Download VTU MBA 4th Sem 16MBAMM403-E-Marketing E marketing Management Module 4 -Important Notes

FirstRanker.com

E-Marketing Research

Module 4

The Purina Story

• Nestle Purina PetCare Company wanted to increase web sites and online advertising.

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• Nestle developed 3 research questions:
  • Are our buyers using our branded Web sites?
  • Should we invest in other Web sites?
  • If so, where should we place the advertising?
• They combined online and off-line shopping and found that:
  • Banner clickthrough was low (0.06%).

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  • 31% of subjects who were exposed to both online mentioned Purina.
  • The high exposure group mentioned Purina more.

Data Drives Strategy

• Organizations are drowning in data.
  • Survey results, internal records, public government reports.

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  • Click stream data, web analytics.
• Marketing insight occurs somewhere between information and knowledge.
• Purina, for example, sorts through millions of pieces of data about 2 million consumers to make decisions.

From Data to Decision: Purina

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Decision

Let's put banner ads on sites where dog owners who see them are likely to buy Purina ONE. We know they visit: firstranker.com

1. Purina buyers are 20% more likely to visit firstranker.com
2. 36% of dog owners who visit firstranker.com will buy the brand.

016030102 (Buyer 1 bought Purina)

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Knowledge

Information

Data

Marketing Knowledge Management

• Knowledge management is the process of managing the creation, use and dissemination of knowledge.

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• Examples of the uses of knowledge management can be found in Examples.

Uses of Knowledge Management

The Marketing Information

• Marketers manage knowledge through a marketing information system (MIS).
  • Many firms store data in databases and data warehouses.

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• The Internet and other technologies have facilitated data collection.
  • Secondary data provides information about competitors, consumers, the economic environment, etc.
  • Marketers use the Net and other technologies to collect primary data about consumers.

Sources of data: Internal records

• Accounting, finance, production, and personnel collect and analyze data.
  • Nonmarketing data, such as sales and spending.

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  • Sales force data
    • Conversion rate, ads effectiveness, behavior
  • Customer characteristics and behavior
    • Universal product codes
    • Tracking of user movements through site

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Secondary data

• Can be collected more quickly and inexpensively than primary data.
• Secondary data may not meet all information needs.
  • Data were gathered for a different purpose.
  • Quality of secondary data may be suspect.

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  • Data may be old.
• Marketers continually gather business intelligence by scanning the environment.

Other approaches

• Monitoring social media

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• Technology enabled Approaches
• Real-space approaches

Monitoring Social Media

• Data mining - post on blogs & social media
• Online communities- open communities and

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• Social media interface - researchers recruit and participate in discussion.

Technology - Enabled Approaches

• Client-Side Data Collection
  • The data collection actually takes place between the client and the data collection server.
• Server-Sided Data collection
  • firstranker.com, through collaborative filtering software, tracks what has been ordered by customers and makes recommendations based on trends.

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Real-Space Approaches

• To gather information offline that is subsequently added to marketing databases to be used for e-marketing.
• Bar code scanner and credit card terminals, etc.
• This offline information's will be combined with online data.

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Marketing Data Base & Data Warehouse

A producer wants to know....

Which are our lowest/highest margin customers ?

What is the most effective distribution channel?

What product promotions have the biggest impact on revenue?

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What impact will new products/services have on revenue and margins?

Various Marketing Data Bases

• 1 Product Database:
  • Information about product features, prices and inventory.
• 2 Customer Database:
  • Track of each customer

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  • What he has purchased?
  • Responses
  • Complaints
  • It is used to build customer relationships

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Various Marketing Data Bases

• 3. Transaction Processing Database:
  • It refers to the adding, changing, deleting or looking up a file or database by entering the data at a terminal.
  • Trading stocks online
  • ATM
  • Online bill payments.

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What is a Data Warehouse

A single, complete and consistent store of data obtained from a variety of different sources made available to end users in a what they can understand and use in a business context.

What is Data Warehouse

A process of transforming data into information and making it available to users in a timely enough manner to make a difference

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Data Warehouse Architecture

Client

Query & Analysis

Metadata

Warehouse

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Source

Integration

Source

• Data analysis and Distribution
• Data mining

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• Customer proofing
• RMF (Resource Measurement Factor)
• REPORT generation

Data Mining

• Data Mining is the process of extracting data from a company's various databases and re-organizing it in ways other than what the databases were originally designed for.

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• It provides a means of extracting previously unknown information from the base of accessible data.
• Data mining process is different for different companies depending upon the nature of the data and objectives.
• Data mining tools use sophisticated, automated algorithms to discover hidden patterns, correlations, and relationships in organizational data.
• Data mining tools are used to predict customer behaviors, allowing businesses to make knowledge driven decisions.
• For ex: for targeted marketing, data mining is used in promotional mailings to identify the target audience and maximize the return on the company's marketing mailings.

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Data Mining works with Data Warehouse

Data Warehousing provides the Enterprise with a memory

Data Mining provides the Enterprise with intelligence

Data mining tools

IT tools and techniques are used by data mining.

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• Neural computing: It is a machine learning technique where historical data can be examined for patterns.
• Intelligent agents: It is the promising approach to extract information from the internet or from intranet-based sources.
• Association analysis: An approach that uses specialized algorithms that sort through large data sets and look for relationships among items.

Text mining

• Text mining is the application of data mining techniques to non structured or less structured information sources.

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• Operates with less structured information.
• Frequently focused on document metadata rather than document content.

Text mining helps

• Find the "hidden" content of documents and discover useful relationships
• Relate documents across previously unknown boundaries (discover that customers in two different segments have the same characteristics)

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• Group documents by common themes (e.g., identify customers of an insurance firms who have a high propensity to drop and cancel their policies)

OLAP

• Online Analytical Processing - EF Codd in 1994 paper contracted by Arbor Software
• Generally synonymous with earlier terms such as Decisions Support, Business Intelligence, Executive Information Systems
• OLAP = Multidimensional Data

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OLAP

• Online analytical processing refers to end-user activities as DSS modelling, spreadsheets and graphics that are online.
• OLAP involves many different data views and complex relationships.
• Objective of OLAP is to analyze relationships and look for patterns and exceptions.

Business intelligence and data

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Customer profiling

• Building a description of customers or a set of customers that includes their characteristics, location and behavior.
• Segment them based on their gender, age, where they live, how, why and what they spend money on.
• Through this marketers can really understand their products and how they react to promotional activities.

RFM (Recency, Frequency and Monetary)

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• It is an marketing technique used to determine the best customers.
• Quantitatively which customers are the best ones by examining how recently a customer has purchased recently,
• How often they purchase frequency and how much the customer spends monetary.
• This process responsive, saving promotional dollars and boosting sales

Report generation

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• Report generators, on other hand automatically produce high quality reports from data warehouse on a scheduled or regular basis.

Knowledge Management Metrics

• A metric is a quantitative measure of the degree to which an entity or processes a given attribute.
• The most commonly reported metrics relate to the number of searchers, hits on an articles, downloads and edits.

KM definition

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• Knowledge management is the deliberate and systematic coordination of an organization's people, technology, processes, and organizational structure in order to add value through reuse and innovation. This coordination is achieved through creating, sharing, and applying knowledge as well as through incorporating the valuable lessons learned and best practices into corporate memory in order to foster continued organizational learning.

The Two Major Types of Knowledge

The two KM metrics

• ROI
  • Total cost of savings divided by total cost of the KM program

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• TCO- total cost ownership
  • all the hidden costs involved in purchasing IT products
  • Cost savings by web server downtime and labour

KM Metrics @ Air

Consumer Behaviour Online

• Market stimuli
  • Product price place promotion
• Other Stimuli
  • Societal technological economical political and legal

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• Buyers response
  • Product/brand choice
  • Dealer/website
  • Purchasing timing
  • Frequency
  • Amount

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Factors influencing Buying Behavior

• External environment
  • Legal
  • Vendors trust
  • Competitors

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• Demographics
  • Age, gender, education, and income
• Personal characteristics
  • Need, internet knowledge & cultural environment

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• Vendor/service
• Website quality

Steps in online buying behavior

• Assignment

Online target marketing STP Analysis

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STP

• Segmentation
• Targeting
• Positioning

Segmentation-Bases

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• Demographic
  • Gender, age, income
• Psychographic
  • Personality values, Lifestyle, interest and opinions
• Behavioural
  • Benefits, occasion, frequency and usage status

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• Others
  • Technical - mail, IP address
  • Contextual - who like to buy what
  • Search - sell them what they want

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Targeting

• Most profitable customers
• Large companies
• Customers that are difficult to reach using other channels
• Customers that are brand loyal

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Targeting strategies

• Undifferentiated marketing
  • Mass marketing strategy, common to all
• Differentiated marketing
  • Marketing to chosen segment

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• Micro marketing
  • Mass customisation

Positioning

• Strategies
• Product or service attribute
  • Size, colour, speed

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  • Amazon's one-click check-out
• Technological Positioning
  • Cutting edge technology
  • Preference to frequent customers

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• User categories
  • Kellogg's has an interactive site for children

Positioning -Strategies

• Integrative positioning
  • Jewellery and hospitals
  • Web travel agencies can move market share to hospitals with discounts.

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Differentiated strategies

• Site environment
  • Easy loading. Portrays accurate information.
  • Clear about product shown
  • Home page

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• Marketing the intangible Tangible
  • Virtual tours
  • 3-d images
  • Image enlargement and trail downloads

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• Building Trust
  • Strong brand recognition
  • Privacy policies
  • Safe and encrypted payment

Differentiated strategies

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• Pricing
• CRM
• Enhancing the experience