We just went over your viral carrier in the last chapter.
It only stands to reason that the next step would be to make that carrier more effective - so that’s exactly what we’re about to do with a viral branching tune-up.
But before we get tangled up in that, let’s do a quick recap.
We started with the basics and analyzed the 12 different types of viral marketing.
We rolled our sleeves up and started Creating Your Viral Engine in 15 Steps.
So far, we’ve made it through five, which have included:
Pretty awesome. You’ve made it this far, and for that, Viral Panda salutes you.
However, as with anything in the growth realm, optimization never ends.
One Critical Micro-KPI of Viral Growth
One of the key performance indicators, or KPIs, that can help you amplify your viral growth in a big bad way, is the number of invites sent out per user on average, which we lovingly refer to as “i“.
Your viral growth over time can be determined by combining this metric with two other key players:
- The conversion rate on those invites (aka conv%)
- The “Cycle Time” – or the amount of time it takes for each viral loop to happen (aka ct)
Each one of these KPIs has smaller micro-KPIs that go into calculating them.
For your i value, one thing that goes into calculating how many invites are sent by each user, on average, is the average number of invites the average user sends out each time they send any invites at all.
(Try saying that 10 times fast.)
This is called your branching factor – and it’s one of the quickest ways to increase i.
Types of Viral Branching
Your users have a short attention span.
The more work you require them to do to complete a task, the fewer will complete it.
It’s not that your product necessarily sucks or that your reward incentives are too low.
It’s that you’re battling against the rest of their lives.
Your users are busy people.
They have other things they need to do that require their utmost time and attention...like binge-watching Netflix or trying to figure out what they should binge-watch on Netflix next.
Therefore, if your invite process is too time-consuming or labor-intensive, your branching factor – and your i value – will be minimal.
So what can you do?
Selection Branching
Say you’ve analyzed the data and have seen that many users will invite one friend.
That’s a fine place to start, knowing that at least some of your users will invite at least one friend to tell you that your process isn’t too time-consuming or intense.
But why stop there?
Why not try injecting a different invite flow that requires the same amount of time or work from the user but allows them to invite multiple friends in one shot?
This is called selection branching.
It comes from doing things like replacing a good ole fashioned email invite flow where users manually enter friends’ emails into a field with a bulk invite option for their entire address book.
You don’t need to completely replace the single-entry email field for those users who would prefer it.
However, having the option of selecting from an address book or Gmail contacts list would make inviting 50 friends as easy as inviting one.
The great thing about this is that not every user needs to invite multiple people for your i value to increase significantly.
In fact, if just a small portion of users use your bulk tool, you’ll see an increase.
Selection Branching in Action (aka Math!)
Let’s say you have 10 users who each invite 1 friend. This means you have 10 users, and you’ve had 10 invites sent out.
i = 10 / 10 = 1.0
Now that you’ve added your bulk invite tool, 9 of those 10 still each invite 1 friend, but the final person invites 6 friends.
You now have the same 10 users, but you’ve had 15 invites sent out.
i = 15 / 10 = 1.5.
Pretty sweet, right? Each time one user invites more than one friend in the same action, your branching factor increases, along with your i value. And your viral awesomeness.
High fives!
But wait, we’re not done. There’s something else we can do to increase branching even more.
Prediction Branching
Every product is unique.
Given the differences between your product, who your users are, and how your users prefer to use your product, there will be a preferred method for sending invites while using your product.
If you can use your data to predict (or at least retroactively analyze and find out) what this method is, not only will your i value increase, but your conv% should too.
(Note: Be sure to test for this last part. In rare cases, you’ll see i increase but conv% decrease to the point where the math doesn’t work in your favor.)
For example, if you’re a B2B SaaS tool, users are likelier to invite friends via email.
However, if you’re a mobile game app, you may see considerably more success with bulk Facebook friend invites.
What’s more, if you’ve done any work in CRO, you’ll know the more users have to scroll down a page, the more they will drop off.
Ideally, you will want to get creative by showing the friends your user will most likely invite at the top of their invite list.
This is viral branching at its best.
You want to predict HOW your users want to send invites to the users they’re MOST LIKELY to send invites to.
Being able to show the most relevant friends at the top will not only increase their likelihood of inviting these friends but may even remind them of people they SHOULD invite that they would have otherwise forgotten about.
Taking this one step further, say you have a SaaS tool that uses viral collaboration marketing.
You could try building a custom function showing users their Gmail contacts with the same email suffix (e.g. @yourawesomecompany.com).
If they’re within the same organization, it’s more likely they’ll want to collaborate on projects.
Boom! Boom! POW!
What’s Next?
Creating a well-architected viral product is the bee’s knees in a big way, BUT architecture is only one piece of the puzzle.
To bring it to a more complete state, we’ll dive back into one of the foundations of viral marketing. You guessed it: fishing.
What Is the Core Reason Why People Share a Product With Others?
Viral marketing and fishing have a lot in common.
They’re both all about getting the user (or fish) to take the bait... but what’s the equivalent of a nice juicy worm in the world of virality?
Find out in our next chapter.
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