Plain-English definitions of 62 terms from AI growth marketing, AI agents and automation, vibe coding, GTM engineering and UI/UX design. Every definition stands on its own, links to the accelerator that teaches it and, where one exists, to a deeper guide.
The metrics, models and tools behind paid acquisition and measurable growth.
Learn it in the AI Growth & Performance Marketing accelerator Back to A to ZA/B testing, or split testing, is an experiment that compares two versions of an ad, web page, email or feature by showing each to a random share of the audience and measuring which performs better against one chosen metric, such as conversion rate. Results are only reliable once enough people have taken part for the difference to be statistically significant.
Also known as: Split testing
An attribution model is the rule an analytics or ad platform uses to assign credit for a conversion to the touchpoints that came before it. Common models include last click, which credits the final interaction, first click, linear, and data-driven attribution, which uses machine learning to weigh each touchpoint. The chosen model changes which channels appear to perform best.
Also known as: Marketing attribution
Course: AI Growth & Performance MarketingGuide: What is RevOps? A 2026 guide to revenue operations
Click-through rate (CTR) is the percentage of people who click an ad, link or search result after seeing it, calculated as clicks divided by impressions, multiplied by 100. For example, 20 clicks from 1,000 impressions is a CTR of 2%. A higher CTR usually means the creative and targeting are relevant to the people seeing them.
Course: AI Growth & Performance MarketingGuide: How to become a performance marketer in India (2026 roadmap)
Conversion rate is the percentage of visitors or users who complete a desired action, such as making a purchase, submitting a form or signing up, out of everyone who had the chance to. It is calculated as conversions divided by visitors, multiplied by 100, and it is a core measure of how well a page, ad or funnel performs.
Course: AI Growth & Performance MarketingGuide: Is a digital marketing course worth it in India in 2026?
Cost per acquisition (CPA) is the average advertising cost of getting one conversion, such as a sale, lead or sign-up, calculated as ad spend divided by the number of conversions. Advertisers often set a target CPA and let the ad platform bid automatically towards it. CPA usually covers ad spend only, unlike the broader customer acquisition cost.
Also known as: Cost per action
Course: AI Growth & Performance MarketingGuide: How to become a performance marketer in India (2026 roadmap)
Cost per click (CPC) is the average amount an advertiser pays for each click on an ad, calculated as total ad spend divided by the number of clicks. It is also a bidding model, often called pay per click, in which the advertiser is charged only when someone clicks. CPC rises and falls with competition, targeting and ad relevance.
Also known as: Pay per click, PPC
Course: AI Growth & Performance MarketingGuide: How to become a performance marketer in India (2026 roadmap)
Cost per mille (CPM) is the cost of 1,000 ad impressions, where mille is Latin for thousand. It is calculated as ad spend divided by impressions, multiplied by 1,000. CPM is the standard way to compare the price of reaching an audience across platforms, and it is the usual pricing model for awareness campaigns on social, video and display networks.
Also known as: Cost per thousand impressions
Course: AI Growth & Performance MarketingGuide: Meta Ads vs Google Ads: which should you learn first in 2026?
Customer acquisition cost (CAC) is the total cost of winning one new customer, calculated as all sales and marketing spend in a period, including ads, tools and salaries, divided by the number of new customers gained in that period. Businesses compare CAC with customer lifetime value to judge whether their growth is profitable and sustainable.
Course: AI Growth & Performance MarketingGuide: What is RevOps? A 2026 guide to revenue operations
Customer lifetime value (LTV or CLV) is an estimate of the total revenue or gross profit a business can expect from one customer over the whole relationship. A simple version multiplies average order value by purchase frequency and by customer lifespan. Comparing LTV with customer acquisition cost shows how much a business can afford to spend to win a customer.
Also known as: CLV, CLTV
Google Analytics 4 (GA4) is the current version of Google's web and app analytics platform, which replaced Universal Analytics in 2023. It uses an event-based data model, in which every interaction such as a page view, click or purchase is recorded as an event, and it can measure a website and an app together in one property.
Course: AI Growth & Performance MarketingGuide: How to become a performance marketer in India (2026 roadmap)
Growth marketing is a data-driven approach to growing a business across the whole customer lifecycle, from acquisition and activation to retention, referral and revenue. Growth marketers run quick experiments on channels, messaging, onboarding and pricing, measure the results and scale what works. It extends performance marketing beyond paid ads to every stage of the funnel.
Course: AI Growth & Performance MarketingGuide: 7 AI skills worth learning in 2026 (and how to get hired)
A marketing funnel is a model of the stages people move through on the way to becoming customers, usually awareness, consideration, conversion and retention. Fewer people reach each stage, which gives the funnel its shape. Marketers use it to match ads, content and offers to each stage and to find the point where potential customers drop off.
Also known as: Sales funnel
Course: AI Growth & Performance MarketingGuide: Meta Ads vs Google Ads: which should you learn first in 2026?
Performance marketing is a form of online advertising in which spend is planned, measured and optimised against trackable outcomes such as clicks, leads, sales or app installs, rather than reach alone. Campaigns typically run on platforms like Meta Ads and Google Ads, and budgets move towards the ads, audiences and channels that deliver results at an acceptable cost.
Course: AI Growth & Performance MarketingGuide: How to become a performance marketer in India (2026 roadmap)
Retargeting, also called remarketing, is the practice of showing ads to people who have already interacted with a brand, for example by visiting its website, using its app, engaging with its content or joining its customer list. Because these people already know the brand, retargeting campaigns often convert at a higher rate than ads shown to new audiences.
Also known as: Remarketing
Course: AI Growth & Performance MarketingGuide: Meta Ads vs Google Ads: which should you learn first in 2026?
Return on ad spend (ROAS) measures the revenue earned for every unit of currency spent on advertising, calculated as attributed revenue divided by ad spend. A ROAS of 4 means ₹4 of revenue for every ₹1 spent. Because ROAS ignores product costs and margins, a campaign can show a healthy ROAS and still lose money.
Course: AI Growth & Performance MarketingGuide: How to become a performance marketer in India (2026 roadmap)
UTM parameters are short tags added to the end of a URL, such as utm_source, utm_medium and utm_campaign, that tell analytics tools like GA4 where a visitor came from. UTM stands for Urchin Tracking Module, named after the analytics company Google acquired in 2005. Consistent tagging makes it possible to compare campaigns, channels and creatives accurately.
Also known as: UTM tags, UTM codes
How language models, agents and workflow tools combine to automate real business work.
Learn it in the AI Agents & Automation Engineering accelerator Back to A to ZAn AI agent is a software system that uses a large language model to pursue a goal with some autonomy: it plans steps, calls tools such as APIs, databases or a web browser, observes the results and decides what to do next. Unlike a simple chatbot that only replies, an agent can take actions, usually within set limits and with human oversight.
Also known as: Autonomous agent, Agentic AI
Course: AI Agents & Automation EngineeringGuide: 15 AI agent use cases for business in 2026
AI automation is the use of artificial intelligence, usually large language models, inside automated workflows to handle tasks that need judgement as well as rules, such as reading emails, classifying leads, summarising documents or drafting replies. It combines traditional workflow tools, which move data between apps when a trigger fires, with AI steps that interpret unstructured text, images or speech.
Course: AI Agents & Automation EngineeringGuide: What is AI automation? A 2026 guide to AI agents and how to build them
An AI hallucination is output from an AI model that sounds confident and plausible but is factually wrong, unsupported or invented, such as a fake statistic, citation or product feature. It happens because language models generate likely-sounding text rather than looking up verified facts. Grounding answers in trusted sources, using retrieval and keeping a human reviewer all reduce the risk.
Function calling, also called tool use, is a capability of large language models that lets them request an action from external code. The developer describes the available functions, such as checking an order or searching a database, and the model replies with a structured request naming the function and its arguments. The application runs it and returns the result to the model.
Also known as: Tool use, Tool calling
Course: AI Agents & Automation EngineeringGuide: What is AI automation? A 2026 guide to AI agents and how to build them
A large language model (LLM) is an AI model trained on very large amounts of text to predict the next token in a sequence, which lets it understand and generate human-like language. LLMs such as GPT, Claude and Gemini power chatbots, writing tools, coding assistants and AI agents. They can produce fluent but incorrect answers, so their output needs checking.
Course: AI Agents & Automation EngineeringGuide: The best AI tools to learn in 2026 (for marketing, design and work)
Make, formerly called Integromat, is a no-code automation platform on which users build workflows, called scenarios, by connecting apps and services on a visual canvas. Each scenario starts with a trigger and passes data through modules that filter, transform and route it. Make is cloud-hosted, priced by usage, and includes modules for calling AI models.
Also known as: Make.com, Integromat
Course: AI Agents & Automation EngineeringGuide: Best AI automation tools in 2026 (n8n, Make, and AI agents)
The Model Context Protocol (MCP) is an open standard, introduced by Anthropic in November 2024, for connecting AI applications to external tools and data sources. An MCP server exposes capabilities such as files, databases or business apps in a common format, so any compatible AI client can use them without a custom integration for every pairing of app and tool.
Course: AI Agents & Automation EngineeringGuide: Best AI automation tools in 2026 (n8n, Make, and AI agents)
n8n is a workflow automation platform for connecting apps, APIs and AI models in a visual, node-based editor. It is distributed under a fair-code licence, so it can be self-hosted as well as used as a paid cloud service, and it lets builders add custom JavaScript or Python inside workflows. It is widely used to build AI agents and business automations.
Course: AI Agents & Automation EngineeringGuide: Best AI automation tools in 2026 (n8n, Make, and AI agents)
Prompt engineering is the practice of writing and refining the instructions given to an AI model so that it produces accurate, useful and consistent output. Good prompts state the task, give context and examples, define the format of the answer and set constraints. In production systems, prompts are tested and versioned like code, because small wording changes can alter results.
Also known as: Prompting
Course: AI Agents & Automation EngineeringGuide: 7 AI skills worth learning in 2026 (and how to get hired)
Retrieval-augmented generation (RAG) is a technique that improves an AI model's answers by first retrieving relevant information from an external source, such as company documents or a knowledge base, and adding it to the prompt. The model then answers using that retrieved context. RAG keeps responses current and grounded in specific data without retraining the model, and can reduce invented answers.
Course: AI Agents & Automation EngineeringGuide: What is AI automation? A 2026 guide to AI agents and how to build them
A vector database stores data as embeddings, which are lists of numbers that represent the meaning of text, images or other content, and finds items by similarity rather than exact keyword match. This makes it a common part of retrieval-augmented generation, where it fetches the passages most relevant to a question. Examples include Pinecone, Weaviate, Qdrant and the pgvector extension for PostgreSQL.
Also known as: Embeddings, Vector store
Course: AI Agents & Automation EngineeringGuide: Best AI automation tools in 2026 (n8n, Make, and AI agents)
A webhook is an automated message that one application sends to another over HTTP when a specific event happens, such as a form submission, a payment or a new sign-up. Instead of repeatedly asking for updates, the receiving system has the data pushed to a URL it provides. Webhooks are a common trigger for workflows in tools such as n8n and Make.
Course: AI Agents & Automation EngineeringGuide: What is AI automation? A 2026 guide to AI agents and how to build them
The building blocks of shipping working software by directing AI.
Learn it in the Vibe Coding & AI Development accelerator Back to A to ZAn AI coding assistant is a tool that uses large language models to help write, explain, test and fix code, either inside a code editor or through a chat or command-line interface. Examples include GitHub Copilot, Cursor and Claude Code. They range from autocomplete suggestions to agents that can edit many files, run commands and propose complete features.
Also known as: AI coding tool, AI pair programmer
Course: Vibe Coding & AI DevelopmentGuide: Best AI coding tools in 2026 (build apps without a CS degree)
An API, or application programming interface, is a defined set of rules that lets one piece of software request data or actions from another. For example, an app can use a payment provider's API to charge a card, or an AI model's API to generate text. Most web APIs exchange data as JSON over HTTP and require a key for access.
Course: Vibe Coding & AI DevelopmentGuide: How to build a SaaS with AI in 2026 (no CS degree)
Authentication is the process of verifying who a user is before giving them access to an app, usually with a password, a one-time code, a magic link or a sign-in provider such as Google. It is different from authorisation, which decides what a verified user is allowed to do. Many apps use a managed authentication service rather than building their own.
Also known as: Sign-in
Course: Vibe Coding & AI DevelopmentGuide: How to build a SaaS with AI in 2026 (no CS degree)
The backend is the server side of an application, the part users do not see, which stores data, applies business rules, handles sign-in and payments, and serves information to the frontend through APIs. It runs on servers or cloud platforms and is written in languages such as JavaScript, Python or Go, or provided by backend-as-a-service platforms such as Supabase or Firebase.
Also known as: Back end, Server side
Course: Vibe Coding & AI DevelopmentGuide: How to build a SaaS with AI in 2026 (no CS degree)
A database is an organised store of data that an application can save, search, update and delete reliably. Relational databases such as PostgreSQL and MySQL keep data in tables with defined relationships and are queried with SQL, while document databases such as MongoDB store flexible, JSON-like records. Almost every app with user accounts or saved content relies on one.
Course: Vibe Coding & AI DevelopmentGuide: How to build a SaaS with AI in 2026 (no CS degree)
Deployment is the process of taking code from a developer's computer and running it live where real users can reach it, usually on a hosting or cloud platform such as Vercel, Netlify or a traditional web host. It typically involves building the project, setting environment variables and secrets, connecting a domain and enabling HTTPS, and it is often automated on every code push.
Also known as: Hosting
Course: Vibe Coding & AI DevelopmentGuide: How to build a SaaS with AI in 2026 (no CS degree)
The frontend is the part of a website or app that users see and interact with in their browser or on their device, including layout, text, buttons, forms and animations. It is built with HTML for structure, CSS for styling and JavaScript for behaviour, often using frameworks such as React, Vue or Svelte, and it talks to the backend to load and save data.
Also known as: Front end, Client side
Course: Vibe Coding & AI DevelopmentGuide: How to build a SaaS with AI in 2026 (no CS degree)
A minimum viable product (MVP) is the simplest version of a product that delivers its core value well enough for real users to try it, so a team can test demand and learn before investing more. The idea was popularised by Eric Ries in his 2011 book The Lean Startup. AI coding tools have made MVPs faster and cheaper to build.
Course: Vibe Coding & AI DevelopmentGuide: What is vibe coding? Build apps with AI, no coding background (2026)
Software as a service (SaaS) is software delivered over the internet and paid for by subscription, rather than installed and owned outright. The provider hosts, maintains and updates it, and customers use it through a browser or app. Familiar examples include Google Workspace, Slack, Notion and Canva. SaaS businesses typically track recurring revenue, churn and customer lifetime value.
Course: Vibe Coding & AI DevelopmentGuide: How to build a SaaS with AI in 2026 (no CS degree)
Vibe coding is a way of building software by describing what you want in plain language and letting AI tools write most of the code, while you test, steer and refine the result. The term was coined by AI researcher Andrej Karpathy in February 2025. It lowers the barrier to building apps, but shipping reliable products still requires understanding, testing and debugging.
Course: Vibe Coding & AI DevelopmentGuide: What is vibe coding? Build apps with AI, no coding background (2026)
The systems, data and processes that turn leads into predictable revenue.
Learn it in the GTM Engineering accelerator Back to A to ZA CRM, short for customer relationship management, is software that stores every contact, company, deal and interaction a business has with its leads and customers in one place. Teams use it to manage the sales pipeline, track conversations, automate follow-ups and report on revenue. Widely used CRMs include HubSpot, Salesforce, Zoho CRM and Pipedrive.
Course: GTM EngineeringGuide: What is RevOps? A 2026 guide to revenue operations
Data enrichment is the process of adding missing or more useful information to existing records, such as a lead's job title, company size, industry, funding stage or verified email address, by pulling it from third-party data providers. Enriched CRM data improves lead scoring, routing and personalised outreach. Tools such as Clay, Apollo and ZoomInfo are commonly used for enrichment.
Also known as: Lead enrichment
Course: GTM EngineeringGuide: What is GTM engineering (RevOps) and why does it pay so well?
A go-to-market (GTM) strategy is the plan a company uses to bring a product to market and win customers. It defines the target customer, the problem being solved, pricing, positioning and messaging, the channels used to reach buyers, and how sales, marketing and customer success work together. Companies create one for a new product, market or customer segment.
Course: GTM EngineeringGuide: What is GTM engineering (RevOps) and why does it pay so well?
GTM engineering is the practice of building the technical systems behind a company's go-to-market motion, combining sales and marketing knowledge with automation, data and code. GTM engineers connect the CRM with enrichment, outreach and AI tools, automate lead research, routing and outbound workflows, and keep revenue data clean so teams can reach the right buyers at scale.
Also known as: Go-to-market engineering
Course: GTM EngineeringGuide: What is GTM engineering (RevOps) and why does it pay so well?
An ideal customer profile (ICP) describes the type of company that gets the most value from a product and is most valuable to the seller, using traits such as industry, size, location, revenue, technology used and common pain points. In B2B sales, the ICP guides who to target, which leads to prioritise and how to tailor messaging. It differs from a buyer persona, which describes individual people.
Course: GTM EngineeringGuide: What is GTM engineering (RevOps) and why does it pay so well?
Lead routing is the automated process of assigning each new lead to the right salesperson or team, using rules such as territory, company size, industry, product interest or rep availability. Fast, accurate routing matters because leads that wait unassigned tend to go cold before anyone contacts them. It is usually set up in the CRM or in a dedicated routing tool.
Also known as: Lead assignment
Course: GTM EngineeringGuide: What is GTM engineering (RevOps) and why does it pay so well?
Lead scoring is a method of ranking leads by how likely they are to buy, so sales teams can focus on the best opportunities first. Points are given for fit, such as job title, company size and industry, and for engagement, such as visiting the pricing page or opening emails. Scores can follow set rules or come from machine learning models.
Course: GTM EngineeringGuide: What is RevOps? A 2026 guide to revenue operations
A marketing qualified lead (MQL) is a lead that marketing judges more likely than others to become a customer, based on fit and engagement, such as downloading a guide, attending a webinar or repeatedly visiting key pages. MQLs are nurtured further or passed to sales for review. The criteria are agreed between marketing and sales, often using lead scoring.
Course: GTM EngineeringGuide: What is RevOps? A 2026 guide to revenue operations
Outbound sales is an approach in which the seller starts the conversation, reaching out to potential customers who have not yet shown interest through cold email, calls or LinkedIn messages. Effective outbound depends on a clear ideal customer profile, accurate contact data, relevant personalised messaging and good email deliverability. It contrasts with inbound, where prospects come to the company first.
Also known as: Outbound prospecting
Course: GTM EngineeringGuide: What is GTM engineering (RevOps) and why does it pay so well?
Revenue operations (RevOps) is the function that aligns a company's marketing, sales and customer success teams around shared revenue goals, data, processes and tools. RevOps teams typically own the CRM and the go-to-market tech stack, define funnel stages and handoffs, maintain data quality and reporting, and remove friction between teams so revenue becomes more predictable.
Course: GTM EngineeringGuide: What is RevOps? A 2026 guide to revenue operations
A sales pipeline is a visual view of every open deal and the stage it has reached, from first contact through qualification, demo or proposal and negotiation to closed won or closed lost. Managed in a CRM, it shows how much revenue is likely to close and when, and it highlights where deals stall so teams can forecast and act.
Course: GTM EngineeringGuide: What is RevOps? A 2026 guide to revenue operations
A sales qualified lead (SQL) is a lead that the sales team has reviewed and accepted as a real opportunity worth pursuing directly, usually because it fits the ideal customer profile and shows clear intent, budget or a timeline to buy. It follows the marketing qualified lead stage. Not to be confused with SQL, the database query language.
Also known as: SQL lead
Course: GTM EngineeringGuide: What is RevOps? A 2026 guide to revenue operations
Designing products and websites that people can use, trust and act on.
Learn it in the Framer UI/UX & Experience Design accelerator Back to A to ZConversion rate optimisation (CRO) is the systematic process of increasing the share of visitors who take a desired action on a website or app. It combines analytics, user research, heatmaps and session recordings to find friction, then tests changes to copy, layout, forms and page speed, usually through A/B tests. CRO gets more value from existing traffic without raising ad spend.
Also known as: Conversion rate optimization
A design system is a shared library of reusable components, visual styles and guidelines, such as colours, typography, spacing, buttons and forms, together with the rules for using them. It keeps a product consistent across screens and teams and speeds up both design and development. Well-known public examples include Google's Material Design and IBM's Carbon Design System.
Course: Framer UI/UX & Experience DesignGuide: Figma vs Framer: which should you learn in 2026?
Figma is a collaborative, browser-based design tool used to create user interfaces, wireframes, prototypes and design systems, with several people able to edit the same file at once. It includes components, variables and auto layout for building consistent screens, and Dev Mode for handing designs over to developers. It is one of the most widely used tools in UI/UX design.
Course: Framer UI/UX & Experience DesignGuide: Figma vs Framer: which should you learn in 2026?
Framer is a website builder and design tool for creating responsive, production-ready websites on a visual canvas and publishing them directly, with hosting, a content management system, animations and SEO settings built in. Designers can lay out pages much as they would in Figma, add interactions without writing code, and extend sites with React components when needed.
Course: Framer UI/UX & Experience DesignGuide: Figma vs Framer: which should you learn in 2026?
A landing page is a standalone web page built for one specific goal, such as collecting leads, selling a product or getting sign-ups, usually as the destination for an ad, email or campaign. Effective landing pages have a clear headline, a single call to action, supporting proof such as testimonials and few distractions, and they are often improved through A/B testing.
Course: Framer UI/UX & Experience DesignGuide: How to become a performance marketer in India (2026 roadmap)
A prototype is an interactive model of a product or feature that simulates how it will work, so designers can test ideas with users and stakeholders before anything is built. Low-fidelity prototypes link rough screens together, while high-fidelity prototypes look and behave close to the finished product. Tools such as Figma and Framer let people click through prototypes in a browser.
Also known as: Prototyping
Course: Framer UI/UX & Experience DesignGuide: How to build a UI/UX portfolio with no experience
Responsive design is an approach to building websites so the layout adapts to the screen it is viewed on, from a small phone to a wide desktop monitor, using flexible grids, fluid images and CSS media queries. The term was coined by web designer Ethan Marcotte in 2010. Many teams design the phone layout first, an approach called mobile-first design.
Also known as: Responsive web design, Mobile-first design
Course: Framer UI/UX & Experience DesignGuide: Figma vs Framer: which should you learn in 2026?
UI design, or user interface design, is the craft of designing the visual and interactive layer of a digital product: layout, typography, colour, buttons, icons, forms and the states they move through. Good UI design is consistent, readable and accessible, and makes it obvious what a user can do on each screen. It is closely linked to, but narrower than, UX design.
Also known as: User interface design
Course: Framer UI/UX & Experience DesignGuide: How to become a UI/UX designer in India (2026 guide)
Usability testing is a research method in which real users try to complete typical tasks with a product or prototype while a researcher observes where they hesitate, make mistakes or get stuck. It can be moderated or unmoderated, in person or remote. Even a small number of sessions usually reveals the most serious problems, which designers then fix before launch.
Also known as: User testing
Course: Framer UI/UX & Experience DesignGuide: How to build a UI/UX portfolio with no experience
UX design, or user experience design, is the process of shaping how a product works for the people who use it, so that it is useful, easy and satisfying. It covers user research, information architecture, user flows, wireframes, prototypes and usability testing. UX focuses on whether people can achieve their goals, while UI design focuses on how each screen looks and behaves.
Also known as: User experience design
Course: Framer UI/UX & Experience DesignGuide: How to become a UI/UX designer in India (2026 guide)
Web accessibility is the practice of designing and building websites and apps that people with disabilities can use, including people who rely on screen readers, keyboard navigation, captions or strong colour contrast. The Web Content Accessibility Guidelines (WCAG), published by the W3C, are the main international standard. Accessible design often makes products easier for everyone to use.
Also known as: a11y, WCAG
Course: Framer UI/UX & Experience DesignGuide: How to become a UI/UX designer in India (2026 guide)
A wireframe is a simple, low-detail layout of a screen or page that shows structure, content placement and hierarchy without final colours, images or styling. Designers use wireframes early in a project to agree on what goes where and how screens connect before investing time in visual design. They range from quick paper sketches to grey-box digital mockups.
Also known as: Wireframing
Course: Framer UI/UX & Experience DesignGuide: How to become a UI/UX designer in India (2026 guide)
No terms match . Try a shorter word or an abbreviation such as ROAS, RAG or UX.
This glossary is maintained by Touch The Skies Academy, a talent accelerator based in London, UK that serves learners across India. Each definition describes widely accepted industry usage in plain English, without statistics or claims that go out of date quickly. Last updated .
You are welcome to quote any definition. Every term has its own address, for example touchtheskies.com/glossary.html#vibe-coding, so a citation can point straight at it.
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