👋 Hi, I’m Lars. “Finding Distribution” is a weekly newsletter with tactics for start-ups to build product traction 🚀 and generate revenue💰. I’m writing it based on my lessons learned from building two companies, so you don’t have to repeat my mistakes.

If you can’t explain the what, for who, how and why of your product within 30 seconds, you’re toast.

Good messaging and positioning matters – for customers, for employees, for investors. A crisp problem statement is a great start. But a problem statement misses a few ingredients, like the solution and the urgency to act.

In this post, I’m covering the three concepts that I’ve most struggled with myself when it comes to talking about what our companies does. That’s messaging, positioning and storytelling – and how exactly the three fit together.

The short version:

• Messaging tells people what your product does (the “what” and “how”)

• Positioning specifies what user segment benefits the most (the “who”)

• Storytelling adds urgency and gives buyers a reason to act (the “why you” and “why now?”)

I’m sharing two examples, Supabase and Snowflake, both of them databases. You wouldn’t expect it, but words can build traction for databases. The examples will show how.

A great example of how positioning can change the trajectory of a company is Supabase.

So what’s Supabase? Let’s look at their homepage.

From the website copy, a reader understands exactly:

• what Supabase is (“an open source Firebase alternative”)

• who it’s for (even though they don’t say it, it’s implied that it’s for developers)

• who will benefit the most (developers who want Postgres, but are using Firebase)

• the outcome (scale to millions, by using the listed features)

The irony here is that the “alternative to” is an apples-to-oranges comparison. Posgres (also “PostgreSQL”) is a relational database, whereas Firebase is not. Turns out that doesn’t matter. The audience knows exactly what they’re getting (the outcome) and cares less about the underlying technology.

Supabase didn’t always position themselves as “an open source Firebase alternative”. Instead, they started with the term “Real-time Postgres”, and while true, it didn’t catch on with users.

On the Open Source Startup Podcast, CEO Paul Copplestone lays out how Supabase struggled to get users. In response, the founders conducted more user interviews. What they found was that people universally loved Postgres, but everyone was using Firebase.

They changed the positioning on the website and posted the link to HackerNews in May 2020 (“Supabase (YC S20) – An open source Firebase alternative”).

The HN thread was on 🔥 for two days. Right after the post, Supabase went from 8 to 800 databases in the space of two days.

The results continue until today, looking at Supabase’s GitHub stars:

Consider that nothing about Supabase the product changed.

The only thing that changed were the words that positioned Supabase – from “real-time Postgres” to “open source alternative to Firebase”.

In their 1973 book “Positioning: The Battle for your mind”, Al Ries and Jack Trout write in the opening chapter how positioning is not about changing the product.

Rather, you’re changing the way you describe the product to position it in the mind of the prospects.

Good positioning starts with a description that creates a need in the user’s mind.

The Supabase example shows how any product can be positioned in multiple ways. But which one you choose to distinguish yourself from the rest of the market can have (for a start-up) quite literally life or death consequences. There’s always an alternative for what you offer. Good positioning differentiates your product from your competition and creates an opening in the mind of your customer.

April Dunford has created a handy positioning framework.

The danger of any “template-based” strategy or positioning is that you can fall into the trap of simply filling it out and calling it a day. That’s not how it works.

There’s a process that includes customer discovery and testing of different positioning works. April Dunford lays out a 5-step process in “A Product Positioning Exercise”.

With your positioning figured, you can start developing your messaging around features and value.

in Software Snack Bites has some great advice. Good product messaging needs to explain the following things:

• What the product is

• What is the result

• How will the product enable that result

• Who will use the product

Use that framework to start, and you’ve fought 80% of the battle. Shomik references liveblocks as an example. Their messaging stands out for “its simplicity and time to value for a reader”.

Start simple, be clear and pick the hill you want to own and be known for. Over time, your messaging and market category will evolve.

An example for an evolving market category is Snowflake with their “data cloud”.

Snowflake is an analytical database. Their original category is known as “data warehousing”, with many big established players like Oracle, Teradata, and in particular AWS with their data warehouse “Amazon Redshift”.

This visual from from Snowflake’s S-1 filing depicts the evolution of their positioning.

Snowflake breaks down the evolution towards the data cloud into three phases. The evolution helps me understand how Snowflake became what it is today. Note how the inner circle “cloud native architecture” describes the change in the market that explains why the time for a product like Snowflake had come.

In their earlier sales decks (like this one from 2017), we can see how the positioning plays out.

Building an analytics stack has lots of individual small little problems – like data loading, integration, collaboration and creating the actual analysis.

You could align each pain point with a feature and value proposition. But that’s a lot to consume for a buyer, and it really doesn’t tell them why they should use Snowflake. All the other data warehouses offer those features too!

Instead, here’s what Snowflake did.

They frame the unique aspects of their product to address a specific segment of users. The type of user that has to deal with a large amount of cloud-generated data, and the pressing need for fast and easy analysis. For that type of users, the existing solutions are too clunky, expensive and slow.

Here are the four steps:

1. Frame the problem

2. Position “old” vs. “new”

3. Introduce your differentiated solution

4. Show proof

Snowflake framed their customers’ pain point as “the struggle for data”. With the term “struggle for data”, they give the problem a name. The problem arises from a shift of enterprise IT to cloud-native architectures. The result is an exponential growth in data that existing data warehouse solutions can’t handle. They’re slow and expensive.

But that’s a long three sentences – “the struggle for data” sounds much better!

Snowflake even has a full-blown website for the problem, with a telling URL:

—> https://www.snowflake.com/datastruggle/

Next, they frame existing players and their architectures as “the old way”, or “traditional architectures” that can’t address the new type of workloads of the cloud. Snowflake however has a “new” architecture that solves the struggle for data.

Now that we’ve established the old vs. new, we can transition to explain the differentiated value proposition. In the context of the problem, and how old solutions can address those problems, these benefits make much more sense to a user.

In the deck, there’s more (technical) context on how exactly Snowflake solves the struggle for data. What matters more though is the proof that they’re not making some unsubstantiated claims.

Even better is their “Data Struggle” website, where they’ve produced a high quality narrative with actors. Notice the “before” and “after” narrative of the website.

Alright, so how did this all play out in the market then?

First, let’s take a look at how AWS went to market to position their data warehouse Amazon Redshift. When you start looking around, you’ll see slides like this one:

It’s really hard to grasp what message a user can take away from this slide. This constellation of confusion (AWS) vs. clarity (Snowflake) translated into market awareness.

DB Engines is a website that ranks databases by their popularity. Snowflake came to market in 2016. Check out how Snowflake’s popularity performed in comparison to the three major cloud providers (AWS, GCP, Azure) and their respective products (Redshift, BigQuery, Azure Synapse).

You can see from the chart how the Snowflake IPO in 2021 amplified their position as the category leader for cloud warehouses. Yes, there were many other factors to their success – like the product itself, and a phenomenal go-to-market motion. But it all started with positioning.

Al Ries and Jack Trout published “Positioning: The Battle for your mind” in the 70s.

The two authors appear to be the first ones who gave positioning its name. Drinking their own champagne, before publishing their book, they positioned Positioning as the new thing in three articles in the May and April 1972 editions of Advertising Age.

Notice how they talk about “the positioning era”, as the evolution from the “product era” and the “image era”.

We see this pattern of “different” and “new” eras elsewhere in marketing. Andy Raskin covered the Zuora sales deck in his Medium post “The Greatest Sales Deck I’ve Ever Seen”.

Another company famous for using this type of market category evolution is Salesforce.

Drew Beechler dissects Salesforce’s narrative over the years in his post “The (Second) Greatest Sales Deck and Pitch I’ve Ever Seen”.

So why this use of “different eras” and evolution? It’s to address “change blindne