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How to use Twitter to predict popular blog posts you should write
Using retweets to assess content virality
Recently I’ve been running an experiment:
- Tweet an insight, idea, or quote
- See how many people retweet it
- If it catches, then write a blog post elaborating on the topic
My recent Growth Hacker post was the result of one such tweet, which you can see above in my Crowdbooster dashboard. I wrote it on a whim, but after the retweets, I developed it into a longer and more comprehensive blog post. (Note that sometimes a tweet is not suitable to developed into a blog post, but most of the time this technique works)
Why this works
This works because the headline is key. It spreads the content behind it.
This is especially true on Twitter, but it’s also true for news sites that will pick up and syndicate your content. If that headline is viral and the content behind it is high quality, there’s a multiplier effect – sometimes a difference of 100X or more. Naturally, you want to optimize the flow of how people interact with your content, starting with what they see first: The title.
After all, what’s a better test for whether the following will be viral:
New blog post: Growth Hacker is the new VP Marketing [link]
than the tweet:
Growth Hacker is the new VP marketing
It’s a natural test.
I’ll also argue that if you can express the core of your idea in a short, pithy tweet, then that’s a good test for whether the underlying blog post will be interesting as well. Great tweets are often provocative insights or mesmerizing quotes, and there’s a lot to say by examining the issues more deeply. Contrast this to writing a long, unfocused, laundry-list essay examining a topic from all angles, taking no interesting positions or risks along the way – now that’s a recipe for boredom.
Combining virality with a high-quality product, of course, is the key to a lot of things – not just blogging
Don’t waste your time writing what people don’t want to read
Testing your ideas like this allows you to invest more time and effort into the content – a clear win.
Personally, I love writing long-form content that dives deep into an area, and also enjoy reading it as well. Unfortunately, writing a blog post often takes a long time – an hour or more. Use this technique to make it safer to spend more time, think more deeply, and research more broadly on you write. In my experience, writing a high-quality, highly retweetable blog post once per month is better than writing a daily stream of short, low-quality posts that no one will read. Plus, it takes less time.
As a smart guy once said: “Do less, but better.”
Quora: Has Facebook’s DAU/MAU always been ~50%?
I recently asked, and then answered my own question on Quora and wanted to share here as well.
Has Facebook’s DAU/MAU always been ~50%?
According to public info, Facebook’s DAU/MAU is 58% these days. Here’s a link.
It states:
- 901 million monthly active users at the end of March 2012
- 526 million daily active users on average in March 2012
Has Facebook’s DAU/MAU always been this good, as a consequence of its product category (communication/photo-sharing/etc.)? Or was it once a lot worse and was improved over time?
(UPDATE: Here’s a followup question I have about the same topic- Was Facebook’s DAU/MAU ~50% prior to launching the Newsfeed in 2009?)
Answer: Yes, Facebook’s DAU/MAU has been close to 50%, at least since 2009.
Since the DAU/MAU data is only available since 2009, it’s hard to say how things were very early on. However, I theorize that Facebook’s high DAU/MAU has always been high as a natural outcome of the communication-oriented usage of the product. Contrast this to a product category like ecommerce which you are unlikely to use and purchase with every day.
In their recent financial filings, the following chart is shown for Facebook’s DAU and MAU since 2009:

If you do a graph of the DAU/MAU on this data, since 2009, you’ll see that it starts around 45-47% and goes up to a very impressive 58% recently.
(As an aside, another interesting aspect is that Facebook’s MAU growth looks pretty much like a straight line, and so the % growth has been slowing down as of late. The MAU growth was around 23% starting in 2009, but is now down to 6-7% in recent months. See below for a graph on MAU vs % MAU growth)
How do I learn to be a growth hacker? Work for one of these guys :)
After writing my recent article on Growth Hackers, I’ve been asked by quite a few folks on how to learn the discipline. The best answer is, learn from someone who’s already good at it – if you’re technical and creative, it’s well worth the time.
I would encourage everyone to also read Andy Johns’s Quora answers on What is Facebook’s User Growth team responsible for and what have they launched? and
What are some decisions taken by the “Growth team” at Facebook that helped Facebook reach 500 million users?- it lays out a lot of the key activities used in a well-run growth team.
The list below includes some of these folks I know personally, some just by reputation- but collectively they’ve grown products up to millions, 10s of millions, and in some cases, 100M+ users. Typically they use quantitatively-oriented techniques centered on virality across different channels such as iOS, Facebook, email, etc. There’s lots of iteration, A/B testing, and experimentation involved. There’s also really great growth hackers centered around SEO, SEM/ad arb, and other techniques, but for the most part I’m just listing out the folks around quant-based virality. The important thing about virality is, it’s free
So it’s an important skill for startups.
Missing from this list are many unsung heroes over at Zynga, Dropbox, Branchout, Viddy/Socialcam, lots of ex-Paypal/Slide people, etc., etc. Also, all of these guys typically have co-founders or entire growth teams around them that are experts, even if I don’t know them by name.
If others in the community would like to make suggestions, tweet me at @andrewchen or just reply in the comments.
| Name | Background | |
| Noah Kagan | AppSumo, Mint, Facebook | noahkagan |
| David King | Blip.me, ex-Lil Green Patch | deekay |
| Mike Greenfield | Circle of Moms, ex LinkedIn | mike_greenfield |
| Ivan Kirigin | Dropbox, ex-Facebook | ikirigin |
| Michael Birch | ex-Bebo, BirthdayAlarm | mickbirch |
| Blake Commegere | ex-Causes/Many games | commagere |
| Ivko Maksimovic | ex-Chainn/Compare People | ivko |
| Dave Zohrob | ex-Hot or Not, MegaTasty | dzohrob |
| Jia Shen | ex-RockYou | metatek |
| James Currier | ex-Tickle | jamescurrier |
| Stan Chudnovsky | ex-Tickle | stan_chudnovsky |
| Siqi Chen | ex-Zynga | blader |
| Ed Baker | esbaker | |
| Alex Schultz | alexschultz | |
| Joe Greenstein | Flixster | joseph77b |
| Yee Lee | yeeguy | |
| Josh Elman | Greylock, ex-Twitter | joshelman |
| Jamie Quint | Lookcraft, ex-Swipely | jamiequint |
| Elliot Shmukler | eshmu | |
| Aatif Awan | aatif_awan | |
| Andy Johns | Quora, Twitter, Facebook | ibringtraffic |
| Robert Cezar Matei | Quora, ex-Zynga | rmatei |
| Nabeel Hyatt | Spark, ex-Zynga | nabeel |
| Paul McKellar | SV Angel, ex-Square | pm |
| Greg Tseng | Tagged | gregtseng |
| Othman Laraki | othman | |
| Akash Garg | Twitter, ex-Hi5 | akashgarg |
| Jonathan Katzman | Yahoo, ex-Xoopit | jkatzman |
| Gustaf Alstromer | Voxer | gustaf |
| Jon Tien | Zynga | jontien |


