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Behavioral Marketing

CommunityPopular
cbrock84
behavioral-marketing

Applies decision science and cognitive bias research to marketing and product decisions — how people actually choose under uncertainty, and how framing, defaults, sequencing, and social context change behavior. Use this to diagnose why a well-argued offer is not converting, to structure choices and pricing presentation, to design an experience around how attention and memory work, or to pressure-test whether a persuasion tactic is legitimate or manipulative.

Overview

Publishercbrock84
Repositoryheadcount
Skill namebehavioral-marketing
Stars
2K
Forks
316
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by cbrock84 on GitHub. Read the source before you install it.

Installation

Install the Behavioral Marketing AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/cbrock84/headcount/tree/main/plugins/marketing/skills/behavioral-marketing
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/cbrock84/headcount.git /tmp/headcount
mkdir -p .claude/skills
cp -r /tmp/headcount/plugins/marketing/skills/behavioral-marketing .claude/skills/behavioral-marketing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Behavioral Marketing in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Behavioral Marketing on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Behavioral Marketing is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Behavioral marketing

People do not evaluate offers on merit and then act. They decide fast, under uncertainty, using whatever the context makes salient — and then explain the decision afterward. Marketing that assumes otherwise loses to marketing that does not.

The effects that most often explain a stuck conversion

Reference dependence. Nothing is judged absolutely. A price is high or low relative to whatever was shown first, so what you present first sets the frame for everything after it.

Loss aversion. Losing something registers considerably more than gaining the equivalent. This is why switching costs are underestimated by sellers and overestimated by buyers, and why "what you are currently losing" often outperforms "what you could gain."

Choice overload. More options reduce the likelihood of any choice being made. Beyond a small number, each additional option raises the cost of deciding faster than it raises the chance of a good match. If a pricing page has seven tiers, the problem is not the copy.

Status quo and default effects. Doing nothing is the most-chosen option in almost every context, and whatever is pre-selected is disproportionately taken. Whether a default exists is often a bigger lever than anything in the argument around it.

Social proof. Evidence of what similar others did carries more weight than claims about quality — and specificity matters. "Used by four hundred logistics teams" works where "trusted by thousands" does not, because the first is checkable and names a peer group.

Zero-price effect. Free is not a very low price; it is a different category that suspends cost-benefit reasoning. This makes free tiers powerful acquisition tools and dangerous pricing anchors.

Present bias. Immediate costs and benefits are weighted far above future ones. An annual plan competes against a monthly one on the immediacy of the charge, not on total value.

Goal-gradient and endowed progress. Effort increases as a visible goal approaches, and progress already granted counts. Progress indicators work; starting someone partway along works better.

Peak-end. An experience is remembered by its most intense moment and its ending, not its average. The last screen of onboarding and the cancellation flow carry disproportionate memory weight.

Using this without becoming manipulative

Every effect above can be used to help someone decide well or to extract a decision they would regret. The distinction is not subtle, and it is testable:

  • Would the customer be comfortable if you explained the technique to them? Anchoring against a real higher-value plan passes. A fake original price does not.
  • Does it help them decide, or prevent them deciding? Reducing choice overload helps. A countdown that resets on refresh does not.
  • Does it survive a satisfied customer? Tactics that work only until the person notices produce churn, chargebacks, and in several jurisdictions regulatory exposure — dark patterns around cancellation and consent are now specifically enforced.

Scarcity and urgency deserve particular caution: legitimate when real and stated precisely, corrosive when manufactured. A false constraint is the single fastest way to lose a customer who was going to buy anyway.

Reasoning about it

  • Look for the constraint, not the list. One thing usually blocks the decision. Applying six techniques to a page with an unclear value proposition addresses none of them.
  • Second-order effects. A tactic that raises conversion and raises refunds has not worked. Judge against downstream behavior, not the immediate step.
  • Effects are contextual and interact. Published effect sizes are directional, not predictions. Treat every application as a hypothesis to test rather than a known quantity — this is where behavioral marketing most often overreaches.

Sources

references/sources.md in this skill lists the outside authorities that settle the questions here — what each one is authoritative for, and what you may do with it. Check them before answering on anything they cover, and cite what you used. Most are free to read and not free to reproduce; the use note on each is binding.

Never

  • Deploy an effect without being able to name the mechanism. A tactic borrowed without its mechanism fails silently in a context that differs in ways nobody checked.
  • Manufacture scarcity, urgency, or social proof that is not true. It works once and costs the relationship permanently.
  • Treat a published effect size as a guaranteed lift. Those numbers come from populations and contexts that are not yours.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Behavioral Marketing AI skill do?

Applies decision science and cognitive bias research to marketing and product decisions — how people actually choose under uncertainty, and how framing, defaults, sequencing, and social context change behavior. Use this to diagnose why a well-argued offer is not converting, to structure choices and pricing presentation, to design an experience around how attention and memory work, or to pressure-test whether a persuasion tactic is legitimate or manipulative.

Why use Behavioral Marketing on TypingMind?

Because you install it once and use it with any model. Behavioral Marketing is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Behavioral Marketing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cbrock84/headcount/tree/main/plugins/marketing/skills/behavioral-marketing. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Behavioral Marketing?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Behavioral Marketing?

As many as you like. As long as a model supports skills, you can use Behavioral Marketing with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Behavioral Marketing AI skill free?

Yes. It is published on GitHub by cbrock84 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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