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The expected product is the aspect of whole-product thinking that captures a Customer’s price sensitivity. Whole-product thinking is a framework that helps to define and deliver a complete solution that meets the Customer’s needs and expectations. Whole-product thinking consists of four levels: generic product, expected product, augmented product, and potential product. The expected product is the level that includes the basic features and benefits that the Customer expects from the product, and that determines the Customer’s willingness to pay for the product. The expected product reflects the Customer’s price sensitivity, which is the degree to which the Customer’s behavior is influenced by the price of the product.

References:

Customer Centricity - Scaled Agile Framework

Analysis of the Effects of Perceived Value, Price Sensitivity, Word-of …

Pricing Sensitivity: Meaning, Calculation & Strategy | Qualtrics

Which aspect of whole-product thinking captures a Customer’s price …

Journey maps are a design thinking tool that help visualize the steps, interactions, and emotions of a user as they go through a process or a service. Journey maps can help redesign work processes by identifying the pain points, opportunities, and gaps in the current state, and by generating ideas for improving the user experience and value proposition in the future state. Journey maps can also help communicate the user needs and expectations to the stakeholders and align them on a common vision and goal.

References:

Journey Maps - Scaled Agile Framework

Journey Mapping 101 | Nielsen Norman Group

Journey Mapping: The Ultimate Guide | Miro

Journey Mapping: How to Create One and Why It’s Important

Primary data is information collected through original research by the marketer or researcher themselves. Primary data is used to test hypotheses, which are tentative statements or assumptions about the relationship between variables or the outcome of an experiment. Testing hypotheses helps to validate or invalidate the assumptions and predictions made by the marketer or researcher, and to measure the effectiveness and impact of their product or service.

References:

Primary Data - Types, Methods and Examples: This article from Research Method defines primary data, explains its types and methods, and provides some examples of primary data collection and analysis.

[Hypothesis Testing]: This article from the Scaled Agile Framework describes the concept and process of hypothesis testing, and how it helps to evaluate the value proposition and assumptions of a product or service using experiments and feedback.

The projected value of a market segment is an estimate of the potential revenue and profit that can be generated from selling products or services to that segment. To increase confidence in this estimate, it is important to keep the calculations transparent and continually updated as more accurate information becomes available. This involves documenting the assumptions, data sources, methods, and results of the calculations, and validating them with stakeholders and experts. It also involves monitoring the changes in the market conditions, customer behavior, and competitor actions, and adjusting the calculations accordingly. By keeping the calculations transparent and updated, the organization can ensure that the projected value of a market segment reflects the current and future reality, and avoid overestimating or underestimating the market opportunity.

References:

Market Segmentation: Definition, Example, Types, Benefits: This article from Investopedia explains the concept and purpose of market segmentation, and describes the four primary types of market segmentation: demographic, geographic, psychographic, and behavioral.

Market Segmentation: Definition, Types, Benefits, & Best Practices: This article from Qualtrics XM provides an overview of market segmentation, and discusses the benefits and best practices of market segmentation for businesses. It also provides some examples and tips on how to segment markets effectively.

Data Integration Market Size, Share & Growth Report, 2030: This article from Grand View Research provides a comprehensive analysis of the global data integration market, including the market size, share, growth, trends, drivers, challenges, opportunities, and segments. It also provides a regional and competitive landscape of the data integration market.

T-Shirt sizing is a sizing standard that is used to estimate Feature effort in the analysis stage of the ART Kanban. T-Shirt sizing is a relative estimation technique that uses predefined categories, such as XS, S, M, L, XL, to assign a size to a Feature based on its complexity, uncertainty, and dependencies. T-Shirt sizing is a quick and simple way to compare and prioritize Features without getting into too much detail or precision. T-Shirt sizing also helps to calculate the Weighted Shortest Job First (WSJF) value of a Feature, which is a prioritization method that considers the cost of delay and the job size.

References:

ART and Solution Train Backlogs - Scaled Agile Framework

ART Kanban - Scaled Agile Framework

New and Updated Kanban Articles provide more effective guidance for …

Program and Solution Kanbans - Scaled Agile Framework