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Measuring GTM strategy: Product-Market Fit vs Customer Adoption Spectrum

April 20, 2021

Jay Desai is the Founder of Swpely – the platform for creating swipe files of blogs, tweets, LinkedIn posts, and more. Jay is an expert in GTM strategy, taking Swpely from idea to sketch to product in just three months, passing 1,000 users in its first 23 days. 

We sat down with Jay to talk about the best way to measure your go-to-market strategy's success. Is it product-market fit (PMF) – the preferred framework for most SaaS startups? Or, as Moz and SparkToro founder Rand Fishkin advocates, the Customer Adoption Spectrum

Scroll 👇 for Jay’s insights - or use the menu to skip to a section.

Measuring GTM | PMF and GTM strategy | Alternatives to PMF | GTM at Swpely | Data-driven insights from Cognism

Measuring GTM

Hi Jay. Let’s start at the beginning. What problems do sales and marketing leaders face when trying to measure the success of their GTM strategies?

I think the biggest struggle is related to attribution. If you have a bunch of different sources that you’re also pulling in, it can be difficult to figure out where to attribute leads and revenue. This can lead to paralysis by analysis as you try really hard to perfect the data and make everything flow. But data is imperfect, and sometimes you just have to use your gut.

My advice is to have a specific method to analyze your data and stick with it. If you know you can accurately attribute 80% or 90% of your data, then at least you understand the limitations.

How does the PMF framework help you overcome these problems?

I use PMF more on the features side – narrowing that scope and layering things on top. When you’re building and going to market, you know your strategy a year from now might be different than it is today. 

As you become more comfortable and better understand your data set, what you’re trying to push, and your results, you can layer different things into your strategy.

PMF and GTM strategy

How do you define PMF?

For me, PMF is when you can meet your target audience’s needs. Most of the time, it’s going to be better than how your competition does it. 

I think you can also hit PMF on certain features when you’re targeting a specific group that your feature solves. 

Rand Fishkin said that product-market fit maybe wasn’t the best tool to use because it can be vague and more of a gut feeling. What do you think?

I like Rand’s Customer Adoption Spectrum, with market size, brand awareness, and conversion rate. 

I like to use a hybrid model which combines both frameworks. You have to look at it holistically. It’s entirely possible to achieve PMF and then eventually lose it because the market is not a static thing. It’s dynamic and constantly shifting.

What are the pros and cons of the product-market fit framework?

The main downside is that it’s binary. Either you’ve got product-market fit, or you haven’t. There’s a middle ground there – with different factors coming into play.

But I’m very much an optimist, which you have to be as a founder. So, I mostly look at the pros. PMF is a really simple way of looking at things, which I like.

Alternatives to PMF

What other frameworks do you like as an alternative to product-market fit?

I like the Superhuman model that a lot of brands use. It’s where you ask the audience how disappointed they would be if your product were no longer around – not disappointed, somewhat disappointed, or very disappointed.

Rand’s Customer Adoption Spectrum lets you look more closely at your market and factors like brand awareness and conversion, so you see your opportunities and decide which levers to pull. The only downside is that it isn’t as simple and binary as PMF.

GTM at Swpely

What would you say to other founders who are working on their go-to-market at the moment?

My number one piece of advice is to connect it back towards a goal – either revenue or users – depending on the product you’re building and what stage you’re at as a business. 

How do you do that at Swpely?

We’re big on user base acquisition, so I always connect back to that. Even if you can’t quantify any sort of revenue (because we’re pre-revenue), we can compare it to other players in the market. We’re working to position Swpely as a Pinterest for business, so I look at other metrics in terms of revenue generated by users for other social platforms. 

Even though we make $0 on each user, we look at our users being around $1 average revenue per user. That means we can look at the money and time we spend on activities and connect it back to customer acquisition costs. For example, if an hour of my time is worth $100 and I’m going to spend three hours on an activity, it needs to produce 300 users.

In terms of go-to-market, we have a survey in our application to gauge product-market fit. We look at user sentiment, which is really important. I want to know how they feel about our product. It creates super-fans, which you’ve got to have when you go to market.

What else are you testing at Swpely?

We do a lot of crazy stuff. We’re doing a lot of influencer marketing – that’s our primary growth driver right now. We also have a unique strategy for email.

Our content strategy is a little different. We don’t run a blog. Our primary acquisition is through social content. 

In my experience, I need to tie everything back to a goal. I recommend testing at a small scale, then build out once some results have come in. I’d also say, keep an eye on the competition. Look at others’ playbooks and see how they execute.

Data-driven insights from Cognism

Thanks to Jay for sharing his knowledge with us.

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