Delight Frequency vs Delight Depth

A friend in the VC community asked me to evaluate a mobile wishlist and deal finder.  Interestingly, that’s what SF darling Pinterest first raised money for with HelloTote.

I advised my friend to focus on how deeply and frequently consumers get delighted by the product.

  • Low delight, high frequency products offer a user low levels of delight daily. Facebook, Instagram, YouTube and Zynga are great examples.
  • High delight,  low frequency products offer delight a handful of times each year.  RentTheRunway and acted upon 50% off deals fall in this category.

If your product doesn’t offer over 50% off, you need to make sure it can deliver delight often. Delight can come in many forms:

* Getting a comment from friend and feeling a sense of connection

* Earning a badge and getting a sense of accomplishment

* Learning something

* Getting a laugh

* Showing something cool

What you don’t want to offer is a few dollars of savings or a few comments from friends a few times a year.  That is what a comparison search engine or mobile shopping tool might do.  Web comparison search engines like and need to invest heavily in advertising and search engine optimization because their product delivers only moderate savings and delight.  They struggle with retention.  A mobile app has an even more difficult time with retention because intent-based marketing opportunities like Search Engine Marketing on the web are immature on mobile.

And, of course, the deeper the delight you provide the more you can charge a consumer.

What impresses me about BirchBox is that they’re doing everything with their community, points, deals, instructional videos, and personality.

On the other hand, I fear Foursquare doesn’t offer quite enough delight beyond just badges with their low levels of interaction among the community and low monetary rewards.

Lastly, “time until first delight” is a metric that will drive retention and virality.  A wishlist and deal finder can  struggle to make a user delighted on their first visit.  On the other hand, a social site the lets a user interact with a friend or earn a badge, or a daily deal sites can offer 50% off, can do much better on offering some delight over the first 30 days.

How often do your favorite products delight you? Where to they fall on the chart?

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Notes from New York Viral Media Meetup on 9/7/2010

The recent meetup on Viral Media had an AMAZING cast of speakers, who each spoke for about 10 minutes. Thanks to AOL for hosting, Jon Steinberg for organizing, and the NY tech community for supporting such great events.

The panel had a great mix of experiences.  From the recent action at Reddit (why are they on Digg’s front page?) to old Milgram experiments, the panelists covered it all.

The speaker list included:

  • Duncan Watts, Principal Research Scientist at Yahoo! Research, author of the great book Six Degrees
  • Nihal Mehta, CEO Buzzd, discussing their new viral offers
  • Greg Galant, Sawhorse Media, on building a viral product: Shoutworthy
  • Erik Martin, Reddit, “How something goes viral on Reddit”
  • Brian Morrissey, Digital Editor AdWeek, “The Science of Sharing”
  • Tim Schigel, CEO
My favorite framework came from Greg Galant at Sawhorse. He said that viral products or campaigns must have 3 elements:
  1. Social Action – Enjoyment of the app or experience REQUIRES sharing
  2. Star Vehicle – Usage of the app or product enhances user’s career or social life, perhaps helping them better communicate with fans or friends. For example, Formspring and Twitter offer celebrities and self-promoters a new way to get their message out
  3. Ruckus – The app or product has something special or noteworthy. Perhaps it sparks imagination or disgust. Maybe its first to market. Maybe it has some simple hook that can easily be passed on.   My mom can’t explain why people Tweet, but she knows its a public message of 140 characters or less. People who don’t use FourSquare still know you can announce where you are and become mayor.

My favorite chart came from Tim of CEO  He said that certain verticals have more people in them who are likely to pass on content in the vertical.  Specifically, it appears that health content has a higher concentration of readers who will share the content.  See the full chart from their case study below:

There was a general agreement that to have a viral hit, you need to try often.  Duncan said its better to regularly trigger lots of small cascades, instead of trying to predict one large cascade.  Brian noted that “Elf yourself” was  one of 25 microsites by OfficeMax for the holidays, and only the elves went viral. [credit to @papillonc for elf reminder]. After the demo, Buzzd’s CEO said they regularly test content on their homepage which gets millions of unique visitors each month to see what has viral potential.

Duncan also noted that “less than 98% of tweets aren’t retweeted, and the majority of those that do, are retweeted once”. [credit to @justinjustin for reminder]

Lastly, I was impressed with how Erik and the 4 person Reddit team handled their recent opportunity from the Digg redesign.  He offered sage advice about milking a viral hit.  Once you have something going, you should do whatever you can:  change your logo for a day, release your stats to bloggers, turn your community into ambassadors, and go above and beyond to keep your company and its hit in the limelight.

Again, many thanks to all the panelists, organizers and hosts. I can’t wait for the next meetup.

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Watch out, Founders! Early decisions lead to awful user generated content

Online communities have a tough time getting started. There is a chicken and egg problem. Who wants to join a community that doesn’t exist? To solve this dilemma, Yelp’s CEO openly admits that early on the company decided to pay reviewers and now pays “community managers” in major cities. A second founding decision was to focus on getting the most reviews possible with its user rewards system.

Yelp’s founding community in any city is those who are willing to contribute reviews for low pay (i’m assuming rates did not attract top writers and bloggers…because it didn’t). For example, for many moderate and expensive restaurants, reviews often cite discounted Restaurant Week specials. Yelp is now challenged with broadening its set of active contributors in order to get broadly applicable content for the larger audience it is attracting.

The second original decision founders made was to encourage the community to review often. Online Karma awards are given for Firsts, and users compete to see who can have the most reviews or Firsts. As the community prefers to be heard rather than rated, Yelp accepts reviews about old meals or reviews that focus on the circumstances of the meal. Sadly, this has led to a proliferation of low quality reviews for restaurants, a category where one size does NOT fit all.

I think Yelp has a lot of potential (17 million unique visitors a month is already impressive), but right now the main feature that helps me is the mashup of google maps, yellow pages, and pictures.

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