In Part 1 we built the foundations and established a framework for our Go-To-Market fit experiment. It is now time to look at the first component of our Revenue Equation: Lead Velocity Rate (LVR).
1.8 – Build out your Go-To-Market model V1
Over the past few weeks, you ran an initial assessment to gauge whether you are ready to embark on your search for Go-To-Market fit. You reverse engineered your next round to get a clear picture of the metrics and milestones to thrive towards. You were introduced to a conceptual framework to help break down the different components of a successful Go-To-Market. You identified your best potential target market and validated that it will be the focus on your search for Go-to-Market fit. You profiled your ideal customer and put together version one of your Buyer’s Journey. You are now ready to complete the final step in our Getting Started section: building out an outline of the Go-To-Market model you will be testing over the next several weeks.
1.7 – ICP and Buyer’s Journey 1.0
At this point you have identified your best potential target market and validated that it will be the focus on your search for Go-to-Market fit. The process of finding a model can be seen as a black box with sales and marketing activities as inputs, and closed deals as outputs. In our previous post, you started decoding that black box by retracing your steps and identifying patterns. This will help generate three key initial components of the overall framework: your Ideal Customer Profile and alpha versions of your Buyer’s Journey and Go-To-Market Model. We will address the first two and leave the latter for the next post.
1.6 – Pick Your Best Potential Target Market
Once you reach PMF, you probably have a pretty good idea of what your ideal target market is. Unfortunately, enterprise startups can reach PMF with 20 paying customers, build a repeatable playbook and still fail to unlock growth. The problem is that the initial set of customers only provide an idea, a hypothesis of a potential target market. In order to unlock growth, that hypothesis needs to be validated through go-to-market experiments. The playbook also need to be lined up on a problem that is both a sizeable opportunity and has hair-on-fire urgency for customers.
1.5 – Minimum Viable Metrics – Part 2
In the last post, we introduced the concept of a Sales Learning Curve. We also defined Product/Market fit for enterprise SaaS startups through the lens of a set of metrics and criteria called the Minimum Viable Metrics for PMF. Now that we are aligned on a starting point for the Hypergrowth Sales Playbook, let’s get an idea of what we are thriving towards. In this post we will take a look at what Go-To-Market fit looks like, how to get there and introduce a second set of metrics and criteria: Minimum Viable Metrics for GTM fit.
1.4 – Minimum Viable Metrics – Part 1
Before getting started with the steps outlined in the Hypergrowth Sales Playbook, it is important to answer one key preliminary question: when is an enterprise startup ready to think about scaling? In order to tackle that question in this post, we will introduce a big picture framework – the sales learning curve – then align on a starting point by answering a second question: what does Product/Market fit mean for an enterprise startup? This is where Minimum Viable Metrics will come into play.
1.3 – The Hypergrowth Sales Playbook
Now that I have introduced the Hypergrowth Sales Playbook and why, in my humble opinion, more Sales and Go-to-Market focused playbooks should exist out there (and be shared!) I wanted to highlight the logic and approach behind it.
1.2 – Introduction
Let’s start with what should be obvious: what separates SaaS startups that succeed at scaling from those that don’t is not necessarily the fact that they have a better product, but rather that they consistently figure out ways to unlock growth before running out of cash.
1.1 – Why do anything? Why me? Why now?
There are more SaaS companies valued at $1B than ever before – 99 as of this writing, according to Bessemer Venture Partners’ latest State of the Cloud report. The proliferation of Startup Accelerators, the availability of Seed funding, methodologies like Lean Startup and new technologies provided by the cloud ecosystem itself are making it easier and cheaper to get started than any other time in history.