Marketing Approaches and Profit Maximization

Textual data lacks a predefined structure, making it difficult to organize and analyze. Imagine a jumbled pile of words instead of neat rows in a spreadsheet.

Textual data often contains errors, inconsistencies, or irrelevant information. Think of typos, misspelled words, and slang in a document.

Textual data can have repeated phrases, sentences, or ideas. Consider the same idea being expressed in different ways.

The meaning of words and phrases can change depending on the surrounding text. Consider the meaning of "cool" in different contexts.

Natural Language Processing (NLP) is a field of computer science and AI that enables computers to understand and process human language.

The process of identifying the parts of speech (nouns, verbs, adjectives, etc.) in a sentence, like tagging a noun as 'NN' or a verb as 'VB'.

A technique that breaks down a sentence into a hierarchical structure, similar to a tree diagram, showing the grammatical relationships between words.

A method that identifies and extracts the most important words or terms from a text, often used to understand the central themes of a document.

A simple way to represent text by counting the occurrences of each word in a document, ignoring word order. Think of this as a bag of words.

The process of determining the emotional tone or sentiment expressed in text, whether it's positive, negative, or neutral.

Only changing one variable at a time allows us to isolate the effect of that change on customer behavior.

Profit change is calculated by subtracting the change in total fixed cost from the product of sales increase and gross margin.

The uphill side of a firm's curve indicates that increasing investments will lead to higher profits. Conversely, the downhill side suggests that decreasing investments are necessary for maximizing profit.

Text analysis examines unstructured data, mostly text, images, audio, and videos, which cannot be organized in a structured format like rows and columns.

The 8 V's of Big Data encompass Volume, Value, Veracity, Visualization, Variety, Velocity, Viscosity, and Virality, all crucial aspects of managing and utilizing large datasets.

The process of breaking a sentence into individual words or tokens.

Reducing words to their root form, like converting 'running' to 'run'.

Removing words that don't add meaning, like 'the' or 'a'.

A list of words with associated positive, negative, or neutral sentiment scores.

A method of sentiment analysis that relies on predefined rules and a lexicon to determine sentiment.

A technique that employs machine learning algorithms to analyze text and predict sentiment.

Combines rules-based and machine learning techniques for a comprehensive and accurate sentiment analysis.

A method for resource allocation that relies on common sense, experience, and intuition. It is simple to understand and apply but often leads to inaccurate decisions.

Marketing outcomes like market share, sales, brand loyalty, customer satisfaction, and stock price can all be influenced by resource allocation decisions.

A decision-making process that starts with an initial estimate (the anchor) and then adjusts it based on new information. This helps refine decisions as more data becomes available.

A systematic approach to maximizing profits by determining the optimal level of marketing effort. It involves analyzing how sales respond to marketing spending.

A technique for understanding how different marketing activities affect customer behavior. It involves controlled experiments to isolate the impact of specific touchpoints in a customer journey.

In an experiment, a group that receives the new marketing intervention being tested. This allows comparison with a control group.

In an experiment, a group that does not receive the new marketing intervention being tested. This is used as a baseline for comparison.

The ability to measure how much each marketing touchpoint contributes to the overall success of a marketing campaign. This helps allocate resources effectively.