# Why a template library is not a growth strategy

# Why a template library is not a growth strategy

## The problem is not a shortage of tactics

Anyone who can ship a product with AI coding tools can also find a list of growth tactics in minutes: SEO, launches, communities, outreach, ads, creator partnerships. The hard part for a solo founder is deciding which tactic to try first with limited time, and tactics that are scattered across tabs and threads are hard to prioritise.

A template library does not fix this. It adds to the pile. It answers 'what exists?' but not 'what should this product do this month?'

## Where templates fall short

Templates are not useless. They are a reasonable source of ideas. As a strategy, they have three weaknesses:

1. **They are written for nobody in particular.** The same checklist is handed to a B2B developer tool and a B2C consumer app, even though their audiences, buying behaviour and channels differ.
2. **They are static.** A list written once does not know that you shipped a feature yesterday, that a competitor changed its pricing, or that one channel produced sign-ups while another produced nothing.
3. **They do not rank.** A list of 40 tactics with no order puts the prioritising back on the founder, which was the original problem.

A growth playbook worth following is a short, ordered plan built around one product, its audience and its evidence. It changes when the evidence changes. This is the idea behind Hockeysticky's positioning: a tailored playbook per product rather than a template library, updated with each release, market signal and learning. Hockeysticky is currently a waitlist product, and this post makes no claim about results. The argument is about method, and the method works with or without any tool.

## A simple method: rank by effort, fit and time to signal

Score each candidate tactic on three questions, from 1 to 5.

| Factor | Question | 5 means | 1 means |
|---|---|---|---|
| Effort | How much work and money to run it properly for a month? | Very little | A lot |
| Fit | Does your audience already show up here, and does the tactic suit your motion (B2B, B2C and so on) and your evidence? | Strong, evidenced fit | Guess or poor fit |
| Time to signal | How soon will you see a sign that it works or doesn't? | Days to a few weeks | Several months |

Note that for effort and time to signal, a higher score means better (less work, faster feedback). Then calculate:

**Priority = Fit × Effort score × Time-to-signal score**

Multiplying means a tactic that fails badly on any one factor drops down the list. A fast, cheap tactic that your audience never sees should not win.

### How to score honestly

- **Fit** is the factor that most needs evidence. Use what you have: search queries people use for the problem, places where the problem is discussed, where your first users came from, what competitors visibly invest in. If you have no evidence, score fit no higher than 2 or 3 and treat the tactic as a test.
- **Effort** should include the work of keeping the tactic going, not only setting it up.
- **Time to signal** should be defined before you start. Decide what a signal looks like, for example qualified visits or sign-ups from that tactic, so you do not judge it by feel.

### A worked example (illustrative)

The scores below are made up for a hypothetical product, to show the mechanics. The signal windows come from the editorial estimates on the Hockeysticky playbooks page (a general view for a solo founder or small team over about 90 days, not measured results): content you own, 4-12 weeks; comparison and alternatives pages, 4-10 weeks; live conversations, 1-3 weeks.

| Tactic | Effort (5 = low) | Fit | Time to signal (5 = fast) | Priority |
|---|---|---|---|---|
| Live conversations | 4 | 4 | 5 | 80 |
| Comparison and alternatives pages | 3 | 4 | 3 | 36 |
| Content you own (blog, docs) | 3 | 3 | 2 | 18 |

In this hypothetical, the fast-feedback tactic goes first. That does not make it the best tactic for every product. If your audience does not discuss the problem in public, fit drops and the order changes. A template cannot know that. A scored list can.

## Re-rank when the evidence changes

The ranking is a snapshot. Re-score when something meaningful happens:

- **A release ships.** A new feature can create a new angle, audience or comparison.
- **A market signal appears.** A competitor moves, a topic starts trending, or someone posts a frustration your product solves.
- **A tactic produces a signal, or doesn't.** Update fit scores from results, not hopes.

```mermaid
flowchart LR
  A[Collect evidence: product, audience, market] --> B[Score tactics: effort, fit, time to signal]
  B --> C[Run the top one or two]
  C --> D[Measure against the signal you defined]
  D --> E[Re-score with what you learned]
  E --> B
```

This loop is what separates a plan from a list. The plan is revised after each pass, while the list stays as it was written.

## A weekly routine for a solo founder

1. List every tactic you are considering, including ones you have already half-started.
2. Score each on effort, fit and time to signal, noting the evidence behind every fit score.
3. Pick the top one or two. Resist running more, since a solo founder's attention is the scarce resource.
4. Write down the signal you expect and the date you will check it.
5. At the next review, update the scores with what happened and what you shipped.

The point is not the arithmetic. It is that every choice has a stated reason, which makes it easy to revisit when the reason stops being true.

## What this means for tooling

A tailored growth playbook only helps if it stays current, and keeping it current is the work most founders skip once they go back to building. That is the gap Hockeysticky is designed for: build a playbook around your product, update it as you learn, and run the tactics within your guardrails. Any such system should be judged on the same test as the method above: does it show its reasons, and does it re-rank when your evidence changes?

## Next step

Hockeysticky is taking sign-ups for its waitlist, with early access and an early-bird discount offered. If you want a ranked, evidence-led playbook for your product instead of a longer list of tactics, join the waitlist at hockeysticky.com.

*Editorial note: this pillar post has no cluster posts to link to yet. Candidate cluster topics for the founder to approve: how to score audience fit from search and conversation evidence, how to define a qualified visit, and how to run a weekly growth review.*