Marketing Analysis Part C- 1 page

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MarketingDataAnalysis.docx

Running Head: MARKETING DATA ANALYSIS 1

MARKETING DATA ANALYSIS 2

Marketing Data Analysis

Name

Institution

Date

Internal Data

Source

What it measures

Data

Potential Usage

Sales data

Monthly sales for each product

Monthly average sales for each product. Data can be segmented by business and consumer markets.

Can be used for analyzing projecting trends and measuring effectiveness of a promotional strategy

Profit and loss data

Profit and loss for all products

Profit and losses made by the organization for each month. This can be analyzed for each product.

To identify products with the highest profit margins. To establish whether the organization is operating at a profit or loss (Eevi, 2020).

Cash flow

Monthly cashflow for all products

Monthly cash inflow and outflow for each product.

To establish the amount of cash that comes in and goes out with regard to each product

Cost accounting information

Cost of production, distribution, and marketing

Monthly production, distribution, and marketing costs

To establish the total cost of producing, distributing, and marketing a single unit of product.

To establish whether the organization is spending more on products than how much the products are returning.

To establish areas of improvement for efficiency and internal cost controls

Secondary Data

Source

What it measures

Data

Potential usage

Retail store analytics

The dollar value of sales

Major players total sales

Seasonal patterns market share analysis

Statistics provided by the government

Economic trends, pricing, trade activity, and regulation

Inflation rate

Provide insight in relation to the state of the economy pricing regulation. This can be important in ensuring compliance with revenant marketing regulations.

Industry associations

Industry trends and participating companies

A list of participating companies and quarterly industry trends

A good place to start when learning about a growing industry or when seeking information that would be available from an insider in the industry is to look to industry associations. Potential usage includes establishing where the industry is heading. Identifying competitors and any other relevant news affecting the industry.

International agencies

The information be used to measure and analyzes foreign market prospects for the organization

The data can involve products imported or exported by specific targeted foreign markets

This information is crucial in analyzing foreign markets that present the opportunity for Amazon to venture in. Specifically, the Asian and African markets present an opportunity that is yet to be fully exploited by the company.

Published surveys

Survey reports on customers

Feedback obtained on products surveyed

To understand what customers want and how products can be improved.

Primary Data

Source

What it measures

Data

Potential usage

Focus group

Group level satisfaction, motive product usage

Qualitative

Identify opportunities in the market and reactions of different market segments

Interviews

Level of customer satisfaction

Quantitative and qualitative

Improve level of customer satisfaction

Key informants

Customer habits

qualitative

Predicting the behavior of customers

Questionnaires

Customer experience

qualitative

Improving the customer shopping experience (Eevi, 2020)

Customer Relationship Management

CRM touchpoint

Purpose and objective

Data

Potential data usage

Product reviews

To collect customer feedback

Comments and product ratings

To establish what customers like and dislike hence improve the product.

Customer profile information

To collect basic information about customers

Name,

Email address, location, customer ID

Tracking purchases made by customers (Anshari et al., 2019)

Subscription renewals

To identify and track loyal customers

Customers preferences

Target loyal customers with tailored offers

Customer purchasing behavior

To establish preferences and choices of customers

Purchasing trends, items purchased

Tracking the most preferred and purchased products

References

Anshari, M., Almunawar, M. N., Lim, S. A., & Al-Mudimigh, A. (2019). Customer relationship management and big data enabled: Personalization & customization of services. Applied Computing and Informatics, 15(2), 94–101. https://doi.org/10.1016/j.aci.2018.05.004

Eevi, V. (2020). Factors affecting the success of AI campaigns in marketing : data perspective. https://jyx.jyu.fi/handle/123456789/71539

Running Head: MARKETING DATA ANALYSIS

1

Marketing Data Analysis

Name

Institution

Date

Running Head: MARKETING DATA ANALYSIS 1

Marketing Data Analysis

Name

Institution

Date