Once your product is growing, and retention is good - both markers of a good product that has achieved product market fit - the next step is to build a growth machine. Elliot thinks of a growth machine as a systematic way of constantly accelerating your growth. This was his role at LinkedIn, where he grew the product from 20M to 200M. He's condensed his learnings into a 3 step process for anyone going from 'things are going well!' to 'now it's time to accelerate growth':
- Set a growth goal
- Understand the drivers of growth
What a good growth goal looks like
The most important characteristic of a good growth goal is that it is measurable. Elliot has found that a growth team simply won't be functional if it doesn't have a goal it can track on a regular basis. On top of being measurable, it is extremely important for the growth goal to be measurable quickly.
Facebook's insight of '10 friends in 13 days' is a great, successful growth goal. In thinking about how they arrived at that goal, it's clear that if you're running the growth team at Facebook, you're focused on MAU and getting to 1B users. According to Elliot, '10 friends in 13 days' permutation of that growth goal is important because it allows you to measure progress in less than half the time it takes to monitor MAU data. When you start your growth team, you'll be running lots of experiments and need results quickly. Waiting for a full month for data leads to an very ineffective growth team. Elliot and his team at LinkedIn got so good that they could see actions taken by new users on their first day that indicated the long-term quality of that user.
As for the goal itself, Elliot talked about how it needs to be aligned with both your product and your business, and that MAU might not make sense for everyone (e.g. an ecommerce company). It also needs to be a single number, as this is the clearest way to motivate the team and organization around the push for growth. If there's one number that matters, Elliot believes that you'll be a lot more effective, vs. making tradeoffs for various numbers.
Understanding growth drivers
The best tactic to understand your growth drivers is simply to work backwards from your goal. If the goal is to sign up new users - look at what steps new users go through and what channels they come through. Elliot suggested creating a large map and putting it up on the wall, showing the origin and steps that each user goes through on their way to being counted toward your growth goal. It's important to capture all of those sources and understand the impact of those channels on your goal, as the next step to building a growth machine is all about optimizing each and every one of those sources.
Optimize each step and channel
The final step in building a growth machine is optimization. Every optimization that Elliot has seen for growth falls into one of three categories:
- Reduce friction
- Increase incentive
- Increase exposure
To reduce friction, LinkedIn collects information for the various subsections of your profile in discrete, time-independent ways. Eliot used the example of collecting the entirety of the information needed to complete a profile entry for a user's 'Publications' section. Here, it's extremely important to fully collect the required information, which consists of several different types of data inputs. With this in mind, instead of asking LinkedIn users to complete the form in one (long) shot, the growth team decided to break the process up into several 'micro-questions' that appear in a blue box at the top of your profile page.
An example of the blue box module:
The team knew that if they could string together enough questions, they would end up with a lot of data. And even if the user drops off in the middle of the question, they can simply ask again next time they've logged in. One extra tip - Elliot mentioned that it's important to vary both the frequency and location of this type of feature, or else users may become 'blind' to it.
Increasing incentives becomes easier once you've already taken the steps to reduce friction'. The fact that reducing friction leads to more user input and tie-ins to the product, means that incentive has already increased. Elliot gave a few examples of this, the first being a checklist on the new homepage of Wealthfront that lifted conversions 20-30%.
Checklists are quick and simple, and work well for a lot of different products - they quickly and easily relay how the product is different, and explain what you'll get if you use the product. In the Wealthfront example, the checklist explains that you'll get better performance on your portfolio. Another great example Elliot used is Dropbox, where they've created a very clear step-by-step process that users can follow to get more space, one of which includes sharing Dropbox with friends.
The final step in optimization is about increasing exposure - this means how do you ask your users more often, more prominently, or in more places. If you want a user to do something, simply ask them more often, ask them in more places, or ask them in more contexts. Elliot gave a really important, basic reminder that we can't all just expect that our users will find whatever it is we want them to do, and instead we have to keep asking them in places that make sense. If you have consistent engagement, your uses will keep getting exposed to the actions that you want for them. As an example, Elliot explained that LinkedIn profiles have a button that read 'Improve your profile'. While this sounds very simple, it's actually a lot easier for people to click that versus seeking out the edit buttons next to each profile item. They pushed this even further, by creating popups to give their users ideas on how to improve their profiles - a simple example of increasing exposure.