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课程名称: 市场营销数据的分析与挖掘  
开课时间: 2019-03-13 
开课地区: 北京 北京  
价格: ¥ 2800  
培训天数: 1  
课程分类: 市场营销  
在线报名:
报名表格:
  021-61521609

 

培训对象

 营销副总、营销总监、市场部经理、营销人员、市场研究人员等

 

 

 

课程介绍

· 概述/Overview

 

您在企业营销的工作中,有没有碰到这样的困惑:

(1)老板让我收集对市场绩效影响相关的信息和数据,但是我不知道如何收集?例如现在产品滞销了,应该如何找原因找数据,我不甚了了

(2)我的营销工作报告太简单了,怎么样才能做得专业丰富一些?

(3)怎么样从我的营销数据中抓取生意点和机会点?

(4)怎么样对我的业务进行评估,并且抓取业务中的异常点?

(5)怎么样对我的客户、业务、经销商等进行有效的分类,并且制定有效的应对策略?

(6)如何对营销活动进行分析?

(7)怎么样分析业务指标中的关联性?

(8)有没有进行业务预测的有效模型?如果构建业务预测模型?

(9)什么是客户画像,如何构造客户画像模型?

(10)如何对营销数据分析的结果进行有效的呈现?

 

纪老师常年从事营销数据分析的培训和咨询工作,具有丰富的营销数据策划、采集、分析、呈现、报告撰写的经验,课程内容丰富翔实,贴近实战,本课程主要在EXCEL环境中进行营销数据的分析和挖掘,学员上手较轻松。

 

Do you encounter such confusion in your work of enterprise marketing:

(1)My boss asked me to collect information and data related to the impact on market performance, but I did not know how to collect it. For example, now the product is unsalable, how to find the reason and the data, I do not know.

(2)My marketing work report is too simple. How can I do it professionally?

(3)How do I capture business and opportunity points from my marketing data?

(4)How do I evaluate my business and capture the outliers in the business?

(5)How to effectively classify my customers, businesses, dealers and so on, and formulate effective countermeasures?

(6)How to analyze marketing activities?

(7)How to analyze the correlations in business indicators?

(8)Is there an effective model for business forecasting? What if you build a business forecasting model?

(9)What is a customer portrait and how do you construct a customer portrait model?

(10)How to effectively present the results of marketing data analysis?

 

Lecturer Ji has been engaged in the training and consultation of marketing data analysis for many years, and has rich experience in marketing data planning, collection, analysis, presentation and report writing. The course content is rich, informative and close to the actual situation. This course mainly analyzes and mines marketing data in EXCEL environment so students learn easily.

 

课程简介:

随着社会经济发展和企业信息化水平的提高,企业在营销过程中会接触到大量的内外部数据,分析和挖掘企业营销数据,对于洞察企业内外部态势、制定有效的有针对性的营销策略等有着极强的指导意义。

本课程首先介绍数据分析的相关基础,然后介绍如何提升数据分析能力、数据分析的常见问题以及基本分析思路,为后续分析工作打好基础。随后介绍数据描述、异常值分析、相关分析、聚类、客户画像、关联分析等重要数据分析工具和模型。

本课程内容丰富,贴近实战,所选择的分析工具、模型均为数据分析领域常用的成熟的分析模型算法。有理论有案例有实际操作,落地性强,能够较好地提高学员的数据分析和挖掘能力。全部案例均采用Excel 2007/2010/2013、数据分析插件进行讲解。

Course Introduction:

With the development of social economy and the improvement of enterprise informatization level, in the marketing process, enterprises will be exposed to a large number of internal and external data, analysis and mining enterprise marketing data. It is great significance to understand the internal and external situation of the enterprise and formulate effective and targeted marketing strategies.

Firstly, this course introduces the relevant basis of data analysis, and then introduces how to improve data analysis ability, common problems of data analysis and basic analysis thinking, laying a solid foundation for subsequent analysis. At last, it introduces important data analysis tools and models such as data description, outlier analysis, correlation analysis, clustering, customer portrait, association analysis, etc.

This course is rich in content and close to actual practice. The selected analysis tools and models are mature analysis model algorithms commonly used in the field of data analysis. There are theories, cases and practical operations, with strong practice ability, which can better improve the data analysis and mining ability of students. All cases were explained using Excel 2007/2010/2013 and data analysis plug-in.

 

课程适用对象:

营销副总、营销总监、市场部经理、营销人员、市场研究人员等。

Applicable Objects For the Course:

Marketing Vice President, Marketing Director, Marketing Manager, Marketing Staff, Market Researchers, etc.

 

课程收获:

(1)了解数据分析的整体步骤

(2)掌握数据分析能力的提升路径

(3)掌握营销数据分析的思路和方法

(4)掌握营销数据挖掘的模型及其应用

Course Benefits:

(1)Understand the overall steps of data analysis

(2)Master the improvement path of data analysis ability

(3)Master marketing data analysis ideas and methods

(4)Master the model and application of marketing data mining

 

课程教学方式:

讲师讲授+互动+软件现场操作

Course Teaching Method:

Lecturers teaching + interaction + software on-site operation

 

· 活动纲要/Outline

 

1.数据分析基础

(1)数据分析与挖掘的概念与差异

(2)分析目标

包括数据整体状况分析、异动分析、数据分类、数据间逻辑关系分析、数据预测等。

(3)分析步骤

包括数据收集、数据整理、报表制作、数据分析与数据挖掘、图形呈现、形成策划案等6个步骤。

1. Basis of Data Analysis

(1)The concept and difference of data analysis and mining

(2)Analysis Targets

It includes the analysis of the overall status of data, abnormal analysis, data classification, logical relationship analysis between data, data prediction, etc.

(3)Analytical Procedure

It includes 6 steps, such as data collection, data sorting, report making, data analysis, data mining, graphic presentation, and form planning

 

2.数据分析与业务逻辑

(1)数据分析能力

包括业务理解能力、逻辑思辨能力、需求转换能力、统计分析挖掘工具的掌握等方面。

(2)常见业务逻辑

a)如何对数据特征进行描述?

b)我的业务的特征是啥样的?

c)如何结合营销现状判断数据中的异常值?

d)A数据和B数据之间有关系吗?如果有关系,关系是怎样的?

e)如果数据之间有影响,有没有重要程度的差异?

f)数据和指标如何分组?

g)如果影响指标比较多,如何处理?

h)我想知道数据之间的对应关系,如何处理?

i)如何考虑A事件对B事件的边际贡献率?

……

(3)分析思路

a)标识分析法

b)二八分析法

c)特征组合分析法

d)排序分析法

e)对比分析法

f)分组分析法

g)结构分析法

h)交叉分析法

i)对应分析法

……

2. Data Analysis and Business Logic

(1)Data Analysis Ability

It includes business understanding ability, logical thinking ability, requirements transformation ability, master statistical analysis and mining tools, etc.

(2)Common Business Logic

a) How to describe data characteristics?

b) What are the characteristics of my business?

c) How to judge the outliers in the data based on the marketing status?

d) Is there a relationship between data A and data B? If so, what does the relationship look like?

e) If there is an effect between the data, is there a difference in significance?

f) How are data and metrics grouped?

g) If there are many influencing indicators, how to deal with them?

h) I want to know the corresponding relationship between the data, how to deal with it?

i) How to consider the marginal contribution rate of event A to event B?

……

(3)Analysis Methods

a) Identifying analysis method

b) Pareto analysis method

c) Characteristic combination Sorting

d) Sorting analysis method

e) Comparative analysis method d

f) Grouping analysis method

g) Structured analysis method

h) Cross analysis method

i) Corresponding analysis method

……

 

3.数据描述

数据描述指对销售数据进行描述统计,采用多种指标和方法揭示数据的概况,为后续分析做好准备工作。描述的指标有求和、计数、平均值、中位数、众数、方差(标准差)、变异系数、峰度、偏度、占比、累计占比、同比、环比等。

(1)整体状况描述

(2)数据的七个百分比

(3)多列对比

这是应培训学员的要求所做的多列对比的小工具,非常方便,可以一次性地输出多列之间平均值、总数、中位数、变异系数、二八系数等的对比。

3. Data Description

Data description refers to descriptive statistics of sales data,using a variety of indicators and methods to reveal the general situation of data,prepare for subsequent analysis. The indicators described are sum, count, average, median, mode, variance (standard deviation), variable coefficient, kurtosis, skewness, proportion, cumulative proportion, on year-on-year basis, month-on-month ratio, etc.

(1)Overall condition description

(2)Seven percentage of data

(3)Multiple columns contrast

This is a multi-column comparison tool that is required by the trainees,very convenient, which could have one-time output in the comparison of the mean, total, median, variable coefficient, and Two-Eight coefficient between multiple columns.

 

4.异常值分析

异常值是数据中脱离正常变化轨道的数据,也是数据分析中需要重点关注的数据。通常采用如下方法分析异常值:

(1)散点图

(2)条件格式

(3)三倍标准差

4. Outliers Analysis

Outliers are the data that deviates from the normal track of change in the data,It is also the data that needs to be paid attention to in data analysis. Outliers are usually analyzed as follows:

(1)Scatter Diagram

(2)Conditional Format

(3)Triple Standard Deviation

 

5.相关分析

(1)相关分析原理

(2)EXCEL“数据分析”模块安装及介绍

(3)操作及输出说明

案例:上海某公路物流企业分析其营销指标间关系

5. Correlation Analysis

(1) Principle of correlation analysis

(2) Installation and introduction of EXCEL "data analysis" module

(3) Operation and output instructions

Case: a highway logistics enterprise in Shanghai analyzed the relationship between its marketing indicators

 

6.聚类-客户细分

单独一个数据,往往因为数据异常或者偶然性等原因,从来很难发现明显的结论,分组不仅仅让分析变得简单,而且能够发现简单对比所无法获得的结论。

(1)单指标的分类

(2)多指标的分类

多指标的分组,可以用来做数据的细分等,采用聚类实现。

案例讨论:最佳聚类分类总数的确定

6. Clustering - Customer Segmentation

A single piece of data, often due to data anomalies or contingency, is never easy to find obvious conclusions. Grouping not only makes analysis easier, but also enables you to find conclusions that simple comparisons cannot got.

(1)Classification of single index

(2)Classification of multiple indicators

Multi-index grouping, can be used to do data segmentation, etc., by using clustering.

Case Study: Determination of the total number of optimal clustering classifications

 

7.关联分析

关联分析可以分析数据中的某些特征同时出现以及次序出现的概率,其输出的结果经常用来做捆绑销售,例如客户购买了A产品之后是否购买了产品B。

(1)相关概念

支持度、置信度、提升度

(2)关联分析算法的使用

7. Correlation Analysis

Correlation analysis can analyze the probability that some features in the data appear simultaneously and the probability that order appears. The output outcome is often used for bundling, for example, does the customer purchase product B after purchasing product A?

(1)Relevant concepts

Support degree, confidence degree, promotion degree

(2)Use of correlation analysis algorithms

 

8.客户画像

客户画像是目前营销数据分析的热点问题之一,4S店的销售人员希望通过数据分析得到其客户的特征是什么,网店的经营者希望知道哪些特征组合的客户在投诉他们。

(1)算法描述

(2)算法执行和输出

案例:某网店利用数据分析影响客户购买的特征

8. Customer Portrait

Customer portrait is one of the hot issues in marketing data analysis. What are the characteristics of 4S stores' customers that salesmen hope to obtain through data analysis? Online shop operators want to know which feature combinations customers are complaining about.

(1)Algorithm description

(2)Algorithm execution and output

Case: An online store uses data to analyze the characteristics that affect customers' purchase.

 

 

师资介绍

纪老师Lecturer Ji

背景经历:

大连理工大学计算机系,复旦大学MBA。长期从事数据分析、市场调查、Excel等方面的培训工作

纪老师曾经在上海贝尔、MOTOROLA、Lucent、新加坡比技公司、上海全成等公司长期工作,担任过项目经理、技术市场经理、销售经理、销售总监等职务,对于数据分析和市场营销有着较多实战经验

纪老师积累了较多的数据分析和挖掘的实战经验,1995年即开始使用Excel、VBA对于Motorola电信交换机的运营数据进行分析和编程处理,1998年即开始采用SPSS软件进行数据分析和市场调查报表的分析工作,在新加坡比技公司、上海全成通信等公司组织和领导了多项移动通信增值业务数据的数据挖掘项目(采用COGNOS商业报表软件和CLEMENTINE软件)。

同时,纪老师也曾经参与或主持过多项数据分析方面的咨询项目,包括 “2005年上海移动有限公司新产品发展模式市场调研”、“内蒙古杏仁露产品上市前调研”、“2009年杨浦区商管公司下属商业网点调研”、“2009格林动力汽车尾气净化剂数据分析”、“2011年我国电子阅读器市场用户消费模式调研”等,在营销数据分析和市场调查方面有着较多实战经验。

Background and Experience:

Computer science department in Dalian University of Technology, MBA of Fudan University. Long-term engaged in data analysis, market research, Excel and other aspects of training.

Lecturer Ji has worked in Shanghai Bell, MOTOROLA, Lucent, Singapore Biti technology company, Shanghai Quancheng and other companies for a long time. Also served as project manager, technical marketing manager, sales manager, sales director and other positions. Lecturer Ji has more practical experience in data analysis and marketing

Lecturer Ji has accumulated more practical experience in data analysis and mining. Lecturer Ji began using Excel and VBA for Motorola telecom switch operating data analysis and programming process in 1995, began with SPSS software for data analysis and the analysis of the market research report in 1998, than the company organization and led a number of mobile value-added business data mining project in Singapore Biti technology company, Shanghai Quancheng Communication Co., LTD and etc., (using COGNOS business reporting software and CLEMENTINE software).

At the same time, Lecturer Ji have participated in or presided over several data analysis aspects of consulting projects, including "2005 Shanghai mobile co., LTD., new product development mode market research", "Inner Mongolia almond products pre-market research", "2009 Yangpu district business company subordinate business outlets research", "2009 green vehicles exhaust purifying agent data analysis", "2011 China's e-reader market customer consumption model research" and so on, in the aspect of marketing data analysis and market research has more experience in practical.

 

擅长领域:

《销售报表制作与分析》、《市场营销数据的分析与挖掘》、《Excel高效操作技巧》、《EXCEL VBA在金融建模中的应用》、《市场调研数据分析和利用》、《大数据时代的数据分析和挖掘》、《Access在数据分析中的高效运用》、《SPSS商业数据分析》。

曾经参与或主持过多项数据分析方面的咨询项目,包括 :

2015年:上海张江高科科技园政府扶持企业资金投入产出绩效分析项目(分析工具提供)(VBA实现DEA算法)

2015年:迪皮埃复材构件(太仓、大丰)两公司生产部报表项目(VBA实现)

2015年:某证券私募企业股票指标数据跟踪与分析系统(VBA实现)

2014年:上海印钞厂统计分析培训专题咨询

2013年:迪皮埃复材构件(太仓)有限公司,生产部数据流程整合咨询项目(包括VBA编码调试)

2013年:上海印钞厂统计分析专题咨询

2011年:内蒙古杏仁露产品上市前调研

2010年:我国电子阅读器市场用户消费模式调研

2009年:格林动力汽车尾气净化剂数据分析

2009年:上海杨浦区商管公司下属商业网点调研

2005年:上海移动有限公司新产品发展模式市场调研

The Field of Expertise:

《Sales Report Preparation and Analysis》、《Marketing Data Analysis and Mining》、《Excel Efficient Operation Skills》、《Application of EXCEL VBA in Financial Modeling》、《Market Research Data Analysis and Utilization》、《Data Analysis and Mining in the Age of Big Data》、《Efficient Application of Access in Data Analysis》、《SPSS Business Data Analysis》

Participated in or led several consulting projects on data analysis, including:

In 2015:Shanghai zhangjiang high-tech park government supported enterprise capital input and output performance analysis project (Analysis tool provided) (DEA algorithm implemented by VBA)

In 2015:Statement item of production department of two companies (Taicang and Dafeng) (VBA implementation)

In 2015:A stock index data tracking and analysis system for a private equity firm (VBA implementation)

In 2014: Special consultation on statistical analysis and training of Shanghai banknote printing factory

In 2013: Data flow integration consulting project of production department (including VBA code debugging) of Dipiai composite components (Taicang) co., LTD.

In 2013:Special consultation on statistical analysis of Shanghai banknote printing factory

In 2011: Inner Mongolia apricot kernel juice products before the market research

In 2010: Research on consumer consumption patterns in China's e-reader market

In 2009:Analysis of exhaust gas purifier data of Green power vehicle

In 2009:Shanghai Yangpu district commercial management co., LTD. Branch commercial network research

In 2005:Market research on new product development model of Shanghai mobile co., LTD

 

服务客户:

华晨宝马、天津壳牌、大连中升之星、赛诺菲、宝钢股份、立邦涂料、迪皮埃(太仓)、阿斯利康、中石化壳牌、上海医疗器械集团、上海印钞厂、上海造币厂、上海浦东新区发改委、大众汽车、大众联合、大众电子、上汽集团、河南移动、大赛璐(中国)、重庆康明斯、奇瑞汽车、中国移动集团公司、中国网通北京分公司、地中海游轮(上海)、杭州华数集团、诺翼航空等

Serving Customers:

Huachen BMW, Tianjin Shell, Dalian Zhongsheng Star, Sanofi, Baosteel Stock, Libang Paint, Dipier (Taicang), AstraZeneca, Sinopec Shell, Shanghai Medical Devices Group, Shanghai Banknote Printing Plant, Shanghai Mint, Shanghai Pudong New Area Development and Reform Commission, Volkswagen Automobile, Volkswagen Union, Volkswagen Electronics, Shanghai Automobile Collection Group, Henan Mobile, Chailu (China), Chongqing Cummins, Chery Automobile, China Mobile Group Corporation, China Netcom Beijing Branch, Mediterranean Cruise (Shanghai), Hangzhou Huashu Group, Novo Airlines, etc.