MyAIDevelopment · Product · Operations notes

Go-to-Market · Launch · PLG and SLG

Go-to-market (GTM) is not a "launch event". It is the design of how a product meets customers, gets bought, and expands.

Components of a GTM Plan

Component Question
Target Which segment / ICP do we pursue first
Value Proposition What do we promise that segment
Pricing & Packaging Free/paid boundary, pricing unit, plan structure
Motion Product-led, sales-led, or a mix
Channels Where are we discovered and where do people buy
Enablement What do sales, support, and partners need to know
Metrics How do we judge success

Comparing GTM Motions

Aspect Product-Led (PLG) Sales-Led (SLG)
First value experience Self-serve use after signup Demo, PoC, sales conversation
Purchase decision The user pays directly Organizational procurement
Fits when Value shows quickly, low price, self-onboarding possible High price, complex adoption, many stakeholders
Key metrics Activation, free-to-paid conversion, expansion Pipeline, win rate, sales cycle
Risk Free users grow but revenue does not High sales cost leads to high CAC

Atlassian and OpenView describe PLG as a go-to-market strategy in which the product itself is the primary driver of acquisition, activation, retention, and expansion.

Hybrid: Product-Led Sales

In practice, the two are often combined: product usage data identifies accounts likely to buy, and sales steps in.

MQL (Marketing Qualified Lead)
= Judged by response to marketing activity (e.g., downloading a resource)

PQL (Product Qualified Lead)
= Judged by behavior in the product (e.g., inviting 5 teammates, repeated use of a core feature)

Do not set PQL criteria by guesswork; derive them from the behavior patterns of accounts that actually converted to paid.

flowchart LR
    S[Signup] --> A[Activation]
    A --> H[Habit]
    H --> Q{PQL?}
    Q -->|Yes| R[Sales Assist]
    Q -->|No| N[Nurture]
    R --> P[Paid]
    N --> H
    P --> X[Expansion]

B2B Buyers Research Alone, and Use AI Too

According to a Gartner survey published on 2026-05-20 (645 B2B buyers, August–September 2025), buyers used an average of seven information sources in a recent purchase, and 45% said they used generative AI. In the same survey, 69% said they prefer to validate AI-generated insights with sales reps.

The share preferring a rep-free buying experience was 61% in the survey published on 2025-06-25 and 67% in the one published on 2026-03-09 (see document 01).

Implications:

Pricing · Packaging

Pricing is not a single number; it is a decision about what you charge for (the value metric) and where free ends (packaging).

Value metric Advantage Disadvantage Applied to the incident-monitoring tool
Seat (number of users) Easy for buyers to understand and forecast Makes people hesitate to invite teammates, slowing spread Small amounts for teams of 1–5; a poor fit if team invites are the core behavior
Usage (log volume, events, alerts) Price moves with value; customers can start small Bills are hard to predict Logs spike during incidents, so bills spike too and cause anxiety; a cap is needed
Tier (bundles of features and limits) Simple, with a clear upgrade path A badly placed boundary leaks value or causes frustration Split tiers by log retention, number of connected services, and team size

Place the free-plan boundary after activation and before PQL.

Signup → Activation (first value experience)   ← free, and generously so, up to here
       → PQL signals (team invites, repeated use, nearing limits)  ← paid boundary here
       → Paid

Bad example:

The free plan blocks log integrations and only sends alerts. Signups leave without ever seeing the root-cause screen.

Good example:

The free plan allows one connected service and 7-day retention, enough to experience the first root-cause investigation. The paid boundary sits where teams need more than 3 members, 30-day retention, or several connected services. (The numbers are assumptions, to be adjusted using the behavior of accounts that actually converted.)

Treat a price change as a Tier 1 launch (table below). It needs existing-customer notices, sales and support scripts, and pricing pages that match the docs. If it raises a subscription price or converts free to paid, also check the E-Commerce Act's prior consent and notice requirements. For subscriptions billed through the App Store or Google Play in Korea, the platform collects this consent itself and auto-cancels without it, so build that into conversion forecasts (document 09).

Tiering Launches

If every launch is the same size, the team burns out and customers become numb.

Tier Example criteria Example activities
Tier 1 New product, new market, pricing change Press release, campaign, sales training, event
Tier 2 Major feature, major integration Blog, email, in-app announcement, sales briefing
Tier 3 Improvements, small features Changelog, in-app tooltip

Launch Checklist

A default schedule for Tier 1 and Tier 2 launches:

T-4 weeks  Finalize positioning and message, finalize measurement plan (baseline, target)
T-2 weeks  Brief sales and support; prepare docs, FAQ, and support scripts
T-0        Launch, send through each channel
T+14 days  Review results → expand / adjust / roll back

Bad Example / Good Example

Bad example:

The feature is done, so we will announce it on every channel next Tuesday.

Good example:

We promise the small-team admin segment "invitations done in 3 minutes". As a Tier 2 launch we use an in-app announcement and email; the goal is to improve the 7-day teammate invitation rate of new workspaces. After two weeks we review results and decide whether to expand.

Common Mistakes

References