[4/10] How to pick the right growth channel

Understanding product-market-channel-scale fit

We started this series with the Growth Formula. Breaking down the problem into two parts: How many potential customers does your business have? And how much value will every customer bring? Some businesses have millions and billions of customers, with each of them bringing in a rather modest net value per customer. While other businesses have relatively fewer customers (dozens to hundreds to thousands), with each customer bringing in a relatively higher net value.

And the Growth Formula is the starting point not just for the growth planning (focus of the previous section), but also for figuring out the actual executional levers to grow a business (focus of the current section). That is: You can either grow the number of users. Or you can grow the value per user. 

For example, say, you join a SaaS business that serves 100 customers who pay $100 each per month, and you have been tasked with the problem statement of growing it by 10 times. While the devil lies in the executional details, at the top level, the problem is simple enough: either you can grow from 100 to 1,000 customers. Or increase value from $100 per month to $1,000 per month. Or a combination of the two: go from 100 to 200 customers and $100 per month to $500 per month.

Let’s call the first type of growth as User Growth, and the second type of growth as Value Growth. And that division will form the basis of how this section of Firestarter series (essays #4 to 7) is structured. The first two essays will focus on User Growth. The third essay will focus on Value Growth. And the last essay of the section will put it all together.

Why have two essays on User Growth and only one on Value Growth? That brings us to a thumb rule: It is easier to move the needle on User Growth, than on Value Growth.

Think about it: An OTT app has 10 million customers each bringing in 10 dollars per month. Which of the following growth scenarios is more likely to happen if they have to grow by 10 times: 100 million customers bringing in 10 dollars per month, or 10 million customers paying 100 dollars per month?

Of course, this is a blanket statement without nuances – as thumb rules generally are – and both the metrics can be increased by the respective growth practitioners. That is to say, it is quite possible that the app increases the value per customer from 10 dollars per month to 15 dollars per month, by providing more value to the user. But, when we are talking about an increase by an order of magnitude (i.e. 10 times, 100 times, 1000 times, etc.), we are often going to look at User Growth rather than Value Growth.

So, why even bother with Value Growth? Because it is what makes or breaks a product-market fit (we quantitatively define this term later in the essay). Value growth might not enable growth by an order of magnitude, but it allows compounding. More importantly, it allows businesses to pursue User Growth in the first place.

Alright, so let’s start with ways to pursue User Growth.

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Selecting your lane of User Growth

Stop me if you have done this, or seen others do this, before: We come up with the idea for a business. We are looking for ways to grow the business. So, we pursue ad-hoc ways of doing it. We share the link to our project in different forum groups. We stand outside apartment complexes distributing our flyers.

Should we be doing this? Yes and no.

Yes: if it is being used to validate the idea. That is, if it is being used to reach the threshold of users required to validate how many people find it useful and keep using it. No: if it is being used as a way to grow the number of users. Once the value per user has been established, it is time to figure out how to get a steady stream of users coming in. How do we do that?

I have come across two frameworks that approach User Growth in a holistic and structured manner. The first one is by Jason Weinberg. In his book ‘Traction’, he lists 19 different channels you can use to increase the number of users. The channels range from PR to trade events, from viral marketing to good old paid advertising. While the list is not comprehensive (and it cannot possibly be), it is as comprehensive as it gets and serves as a good starting point.

The second framework that I have come across, which is the one I prefer (and you will shortly see why) is by Dan Hockenmaier & Lenny Rachitsky. Essentially, it combines all possible channels you can pursue thematically into 3 ‘growth lanes’. The lanes – and I have done some tweaking to their framework here – are: 

• Advertising directly to customers

• Reaching customers indirectly through partnerships

• Getting customers to discover you through content

So even if you are running Facebook ads to customers, running newspapers ads, or getting salespersons to call them on phone, these are all different channels, but are in the first lane.

Why it is an important framework is because it helps us get a holistic view of types of channels out there, and lets us think about our specific context first, rather than chase one channel after another. That is to say: considering the domain my business operates in, with the type of customers my business serves, and with the kind of cost structure I have, which growth lane makes most sense for me. Let’s jump to some examples to understand this concept.

For example, say, you are running a mobile phone review site. And displaying advertisements to the traffic is the primary source of revenue. So, how do you grow the revenue of this business? You consider Value Growth but since the problem is about growing this business by an order of magnitude of 10x or 100x, you consider User Growth first.

But which growth lane should you use for pursuing User Growth? Should you be going directly to the customers (advertising to people on social media or search engines who might be in the market for buying new phones)? Or should you partner with those who already have aggregated such users to indirectly reach such users? Or should you be generating content that gets potential users to discover you? Let’s look at the options one-by-one.

Advertising to the customers is the most obvious and the easiest way to go about User Growth generally. However, some businesses do not lend themselves to this lane of growth. For example, if Instagram charges you ₹20 for sending a relevant customer to your D2C brand’s website, but you generate on an average ₹10 from every such website visitor, Instagram Ads as a channel is not going to work for you. The business we were discussing was a mobile phone review website with display ads as its revenue. With the low value per user, advertising is probably not a good growth lane for such a business.

So, inversely, high margin businesses generally lend well to advertising. For example, if Instagram charges you ₹20 for sending a relevant customer to your D2C brand’s website, but you generate on an average ₹60 per customer, congratulations, you have just built a cash machine.

High volume businesses lend well to digital advertising. This is because the advertising platforms (Meta Ads, Google Ads, Amazon Ads, etc.) run on machine learning algorithms. They need more data points and quickly. So, if you are selling a very niche product, suitable for a very few people, it might not lend well to digital advertising, despite having a high margin e.g. yachts, expensive artwork.

Which brings us to partnerships as a growth lane. If your product offers a healthy margin to support significant variable marketing costs, but is not common enough to be suitable for digital advertising platforms, partnerships might be the way to go. Especially if you know of places, offline or online, where your ideal customer profile aggregates. (I refer to this as: ‘fantastic beasts and where to find them’).

This is a fairly common concept in B2B marketing, for example, enterprise software companies partnering with the respective industry events. In the consumer domain, influencer marketing is such an example. For example, if you are trying to grow your health supplement business, and it has healthy margins to support ongoing marketing costs. However, it is not a product everyone will buy, so digital advertising might not be suitable for you. Or, perhaps the product is common enough but digital advertising platforms do not provide the exact targeting attributes for your ideal customer profile (for example, teeth aligners). So, you can look for partners who already aggregate such ideal customers. Perhaps, dentists for teeth aligners and fitness influencers on Instagram or YouTube for health supplements whose respective followers are your ideal customers.

Coming to the last growth lane of getting users to discover you. This is, arguably, the hardest one to crack. But for very low margin businesses (e.g. content websites and apps), this becomes the only way to grow since there is no place in the cost structure to support variable marketing costs.

On the other hand, while this might be the hardest lane of growth to crack, this is one that lends a more durable moat to the business. For example, if you run ads to consumers to sell your beauty products, or partner with influencers to sell them, there is nothing wrong with picking these growth channels as long as the margin you make per customer is more than what it takes to acquire a customer. However, by definition, your cost structure will always have marketing cost as a variable.

The alternative approach could be to start a beauty blog or Instagram page or Youtube channel. You would first create some content (or a tool) that provides some free value to users. Some early adopters will discover it, and then you will overtime grow based on the platform (Google search / YouTube / Instagram) recommending it to others.

But just as having a high margin is not a guarantee for direct advertising or indirect partnership lanes to work, having a low margin is not enough for this lane to work for you. So, what are the prerequisites for this lane to work for your business?

Within this lane of organic growth, there are two sub-lanes: push (content/tool going viral and finding the right users) and pull (content being discovered on a platform by the right users looking for it). Within the pull sub-lane, the content can either be low in throughput volume and editorial in nature, or it can be high in throughput volume and be programmatically generated (often over user generated content). 

For  organic growth to come from push-properties, as opposed to pull-properties, the prerequisite is: can you consistently make viral content?

For pull-properties and editorial content: does your content have any attribute that sets you apart? Authoritative knowledge, or common knowledge but distinctive style – both make for great blogs as well as Instagram pages and Youtube channels.

And for pull-properties and programmatic content: do you have some proprietary data to generate unique secondary content from? For example, content forums and review sites do well in SEO because of having proprietary user-generated content on their platforms.

Alright, so putting it altogether:

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Selecting a channel: Experiments to validate a positive value per user

Once you have selected a lane, which makes conceptually sense in your business context, you still need to test different channels within that lane for yourself.

Deploying a channel requires approaching it as an experiment. You need to have a hypothesis which will either get validated or invalidated, as a result of the data you will collect from the experiment.

Let’s say you have a D2C brand with a reasonably common consumer profile, and a cost structure that can absorb variable marketing costs. You can therefore perhaps try direct advertising. You can run the first set of experiments (the how of this will be covered in the next essay), and see if the ‘net value per user’ part of the growth formula is positive for you or not. That is, is LTV more than CAC for you for this channel or not? If it is, this channel is working for you, and you can focus on scaling it. If it isn’t, despite multiple iterations of the experiment with different independent levers, this channel cannot be scaled for your brand since any number of users will not make up for a negative net value per user in the growth formula. 

Let’s consider a different example. Let’s say you sell a niche product that has a good margin to support variable marketing costs but a specific customer profile which is not easily accessible by digital advertising route. You decide to pursue partnerships as the growth lane. But within the lane, you have multiple ideas. You can partner with another brand which serves the same customer niche. The other idea is to partner with affiliates or influencers. Or you can start a referral program where your users can refer other potential customers that are hard to reach for you but are in their network.

The only way for you to actually know the specific channel idea that will work out for you is to test them out with small experiments, collect data specific to your business, and see which of them produces a positive net value per customer. Let’s say you decided to test out the influencer partnership channel, and ran a small campaign with 10 influencers that cost you ₹100k. You want to break even on the first order to ensure LTV is higher than CAC, and let’s say this requires a Return on Advertising Spend (RoAS) of 3 based on your cost structure. So, if you do generate sales of ₹300k+ from this campaign, you have validated this channel. But if you don’t, you can look at the independent metrics in the data collected from this experiment, look at the levers driving them, and repeat the experiment after tweaking the levers. We will go into more executional details of this in the next essay on User Growth.

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Product-market fit versus product-market-channel fit

What if you try out multiple different channels and are not able to find a net positive value per user in any of them? How do you differentiate between the scenario of users not finding your product useful and the scenario of users finding the product useful but you not being able to figure out a sustainable distribution channel. The former would be a case of lack of product-market fit (a term coined by Marc Andreessen). While the latter would be a case of lack of product-market-channel fit (a framework by Brian Balfour). Let’s understand the difference between the two. 

We have covered the way to quantify product-market-channel fit: is the net value per customer in the growth formula positive or not? Which in turn means, is the LTV greater than the CAC or not? But both the metrics are calculated for a particular channel. So how do you quantify product-market fit (PMF), independent of a channel?

Marc Andreessen defined PMF in a when-you-see-it-you-know-it kind of way. When the products are flying off the shelves, when servers can’t keep up with the demand, and so on. Sean Ellis, in his book ‘Hacking Growth’, however, made it more quantitative, and similar to a Net Promoter Score metric (NPS). He defined it as: what % of your customers will be very disappointed if they could no longer use your product? The threshold for PMF, he proposed, was that at least 40% of your customers should be very disappointed if that happened.

So, the unscalable ways of acquiring the initial users are actually good to get to a critical mass of customers, in order to understand the leading indicators of PMF i.e. customer satisfaction scores, and the lagging indicators of PMF i.e. customer retention rates, which will in turn determine the LTV of the specific customer profile.

Once a business has validated product-market fit for an ideal customer profile, but is unable to find a sustainable distribution channel, it is a case of lack of product-market-channel fit.

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Product-market-channel-scale fit

Although we think of concepts of product-market fit and product-market-channel fit as one-time certifications awarded in the early stages of the business, they are more like licenses that require regular monitoring and can be lost if not handled well. 

The biggest reason why product-market fit is weakened or lost is because businesses lose track of the core customer profile, and, in a bid to scale rapidly, they end up acquiring a lot of other customer profiles for which they did not have product-market fit. 

And the biggest reason product-market-channel fit is lost – even for the same customer profile over the same channel – is because we forget about a key determinant of product-market-channel fit: the scale of the product. Let’s understand it with an example.

Let’s say you are building an organic goods brand. You have a margin of ₹100 on every order. And your ideal customer on an average gives you 6 orders in the first 6 months, which is the window you consider for your lifetime value calculation. Your customer acquisition cost over Instagram ads is ₹300. So, after the first 3 orders, you break even for an average customer, and then, over their next 3 orders, you make a net value of ₹300.

Based on this data, you realize you have a cash generating machine on your hand. If you have some venture capital to fund the customer acquisition costs that happen upfront, you can scale it to a sizable portion of your entire potential customer base as soon as possible. The only missing piece of this logic is that we are not factoring in what scale has the data in the previous paragraph been collected at. Is it for 100 users per month, 10k users per month, or 1 million users per month?

The product-market-channel fit data holds only around a certain scale and changes rapidly as the scale changes. However, this is not to say that the customer acquisition costs only increase over time. It follows a more U-shaped curve.

Initially as you scale from a few dozen customers per day to a few hundreds customers per day, the customer acquisition costs actually improve (other things like ideal customer profile and the channel remaining unchanged). This is because of the nature of digital advertising mediums, which prefer more data points for their machine learning algorithms.

However, beyond a certain point, the customer acquisition costs start increasing. That is, a CAC of ₹200 per new customer for a scale of 1,000 new customers per day, can quickly become a CAC of ₹500 per new customer for a scale of 10,000 new customers per day.

This happens because at any point in time there are only a finite number of people who are in-market for buying the product (i.e. market size at that point), but, more importantly, only a certain % of them are actually are aware of and are considering to try out your particular brand within the wider category.

While there are thumb rules you can use for maintaining the right ratio of

• how many people in the market to

• how many of those are aware of your brand to

• how many of those are considering your product to

• how many of them you can acquire,

it is also important to play the situation by the ear.

If your costs are suddenly increasing as you increase the scale of acquisition, and become manageable as soon as you scale down, you are perhaps at the optimum ratio already. Inversely, if you have kept the scale of new users per week or per month at the same scale for a long period of time, and your CAC is actually improving, it might mean that you have probably a larger aware and considering base, and that you might be leaving money on the table. How do we plan out campaigns which build awareness, build consideration, and drive conversions? This will be a topic for the next essay on User Growth.

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Summary

Wrapping it all up: in this essay, we answered the following questions:

• What is the difference between User Growth and Value Growth?

• How does a business figure out which type of channel to drive User Growth?

• With a type of channel, how does a business determine the exact channel which fits the business?

• How do we know if a business lacks Product-market fit or Product-market-channel fit?

• Is there a ceiling to scale once a business has found product-market-channel fit?

In the next essay, we will explore the functional nuances of planning a campaign, creative levers in a campaign, and cover some basics of digital marketing, influencer marketing, and referral programs.

If you have any suggestions on this article, or need any clarifications, I am reachable at sudhanshu@skilletal.com