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What to consider with online and other secondary data sources

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Secondary data is information that has been gathered by someone other than the researcher and/or for some other purpose than the project at hand.

This article is concerned with externally available secondary sources, for which the specification, collection, and recording of the data are done by someone other than the user.

This becomes evident when census data are used to analyze market demand. We will also look at secondary data that are collected especially for a set of information users with a common need.

Such data are both purpose-specific and expensive, but still cheaper than each user gathering the information independently.

The amount of secondary data available is overwhelming, and researchers have to locate and use the data relevant to their research.

Most search procedures follow a distinctive pattern, which begins with the most available and least costly sources.

Advantages and disadvantages of secondary data
Table 1 provides an overview of the advantages and disadvantages of secondary data.
The most significant advantage secondary data offers is savings in cost and time.

Secondary data research involves spending time in a library extracting the data and compiling relevant information.

This involves little time, effort, and money compared with primary research. Even if the data are bought from another source, it will be cheaper than collecting primary data, because the cost of data collection is shared by all those using the data.

Table 1 Advantages/disadvantages of secondary data

Advantages    Disadvantages
Quick way of obtaining data  Collected for some other purpose
Low cost    No control over data collection
Less effort expended   May not be accurate
Less time taken May not be reported in the required form
Sometimes more accurate than primary data May be outdated
Some information can be obtained only
from secondary data   May not meet data requirements
A number of assumptions have to be made

Certain research projects may not be feasible and in such cases, secondary data will be the only option. Historical data is always secondary data.

If a firm wants to obtain information on incidents that happened in the past, it cannot conduct primary research to obtain it.

In some cases secondary data can be more accurate than primary data. For example, if a company wants information on the sales, profits, and so forth, of other companies, it can get more reliable and accurate information from government-released sources than from the companies themselves.

Despite the advantages of secondary data, there are also disadvantages. By definition, secondary data has been collected for purposes other than the current research.

Hence, problems of fit are likely to occur between the data required for current research and the available data.

The available data may have different units of measurement from those required. For example, consumer income can be measured and reported at the individual, family, or household level.

Even assuming that the data use the same unit of measurement, there still may be differences in the class definition.

The researchers have no knowledge of how the data was collected, nor do they have any control over it.

Therefore, they do not know anything about the level of accuracy or bounds of error, and so must make assumptions before they can do any analysis.

It is also difficult to evaluate the accuracy of the data, because one can only gauge the level of accuracy by assessing research characteristics, such as the methodology or evidence of conscientious work.

In many cases the secondary data may not be sufficient to meet the data requirement for the research at hand. In these cases, researchers may have to use primary research.

Secondary data may also be outdated, and hence cannot be used in current research. Some secondary data may only be published once.

However, even for secondary data published at regular intervals, the time passed since the last publication can be a problem.

Another issue frequently faced by researchers using secondary data is that the time from data collection to data publication is often lengthy; hence, the data is outdated even when first available. An example is a government census, which takes years to be published.

Evaluating secondary data
All information gathered must be evaluated before it is used as a basis for decision-making.

To determine the reliability of secondary data, marketing researchers must evaluate it. This is done by answering these questions:

? What was the purpose of the study?
? Who collected the information?
? What information was collected?
? How was the information collected?
? How consistent is the information with other sources?

A discussion of each of these questions follows.

What was the purpose of the study?
Studies are conducted for a purpose and will indicate why the data was collected. However, studies are sometimes conducted in order to prove some position or advance the special interest of those conducting the study.

Who collected the information?
Even when convinced there is no bias in the purpose of a study, a researcher should question the competence of the organization that collected the information.

Why? Because organizations differ in terms of the resources they command and also in their quality control.

But how do you determine the competency of the organization that collected the data? There are several mechanisms for evaluation:

? Examination of the report. Competent firms provide carefully written and detailed explanations of the procedures and methods used in collecting the information.

? Ask others who have more experience in a given industry. Typically, professional organizations have a reputation based upon their credibility and experience.

? Ascertain customer satisfaction levels by contacting previous clients of the firm. Have they been satisfied with the quality of the work performed by the organization?

What information was collected?
There are many studies available on topics such as economic impact, market potential, feasibility, and the like, but what exactly was measured in the studies that constituted impact, potential, or feasibility?

There are many examples of studies that claim to provide information on a specific subject but, in fact, measure something quite different. The important point here is that the user should discover exactly what information was collected.

How was the information collected?
Before evaluating secondary data, it should be remembered that it was gathered as primary data by someone.

Therefore, the options for gathering the data had an effect on the nature and quality of the data. It is not always easy to find out how the secondary data was gathered.

Therefore researchers should be aware of the methods used to obtain information reported in secondary sources.

What was the sample? How large was the sample? What was the response rate? Was the information validated?

There are many ways of collecting primary data and each may influence the information collected.

Reputable organizations who provide secondary data also provide information about their data collection methods.

If this information is not readily available and the use of the secondary data is very important to a research project, you should make the extra effort to find out how the information was obtained.

How consistent is the information with other sources?
In some cases, the same secondary data is reported by several different organizations, which provides an excellent way to evaluate secondary data sources.

Ideally, if two or more independent organizations report the same data, you can have greater confidence in the validity and reliability of the data.

However, if all independent sources report very large differences of the same variable, then you may not have much confidence in any of the data.

You should look at some of the factors already discussed to help understand why these differences may occur.

Sources of internal secondary data
The answers too many problems often lie within the files of an organization or in published material.

Internal data refers to data that has been collected within the firm. Such data includes sales records, purchase requisitions, and invoices. Obviously, a good marketing researcher always checks for internal information.

Internal databases are often available. These typically hold information gathered about customers.

Think about the information you may have provided to marketing agencies: your name, address, telephone number, fax number, e-mail address, and so on.

Coupled with a knowledge of what products you have purchased and other information provided by government and commercial sources, many companies know quite a bit about you.

Although there are issues here regarding the privacy rights of consumers, companies do use their internal databases for direct marketing and to strengthen their relationships with customers.

Records of frequent customers and their transactions are maintained, and the companies use this data to identify trends among customers.

This data can also be used to find out about customers’ product preferences, form of payment, and so on.

Increasingly, companies are augmenting internal records with systematic compilations of product returns, service records, and customer correspondence, in a manner that permits easy retrieval.

Responding to the customer has become critical to maintain or increase sales. Complaint letters are being used as sources of data on product quality and service problems.

One reason is the insight they can provide into the problems of small groups with unusual requirements, reactions, or problems.

Complaint letters, however, can present an incomplete and distorted picture. People who write such letters are not typical clients or customers.

They are most likely to be highly educated, articulate, and fussy, with more than average amounts of free time.

A letter of complaint is an infrequently used method of resolving dissatisfaction; instead, people are more likely to switch brands, shop in a different store, or complain to friends.

Sometimes insightful analyses based on internal data are difficult because of limitations in the accounting system and distortions in the data.

The first problem is that accounting systems are designed to satisfy many different needs. As a result, the reporting formats tend to be rigid and inappropriate for marketing decisions.

Often the accounting data is too highly aggregated into summary results and not available for managerial units, such as geographic areas, customer types, or product types.

Efforts to break down sales and profitability data by different units may involve special, time-consuming studies.

Production, sales, and profit figures are each measured in slightly different time frames, which are all at variance with external data such as bimonthly store audit data.

Another problem is the quality of data in internal records. On the input side, the reports of salespeople’s call activities may be exaggerated if they are being evaluated in this way, and the well-known optimism of sales staff may unconsciously pervade all such data. Even accounting data is not exempt from such problems.

The usual interpretation of a sales invoice is compromised if liberal return privileges are permitted or if the product is purchased at one location, but delivered to or used in another.

In general, whenever there is a long distribution channel, with several places where inventories can be accumulated, the data on orders received or invoices billed may not correspond to actual sales activity.

Global marketing and sales departments are the main points of commercial interaction between an organization and its foreign customers. Consequently, a great deal of information should be available, including the following:

? Total sales. Every company keeps a record of its total sales over a defined time period: for example, weekly or monthly records.

? Sales by countries. Sales statistics should be split up by countries. This is partly to measure the progress and competence of the export manager or the salesperson (sometimes to influence earnings because commission may be paid on sales) and partly to measure the degree of market penetration in a particular country.

? Sales by products. Most companies sell several products and keep records for each kind of product or, if the range is large, each product group.

? Sales volume by market segment. Such segmentation may be geographical or by type of industry. This will give an indication of segment trends in terms of whether they are static, declining or expanding.

? Sales volume by type of channel distribution. Where a company uses several distribution channels, it is possible to calculate the effectiveness and profitability of each type of channel.

Such information allows marketing management to identify and develop promising channel opportunities, and results in more effective channel marketing.

? Pricing information. Historical information relating to price adjustments by product allows the organization to establish the effect of price changes on demand.

? Communication mix information. This includes historical data on the effects of advertising campaigns, sponsorship, and direct mail on sales.

Such information can act as a guide to the likely effectiveness of communication expenditure plans.

? Sales representatives’ records and reports. Sales representatives should keep a visit card or file on every “live” customer.

In addition, representatives often send reports to the sales office on such matters as orders lost to competitors and possible reasons why, as well as on firms that are planning purchasing decisions. Such information could help to bring improvements in marketing strategy.

Data warehouses
A data warehouse can be seen as a “super-database.” It contains a collection of integrated databases designed to support decision-making.

Customer data warehouses can be seen as “gold mines” of information about the customer, from sources both internal to the company and from the customer and third sources, such as the government, credit bureaux and market research firms.

Data can include behaviours, preferences, lifestyle information, transactional data and data about contact with the firm before, during and after the sale.

It may include information about customer profitability, satisfaction, retention, loyalty, and referrals.

Customer data warehouses can be described in terms of the processes and layers needed to automate and add value to communications with the customer and to facilitate mass customization.

Data warehousing enables companies to extract information from the underlying data to develop a better understanding of the most profitable relationships.

The process of exploring the databases uses data mining techniques. Data mining relies on statistical modeling and the other tools discussed below to turn information from a data warehouse into rules and patterns.

Data mining
Data mining is a process that employs information technology to uncover previously unknown patterns of behaviour, trends and issues from assessment of warehoused data

The focus is on finding consumers’ buying patterns to help marketers make better decisions.

One example of data mining is the process of classification of customers into specific segments that are meaningful to decision-makers.

The use of data mining may depend on a series of interactive, structured databases (data warehouse).

With the explosion of supermarket scanner data, data-mining techniques were developed to analyze sales data.

The results portrayed the most important changes in a particular product’s volume and market share, indicating location, product type, price level or other factor.

Still other knowledge discovery tools have concentrated on the movement of stock at a point of sale.

Such information can support decisions about shelf-space allocation, store layout, promotional effectiveness, product location, and product turnover.

With data mining, the decision-maker discovers more from the data and explores new areas, integrating other sources of data, going through an iterative process to dig deeper.

The customer information file
The benefits of keeping a customer information file, internal in the company, include (Gordon, 1998):

? Marketing effort becomes more efficient and more effective because a marketer is able to identify the most important customers and then present to them the right offer, product, or service at the right time.

? Information technology is harnessed to manage the vast amounts of data the marketer requires to interact with customers in a personalized manner.

? A true “dialogue” can be maintained with consumers by tracking interactions over time, identifying changes in purchasing, and allowing the marketer to anticipate changes.

? Product development is facilitated by knowing who has purchased a product, how satisfied he or she is and whether any changes would enhance the performance of the product.

In the following example, a customer information file (from the business-to-business market) is presented (only the most important data are shown):

? Account or identification number
? Company name
? Main telephone number/fax/e-mail
? Website address

? Business demographic
? Industry classification code (SIC)
? History of company
? Geography

Sales, profitability, cash flow and financial position
? Size: total sales
? Growth rate: total
? Size: relevant products
? Growth rate: relevant products
? Profitability: overall
? Profitability: relevant products
? Cash flow: overall
? Return on investment
? Operating profit on net sales

Market position
? Market size for customer’s products
Market segment participation
? Market share
? Customer’s major customers

? Big suppliers to this company
? Duration of relationships with big suppliers

Pre-sale contact
? Number of “touches” or contacts prior to purchases
? Types of information sought
? Channels of communication initiated by customer (telephone, online, interactive voice response, etc.), by type of information sought
? Call history: personal sales calls, by date, by audience

? Purchase behaviour

? Frequency with which purchases are made (per day, week, month, year)

Monetary value
? Amount spent on purchases
? Average margin on customer’s purchase

? Names, titles
? Our staff who have relationships with these people

Decision-making process/Buying centre
? Decision-initiators (users)
? Decision-influencers (influencers)
? Decision-makers
? Executors of decision (buyers)
? Gate-keepers

Purchase cycle
? Time required to make decision, by type of decision:
- New buy
- Modified rebuy
- Rebuy

Customer’s buying criteria
? Vendor selection criteria
? Product selection criteria
? Main selection and patronage criteria, overall company
? Perceptions of our company in respect of criteria
? Perceptions of competitors in respect of criteria

Post-purchase behaviour
? Services required
? Items returned
? Condition in which returned
? Purchase amounts of returned product
? Tone and manner of return, customer
? Customer complaint frequency
? Customer satisfaction
- Overall company satisfaction
- Specific product/service satisfaction

Distribution channels used by customers
? Intermediaries used for product/service, type and name
? Customer satisfaction with channel intermediaries

? Pricing history
? Pricing expectations
? Win/loss assessments: prices of winning vendors

? Debt history
? Receivables on account
? Payment schedule
? Credit scoring and rating

Selected relevant information
? Customer’s customers
? Business strategies

Source: Adapted from:;; Rothberg (1999)

Customer databases, data warehouses and the use of data-mining techniques promote a wider and shared use of data, with graphical ways of presenting data breaking down barriers for decision-makers, who have previously resisted formal statistical analyses.

Sources of external secondary data
Secondary data can be useful in exploratory work, as a news source or in marketing decisions.

When used as part of an exploratory study, secondary data are often associated with long-range considerations, such as whether to consider developing a new product or

Published data sources
Published data is the most popular source of marketing information, being readily available, and often sufficient to answer many research questions.

Studying the growth trends of production data over a period of years, for example, can help a manufacturer to identify new product lines or additions to a product line.

A marketing manager studying developments in the beer industry will use trade association data to learn how the total consumption of beer is broken down, by type of customer, geographic area, type of beer, brand, and distribution client.

The data is available annually and sometimes quarterly, so trends can be isolated.
A person opening a shop will use census data on family characteristics and income to find a likely location.

Demographic data would also be useful. Furthermore, a firm may establish territories for its sales staff using the population census.

The prospective user of published data is often confronted with the problem of matching a specific need for information with an array of secondary data sources of variable and often indeterminate quality.

What is needed first is a flexible search procedure to ensure that no pertinent source is overlooked, and secondly, some general criteria for evaluating quality.

Search procedure
How should someone who is unfamiliar with a market or research topic proceed? In general, two basic rules are suggested: start with the general and go to the specific; and make use of all available expertise.

Step 1: Identify what you wish to know and what is known
This is the most important step in searching for information. Without having a clear understanding of what you are looking for, you will have difficulties.

Clearly define your topic; the relevant facts; names of researchers or organizations associated with the topic; key papers and other publications; and any other information.

Step 2: List the main terms and names
These terms and names will provide access to secondary sources. Unless you have a very specific topic in mind, keep this initial list long and general. Use business dictionaries and handbooks to help develop the list.

Step 3: Begin the data search using the “easiest” sources
The best starting point is someone else who has conducted research on the same subject. Trade associations and specialized trade publications are particularly useful, for they often compile government data and collect additional information from their subscribers or members.

If information about a specific geographic area is sought, the local chamber of commerce is a good place to begin.

Types of external secondary sources
The key to obtaining census data in the industrial and services market is the Standard Industrial Classification system (SIC).

This is a uniform numbering system for classifying establishments according to their economic activities.

The total economy is first divided into 11 divisions, such as mining, manufacturing, retail trade, and public administration.

Within each of these divisions, the main industry groups are classified by two-digit numbers, e.g.:

Classification SIC number Description
Major group  57 Home furniture, furnishings, and equipment
Industry sub-group 571 Home furniture and furnishing stores
Detailed industry 571.1 Furniture stores
571.2              Floor covering stores

The SIC is often used by companies in order to segment their markets.

Compilations are intermediate sources that provide access to original sources. This is particularly desirable with statistical information.

A standard work in this area is the Statistical Abstract of the United States, which contains selections from the various censuses as well as data collected by other agencies.

Private research firms are often overlooked by researchers yet they provide valuable information on trends and conditions in specific markets.

Example companies include Frost and Sullivan, Predicasts, Euromonitor, Economist Inteligence Unit, Stanford Research Institute, and A. D. Little.

Although their reports may be expensive, they are usually much cheaper than primary research.

Source databases provide numerical data, complex text, or a combination of both, and include the many economic and financial databases and textual source databases that contain the complete texts of newspaper and journal articles.

As opposed to the indices and summaries in the reference database, source databases provide complete textual or numerical information.

They can be classified into: full-text information sources; economic and financial statistical databases, and online data and descriptive information on companies.

For example, Lexis-Nexis has three services. Tracker scans thousands of publications daily and delivers relevant news for only those topics designated by the customer.

Pub Watch allows users to scan a publication’s table of contents and select only the stories they want to read. AM News Brief provides news summaries every day.

Market research reports from more than a dozen brand names such as Data Monitor, Find/SVP, and Nielsen are also available on Nexis.

Online databases can be accessed in real time directly from the producers of the database or through a vendor.

To access online databases, all one needs is a personal computer, a modem, and a telephone line.

These databases greatly reduce the time required for a search and bring data right to the desk.

Standardized sources and syndicated services are agencies that collect information and report their findings to subscribers.

Usually, the data are not problem-specific, but are provided in a standardized format. Service providers include A.C. Nielsen for its television ratings in the US.

Another example is Roper Starch, which uses a standardized approach to evaluate the effectiveness of print advertisements through its US readership survey.

Competitive intelligence (CI)
Competitive intelligence (CI) is a systematic way to identify and gather timely and relevant information about existing and potential competitors.

Information gathered from relevant sources is analyzed to identify competitors’ strategies. Maintaining an understanding of competitors’ strengths and weaknesses puts an organization in a better position to exploit opportunities and alleviate threats, as well as to anticipate and respond to competition.

Competitor intelligence is based on published material and other types of information on competitors, current and potential, which provides an important basis for formulating strategy.

No general would order an army to march without knowing the enemy’s position and intentions.

Likewise, before deciding which competitive moves to make, a firm must be aware of the perspectives of its competitors.

CI includes information beyond industry statistics and trade gossip. It involves close observation of competitors to learn what they do best and why and where they are weak.

Most western countries have seen an intensification of competitor analysis. The reasons are:

? Increasing competition between companies
? Deregulation
? Liberalization of trade
? Globalization
? Periods of economic recession
? Reduced product and service differentiation.

Factors inhibiting the growth of CI include:
? Data protection
? Different legislation in various countries
? Fears that competitive intelligence is unethical
? Fears of counter intelligence
? Failure of competitive strategies to yield the expected gain.

The increasing use of CI is not a process that occurs in a single step. Rather, it takes place over a period of time during which there is a growing awareness of the need to have a competitor strategy, which is every bit as important as the customer strategies that are already commonplace (West, 1999).

In terms of their use of competitive intelligence, companies seem to go through a series of stages.

The first stage is competitor awareness. This begins soon after a company is formed, or even before, when the start-up is being planned.

Being competitor aware means that competitors are known and that there is some knowledge – usually incomplete and certainly unverified – about their products, their prices, the clients they have won business from, the market sectors they service and the staff they employ.

The organization that is competitor-aware rarely uses the data that it holds other than for occasional tactical exercises, such as competitive pricing decisions, or as an input to a business plan that has to be submitted to an external organization, such as a bank, or a contractual tender bid.

As companies grow they tend to become competitor sensitive -both in terms of their awareness of the damage competitors can inflict on their business and the need to win orders by competing more effectively.

Unfortunately, being competitor sensitive does not always increase the demand for information on competitors.

An alarming proportion of competitor-sensitive companies continue to rely exclusively on informal information flows through their sales forces, business contacts and scans of the trade press, rather than a structured program.

When they do step outside the informal information channels the prime motive is usually emulation, seeking to copy what they perceive to be the best of their competitor’s practices.

There is nothing wrong with emulation as a business process, providing it is factually driven using such techniques as reverse engineering and competitor benchmarking, but it represents a limited application for the data that can be derived about competitors.

The organization that is competitor intelligent devotes resources to studying competitors and anticipating their actions.

This includes: identifying competitors’ physical and intangible resources; studying their organizations and their methods in as much detail as is practical; and developing knowledge of their strategies and potential game plans.

The competitor intelligent organization is continuously aware of the threats posed by competitors, the nature and seriousness of those threats and what needs to be done to counteract them.

They recognize the need to look forward to anticipate competitive actions and to predict the likely responses to actions they are proposing to take themselves.

They are also aware that the most serious threats may arise from companies that are not yet active in their business sector.

There is a close parallel between the growth in competitor analysis and the development of customer analysis. There was a time when organizations were only customer aware.

This was accompanied by a short flirtation with marketing warfare that focused on beating the competition by adopting military tactics.

Competition is good for the customers because it means that companies have to try harder or lose their customer base. In many markets competition is the driving force of change.

Strategic and tactical levels
Strategic intelligence is future-oriented and allows an organization to make informed decisions concerning future conditions in the marketplace and/or industry.

Tactical intelligence focuses on the present. This level of intelligence provides decision-makers with the information necessary to monitor changes in the company’s current environment and proactively helps them search for new opportunities.

To maximize the benefit of CI, the strategic and tactical levels must be coordinated and all partner companies treat coordination as a priority.

These companies believe that coordinating strategic and tactical intelligence with sales and marketing has led to a strengthening in competitive positions as well as increases in customer satisfaction and customer retention.

Questions for competitive intelligence can include the following:

? Who are our competitors?

? How do we learn about our competitors? (How do we gather competitor information?) a What are the strengths and weaknesses of our competitors (competitor audit)?

? What are the objectives and strategies of our competitors? v What are the response patterns of our competitors?

? How can we set up an organization for competitive intelligence?

Gathering competitor information
The information-gathering techniques summarized below are all legally used to gain competitive insights, although some may involve questionable ethics.

A responsible company should carefully review each technique before using it to avoid practices that might be illegal or unethical.

? Information from own staff and employees of competing companies. Firms can collect data about their competitors through interviews with new recruits or by speaking with employees of competing companies.

When firms interview, e.g. students for jobs, they may pay special attention to those who have worked for competitors, even temporarily Job-seekers are eager to impress and often have not been warned about divulging what is proprietary information.

Companies send engineers to conferences and trade shows to question competitors’ technical people.

Another tactic in corporate intelligence gathering is to hire executives from competitors to find out what they know.

? Information from competitors’ customers. Some customers may give out information on competitors’ products.

The co-operative relationship that is cultivated with the customer may encourage these customers to divulge competitor activities.

? Information from competitors’ suppliers. A firm and its main competitor are sometimes supplied by the same subcontractor.

As many firms today have close relations to their suppliers some information exchange may be possible.

? Information from observing competitors or by analyzing physical evidence. Companies can get to know competitors better by buying their products or by examining other physical evidence.

Companies increasingly buy competitors’ products and take them apart to determine costs of production and even manufacturing methods.

? Published materials and public documents. Examples of published material include: financial reports of the company; government reports; company presentation brochure: profiles in industry journals. Much of this information may be found on the web.

Why the web is a good source of competitive intelligence
Online resources will provide an array of basic information. However, just because something is on the web does not mean it is accurate.

“www” is not the source of the data, it is just part of an electronic address. The analyst must document the author, method of data collection, date, publisher location, and purpose of publishing the data.

Experienced researchers question the authenticity of data until there has been an opportunity to assess the reliability of the online (and any other) data source.

Although sales exaggerations affect few people, such a practice on the web could lead to vastly different conclusions unless the information and source credibility are questioned by those who use information in making important strategic decisions.

Falsifying data on the web is rare. However, the inability to police the internet could lead to inaccurate if not intentionally false data inputs.

Always keep in mind the fact that it is up to the data collector to verify the quality of information found using the internet.

Types of competitive intelligence
In the broadest sense, data sources are either free or available for a fee. Paid-for services are of three types:

? A database that charges a monthly fee for access to data.
? Services that provide data to subscribers on a per-inquiry basis.
? Reports from research firms.

Subscription services
Numerous online data links give subscribers access to special databases. A subscription to Lexis-Nexis is one possibility. Subscribers get up-to-date information direct from

Lexis-Nexis is one of the leading business intelligence providers. More than 30,000 sources are covered with three billion searchable documents.

Over a million documents are added every week. Nexis will provide regular reports (such as Lexis-monthly). Each of these updates would show any new article on this subject published in the past month.

There are many other online subscription services. Others include:
? Dun & Bradstreet, ( There is also Dun & Bradstreet On-Line giving selected operating ratios by SIC code, credit reports, etc.

? Hoovers ( provides profiles of companies. A great deal of financial data is available.

? Moody ( is useful for checking out the credit ratings of competitors.

? Database America ( provides current information on competitors’ products and strategies.

? Euromonitor ( publish market and competitor research reports.

? Phoenix Consulting Group ( provides competitive intelligence and counterintelligence services.

? Fuld & Company ( is a pioneer in CI – in the US. It offers detailed descriptions of competitive intelligence, seminars and consulting services.

? Aware ( provides CI for businesses in Europe and the UK.

? Datamonitor ( provides market and competitor analyses.

? Current Analysis ( brings action-oriented CI to clients within 24-28 hours of a significant development.

? Free internet sources. High on any list of sites for those who want to start building CI systems using online sources should be industry or trade associations. Similarly, professional associations can provide valuable data.

Sources for general information
Perhaps one of the more interesting competitive intelligence (CI) developments can be found when one looks at any of the various free global news retrieval services.

These online services are of special interest because they are delivered to a computer as often as every 15 minutes.

In some cases, the material is available before it is in print. Suppose a company is doing business throughout Europe or the US.

How can it track news of special interest to its business? Here are some of the possibilities:

? Corporate Information ( allows searches on company names (250,000 company profiles) and industry in the US.

? Comfind ( is a US service on industries, companies, and their products.

? Society of Competitive Intelligence Professionals ( offers assistance, articles, and advice.

Online annual reports
Several services provide free access to company annual reports, in PDF format so they look exactly like the printed version.

Shadow teams provide a way to integrate a company’s internal knowledge with external competitive intelligence.

Shadow team members should represent a cross functional composite, drawn from the organization’s best and brightest employees.

Each team’s mission is to “shadow” a competitor and to learn everything possible about the rival from published data, firm personnel, contacts, etc.

As information is collected and analyzed, the shadow team becomes a knowledge base that may soon operate as a think tank.

Setting up an organization for CI
Competitive, or business, intelligence enhances a corporation’s ability to succeed in global markets.

It provides early warning intelligence and a framework for understanding and countering competitors’ initiatives. Competitive activities can be monitored in-house or assigned to an outside agency.

Within the organization, competitive information should be acquired both at the corporate level and at the business division level.

At the corporate level, CI is concerned with competitors’ investment strengths and priorities.

At the divisional level, the main interest is in marketing strategy, that is, product, pricing, distribution, and promotion strategies that a competitor is likely to pursue. The true payoff of CI comes from a divisional review.

The CI task can be assigned to various individuals but, whoever is given the task of gathering competitive intelligence should be allowed adequate time and money to do a thorough job.

Special problems and methods associated with secondary data
Two main problems are associated with secondary data in international marketing research: the accuracy of the data and the comparability of data obtained from different countries (Engle, 2005).

Different sources often report different values for the same macroeconomic factor, such as gross national product (GDP), or per-capita income.

This casts doubt on the accuracy of the data. This may be due to different definitions and interpretations, for each of those statistics in different countries. The accuracy of data also varies from one country to another.

Data from industrialized nations is likely to have a higher level of accuracy than data from developing countries, because of the difference in the sophistication of the procedures adopted.

The level of literacy in a country also plays a role in the accuracy of the macroeconomic data.

Business statistics and income data vary because different countries have different tax structures.

Hence, it may not be useful to compare these statistics across countries. Population censuses may not only be inaccurate, they also may vary in frequency and the year in which the information was collected.

Another problem is that the measurement units are not necessarily equivalent. For example, the cost of buying a television in Germany would be classified as an entertainment expense, whereas in the US it would be a furniture expense.

Use of secondary data
Secondary data is particularly useful in the screening of potential international markets in order to select the most attractive new markets.

Once the appropriate markets have been selected and the initial market-entry decision has been made, the next step is to make an explicit evaluation of demand in those countries or markets.

Because of the high costs and uncertainty associated with entering markets, management has to make an initial estimate of demand potential, and also project market trends. Four types of methods and data analyses are discussed here, regarding demand estimation in an international context.

Lead-lag analyses
This uses time-series (yearly) data from a country to project sales in other countries. This technique is based on the use of time-series data from one country to project sales in other countries.

It assumes that the determinants of demand in the two countries are the same, and that only time separates them.

This requires the diffusion process, and specifically the rate of diffusion, to be the same in all countries.

Of course, this is not always the case, and it seems that products introduced more recently diffused more quickly (Craig and Douglas, 2000).

The difficulty in using the lead-lag analysis includes the problem of identifying the relevant time lag and the factors that influence future demand.

However, the technique has considerable intuitive appeal to managers and is likely to guide some of their thinking.

Estimation by analogy
This method relies on the use of cross-sectional data (data from different countries). One assumes that if there is a direct relationship between the demand for a product, service, or commodity and an indicator in one country, the same relationship will hold in other countries to estimate the demand.

This is essentially a single-factor index with a correlation value (between a factor and demand for a product) obtained in one country applied to a target international market.

First a relationship/correlation must be established between the demand to be estimated and the factor that is to serve as the basis for the analogy.

Once the known relationship is established, the correlation value then attempts to draw an analogy between the known situation and the market demand in question.

A company wants to estimate demand for refrigerators in Germany. It knows the market size in the UK but not in Germany.

As nearly all households in the two countries already have a refrigerator, a good correlation could be the number of households or population size in the two countries.
Choosing the population size as the basis for the analogy:

UK population: 60 million
German population: 82 million
The number of refrigerators sold in the UK in 2002 was L 1 million Then an estimate of sales in Germany is: (82/60) X 1.1 million = 1.5 million

Generally, caution must be used with estimation by analogy because the method assumes that factors other than the correlation factor used (in this example population size) are similar in both countries, such as the same culture, buying power of consumers, tastes, taxes, prices, selling methods, availability of products, consumption patterns, and so forth.

Despite the apparent drawbacks, analogy is useful where international data is limited.

Surrogate indicators
This is similar to the use of general macro-indicators, but develops the macro-indicators relative to a specific industry or product market.

An example of a surrogate indicator is the number of childbirths in a country as an indicator of the demand potential for baby carriages.

Econometric forecasting models
Here, the researcher uses cross-sectional and time-series data on factors underlying sales for a given product market for a number of countries to estimate certain parameters.

Collecting international secondary data across the internet
Consider the case of a fictitious British electronic company, Monitoring Systems, which wants to start exporting a system for remote monitoring of wind turbines.

The system works through communications hardware installed on the wind turbine. This is linked to software on a computer, so that all the important functions of the wind turbine can be monitored.

Expanded versions allow online access to the monitoring data across the internet. This means that the owner of the wind turbine can be on holiday in Canada and still be able to monitor a wind turbine back in Germany.

The company has no idea where to start exporting its product but the collected data should form the basis for penetration of the chosen market.

The monitor may be installed when the wind turbine is delivered or later on (after-sales installation). Thus, the system can be sold through the turbine manufacturers.

The makers of the wind turbines can install the monitor when producing the wind turbine. Another possibility is that the system may be sold to owners of existing wind turbines.

To summarize: in this situation the objective of collecting market data for Monitoring Systems is:

? to select the most attractive international country for the company (international market selection);

? to segment the chosen market as the basis for targeting the most attractive segments (micro-segmentation).

Summimg up
The article considered the various sources of secondary data and suggested systematic ways of searching for appropriate data or information relevant to a marketing problem.

There is a surprising amoung of material available for little effort. Even if they are not entirely suitable, secondary data sources can provide useful pointers on how to design a research study.

Many management problems can be resolved by access to the firm’s internal records or to secondary sources such as government statistics, trade association reports, periodicals, books, and the various databases accessed via the internet.

In terms of secondary consumer intelligence data, numerous resources are available to market researchers on the web.

General characteristics of consumer markets can be obtained from the many government-based and private statistical services and many of these are online.

This information can be used to generate a situational analysis of select target markets and design strategies according to the characteristics of consumers in that specific market.

Product and media consumption data are increasingly in demand, especially due to the growth of new media.

Such data can help marketers make strategic marketing decisions about new and existing products and the appropriate media vehicles to use for promotion.

The web has opened up opportunities for organizations to set up a competitive intelligence system in-house, so it is both cost-effective and timely.

There is a vast number of resources that can be accessed online. The abundance of information may create problems for researchers who do not have the skills to filter relevant information.

Why is it important to know the purpose of a study based on secondary data?

Why should a company use all potential sources of secondary data before initiating primary data research?
Why is secondary often preferred to primary data?

What pitfalls might a researcher encounter in using secondary data?

What is the difference between internal and external secondary data?

On what criteria should secondary data be evaluated?

What are the major sources of competitive intelligence?

How would you design a CI system?

What is the difference between “data warehouse” and “data mining”?

Why is the internet of such great value to researchers seeking secondary data?

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Keywords: Secondary data, market demand, marketing researchers, Internal secondary data, external secondary data, Global marketing, data warehouse, data, data mining, Customer, customer information file, business-to-business market, Published data, Demographic data, census data, Compilations, Private research firms, Source databases, marketing databases, Competitive intelligence, competitor, data sources, Subscription services, information, annual report, lead-lag analysis, Surrogate indicators, Econometric forecasting models, data collection,


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