Accelerating growth with network effects and churn reduction
A high degree of churn can not be neglected in any business or growth marketing campaign – neither in a viral business nor in a more linear sales model. And it can not be compensated with the greatest online marketing. In this article we are going to explore with you the impact of different levels of churn on revenue, monthly recurring revenue (MRR) and customer base growth.
Why care about churn and network effects?
Is it not enough to keep growing at a steady rate? Well, yes and no. Of course it is great to see a business growing. But the real question is: how much faster can it grow? It is better if you are asking this question first before your competitors find out the secret sauce. Time and budgets are limited and the question is how much growth can you get out of the resources you have available?
If you compare some of the new, viral business models versus traditional business models you can see the point. Take airbnb, Uber or the social networks. Their viral adoption models captured market share swiftly – and yet most of them also struggle with retention of customers.
Linear versus Viral sales and product adoption
First we are looking at the base scenario for two different sales and marketing models: one is linear, the other one has a viral nature.
- Linear: this business model is producing a fairly linear growth. That means the sales per month is fairly steady and does not accelerate.
- Viral: in the business model with viral adoption we see an increasing, accelerating rate of growth. This is driven by network effects, in our case it is word-of-mouth promotion by the customer base.
In order to explore the different behaviours of these two business models we are going into our system lab and use a “management flight simulator”. The underlying model in this simulation is based on the Bass Diffusion Model which gives us two important parameters we can work with:
- The number of contacts each customer has per month.
- The probability of adoption (purchase).
This model provides a reasonable basis for exploring the effects of churn (= loosing customers from our customer base).
One very nice benefit of this formulation is that it helps us to explain how accelerating growth is happening and which networks effects are in place. In this blog post I am not going into much detail on this. But I put a complete briefing series “Shape Growth” in WITTIGONIA® Online Academy together about this topic.
The base scenario we are using only differs in the number of contacts. In other words, we are keeping the probability of adoption constant for now. We can relate this easily to a real world scenario: let’s say we have a given product and we are looking at different go-to-market and sales strategies. Usually the product can not be changed easily and quickly, whereas we can choose between different strategies and resource allocation models.
When we are plugging these values in our simulation tool, it produces the different behaviours as base scenarios.
The first thing we notice is that the viral model captures the market fairly swiftly and then goes into a decline. This decline is caused by the constraint of a limited market size and by a fairly high degree of churn. In our base case a 5% per month churn does not sound terribly high. But it means the business would loose about 60% of the customer base over the cause of a year.
Let’s say our product pricing is $100.- / month. This is fairly typical for a business solution such as Software-as-a-Service (SaaS), tools for productivity like Office 365, online marketing, accounting, CRM or it could be a premium membership in a professional network such as LinkedIn.
The resulting recurring revenue would look something like this:
Impact of reducing churn
The question of interest is: what is the impact of churn reduction in these two sales models?
In our simulation we are cutting down the churn fraction to 1% which would be the characteristic of a rather higher performing business. The results are staggering:
And if we compare the size of the customer base at the end of the planning horizon / the end of the simulation (which is 5 years in our case) we can see a remarkable difference not only in the different sales models but also in the impact of churn reduction.
Impact of network effects and churn reduction
The reduction of churn to a competitive level in the industry has remarkable impact on the customer base. And of course the MRR would directly benefit form this. The reduction of churn from 5% to 1% per month delivers significant benefits:
- Reducing churn: 2x impact. Doubling the customer bases in both scenarios (linear and viral adoption).
- Moving from linear to viral sales model: 8x.
- Combined effect: 27x. By moving towards viral sales model and reducing churn.
In this blog post we are not going into much detail on the how-to of churn reduction. We will cover this in another blog post or you can search for some tactics. There are many great articles out there.
Moving towards a sales and marketing approach which leverages the network effects in the installed base has great advantages (an 8x impact in our example). And focusing on churn reduction in addition to viral sales and marketing boosts the customer base much faster and higher (27x impact).
- Make churn reduction a priority from day one.
- Move towards a sales model which leverages network effects.
- Understand and validate the size of the addressable market.
- Factor churn into your business model. And the resource and profit impact.
- Implement these KPIs on the management dashboard: Churn, Acquisition from Sales vs organic network effects.
The first line of defence and single most important ingredient for growth is product quality. It has a profound impact on both retention and reputation which is driving network effects. Therefore, product quality and product market fit always come first before considering allocating resources towards viral marketing.
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