3 Types of Notifications

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Talking with founders is one of my favorite parts of being an early stage investor. Recently a founder casually mentioned there were three types of push notifications. I pounced on the comment as I had thought the same thing independently and was I excited to hear someone else’s definitions. Turns out we were in completely different places: the founder was thinking about notification technology while I was thinking notification use cases.

The three technical types she outlined were push, local, and in-app. In reviewing the iOS dev docs, one could also frame three as badge, message, and sound. The reality is that on either dominant mobile platform, notifications have a lot of unexplored potential in terms of tech and UX.  And as the sophistication of notifications design grows in support of user engagement (not new user growth as is commonly discussed) the need for specific

?

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3 Types of Notifications

https://www.flickr.com/photos/postmemes/14876404921/in/photolist-oEzsU2-6ySueJ-6yNpCp-o5SmJA-9aqABV-awo33u-4UHdYz-9AM9vi-yP8Ni-4UHeiF-9QWcmV-9atiAk-9fpeaj-9fyWAN-8iXQ5k-9fvP22-9fyWzJ-a69WFk-68thin-9n4wdv-aVrJBr-7XiLD3-7aXSx1-7xk83j-bVShhj-6s3Lk3-efr8xX-dFCvDi-fLur7b-a5CpcV-dTaciK-gYy1G4-btt8yn-6YwU6j-fieNMs-6TACCc-77WX54-6UCabD-7tKmy9-fqgG5K-b2Kmn6-fGJdaU-74ySFz-6U4jSe-efr9pK-efr8Vn-7zZWk2-efqUmD-efqTvD-6FNCt1/

Photo credit: Post Memes via Flickr

Talking with founders is one of my favorite parts of being an early stage investor. Recently a founder casually mentioned there were three types of push notifications. I pounced on the comment as I had thought the same thing independently and was I excited to hear someone else’s definitions. Turns out we were in completely different places: the founder was thinking about notification technology while I was thinking notification use cases.

The three technical types she outlined were push, local, and in-app. In reviewing the iOS dev docs, one could also frame three as badge, message, and sound. The reality is that on either dominant mobile platform, notifications have a lot of unexplored potential in terms of tech and UX.  And as the sophistication of notifications design grows in support of user engagement (not new user growth as is commonly discussed) the need for specific language to analyze the different types of notifications grows since not all of them are made equal!

With that in mind I’m going to enumerate the key notification use cases given their importance to mobile application design, engagement, and growth. Personally, I’ve come to believe there are three common types of use cases for notifications*: (1) user-generated, (2) context generated, and  (3) system generated. Diving into each a bit more:

  1. User-generated notifications: These notifications contain content created by a human using the app to other humans. Generally, these are the most engaging but especially so when the content they contain is private and directed to specific people. Mobile messaging is the highest volume example of this type of notification but other examples include comments / likes / favorites on posted content or @ mentions. My current favorite example of this notification is getting a new photo of my son from my wife.
  2. Context-generated notifications. These notifications are generated by an application based on the permission of its users. This is the fast growing category of notifications because the amount of machine readable data mobile devices create: location, contacts, calendars, and much much more. The norms around context-generated notifications are still be worked out between developers and users. Location-based notifications currently dominate this category but other examples include information about your next meeting (time relevance) or updates about your favorite sports teams (interest relevance). My current favorite example of this notification is when I get notified there is a designer nearby via Highlight (disclosure: I’m an investor there).
  3. System-generated notifications. These notifications are generated by an app based on the needs of the app. This type of notification can usually be called re-engagement at best or spam at worst.  Sometimes these can create value for the end user like letting you know a friend has started

    Continue reading “3 Types of Notifications”

Learn from Your Analytics Failures

By far, the safest prediction about the business future of predictive analytics is that more thought and effort will go into prediction than analytics. That’s bad news and worse management. Grasping the analytic “hows” and “whys” matters more than the promise of prediction.

In the good old days, of course, predictions were called forecasts and stodgy statisticians would torture their time series and/or molest multivariate analyses to get them. Today, brave new data scientists discipline k-means clusters and random graphs to proffer their predictions. Did I mention they have petabytes more data to play with and process?

While the computational resources and techniques for prediction may be novel and astonishingly powerful, many of the human problems and organizational pathologies appear depressingly familiar. The prediction imperative frequently narrows focus rather than broadens perception.  “Predicting the future” can—in the spirit of Dan Ariely’s Predictably Irrational—unfortunately bring out the worst cognitive

Continue reading “Learn from Your Analytics Failures”

Learn from Your Analytics Failures

By far, the safest prediction about the business future of predictive analytics is that more thought and effort will go into prediction than analytics. That’s bad news and worse management. Grasping the analytic “hows” and “whys” matters more than the promise of prediction.

In the good old days, of course, predictions were called forecasts and stodgy statisticians would torture their time series and/or molest multivariate analyses to get them. Today, brave new data scientists discipline k-means clusters and random graphs to proffer their predictions. Did I mention they have petabytes more data to play with and process?

While the computational resources and techniques for prediction may be novel and astonishingly powerful, many of the human problems and organizational pathologies appear depressingly familiar. The prediction imperative frequently narrows focus rather than broadens perception.  “Predicting the future” can—in the spirit of Dan Ariely’s Predictably Irrational—unfortunately bring out the worst cognitive

Continue reading “Learn from Your Analytics Failures”

OpenTable – Opportunity


When I co-founded PrimaTable, a restaurant marketplace startup, I had prior experience within Google’s Adwords and YouTube’s media marketplace. Taking the plunge, I tried to systematically learn about marketplaces from as many public company as possible. Unfortunately, many marketplace companies don’t report on the essential operational metrics (unit economics, CAC, LTV, liquidity, geographic density …) and require crude assumptions to decompose their performance. OpenTable was my closest comparable and reports nearly a complete set of supply side unit economics going back to 2006. Let’s take a look at their business.

History

Founded in 1998, OpenTable is a two-sided local marketplace connecting diners with restaurants. OpenTable started as a restaurant electronic reservation book (ERB). To grow their marketplace, OpenTable focused on single side utility, adding value to restaurants focused on customer service with a CRM and table management system. OpenTable focused on liquidity in a local geography prior to broader expansion. After the aggregation of a comprehensive list of restaurants in a metropolitan area, OpenTable.com provides value to consumers by facilitating the discovery of reservation availability.

Acquired by Priceline in July of 2014 for $2.6B, OpenTable takes reservations currently has over 32K restaurants internationally and has seated over 665 million dinners.

In this post, I’ll dig into OpenTable’s business with a focus on opportunities Priceline can capture. Priceline has stated a focus on three strategic areas (SAs) post-acquisition:

  1. International expansion
  2. Demand generation
  3. Marketplace innovation, especially in mobile

OpenTable’s business model is very similar to Priceline’s, in demand generation, supply aggregation and operational needs. Like hotels and airlines in the travel industry, restaurants have a high fixed cost and low variable cost (35%). To maximize profit, restaurants want to be at 100% occupancy and have significant margin to spend to acquire customers. Unlike Priceline, OpenTable has a much more frequent but lower margin and volume transaction.

Stage

OpenTable has grown to nearly $200M in revenue. The fastest growing portion of their revenue is reservation performance marketing product. SA #2 post-acquisition will be to focus on the marketing products further increasing the growth within performance marketing.

Revenue by Type.

Network effects

The beauty of marketplace businesses is – at liquidity there are strong network effects. Year over year growth in diners has consistently outpaced that of restaurants (outside of the Top Table acquisition in 2010). This is due to the increased value that each incremental user of OpenTable has due to the comprehensive coverage of supply. As OpenTable focuses on SA #3 marketplace innovation, expect revenue growth to begin to outpace even diner growth. OpenTable can offer additional value to both consumers and restaurants by creating a more efficient market.

Year over Year Growth.

Unit Economics

Restaurant Acquisition

Continue reading “OpenTable – Opportunity”

TechCrunch / The case for intelligent failure to invent the future


This post is by Kathy Chan from Khosla Ventures

This post also appears on TechCrunch. 

The world is changing at an increasingly rapid pace. In the past, experts with spreadsheets and econometric models or social scientists with subscale studies and linear models may have been useful. These so-called experts extrapolated from what came before, but as the rate of change has increased, looking to the past often is no longer meaningful – especially in a world driven by new technology.

In 1986, the McKinsey consulting group was asked to forecast the number of cell phones that would be in use in the United States by the year 2000; their model predicted fewer than one million, but the actual figure was more than two orders of magnitude greater at 109 million. How could one predict in 1986 what technology would look like by 2000?

Today, the means of production and distribution are being democratized and technology’s ability to enable creative uses and business models is quickly evolving. One person can spread an idea to billions. One person can build a product used by billions. The future will not be like the past. The future will be built by those who will take risks and action to invent the world they want.

Our civilization’s needs are expanding rapidly as seven billion people reach for the lifestyle of the 700 million most well off while our physical resources cannot keep pace.

The only way to bridge the gap is with intellectual capital, which will multiply the resources available to us. When Continue reading “TechCrunch / The case for intelligent failure to invent the future”

Benchmarking Zendesk’s S-1 – How 7 Key SaaS Metrics Stack Up

This post is part of a continuing series evaluating the S-1s of publicly traded SaaS companies in order to better understand the core business and build a library of benchmarks that might be useful to founders.
Zendesk is a 700 person company that builds customer support software. Zendesk went public earlier this year. It’s a remarkable business primarily because the founders and the team have built an incredibly efficient customer acquisition funnel.

Benchmarking Zendesk’s S-1 – How 7 Key SaaS Metrics Stack Up

This post is part of a continuing series evaluating the S-1s of publicly traded SaaS companies in order to better understand the core business and build a library of benchmarks that might be useful to founders.

Zendesk is a 700 person company that builds customer support software. Zendesk went public earlier this year. It’s a remarkable business primarily because the founders and the team have built an incredibly efficient customer acquisition funnel. It’s important to note that Redpoint is an investor in and shareholder of the company.

In the next seven charts, we’ll explore how Zendesk built their business. We will explore revenue growth, average revenue per customer, sales efficiency, payback periods, net income, gross margin and engineering spending. In these plots, I’ve used Zendesk’s colors as a consistent legend. Zendesk company data is green, median values are black, and other company values are gray. All the data come from

Continue reading “Benchmarking Zendesk’s S-1 – How 7 Key SaaS Metrics Stack Up”

trendwatching.com | THE FUTURE OF CUSTOMER SERVICE | Consumer Trend Briefing | September 2014


This post is by trendwatching.com from trendwatching.com

Five trends that will redefine great service in 2015 and beyond.

Read the THE FUTURE OF CUSTOMER SERVICE Consumer Trend Briefing from trendwatching.com »

A Predictive Analytics Primer

No one has the ability to capture and analyze data from the future. However, there is a way to predict the future using data from the past. It’s called predictive analytics, and organizations do it every day.

Has your company, for example, developed a customer lifetime value (CLTV) measure? That’s using predictive analytics to determine how much a customer will buy from the company over time. Do you have a “next best offer” or product recommendation capability? That’s an analytical prediction of the product or service that your customer is most likely to buy next. Have you made a forecast of next quarter’s sales? Used digital marketing models to determine what ad to place on what publisher’s site? All of these are forms of predictive analytics.

Predictive analytics are gaining in popularity, but what do you—a manager, not an analyst—really need to know in order to interpret results and

Continue reading “A Predictive Analytics Primer”

A Predictive Analytics Primer

No one has the ability to capture and analyze data from the future. However, there is a way to predict the future using data from the past. It’s called predictive analytics, and organizations do it every day.

Has your company, for example, developed a customer lifetime value (CLTV) measure? That’s using predictive analytics to determine how much a customer will buy from the company over time. Do you have a “next best offer” or product recommendation capability? That’s an analytical prediction of the product or service that your customer is most likely to buy next. Have you made a forecast of next quarter’s sales? Used digital marketing models to determine what ad to place on what publisher’s site? All of these are forms of predictive analytics.

Predictive analytics are gaining in popularity, but what do you—a manager, not an analyst—really need to know in order to interpret results and

Continue reading “A Predictive Analytics Primer”

A Predictive Analytics Primer

No one has the ability to capture and analyze data from the future. However, there is a way to predict the future using data from the past. It’s called predictive analytics, and organizations do it every day.

Has your company, for example, developed a customer lifetime value (CLTV) measure? That’s using predictive analytics to determine how much a customer will buy from the company over time. Do you have a “next best offer” or product recommendation capability? That’s an analytical prediction of the product or service that your customer is most likely to buy next. Have you made a forecast of next quarter’s sales? Used digital marketing models to determine what ad to place on what publisher’s site? All of these are forms of predictive analytics.

Predictive analytics are gaining in popularity, but what do you—a manager, not an analyst—really need to know in order to interpret results and

Continue reading “A Predictive Analytics Primer”

Oh, The Places You’ll Go!

“You have brains in your head. You have feet in your shoes. You can steer yourself any direction you choose. You’re on your own. And you know what you know. And YOU are the one who’ll decide where to go…”

Dr. Seuss, Oh, The Places You’ll Go!

My son was born a month ago. It has been one of the most amazing experiences, nothing short of miraculous. One night while soothing him back to sleep, I reflected on how different a world he will face when he starts his family. The amount of innovation that has happened over the course of my lifetime is staggering. The cumulative nature of discovery, each invention building upon a growing base of knowledge, dictates that this innovation only continues to accelerate. From our seat in Silicon Valley, acceleration is readily apparent.

In the last 30 years, we’ve seen the mass adoption of personal computers, a global internet, and smartphones. Long the domain of only science fiction, technologies like 3d printing, virtual reality, connected devices, quantified self, consumer robotics, and self-driving cars are on the immediate horizon. A series of simultaneous parallel inventions served to create the modern information technology economy. Exponential growth of compute power (Moore’s law), storage capacity (Kryder’s law), and data transmission (Butters’ and Nielsen’s have driven unfathomable hardware advancement. The lasting effect of these inventions is still playing out.

Previous leaps in efficiency during the Industrial Revolution centered around augmenting physical processes and were limited by fuel and mechanical innovation. More so than anytime before, the technical innovation today serves to enable further innovation (whether explicitly with computer aided design, or implicitly changing how we learn). Information technology augments mental processes and allows the transformation of every facet of our world.

As a huge fan of science fiction I recognize I’m no Hari Seldon. Here are some thoughts about what the next 10 years may bring, looking at startups founded today.

Information Revolution

Information is being digitized, organized and made universally accessible. To quote the film Serenity, “You can’t stop the signal, Mal.” With the rise of connected devices and cheap sensors, data is increasing exponentially. Anything that can, will be quantified. Once quantified, it will be analyzed and understood. Put another way, every physical thing will become smart. Everything will be connected, measured and responsive.

The information revolution that is currently happening in this rapid digitization is what powers much of the modern innovation. As Google Research Director Peter Norvig says, the combination of rapidly increasing data and new methods to process this data means new and better models yielding increased information, relevance and personalization. Already, services are moving from comprehensiveness (10 Continue reading “Oh, The Places You’ll Go!”

Awesome quotes from The Effective Executive

I recently finished reading The Effective Executive by Peter Drucker.  It’s a business classic that’s chock full of exceptional advice and insights.  It was originally published in 1966 and all of the lessons still apply.  Here are my highlights.  Enjoy. 

The Effective Executive (Harperbusiness Essentials) by Peter F. Drucker

“The fewer people, the smaller, the less activity inside, the more nearly perfect is the organization in terms of its only reason for existence: the service to the environment.”

“An organization, a social artifact, is very different from a biological organism. Yet it stands under the law that governs the structure and size of animals and plants: The surface goes up with the square of the radius, but the mass grows with the cube. The larger the animal becomes, the more resources have to be devoted to the mass and to the internal tasks, to circulation and information, to the nervous system, and so on.”

“The danger is that executives will become contemptuous of information and stimulus that cannot be reduced to computer logic and computer language. Executives may become blind to everything that is perception (i.e., event) rather than fact (i.e., after the event). The tremendous amount of computer information may thus shut out access to reality.” 

“Whether this theorem is valid or not, there is little doubt that the more people have to work together, the more time will be spent on “interacting” rather than on work and accomplishment.”

“Few executives make personnel decisions of such impact. But all effective executives I have had occasion to observe have learned that they have to give several hours of continuous and uninterrupted thought to decisions on people if they hope to come up with the right answer.”

“I have yet to see an executive, regardless of rank or station, who could not consign something like a quarter of the demands on his time to the wastepaper basket without anybody’s noticing their disappearance.”

“What do I do that wastes your time without contributing to your effectiveness?” To ask this question, and to ask it without being afraid of the truth, is a mark of the effective executive.”

“The man who focuses on efforts and who stresses his downward authority is a subordinate no matter how exalted his title and rank. But the man who focuses on contribution and who takes responsibility for results, no matter how junior, is in the most literal sense of the phrase, “top management.” He holds himself accountable for the performance of the whole.”

“If I had a son or daughter, would I be willing to have him or her work under this Continue reading “Awesome quotes from The Effective Executive”

The Art of Profitability

I've read Adrian Slywotzky's The Art of Profitability three times now, and each time I learn something new. According to its Amazon page, the book "offers 23 business lessons via the tale of a manager's quest to learn the "art of profitability" from David Zhao, a wise master." Each lesson starts with basic principles and uses the Socratic method to build up to a profitable business model. I think current founders, aspiring founders, investors, and employees would find this book valuable and practical. Here are some notes on the profit models that are most relevant to software companies — although the notes are no substitute for reading the book!

The main theme: "The path to profitability lies in understanding your customer."

Assorted Profit Models

Pyramid Profit

Key insight: Different segments of customers want different levels of quality/service and have different abilities to pay. Product lines that Continue reading “The Art of Profitability”

The Art of Profitability

I've read Adrian Slywotzky's The Art of Profitability three times now, and each time I learn something new. According to its Amazon page, the book "offers 23 business lessons via the tale of a manager's quest to learn the "art of profitability" from David Zhao, a wise master." Each lesson starts with basic principles and uses the Socratic method to build up to a profitable business model. I think current founders, aspiring founders, investors, and employees would find this book valuable and practical. Here are some notes on the profit models that are most relevant to software companies — although the notes are no substitute for reading the book!

The main theme: "The path to profitability lies in understanding your customer."

Assorted Profit Models

Pyramid Profit

Key insight: Different segments of customers want different levels of quality/service and have different abilities to pay. Product lines that map well to different customer segments can capture more profit.

Explanation: A pyramid is a system of three profit tiers:

  • a defensively priced bare-bones product to keep competition out.
  • a standard product for most people.
  • deluxe version to get maximum profit from those with a high willingness to pay.

Many SaaS businesses follow this profit model: there's a free/cheap tier, a medium priced tier that is appropriate to most customers, and an enterprise tier for customers with deep pockets who want the most features and services. Another example of this profit model would be different car models for a single brand (e.g. Nissan Versa vs Altima/Maxima vs GT-R).

Multi-Component Profit

Key insight: Customers can have different price sensitivities for the same item in different contexts. Someone who needs a resume proofread might pay $25, but someone who needs it proofread in the next 24-hours might pay $100.

Explanation: You can often sell the same thing in different contexts and for different prices. For example, you can sell a bar of soap     for $1 at 7-11, a 6-pack $3 at a grocery store, and a 30-pack for $10 at Costco. Similarly, you can rent out a hotel room to individuals, wedding parties, or business conference attendees — the prices and profitability levels will vary greatly across these use cases, but the room is always the same.

Switchboard Profit

Key insight: In contexts where assembling a package of related goods and services takes a lot of effort, customers will pay a premium for pre-assembled packages.

Explanation: There are situations where a customer prefers to buy a package of several interlocking pieces instead of hunting down each piece separately. The book uses the example of movie studios, which need a director, a script, and a star Continue reading “The Art of Profitability”

Disruption In Venture Capital: Government Strategic Investing

Gilman Louie discussed Government Strategic Investing at Stanford’s Entrepreneurship Through the Lens of Venture Capital course.

Continue reading “Disruption In Venture Capital: Government Strategic Investing”

NYC: A Natural Home for European Entrepreneurs

Last night I was invited to speak at the inaugural NYC European Tech Meetup.  There are tons of obvious reasons why the NYC and European tech ecosystems should work closely with one another, so a meetup on the topic was long overdue.  Congrats to Alban Denoyel and Anthony Marnell for starting it, and thanks for inviting me to speak, was a lot of fun.  Below are the slides I used – the presentation was meant to be a “State of the Union” of European tech in NYC, a high level overview fit for an inaugural meetup and get the conversation started.

 

Many thanks to David Rogg, our newest associate at FirstMark, for helping me with this.  I’m sure we missed some companies and people – if so, let us know in the comments, and we’ll update the presentation.

Shelly Hod Moyal: Minding the Gap Between U.S. and Israeli Valuations


This post is by omer from iAngels

Sit down with any entrepreneur or investor in the world and the topic of valuation is sure to pop up in the first five minutes. And who can blame them? It’s a lightning rod topic that can make or break a startup, regardless of which tech hub you call home. According to 2010-2014 data on […]

The post Shelly Hod Moyal: Minding the Gap Between U.S. and Israeli Valuations appeared first on iAngels.

Startup Traction Starts With The Right Goal. How To Get It Right.

Without traction — sustainable customer growth — your startup will languish or die. As such, traction should always be top of mind.

To focus your traction efforts, you need a traction goal to work towards. Example goals are 1,000 new users, 100 new customers or 10% market share.

The right goal for you depends on your business. It should  be chosen carefully and align with your company’s next inflection point. When you reach this goal, what will change significantly? Perhaps you’d be profitable, be able to raise money, or become the market leader.

The importance of choosing the right traction goal cannot be overstated. Are you going for growth, profitability, or something in between? If you need to raise money in 12 months, how much traction do you need to do so? These are the types of questions that help you determine the right traction goal.traction-book

DuckDuckGo Example

DuckDuckGo is the search engine that doesn’t track you. We saw more than a billion searches in 2013, six years after I founded the company. At DuckDuckGo, our current traction goal is one percent of the general search market. Achieving that goal is meaningful because at that point we will be an entrenched part of the market and receive everything that comes with that (recognition, better deals, PR, etc.).

This traction goal wouldn’t work well for most other companies because usually one percent of a well-defined market is not that significant or valuable. It works in the search engine space because the market is so big and there are so few companies in it. This speaks to the importance of setting a traction goal that is significant for your company.

Before this traction goal, DuckDuckGo had a traction goal of 100 million searches a month, which took us to break-even. Getting to break-even was the significant company milestone that aligned with this traction goal.

Before that, the traction goal was to get the product and messaging to a point where people were switching to DuckDuckGo as their primary search engine and sticking indefinitely. The company significance there was to achieve true product/market fit.

These are big goals, and that’s the point. Our traction goals have each taken about two years to achieve. The timescale is not important, however. The significance to your company is important. If the significance you are trying to achieve is profitability and you think you can get there in six months then that’s great!

Focusing on your Goal

Once you establish a traction goal, you can use it to evaluate what you should be working on. If activities are not related to achieving your traction goal, you should not be doing them. If marketing campaigns won’t move

Continue reading “Startup Traction Starts With The Right Goal. How To Get It Right.”