Category Archives: Guest Posts

Why Underestimating Small Growth Wins is a Costly Mistake

This is a guest post by Nancy Hua, CEO and co-founder of Apptimize. Apptimize’s real-time mobile development technology allows app owners to update their native mobile apps instantly for A/B testing, targeting, and innovative UX.

When it comes to mobile apps, it’s tempting to only look for big wins. Growth teams look for hacks that boost retention 5%, 10%, or even 15%. Anything less than that is often deemed a waste of time.

But there are only so many “big swings” to retention that you can pull off. And if your retention numbers aren’t dangerously low, then there isn’t any one feature release or UI element that will flatten that retention curve. The closer you get to great retention, the harder it is to find anything that will bump up that retention number.

That’s why at Apptimize, we do sweat the small stuff. Many of the most successful mobile apps— such as Glassdoor, Vevo, Glide, Strava—perform growth tests to find even the small wins. They look for every possible opportunity to increase retention even a single percentage point, because they know that those adjustments add up over time. Kevin Li, formerly of Yahoo Growth, swears by it:

“If there’s one takeaway it’s just that it’s okay to do small wins. Small wins are good, they will compound. If you’re doing it right the end result will be massive.”

So before your team brushes off testing as not effective enough, show them these huge upsides.

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How to Find Value in a Failed A/B Test

This guest post is by Stefan Bhagwandin, social media and content intern at Leanplum. Leanplum is an all-in-one mobile marketing platform for driving engagement and ROI.

For a new marketer reading about mobile A/B testing, the possibilities can feel limitless and bright. Statistically significant changes abound, and tweaking the color of a CTA is enough to earn a 10 percent lift in conversions.

In reality, A/B testing is not this pretty. Many A/B tests return results that are negative or — sometimes even worse — flat. Furthermore, testing too many variables at once could return seemingly contradictory results, where it’s difficult to correlate a specific change with a specific outcome.

But there’s still value in these “failed” A/B tests. It all depends on how you interpret the results. Let’s go over a few ways in which you can learn something new from an otherwise inconclusive test.


(Source: Unsplash)

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How to Choose a User Onboarding Stack That Drives Retention

This guest post is by Pulkit Agrawal, CEO and co-founder of Chameleon. Chameleon helps build and test personalized interactive product tutorials without writing code, making for a better onboarding experience for new users, while saving weeks of engineering time.

When product designers think about user onboarding today, they all too often think about tooltips and product tours, not the entire onboarding stack.

Product tours are the centerpiece of the onboarding experience, but they’re only one part of an entire suite of tools that makes user onboarding work. That includes analytics, customer communication and support tools.

The right stack is absolutely critical for your app because user onboarding is something that you need to continuously optimize. A massive amount of churn occurs in the onboarding phase of your product. If your new users can’t quickly find success in your app, they will simply give up and go elsewhere.

This hypothetical graph shows the big problem with losing customers early in their potential lifecycle:

retention with and without effective user onboarding

Retention from the end of month 1 to month 12 is the same. But that first drop off in short-term retention, from initial onboarding to the end of the first month, means that you have already lost customers. They missed their “Aha!” moment and missed the chance for success.

To get the lift you need in early retention, you need this stack of tools to measure, analyze and evolve your user onboarding flow.

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One Metric Is All Your Product Team Needs

This article comes excerpted from Hiten Shah’s eBook 5 Habits to Building Better Products Faster.

Over the past 10 years, Hiten has built and grown 8 different web-products, including Crazy Egg, KISSmetrics, and now Quick Sprout. Each of these companies used content marketing to drive the lion’s share of growth.

Sign up for Hiten’s SaaS Weekly newsletter to get a free copy of the book delivered straight to your inbox, along with fresh business insights every Monday morning.

“Being data-informed means that you acknowledge the fact that you only have a small subset of the information that you need to build a successful product,” Andrew Chen says. Nothing could be more pertinent for early product teams than that lesson. Despite the amount of data you’re collecting, you don’t know it all—you need to test, test, and test some more.

As a team, your success is rooted in that experimentation. You need to move fast, come up with hypotheses, and validate them. To do this effectively, everyone on your team has to know why they’re working on what they’re working on and what they’re trying to accomplish.

The best way to give your product team a clear direction and purpose is to boil down your efforts into one metric.

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It’s a Sticky Business: Combining Customer Data and Analytics

This is a guest post by Matt Sornson, Growth at Clearbit.

Clearbit provides data APIs to help businesses grow, from customer analysis and geolocation to fraud prevention and background checks. By improving tooling Clearbit enables their customers to focus on building great products.

Sticky products are just as important when you’re working with the enterprise. Organizational buyers have tons of options, which means that a tool that gets the job done and delights its users will have a huge advantage.

B2C apps have been using analytics to build better user experiences for years, but B2B analytics are a bit trickier.

Good B2B analytics involves both segmenting your users based on the actions they take—behavioral cohorting—and segmenting them based on their unique context for using your app—where they work and what they do.

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Scaling Your Content Marketing Strategy from 0 to 15 Million Visits a Year

This article comes excerpted from Hiten Shah’s soon-to-be-released book: Content Marketing Playbook from 83,232,461 Website Visits.

Over the past 10 years, Hiten has built and grown 8 different web-products, including Crazy Egg, KISSmetrics, and now Quick Sprout. Each of these companies used content marketing to drive the lion’s share of growth.

Sign up for Hiten’s SaaS Weekly newsletter to get a free copy of the book delivered straight to your inbox, along with fresh business insights every Monday morning. 

Like good products, quality content keeps a company’s audience hooked and coming back for more. Content marketing allows you to build up retention for your product—before your audience has even tried it out. There’s no better way to nurture an audience of engaged, repeat visitors to your company.

The problem that most companies run into is that while they know how valuable content is, they have a much harder time turning that knowledge into growth strategy. The web is filled with content on why you should produce more content, but it’s far more difficult to get your hands on solid facts and data relevant to how your company can succeed through content.

Different companies have different compositions of traffic that are highly specific to the stage of growth they’re in. A software blog that receives under 150k visits in a year operates under a completely different rubric than one that scores millions.

At each stage, you see different results—but patterns begin to emerge. I researched the traffic sources of 15 different blogs, ranging from well-known software products to community websites, and bucketed them according to traffic volume. This is my analysis.

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5 Cognitive Biases Ruining Your Growth

This is a guest post by Alex Birkett, Growth Marketer, ConversionXL.

ConversionXL, the leading authority on conversion optimization, recently launched their own master academy – ConversionXL Institute. It features a full-suite conversion optimization course designed to bring you from zero to hero (and the certification to prove it). Sign up now and start increasing revenues/sign-ups/conversions today!

As data-driven as we try to be, all organizations are essentially and necessarily human-driven. And humans, naturally, are riddled with irrationality and biases.

No one is exempt. And while you can’t totally avoid biases, just being aware of them and vigilant can help you mitigate the downsides. Besides, if you’re not aware that you’re biased, that’s simply your Bias Blind Spot.

The biggest problem with biases is that they work under the radar. You can think you’re making data-driven decisions while totally messing up. This is bad because your confidence increases even while driving decisions based on inaccurate inferences.

So to help you recognize some of the most common biases that afflict analytics, optimization, and growth, we’ll outline five biases and what to do about them. They are as follows:

  1. The Narrative Fallacy
  2. Confirmation Bias
  3. Dunning-Kruger Effect
  4. Backfire Effect
  5. Bandwagon Effect

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