Good Bad 3 Helpdesk Support 5 $ Usability escalation costs 7 4 Good Bad Productivity Good Bad 6 Churn $ Impact on site $ Positive $ Negative
  • $ Media site Enrolment Targeted 2 embedded ad 5 $ 6 1 Ad Visitor network 4 3 5 Advertiser $ Departure $ site Impact on site $ Positive $ Negative
  • Analytics is the measurement of movement towards those goals. http://www.flickr.com/photos/itsgreg/446061432/
  • ATTENTION SEARCHES TWEETS MENTIONS ADS SEEN
  • ATTENTION SEARCHES TWEETS NUMBER MENTIONS OF VISITS ADS SEEN
  • ATTENTION SEARCHES TWEETS NUMBER MENTIONS OF VISITS ADS SEEN LOSS BOUNCE RATE
  • ATTENTION NEW VISITORS SEARCHES GROWTH TWEETS NUMBER MENTIONS OF VISITS ADS SEEN LOSS BOUNCE RATE
  • ATTENTION ENGAGEMENT NEW VISITORS SEARCHES GROWTH NUMBER PAGES TWEETS PER MENTIONS OF VISITS VISIT ADS SEEN LOSS BOUNCE RATE
  • ATTENTION ENGAGEMENT NEW VISITORS SEARCHES GROWTH NUMBER PAGES TIME TWEETS PER ON MENTIONS OF VISITS VISIT SITE ADS SEEN LOSS BOUNCE RATE
  • ATTENTION ENGAGEMENT CONVERSION NEW VISITORS SEARCHES GROWTH CONVERSION PAGES TIME RATE TWEETS NUMBER OF VISITS PER ON x MENTIONS VISIT SITE GOAL ADS SEEN LOSS VALUE BOUNCE RATE
  • Visits Shopping cart Payment options Conversions
  • Visits Shopping cart KPIs Payment options Conversions
  • Visits Shopping cart Payment options Conversions
  • Visits Shopping cart Payment options Conversions
  • Visits Shopping cart Payment options Conversions
  • http://www.flickr.com/photos/mrmoorey/160654236
  • http://www.flickr.com/photos/duncan/1252272164/
  • http://www.flickr.com/photos/intherough/3573333256/
  • http://www.flickr.com/photos/jetheriot/648950773/
  • “Hard” data Analytics Usability Performability (what did they (how did they (could they do do on the interact with what they site?) it?) wanted to?) Complete Web Monitoring Community VoC Competition (what were (what were (what are they they saying?) their up to?) motivations?) “Soft” data
  • http://www.flickr.com/photos/trekkyandy/189717616/
  • Yes Perceptual information (did I see it?) No No Affordance Yes (was I supposed to interact with it?) Adapted from Gaver (1991)
  • Yes False Perceptual information affordance (did I see it?) No No Affordance Yes (was I supposed to interact with it?) Adapted from Gaver (1991)
  • Yes Seen False (perceptible) Perceptual information affordance affordance (did I see it?) No No Affordance Yes (was I supposed to interact with it?) Adapted from Gaver (1991)
  • Yes Seen False (perceptible) Perceptual information affordance affordance (did I see it?) Correct rejection No No Affordance Yes (was I supposed to interact with it?) Adapted from Gaver (1991)
  • Yes Seen False (perceptible) Perceptual information affordance affordance (did I see it?) Unseen Correct (hidden) rejection affordance No No Affordance Yes (was I supposed to interact with it?) Adapted from Gaver (1991)
  • “Hard” data Analytics Usability Performability (what did they (how did they (could they do do on the interact with what they site?) it?) wanted to?) Complete Web Monitoring Community VoC Competition (what were (what were (what are they they saying?) their up to?) motivations?) “Soft” data
  • “Hard” data Analytics Usability Performability (what did they (how did they (could they do on the interact with do what they site?) it?) wanted to?) Complete Web Monitoring Community VoC Competition (what were (what were (what are they they saying?) their up to?) motivations?) “Soft” data
  • Websites have a dirty little secret http://todaystatus.files.wordpress.com/2009/04/ww11-secret.jpg
  • http://www.inquisitr.com/2097/site-meter-causing-internet-explorer-failure/
  • Figure 3 Interactive user productivity versus computer response time for human-intensive interactions for system A E 600 - 3 T -" INTERACTIVE USER PRODUCTIVITY (IUP) w -HUMAN-INTENSIVE COMPONENT OF IUP 7 MEASURED DATA (HUMAN-INTENSIVE E 500 - A z " COMPONENT) U E - w E 0 > - > - - 400 3 n F 2 0 0 300 - 200 - 100 - 0 0- I 1 I I I 0 1 2 3 4 5 COMPUTER RESPONSE TIME (SI (1981) A. J. Thadhani, IBM Systems Journal, Volume 20, number 4
  • 10 ms
  • 100 ms 10 ms
  • 1s 100 ms 10 ms
  • 10 s 1s 100 ms 10 ms
  • 10 s 1s 100 ms 10 ms ! Zzz
  • http://www.flickr.com/photos/spunter/393793587 http://www.flickr.com/photos/laurenclose/2217307446
  • Everything is interwoven.
  • We’re getting better.
  • Impact of page load time on average daily searches per user 0% -0.15% -0.30% -0.45% -0.60% 50ms pre-header 100ms pre-header 200ms post-header 200ms post-ad 400ms post-header
  • Impact of additional delay on business metrics 0% -1.25% -2.50% -3.75% -5.00% 50 200 500 1000 2000 Queries/visitor Query refinement Revenue/visitor Any clicks Satisfaction
  • Shopzilla had another angle • Big, high-traffic site • 16 month re-engineering • 100M impressions a day • Page load from 6 seconds to 1.2 • 8,000 searches a second • Uptime from 99.65% to • 20-29M unique visitors a 99.97% month • 100M products • 10% of previous hardware needs http://en.oreilly.com/velocity2009/public/schedule/detail/7709
  • 5-12% increase in revenue.
  • http://www.flickr.com/photos/spunter/393793587 http://www.flickr.com/photos/laurenclose/2217307446 KPIs
  • VISITOR STRANGELOOP WEB ACCELERATOR SERVER
  • VISITOR STRANGELOOP WEB ACCELERATOR SERVER Decide whether to optimize
  • VISITOR STRANGELOOP WEB ACCELERATOR SERVER Decide whether to optimize Normal content
  • VISITOR STRANGELOOP WEB ACCELERATOR SERVER Decide whether to optimize Normal content Insert segment marker
  • VISITOR STRANGELOOP WEB ACCELERATOR SERVER Decide whether to optimize Normal content Insert Optimize? segment marker
  • VISITOR STRANGELOOP WEB ACCELERATOR SERVER Decide whether to optimize Normal Accelerated content Insert Optimize? segment marker
  • VISITOR STRANGELOOP WEB ACCELERATOR SERVER Decide whether to optimize Normal Accelerated content Insert Optimize? segment marker Unaccelerated
  • VISITOR STRANGELOOP WEB ACCELERATOR SERVER Decide whether to optimize Normal Receive Accelerated content page Insert Process scripts Optimize? segment marker Send analytics Unaccelerated
  • VISITOR STRANGELOOP WEB ACCELERATOR SERVER Decide whether to optimize Normal Receive Accelerated content page Insert Process scripts Optimize? segment marker Send analytics Unaccelerated GOOGLE ANALYTICS
  • What we learned:
  • Traffic levels 9,000 Total number of visits 6,750 4,500 8,505 2,250 4,740 0 Optimized Unoptimized Visitor experience
  • Bounce rate 20 15 Visits that bounced 10 13.38% 14.35% 5 0 Optimized Unoptimized Visitor experience
  • % visits marked “new” % of visits that had no returning cookie 14 11 7 13.61% 10.85% 4 0 Optimized Unoptimized Visitor experience
  • That means... 9000 Value Number of visits 6750 4500 7,582 4,095 2250 923 645 0 Optimized Unoptimized
  • Average time on site 31 Time on site (minutes) 23 16 30.17 23.83 8 0 Optimized Unoptimized Visitor experience
  • Pages per visit 16 Average pages seen 12 8 15.64 11.04 4 0 Optimized Unoptimized Visitor experience
  • Conversion rate 20 and order value Difference due to optimization 15 10 16.07 5 5.51 0 Conversion rate Order value
  • This is just one case LOTS # OF VISITS OPTIMIZED 0 0 VISITOR LATENCY 10,000 Different visitors experienced different performance levels.
  • With one outcome LOTS # OF VISITS 21.58% 0 BETTER 0 VISITOR LATENCY 10,000 Right now we have a single experiment, and a single resulting business impact.
  • With one outcome LOTS Best 5% Worst 5% # OF VISITS 21.58% 0 BETTER 0 VISITOR LATENCY 10,000 Visitors who were optimized fall into a range – the 5th to 95th percentile.
  • Lots of different results LOTS $ PER DAY 0 0 VISITOR LATENCY 10,000 If we have several experiments, we can understand the relationship better.
  • Lots of different results LOTS 24% $ PER DAY 0 0 VISITOR LATENCY 10,000 If we have several experiments, we can understand the relationship better.
  • Lots of different results LOTS 18% $ PER DAY 0 0 VISITOR LATENCY 10,000 If we have several experiments, we can understand the relationship better.
  • Lots of different results LOTS $ PER 14% DAY 0 0 VISITOR LATENCY 10,000 If we have several experiments, we can understand the relationship better.
  • Lots of different results LOTS $ PER 12% DAY 0 0 VISITOR LATENCY 10,000 If we have several experiments, we can understand the relationship better.
  • Lots of different results LOTS $ PER DAY 9.5% 0 0 VISITOR LATENCY 10,000 If we have several experiments, we can understand the relationship better.
  • Lots of different results LOTS $ PER DAY 0 0 VISITOR LATENCY 10,000 If we have several experiments, we can understand the relationship better.
  • You have your own curve LOTS $ PER DAY 0 0 VISITOR LATENCY 10,000 Every web business has a curve like this hidden inside it.
  • “Hard” data Analytics Usability Performability (what did they (how did they (could they do do on the interact with what they site?) it?) wanted to?) Complete Web Monitoring Community VoC Competition (what were (what were (what are they they saying?) their up to?) motivations?) “Soft” data
  • * This slide may not reflect the opinions of @seanpower (Kudos to @snipeyhead)
  • Community gardening is changing.
  • http://www.flickr.com/photos/jantik/111670098/
  • Communities: Getting a message out
  • http://www.flickr.com/photos/ockam/3364234970/
  • ------------------------------------------------------ Get your free private email at http://www.hotmail.com ------------------------------------------------------
  • !
  • You really don’t want web users to call you. $15 $12 $9 $6 $3 $0 Web self-service IVR Email Live phone Cost estimates BiT Group White Paper: “Web Self-Service Lowers Call Center Costs and Improves Customer Service” Low Average High
  • You really don’t want web users to call you. $15 $12 $9 $6 $3 Can$0.24 $0 Web self-service IVR Email Live phone Cost estimates BiT Group White Paper: “Web Self-Service Lowers Call Center Costs and Improves Customer Service” Low Average High
  • You really don’t want web users to call you. $15 $12 $9 $6 $3 Can$0.24 Can$0.45 $0 Web self-service IVR Email Live phone Cost estimates BiT Group White Paper: “Web Self-Service Lowers Call Center Costs and Improves Customer Service” Low Average High
  • You really don’t want web users to call you. $15 $12 $9 $6 Can$3.00 $3 Can$0.24 Can$0.45 $0 Web self-service IVR Email Live phone Cost estimates BiT Group White Paper: “Web Self-Service Lowers Call Center Costs and Improves Customer Service” Low Average High
  • You really don’t want web users to call you. $15 $12 $9 $6 Can$5.50 Can$3.00 $3 Can$0.24 Can$0.45 $0 Web self-service IVR Email Live phone Cost estimates BiT Group White Paper: “Web Self-Service Lowers Call Center Costs and Improves Customer Service” Low Average High
  • !
  • Change you don’t want on your computer
  • Base: Global active Internet users (uses the Internet every day/other day) Note: Percent of active Internet users that do this at least weekly Source: Universal McCann Social Media Tracker Wave 3, March 2008
  • • Watch online video (59%) Watchers • Read blogs (48%) • Download podcasts (23%) Base: Global active Internet users (uses the Internet every day/other day) Note: Percent of active Internet users that do this at least weekly Source: Universal McCann Social Media Tracker Wave 3, March 2008
  • • Share online video (37%) Sharers • Update profile (35%) • Upload photos (23%) • Watch online video (59%) Watchers • Read blogs (48%) • Download podcasts (23%) Base: Global active Internet users (uses the Internet every day/other day) Note: Percent of active Internet users that do this at least weekly Source: Universal McCann Social Media Tracker Wave 3, March 2008
  • • Rate a product or service Commenters • Comment on a blog post • Write in a discussion forum • Share online video (37%) Sharers • Update profile (35%) • Upload photos (23%) • Watch online video (59%) Watchers • Read blogs (48%) • Download podcasts (23%) Base: Global active Internet users (uses the Internet every day/other day) Note: Percent of active Internet users that do this at least weekly Source: Universal McCann Social Media Tracker Wave 3, March 2008
  • Producers • Write in a blog (21%) • Upload a video (18%) • Rate a product or service Commenters • Comment on a blog post • Write in a discussion forum • Share online video (37%) Sharers • Update profile (35%) • Upload photos (23%) • Watch online video (59%) Watchers • Read blogs (48%) • Download podcasts (23%) Base: Global active Internet users (uses the Internet every day/other day) Note: Percent of active Internet users that do this at least weekly Source: Universal McCann Social Media Tracker Wave 3, March 2008
  • • Edit a wiki Curators • Moderate a forum Producers • Write in a blog (21%) • Upload a video (18%) • Rate a product or service Commenters • Comment on a blog post • Write in a discussion forum • Share online video (37%) Sharers • Update profile (35%) • Upload photos (23%) • Watch online video (59%) Watchers • Read blogs (48%) • Download podcasts (23%) Base: Global active Internet users (uses the Internet every day/other day) Note: Percent of active Internet users that do this at least weekly Source: Universal McCann Social Media Tracker Wave 3, March 2008
  • Community Detailed Email Article Blog Private post wiki Forum Google comment group Forum Linkedin post IRC profile change Blog comment Facebook Complexity status update IM Twitter Simple One to one One to many
  • Purchased lists List Manual entry Legend Site widgets Self-enrolled Mail marketer Content Spam scoring Previews Campaign Email provider/platform Dangers & risks Schedule Mailings Shaping Bounces Transmission ISP suppresses sending Routers due to high volumes Bad email bounces Problems Viral forwarding DNS with list Reporting & tracking “Trap” address used ISP relations Honeypots Formal spam violation Firewalls Sender address blocked Mail server Server spam filters with content Problems Client Client (personalized) spam filters Forwarded Flagged as junk Open rate Opened message Click rate Clicked on Opted out
  • Unpaid search Community Email Banner ad mentions campaign Visits Shopping cart Payment options Conversions
  • Unpaid search Community Email Banner ad mentions campaign • Google PageRank • Sessions-to-clicks ratio
  • Unpaid search Community Email Banner ad mentions campaign • Google PageRank • Cost of ads • Sessions-to-clicks (CPM) ratio • Clickthrough rate
  • Unpaid search Community Email Banner ad mentions campaign • Google PageRank • Open rate • Cost of ads • Sessions-to-clicks • Opt-out rate (CPM) ratio • Clickthrough rate
  • Unpaid search Community Email Banner ad mentions campaign ? • Google PageRank • Open rate • Cost of ads • Sessions-to-clicks • Opt-out rate (CPM) ratio • Clickthrough rate
  • 9 followers 9 reach
  • 9 followers 9 reach 4 followers 16 reach
  • 10% 25% 50% 25%
  • 10% 25% 50% 25% =4
  • 10% 25% 50% 25% =4
  • 10% 25% 50% 25% =4 0.4 1 2 1 = 4.4
  • 10% 25% 50% 25% =4 0.4 1 2 1 = 4.4 8.4
  • 10% 25% 50% 25% =4 0.4 1 2 1 = 4.4 8.4
  • 10% 25% 50% 25% =4 0.4 1 2 1 = 4.4 8.4 50% 75% 100% 50%
  • 10% 25% 50% 25% =4 0.4 1 2 1 = 4.4 8.4 50% 75% 100% 50% =4
  • 10% 25% 50% 25% =4 0.4 1 2 1 = 4.4 8.4 50% 75% 100% 50% =4
  • 10% 25% 50% 25% =4 0.4 1 2 1 = 4.4 8.4 50% 75% 100% 50% =4 2 3 4 2 = 11
  • 10% 25% 50% 25% =4 0.4 1 2 1 = 4.4 8.4 50% 75% 100% 50% =4 2 3 4 2 = 11 15
  • 25% 50% 50% .5 2 1 = 3.5
  • 50% 75% 100% 50% =4 25% 50% 50% .5 2 1 = 3.5
  • 50% 75% 100% 50% =4 2 3 1 =6 25% 50% 50% .5 2 1 = 3.5
  • 50% 75% 100% 50% =4 2 3 1 =6 25% 50% 50% .5 2 1 = 3.5 14.5
  • Downstream reach (aggregate followers) 50% 75% 100% 50% =4 2 3 1 =6 25% 50% 50% .5 2 1 = 3.5 14.5
  • Downstream reach (aggregate followers) 50% 75% 100% 50% =4 2 3 1 =6 Amplification chance (how relevant the content 25% 50% 50% is + what the recipient thinks of the sender) .5 2 1 = 3.5 14.5
  • What might a community do?
  • It might spread a message.
  • That message could be viral* * Average number of people someone tells >1
  • It might accomplish a goal
  • It might accomplish a goal Visits
  • That goal might be inviting others
  • That goal might be inviting others Invite process
  • Seed Spread Impressions Visits Shopping cart Payment options Conversions
  • Seed Spread Impressions Visits Shopping cart Payment options Conversions Higher likelihood of conversion
  • A communilytics funnel Visits Shopping cart Payment options Conversions
  • A communilytics funnel Reach (impressions) Visits Shopping cart Payment options Conversions
  • A communilytics funnel Seed (starting community) Reach (impressions) Visits Shopping cart Payment options Conversions
  • A communilytics funnel Seed (starting community) Reach (impressions) Visits Shopping cart Amplification (virality and Payment options message spread) Conversions
  • A communilytics funnel Seed (starting community) Repurposing Reach (spread to other (impressions) communities) Visits Shopping cart Amplification (virality and Payment options message spread) Conversions
  • Different funnels for different communities and goals
  • Viral message spread Reach (impressions) Emphasis on Visits getting virality ratio above 1 Shopping cart (Retweeting, Fan, Email Payment options forward, Reddit upvote) Conversions
  • Megablogger proponents Seed (starting Emphasis on community) convincing highly- Reach followed, highly (impressions) acted-upon seed Visits group to spread the word. Shopping cart Payment options Conversions
  • A call to action Reach (impressions) Visits Shopping cart Emphasis on maximizing Payment options impression-to- click ratio within Conversions the community
  • Goal attainment: funnel
  • Goal attainment: funnel 20
  • Goal attainment: funnel 20 Followers
  • Goal attainment: funnel 20 Followers 700,000s
  • Goal attainment: funnel Seed ratio: 20 35,000:1 Followers 700,000s
  • Goal attainment: funnel Seed ratio: 20 35,000:1 Followers 700,000s 2
  • Goal attainment: funnel Seed ratio: 20 35,000:1 Followers 700,000s 2 Repurposing
  • Goal attainment: funnel Seed ratio: 20 35,000:1 Followers 700,000s 2 Repurposing 150 RT
  • Goal attainment: funnel Seed ratio: 20 35,000:1 Followers 700,000s 2 Repurposing 150 2,000 RT
  • Goal attainment: funnel Seed ratio: 20 35,000:1 Followers 700,000s 2 Repurposing 150 Amplification: 2,000 RT 2.9%
  • Goal attainment: funnel Seed ratio: 20 35,000:1 Followers 700,000s 2 Repurposing 150 Amplification: 2,000 RT 2.9% 1,642
  • Goal attainment: funnel Seed ratio: 20 35,000:1 Followers 700,000s 2 Repurposing 150 Amplification: Visitors: 2,000 RT 2.9% 1,642 0.23%
  • Goal attainment: funnel Seed ratio: 20 35,000:1 Followers 700,000s 2 Repurposing 150 Amplification: Visitors: 2,000 RT 2.9% 1,642 0.23% 32
  • Goal attainment: funnel Seed ratio: 20 35,000:1 Followers 700,000s 2 Repurposing 150 Amplification: Visitors: 2,000 RT 2.9% 1,642 0.23% Conversions: 1.95% 32
  • Goal attainment: funnel Seed ratio: 20 35,000:1 Followers 700,000s 2 Repurposing 150 Amplification: Visitors: 2,000 RT 2.9% 1,642 0.23% 7 Conversions: 1.95% 32 10 15
  • Goal attainment: funnel Seed ratio: 20 35,000:1 Followers 700,000s 2 Repurposing 150 Amplification: Visitors: 2,000 RT 2.9% 1,642 0.23% 7 x $100 Conversions: 1.95% 32 10 x $20 15 x $7
  • Goal attainment: funnel Seed ratio: 20 35,000:1 Followers 700,000s 2 Repurposing 150 Amplification: Visitors: 2,000 RT 2.9% 1,642 0.23% 7 x $100 Conversions: 1.95% 32 10 x $20 15 x $7
  • Goal attainment: funnel Seed ratio: 20 35,000:1 Followers 700,000s 2 Repurposing 150 Amplification: Visitors: 2,000 RT 2.9% 1,642 0.23% 7 x $100 Revenues: Conversions: 1.95% 32 10 x $20 Average: $39.54 Median: $20 15 x $7 Total: $1,005
  • Create something of value
  • Create Seed something of value it online
  • Create Seed Watch something of value it online its growth
  • Create Seed Watch Respond something of value it online its growth to it
  • Create Seed Watch Respond Lick something of value it online its growth to it your wounds
  • Amplify any interest Create Seed Watch Respond Lick something of value it online its growth to it your wounds
  • Repurpose in new ways Amplify any interest Create Seed Watch Respond Lick something of value it online its growth to it your wounds
  • Repurpose in new ways Amplify any interest Create Seed Watch Respond Lick something of value it online its growth to it your wounds Mitigate mistakes honestly
  • Analytics on the cheap (or nearly free)
  • The 8 communities you’ll meet
  • Groups and Blogs mailing lists Forums Wikis Real-time chat Micromessaging Social news Social networks aggregators
  • !
  • Search Anonymous, but little insight into what’s going on behind closed doors
  • Search Join Anonymous, but Permission- little insight into based access to what’s going on activity (friends, behind closed forums) doors
  • Search Join Moderate Anonymous, but Permission- Some little insight into based access to administrative what’s going on activity (friends, control, but you behind closed forums) have to earn it doors
  • Search Join Moderate Run Anonymous, but Permission- Some Complete control little insight into based access to administrative and visibility but what’s going on activity (friends, control, but you no guarantee behind closed forums) have to earn it anyone will show doors up
  • Search Join Moderate Run Anonymous, but Permission- Some Complete control little insight into based access to administrative and visibility but what’s going on activity (friends, control, but you no guarantee behind closed forums) have to earn it anyone will show doors up
  • Search Join Moderate Run Anonymous, but Permission- Some Complete control little insight into based access to administrative and visibility but what’s going on activity (friends, control, but you no guarantee behind closed forums) have to earn it anyone will show doors up
  • Search Join Moderate Run Anonymous, but Permission- Some Complete control little insight into based access to administrative and visibility but what’s going on activity (friends, control, but you no guarantee behind closed forums) have to earn it anyone will show doors up
  • Search Join Moderate Run Anonymous, but Permission- Some Complete control little insight into based access to administrative and visibility but what’s going on activity (friends, control, but you no guarantee behind closed forums) have to earn it anyone will show doors up
  • What VCs should ask you ...and you’d better answer.
  • Marketing reach
  • Viral coefficient On average, for each message they hear, how many people does someone tell?
  • How well are messages being amplified?
  • Infrastructure health
  • How performable are we? Health of the infrastructure (uptime, latency)
  • Market sentiment
  • What do visitors think of us? Both on the site (VoC) and in the world (community monitoring)
  • How engaged are users? Time since last visit, as a histogram, not an average, compared to baselines.
  • Lean analytics
  • Core goals driving the business Pick the 3-4 tasks you’ve set for users. Always know what these are and why they correlate to business growth.
  • Extended funnel abandonment Not just on the site: Email open rate See: Productplanner
  • In the last build, what moved us towards & away from goals? Requires knowing the goals and the key features added
  • Funnel changes What changed since the last board meeting?
  • Business sustainability
  • Cost per visitor Operations costs per site visitor (this had better be greater than the revenues and conversion rate)
  • Peak-to-average ratio How much busier are you at busy times? What premium do you pay for that surplus? Can you decommission well?
  • Minimum sustainable burn If you had to hibernate, what’s the steady-state cost of keeping the site running?
  • Thanks! @acroll @seanpower www.watchingwebsites.com