Why Every Company Should Know Its Viral Coefficient

Transcript

I don’t care what market you’re in, every business in every sector has looked at the growth of the big digital platforms over the last 10 years and thought to themselves, “How the hell do we do something like that?”

Now of course every market is different, and if you’re super high end or B2B, it’s unlikely that you’re going to be hiring a team of data analysts to develop sophisticated growth models. Not least because, when you’re entire customer universe is barely in the thousands, the data you’re working with is statistically meaningless.

That said, while the practical applications of these concepts might be limited to a particular kind of company, the principles behind them are universally relevant, which is why I think every business should have a rudimentary understanding of the big ones. In particular, viral coefficients.

The term viral coefficient essentially just means the degree to which one customer will, over time, lead to additional customers via referral. If the new batch of users exceeds the previous batch of new users each time period, your product is said to be going viral.

To illustrate this we’ll start by looking at a business with a high volume of users; the kind that would conventionally use this sort of data modelling. I’m then going to give you three reasons why every business, no matter how small its customer base, should learn from the principles that this teaches us.

So if we imagine a business that begins with 1,000 users, and for the sake of simplicity we’ll call each time period 1 month. If the average customer makes 2 recommendations per time period, and the conversion rate of those referrals is 20%, then the 1,000 original users will add 400 users after the end of month 1, then a further 480 at the end of month 2, and so on, giving us a graph that looks like this. As you can see, there is quite an astonishing level of growth, hitting nearly 600,000 users after just 20 months.

However, this graph neglects a few important realities of networks. For a start, they are not infinite. There may not be 600,000 potential users in the network, for example, and a proportion of the potential users that do exist may never adopt this product as their long term loyal customers of another, similar brand. So if we imagine the long term realistic user base in this example is actually say 50,000, then as we approach this number the conversion rates are going to decline. After all, some of the referrals will now go out to people who are already using the product, or to people who have received an invite before and declined it, in which case it’s unlikely they’ll be signing up this time either.

So the graph actually looks more like this, eventually plateauing at 50,000.

Now depending on the value per user, this continues to look like it could be a pretty healthy business, but we are still missing something, and it’s the thing that underpins success or failure in just about every market – user retention.

You see perhaps those referrals are not happening simply because everyone thinks the product is awesome, but rather because they’re being incentivised somehow to forward on invites. Perhaps their experience of the product is actually pretty average, and each month only 50% of customers keep active. Suddenly the graph looks very different. Not only does it only reach a peak of under 10,000 rather than 50,000 users, but just a few months after hitting that peak it’s fallen off a cliff and soon it will have almost no users at all.

In silicone valley they call this jumping the shark, in reference to the shark fin shape of the graph, and it’s what every platform is fighting to avoid in those early days.

Now you might argue that this is because 50% retention is awful, but even at 90% retention we can see that while the peak may be higher and the decline may be delayed by a few months, soon enough we see the curve taking a sharp turn downwards again…

This is the problem that so many businesses face, and it holds a lesson for every business, regardless of sector, and it’s this…

The model illustrates that by far the most important thing of all – the thing that will almost certainly define the success of your business – is the customer experience. This is what will determine whether you’re building an asset or just burning through a market. It will also define your customer lifetime value which of course in turn means you can afford to spend far more acquiring each customer in the first place.

Fast growth and 90% retention simply aren’t good enough. To truly sow up a market, we need to be up around 98/99% retention, and if we do that, then the referrals and growth will all but take care of themselves.

See you next time.