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IAC’s HowAboutWe co-founder: How to Avoid Delusional Thinking in Start-up Growth Strategy (Guest Post)

[Andrew: Trying to build and launch dating apps is a favorite pastime of 20-something tech entrepreneurs. However, dating products are notoriously hard to grow because it requires people to be "in-market" and also they don't necessarily want their friends to know they're online dating. Today, we have a great piece from a veteran of the space. Earlier this year, IAC bought HowAboutWe, a new dating product that was trying to reinvent the entire experience so that it'd focus on activities rather than dating profiles. The cofounder, Aaron Schildkrout, contributed the following essay below, enumerating the difficulties of the various growth channels, and also more generally, how to be realistic about your growth strategy. You can follow Aaron at @schildkrout on Twitter.]

Aaron Schildkrout:
How to Avoid Delusional Thinking in Start-up Growth Strategy

howaboutwe_logo_310x206_color

So, you have a consumer internet idea you think could be big.

The statistics say you’re are almost surely wrong. There is a 95+% chance you will fail for one of the following five reasons: a) your product idea is shitty; b) your market is small; c) your execution or team is weak; d) you are undercapitalized; or e) your growth strategy belies a belief in magic.

In this piece I’ll focus on this fifth demon: Magical strategy for growth. My primary case study will be the online dating industry, a petri dish for delusional startup growth strategies.

I co-founded @howaboutwe in 2010 and was co-CEO until its recent acquisition by IAC. Like everyone who has ever built an online dating company, we started off with a growth strategy that looked a lot like a manual of magic tricks. Most online dating startups never escape this; the number of historical failures in the dating space is staggering — the vapidity of magical thinking coming home to roost. We succeeding to an extent in transcending these challenges; I’ll speak about our small victories against delusion.

Magical Thinking

When I ask pre-launch or very early stage founders about their customer acquisition strategies, they invariably think they have a plan. They might share a document or slide with a list of tactics like “press,” “word of mouth and friend invites,” “biz dev,” and “content.” They may even thoughtfully quote Andrew Chen.

But when you really dig into their ideas and predicted results, the defining characteristic of such plans is almost invariably an uncanny belief in magic.

Here’s a basic overview of why magical thinking is so pervasive in early stage online dating distribution strategies, organized by acquisition channel:

Virality: The only two dating sites in the world that have attained true virality are Badoo and Tinder. A few others have attained rapid exponential growth through some complex dynamic including a large advertising spend. But in every one of these cases, the result has been a massively degraded experience verging on soft porn, disturbingly spammy tactics, and a userbase with very low lifetime values relative to match.com. With the unicorn exception of Tinder, the only way to attain virality in dating (discovered thus far) is to aggressively (read: deceptively?) capture the user’s email address book and spam the entire list. Basically: block the feeling that the user might find love (or, more to the point: sex) with a tricky address book capture. If your goal is to create a dating site that isn’t solely about finding sex and that has the potential to become a well-respected national or international brand with high subscription revenues, virality has, to-date, been nearly impossible to achieve. I’ve met with two or three dozen people in the last few years thinking about starting dating sites. Of these, maybe 90% have believed in some magic virality system. Of these, none have achieved magic.

Press: About 3 months into launching HowAboutWe we had a full-page front-page print article in the New York Times Sunday Styles section. It was literally the best non-TV press we could have gotten. It drove more traffic than we’d ever had by about 10x. It was an awesome achievement at that stage. Four years later, while an article like that would have been great, it would have driven a nearly indiscernible increase in traffic. It would be a cool, small, irrelevant bump. For early stage startups we were probably in the top 2 percentile for press converge. And this was key for branding and so on. But it was categorically NOT a business-creating source of traffic. This is very hard to understand for new entrepreneurs. They imbue press — like most things — with a magical aura of inexplicable growth creating powers.

BizDev: The problem here is distorted ideas about how much traffic other entities can drive. For instance, with HowAboutWe we had the idea that we would feature venues as great date spots and that, in return, they would drive their lists to us. But small venues don’t really have meaningful lists. We didn’t understand this at all — we believed in a magical conception of biz dev. Ultimately we found a biz dev strategy that has worked to a much more significant extent (see nymag.howaboutwe.com for an example of how we worked with much larger traffic sources to drive growth); but it is fairly rare to find such a tactic. Many — if not most — early BizDev ideas are rooted in delusion about the traffic-driving potential of proposed partners.

Content: Content is wonderful for branding. And if you have a product with high lifetime values, it can easily pay for itself. But it does not provide a business-supporting customer acquisition channel unless content is your product. HowAboutWe has a highly successful blog strategy rooted in thedatereport.com and nerve.com. But as a pure traffic-driver into our dating product, it was never, well, magical. Let’s say (none of these are real numbers) 100,000 people visited our articles each day. The conversion to the dating site is basically a glorified advertising system — so let’s say 1% of visitors click-thru. That’s 1,000 visitors. If we get a 20% conversion rates off those visitors, that’s 200 sign ups. If we have a 10% conversion to paid, that’s 20 paid users per day. Let’s say paid users are worth $100 to us. That’s ~$2,000 per day. That’s a bit over half a million bucks per year. Not bad; but it’s not a significant business. Content is cool, but not magic.

SEO: Yeah right.

Paid Acquisition / Direct Marketing: For dating, this is by far the most interesting category. It is the ONLY strategy that has ever worked to build a truly mainstream dating brand over time, with the sole exceptions of OKCupid (whose primary strategy was being free and which took nearly a decade to attain true scale) and possibly Tinder (tbd). Very few consumer web companies talk in their very early stages about buying traffic as a core part of their customer acquisition strategy (though this is changing). This relative absence is indicative — more than anything else — of the belief in magic. Advertising is the only reliable, scalable, predictable way of acquiring users for mainstream dating sites.

For those who do include direct acquisition in their strategy, there is usually a massive underestimation of the amount of work required for hardcore funnel and LTV optimization. Building a truly effective CRM alone is years of work, and this is just one piece of the optimization required to even begin to compete for positive ROIs with the major dating advertisers in the world (match.com, for example, spends hundred(s) of millions of dollars each year on ads; you can be sure their conversion funnel is fairly well-optimized).

So, either the absence of a paid acquisition strategy or the presence of one that underestimates what optimizing a conversion funnel really takes both echo the magical beliefs that pervade most early distribution plans.

~~

Delusion about customer acquisition is incredibly understandable, particularly for first time entrepreneurs. It’s painful to truly understand how hard attracting users is, and pain is hard to face.

Enter: PainMath, my antidote to blind magical thinking.

PainMath: An exercise in anti-delusion

a. Imagine you are building a new product. Magic aside, describe very clearly and mathematically a scenario in which there is genuine, business-validating, detectable desire for this product? Specifically, how many people will have to enter the top of your funnel daily for you to get to an annual revenue run rate of $10mm or a user base of 10mm? (This number/metric will be different depending on your business — but pick something that would be a significant achievement, that would leave you firmly outside of very early stage company building.)

b. Figure out from where you think these will people come. Include in your description conversion rates at every stage of your funnel plus virality coefficients.

c. Now, cut to a bare minimum all unexplained “organic” traffic (this includes press, unexplained word-of-mouth, any nondescript biz dev strategy, and content), cut your projected conversion rates by 50% at every stage of your funnel, and do the math again.

d. If you have included virality in your traffic sources, really do the math about what the virality coefficient will have to be to achieve what you are predicting. If it’s over .3%, you are likely deceiving yourself. Do your math again.

e. Then remember that almost every single startup, of which almost all have failed, had a reasonably smart but prideful person at the helm thinking their idea would work — a reasonably smart but prideful person like you and me — and do your math again.

f. Then, as you set out (because you almost invariably will, even if this math revealed a desert of implausibility), continue to do this math. Aggressively. And measure your results against this. Again and again.

The result of this PainMath is going to be rough for almost every new entrepreneur, particularly in the consumer web space.

No wonder we resort to the wand.

Making Magic

Here’s the rub: to win at the game of company-making, you have to believe in magic.

Why? Because by far the most important and powerful customer acquisition tactic is building a product that people love. And this — this is actually a matter of magic. It is something magical about what you make that will create true love and deep, sustainable distribution. The other tactics are important — and sometimes become the key to growth — but in almost no consumer product cases can they be relied upon.

To be clear: blind faith will destroy you almost every time. The key is to KNOW what magic you are believing in and to seek to move from magic to realism as quickly as possible. If you can’t bridge this gap, then you need to pivot. Magical thinking too-long harbored is failure in the works. But without magical thinking — in almost every case — you won’t be able to get started.

Instagram is a great example of this. I don’t know what their early thoughts about distribution were, but I can tell you right now that there is no customer acquisition plan they could have made that, when faced with the PainMath crucible, wouldn’t have yielded a quick sprint for the woods. What made them explode was the magic of the product. Instagram made everyday people into artists. And basically everyone in the early 3rd millennium crafts epoch of which we’re all part wants to be an artist or craftsperson. Instagram gave people a magical experience, transforming them, and this generated tremendous — magical—growth.

At HowAboutWe we created a new way to date based on the incredibly obvious idea that online dating interactions should be based on getting offline. We made dating about actually going on dates, in the real world. This was the newest dating idea since eharmony’s no-search matching algorithm. And there was a magic in it, in scrolling through a stream of people saying the romantic things they wanted to do. This created high conversion rates, which let us advertise increasingly profitably. This small bit of magic (and I have no presumptions here) allowed us to close biz dev deals with real distribution potential. It allowed content, press, and word-of-mouth to be above average contributors to growth.

Tinder has achieved this to a far more dramatic extent: swipe right…mutual match…magic! Safe, hot, addictive magic. This has been the absolute key to their growth.

Likewise with every other great consumer product for which the PainMath equation yielded hopelessness: magic has, ironically, been the solution.

It’s a lovely catch 22. It’s magical thinking that causes nearly every consumer web startup to fail. And yet it’s magic that’s at the root of customer love — and thus at the root of truly successful customer acquisition strategies.

You can’t believe in magic. But occasionally, you can make it.

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Mobile retention benchmarks for 2014 vs 2013 show a 50% drop in D1 retention (Guest post)

[Andrew: There's very little data out there on mobile, and so in the last few weeks, I've had guest posts on the % of users who opt-in to push notifications, as well as clickthrough rates of push. Today, I have some new metrics around retention, including for the first time, a systematic study of D1/D7/D30 retention for mobile apps. This is released by Mack Flavelle of Tapstream, who you can follow on Twitter]

Mack Flavelle, Tapstream:

As most app developers know, retaining new users is hard and some would say it gets harder every year. At Tapstream we wanted to test that notion so we looked at anonymized aggregates of attribution data collected by our platform as our customers acquire and engage their mobile users. The steep decline of engagement rates year over year was a surprise even to us.

We compared data from May 2013 to data from May 2014. To give you some context, in May 2013 an average app developer would retain about a quarter of their users a day after acquisition.

This is what keeps marketers up at nights: it means that three quarters of their acquired users didn’t stick around even for one day.

But when compared to May 2014, 25.5% retention on day one suddenly started looking very good:

Tapstream-User-Retention-Report-graph-01-large

On average only 14% of users stuck around a day after downloading an app. That is less than one in seven users. Those are abysmal rates by any measure.

This is exactly why we at Tapstream created Onboarding Links: to engage new users the moment they run the app for the first time. Reducing the app abandonment rates is becoming a crucial part of user acquisition.

Beyond day one

Another dimension of this data is looking further down the funnel to see how user retention fared at day 7 and day 30 after acquisition.

Again, the results are not encouraging:

Tapstream-User-Retention-Report-graph-02-large

Day 7 retention went from a respectable 23% to a measly 10% in May 2014, while Day 30 retention plummeted from 14% to 2.3% – a full 84% decrease.

To put this into perspective, the average next-day retention rate in May 2014 is almost the same (14.06%) as Day 30 retention rate a year ago (14.30%).

The story behind the numbers

What’s causing this dynamic to play out in the mobile app ecosystem is up for debate, but here are the most obvious culprits for why user retention in mobile has dropped 50% in the last year:

Incredibly low barrier to entry so no sunk cost loyalty

It takes about 10 seconds, a smattering of taps and usually zero dollars before a consumer is the proud new owner of your app. But easy come, easy go – there’s usually so little investment in your app there’s no pain of switching. As table stakes for app design get raised (remember when every app used default nave elements and controller views?) the next shiny thing to come along and grab consumer attention really is very shiny.

Incredibly low barrier to entry so no filter on user quality

When you have an expensive product and somebody buys it you can generally assume they did some research beforehand and had an idea of what they were getting into. They essentially self-filter to be loyal users by the time they engage with the product. With apps any such assumptions are out the window – there is nearly zero intent signalling by the consumer, even after they have “purchased” your app.

Disconnect between time of download and first open

There’s often a lack of context when a new user opens an app. This isn’t Christmas morning, unwrapping the box hoping for an NES. Between the moment somebody absent-mindedly downloads your app and opens it for the first time they’ve probably checked Facebook six times, Twitter three, bid on two obscure statues on Ebay and attended a funeral. The likelihood of them remembering the emotional switch that got them to download is reasonably slim.

Forklifting apps and other bad initial experiences

One of the tricks du jour, championed by the Japanese card games and the genre they inspired, is forklifting content into the app on first open. Sure the app itself is tiny, you don’t even need WiFi to get it, but then there’s a six-minute load time the first time you open it. This and other terrible first-run experiences can lead to serious drop off.

None of those explain the drastic decrease in retention over the last year. That may be a byproduct of the explosion in available apps. In fact most people would assume so, considering the huge number of apps available today.

The problem with that theory is that in May of 2013 nobody said

“I really wish there were more than half a million apps available, because I would definitely download and use more”

Arguably the variety of supply already far outstripped the demand.

So the relevant info becomes how many apps are being downloaded per device in May 2013 versus a year later. Are people downloading more apps and that’s why they’re not sticking around, or are they downloading better apps which is why they’re not sticking around?

Lucky for us one of the smartest minds in mobile started looking at that last year.

“Finally, these numbers are accelerating. Apple did 5bn downloads in the three months from December 2012 to March 2013, and then another 5bn from March to 15 May. The lack of precision means we can’t say this was double the rate, but the trend is clear, and it looks the same at Android…”

- Benedict Evans, from his blog.

Assuming Ben is right (and he often is) we can infer a gentle increase in the number of apps downloaded per phone, coupled with a higher quality of apps across the board has meant that the competition in the app store has become more fierce not only in terms of number of animals in the jungle but also the ferocity of those animals. Both of these factors end up driving down user retention in mobile apps versus a year ago.

AppleAppStoreStatistics

source: http://en.wikipedia.org/wiki/App_Store_(iOS)

Though this chart ends in 2012 and is iOS-specific we know that the trend continues but only steeper across both ecosystems as seen here and here.

About data used to generate this report:

Data was collected by Tapstream for months of May 2013 and May 2014 from over 100M devices. It is anonymized and it includes both iOS and Android apps, spanning many verticals from gaming to travel. The data excludes apps with DAUs of over 1M.

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New data on push notifications show up to 40% CTRs, the best perform 4X better than the worst (Guest post)

[Andrew: A few weeks ago, the folks at Kahuna released some great data showing that up to 60% of users opt-out of push notifications. Now they're releasing some new data on the click-through rates of push notifications, showing the differences between app categories and breaking down the reasons why some apps are so much stronger than others. They were gracious enough to share this data for the first time, as a guest post  on here - you can get in touch with the author, Alli Brian or Adam Marchick, Kahuna's CEO.]

Push notification click-through rates via Alli Brian @ Kahuna

The best apps know how to use push notifications to their advantage. They’ve figure out how to make their service part of their users’ daily routine, and they leverage push as a vehicle to do this.

Recent data from Kahuna reveals that push engagement rates vary widely across industries – utility and financial services apps seeing the highest performance, and retail and social experiencing the worst. Here’s a comprehensive look at the state of push engagement rates, as well as a roadmap for getting back on track if your app is trailing behind.

Here’s the data:

push engagement graph

You can see that push engagement rates for utility and financial services notifications (40%) are nearly four times higher than for e-commerce & retail notifications (12%). While all industry notifications benefit from significantly higher engagement rate than they see from traditional email engagement, the wide discrepancy can result in significant revenue loss for underperforming apps.

Apps That Are Winning
High push notification engagement rates are most often seen by apps with high frequency users. These apps use notifications to nudge their users do something that has become part of their regular routines. Utility, Financial Services and Ride Sharing apps lead the way – think about how normal it is to make these apps part of your daily or weekly routine. Looking for directions, watching your budget and taking a taxi are very regular activities, and using push to incentivize these actions is extremely effective. Here are a few examples:

1 - waze push

Utility apps have an obvious job to do – know your users daily routines and help them out when they appear to be getting into trouble. That’s what this push notification from Waze did – it was sent to Waze users  folks who regularly take the 280 freeway from San Francisco to Silicon Valley. And Waze users appreciated the heads up. Other high performing notifications from utility apps like job search or apartment rental services include new job listings or apartment availability alerts.

User engagement with these notifications (when appropriately timed) can be off the charts – as high as 80%.

2-levelmoney notification

 

Financial services apps also experience strong push engagement. By nature of the industry, money management is an important part of our daily lives. Hold the purse strings (or send a notification about them) and your users will be quick to respond. Take a look at this notification from Level Money. Their push engagement is off the chart.

But What If You’re Having A Harder Time Of It?
If you are in an industry that suffers from low push engagement rates, how do you overcome this? Retail, social and media apps typically have a more difficult time creating push notifications in a way that provides real user value. The good news: research shows that you can influence push engagement rates by using strategies that motivate users to integrate your app into their regular routines. Here are the top three techniques that will improve your notification response rates.

1. Find your Cadence:
Notification tolerance varies across app industries and individual users, so make the most of your notifications. Not all apps should be sending push notifications once a day, and engaged users have a vastly different tolerance for notifications than do new users or dormant users. Rather, it’s about sending the right message to the right person at the right time. In many cases, the elegance is in knowing when not to send a message. Check out the example below.

crunchyroll

 

Netflix does a great job of personalizing their notifications to the individual receiving them. Every user receives a unique message about the specific show they have been watching.  Rather than sending every user a notification every time a new episode of any show is released, consider one perfectly personalized notification. Crunchyroll could take a page out of their book.

Note: Sophisticated automation that limits and prioritizes the number of pushes each user is eligible to receive is the best way to achieve the appropriate cadence, given the numerous corner cases.

2. Make it personal
Don’t assume every user wants to hear about the same thing. Sending a notification that is valuable to the user isn’t just about a 10% coupon – it’s about presenting a relevant offer. The most compelling offer is one that contains information that the user deems important. Check out reactions to the notifications below.

 

 

fantasy football

 

These notifications both came from sports apps but elicited very different user responses.  The FIFA notification about the world cup was perceived as spam – simply because the app users to which it was sent was uninterested in the particular game mentioned in the message. In contract, the notification from SportsCenter that referenced the user’s specific fantasy football league was perceived as delightful content.

Worst of all is the mis-personalized push notification. We can’t emphasize enough how critical it is to gather accurate, person-level data to inform your notification. Use a unique identifier so even anonymous users will get accurately personalized notifications. Check out what happens if you send notifications to “devices”, not people.

groupon

 

As you can see above, device-based tracking does more harm than good. For example, if your wife borrows your phone and does a bit of browsing, all of a sudden you’ll be receiving notifications about irrelevant flash sales.

3. Timing is everything
Great timing should consider both user behavior and urgency. Notifications that include urgent information need to be sent at a time that is relevant to the context of the message, such as the notifications below.

refresh

united

As you can see, the notifications sent by Refresh and United Airlines both reference urgent and important information, and are tailored to the specific person receiving the message. As such, the response to the notifications are very positive.

For notifications that are not critically urgent, the goal is to minimize disruption and maximize delight. The horror stories about waking up to a mis-timed push notification abound, and users are not forgiving (see below).

9 - espn8- guardian

 

Considering every user keeps a different schedule, the only solution is to send push notifications at the time when each user is most likely to engage with your app. Kahuna data reveals that customizing delivery time based on user preference results in an average conversion uplift of 384%.

Great push is all about inspiring delight – facilitating a relevant and valuable app experience for your users and securing a prized place in their daily routines. Whether you’re in a high-performing industry like Utility or Financial Services or a low-performing one like Retail or Social, there is always room for improvement. Focus on understanding what your users value about your service and tailor your messages to their unique needs and interests. You’ll see push engagement skyrocket, and your users transform into rabid advocates.

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