Anomalous data can lead to growth opportunities

We’ve aggregated many of the world’s best growth marketers into one community. Twice a month, we ask them to share their most effective growth tactics, and we compile them into this growth report.

This is how you stay up-to-date on growth marketing tactics — with advice that’s hard to find elsewhere.

Our community consists of 1,000 startup founders and VPs of growth from later-stage companies. We have 400 YC founders, plus senior marketers from companies including Medium, Docker, Invision, Intuit, Pinterest, Discord, Webflow, Lambda School, Perfect Keto, Typeform, Modern Fertility, Segment, Udemy, Puma, Cameo and Ritual.

You can participate in our community by joining Demand Curve’s marketing webinars, Slack group or marketing training program.

Without further ado, on to our community’s advice.

No one wants your $25 referral bonus

Insights from Julian Shapiro of Demand Curve.

Even people who earn minimum wage can’t be bothered to refer a friend for a $25 referral fee. The most successful referral programs typically focus on app features that naturally incentivize users to invite friends and colleagues.

  • Consider Dropbox and PayPal: when you send money/files to someone, the recipient is incentivized to sign up so they can receive and store your goods.
  • Consider Instagram: Once you’ve created an account, you’re incentivized to plug your Insta handle everywhere — from your site to your YouTube videos. Because you crave attention, you filthy animal.
  • With those strong “referral” examples in mind, let’s re-imagine Instacart’s referral program. Currently, it’s offering cash referral bonuses for invites. Instead, imagine if it built a feature to help friends split grocery costs for dinner parties. Meaning, the existing Instacart user coerces the other dinner-goers to sign up to Instacart and add their credit cards.

There you have it: product-led referrals that are sustainable.

Anomalous data → growth opportunities

Insights from Keith Rabois from the Starting Greatness podcast with Mike Maples, Jr.

Keith Rabois: “I always teach that whatever you’re doing, from the CEO down to an intern, look for anomalous data. Anomalous data can generate epiphanies about the future.”

For example, after Square launched a technical trial to its first ~25 users, Jack Dorsey noticed that it was growing in particular areas without doing marketing. Keith theorized that after someone saw Square at a kiosk, customers wanted to become users themselves.

So, Keith suggested they test outdoor exposure as a serious acquisition channel. They monitored the data and saw a high correlation between the number of Square credit card devices distributed in a location and the number of user sign-ups the following week. (It turns out that 1% of all people who transact via Square end up signing up to use it themselves.)

One sneaky reason LinkedIn Ads perform poorly

Insights from AJ Wilcox of B2Linked.

LinkedIn uses UTC time when running ads. So your budget will be spent according to Greenwich time, not your local time. That means that by the time your prospects actually get to their office, your budget is partially shot because your ads have been running all night.

In other words, LinkedIn doesn’t do much to protect you from blowing money at suboptimal times.

To run ads during specific work hours, either manually toggle LinkedIn ads on and off every day, or use a tool like AdStage to automate scheduling.

By the way, time of day targeting — also known as “dayparting” — also affects your ad performance on Facebook and everywhere else. People are less likely to buy stuff at 2 a.m. unless it’s pizza.