Saturday, July 25, 2009

E-Tailing at a Children's Toy Company

Search Strategy
A regional toy company is considering the Internet as a selling channel and commissioned a background research report to decide if this retailing channel warrants further investigation. I used the Internet to do background research on toy retailing on the Internet. McDaniel and Gates (2008, p 86) recommend listing the distinctive words that might identify articles as a first step for an Internet search. I chose the following words: buy educational toys online. For my first search I did not try to enclose phrases or clich├ęs in quotes because I wanted to see a wider range of results to get other ideas for searching. This starting gambit hit a rich vein of useful material. In addition to educational toy company Web sites, I found this blog that reviews educational toy companies: Suite 101.

The companies reviewed in the blog such as The Discovery Channel provided useful information. Moreover, I followed the McDaniel and Gates guidance (p. 87) to “vary your approach with what you learn,” and picked up some words and other ideas in the review of these companies. E-tailing was a new word and eToys was a high profile failure that merited investigation. I decided to also improve the quality of my source material (see McDaniel and Gates, 2008, p. 87) and started searching with my new terms and information in EBSCOHOST. The following is my report to the toy retailer, call them KidzBiz.

The Market Reality for Online Educational Toy Sales
There is no mistake that revenue growth for online educational toy sales is front-running its brick and mortar relation by a significant margin. Online sales now form a significant share of sales for educational toy companies with the vision to participate in this channel. On example is Fat Brain (see Davis, 2008, p. 1), which has most of its sales online. It also takes advantage of the infrastructure services provided by Amazon to reduce the risk and cost of selling online by sharing Amazon server capacity, technical services and expertise.

Carson (2009, p 1) reports that Fat Brain is now on the Internet Retailer’s Hot 100 List. Furthermore, Inc. Magazine (2008, p 1) reports the astonishing growth in Fat Brain sales of 428% from 2002-2008. It also reports that the company is ranked number 40 in the Top 100 Consumer Product Companies. Not bad for a small family owned business that started in a garage selling educational toys through local stores.

What about established players? According to Internet Retailer (2006, p. 1), Toys-R-Us online sales jumped 20% with increasing strength in both number of orders and average order size. Although they do not specialize in only educational toys, they do sell them and experienced a 33% growth in sales of toys for toddlers. Hughes (p 32) reports that Disney has experienced phenomenal success in selling educational toys by “redefining babies solely as learners whose potential to learn can be released by consuming these products.” The combined message is a powerful indicator that online sales of educational toys for toddlers yield rich returns.

Are there other examples? Consider Leapfrog, an educational toy vendor who sells in brick and mortar retail stores, through its own online store and through online channels like Yahoo Shopping. In its quarterly filing with the SEC (see SEC, 2009, p. 15), Leapfrog reports that it plans to increase its online presence. This is in spite of, or perhaps because of the beating retailers are getting from the economic downturn (see SEC, 2009, p. 14).

The Discovery Channel (2008, p. 12) reported in its 10-Q news conference review that it closed all brick and mortar stores on May 17, 2007 and now will sell its educational products solely through catalog and their online store. They further inform us (p. 3) that they are aggressively investing in their online properties. Web traffic to their Web sites almost tripled from March 2007 to March 2008 from 13 million unique visitors per month to 33 million. Please note that the report does not break out visits to their online store from visits to their informational sites.

What about the high profile failures
The most high profile failure for an online toy company was eToys. Sliwa (2001, p 1) reports that eToys faced strong Internet competition from Amazon. As noted above, Amazon is now willing to partner with toy sellers. Moreover, Gomolski (2001, p. 72) goes into more depth about why eToys withered before Amazon. She reports that the eToys business model was based on competitive pricing but they had neglected to build awareness about their pricing. In addition, they failed to use the Internet to build customer relations of any kind. This resulted not only in inadequate brand awareness but also a failure to connect with children.

Moreover, eToys did not have the critical mass to reach profitability quickly and at the same time did not have cash flow from conventional business operations to sustain itself. The result is that eToys was not able to initially compete online with Amazon and could not sustain itself until it could.

How Can We Trust the Data
Can we trust the information used in this report? The sources are well respected. Inc. magazine, InternetRetailer, ComputerWorld, and InfoWorld are news magazines of note. They follow standard journalistic practice, which is designed to ensure reliable reporting. The Contemporary Issues in Early Childhood is a professional journal. Articles are peer reviewed to again ensure information reliability.

McDaniels and Gates is an academic textbook. It has been reviewed by the editorial board of John Wiley, one of the most trusted publishers. Finally, audited 10-Q statements are filed with the federal government. Heavy penalties under the administrative law are assessed for publishing false information on these statements.

KidzBiz has a lucrative opportunity to expand its sales and establish a presence in a new and growing sales and distribution system, the Internet. That system is placing relentless pressure on traditional brick and mortar operations. Today, KidzBiz is solely dependent on that old tired soldier. The next step should be to review Kidz Biz internal customer, product and sales data.

Johnson (2009, p. 3) says that, “secondary data can be greatly enhanced when merged with internally-generated data.” Kuchinskas (2003, p. 2) reports that in 2000 Dell experienced declining growth in the educational market because of tightening education budgets. They responded with a database-marketing program to the education sector. Database marketing on the Internet should enhance KidzBiz sales.

Carson, Mark (January 8, 2009). Fat Brain Toys Named To Internet Retailer’s 2009 Hot 100 List. Fat Brain Press Release. Retrieved on May 26, 2009 from

Davis, Don (September 2008). Advantage Amazon. Internet Retailer. Retrieved on May 26, 2009 from

Discovery Holding (May 8, 2008). Discovery Holding Company First Quarter Earnings Release. Retrieved on May 27, 2009 from

Gomolski, Barb (02/05/2001). Going global: Some lessons from eToys and Yahoo that might help you. InfoWorld. Retrieved on May 29, 2009 from EBSCOHOST.

Hughes, P (March 2005). Baby, It's You: international capital discovers the under threes. Comtemporary issues in early childhood. Contemporary Issues in Early Childhood. Retrieved on May 26, 2009 from

Inc. Magazine (2008). Company Profile: Fat Brain Toys. Retrieved on May 27, 2009 from

Internet Retailer (June 21, 2006). swings into the black in first quarter. Retrieved on May 26, 2009 from

Johnson, E. (2009). Using Secondary Data & Databases. Retrieved on May 30, 2009 from WVU

Kuchinskas, Susan (Sep 2003). Data-based Dell. Adweek Magazines' Technology Marketing. Rertieved on June 5, 2009 from WVU IMC 611 week 3 readings.

McDaniels, C and R Gates (2008). Marketing Research Essentials. John Wiley.

SEC (March 31, 2009). Form 10-Q for Leapfrog Enterprises. Retrieved on May 27, 2009 from

Sliwa, Carol (1/8/2001). Facing Tough Rivals, eToys Nears Oblivion. Computerworld. Retrieved on May 29, 2009 from EBSCOHOST.

Wednesday, July 22, 2009

Using ColdFusion to add XML data to a SQL database

Using the ColdFusion XML document object can present some unexpected challenges when updating databases. Variable references to elements in this structure do not return values as one might expect but instead return new structures. Useful ColdFusion functions such as <cfoutput> resolve these new structures into values behind the scene, which can mislead you when trying to debug wrong values being placed into the database.

As an example, consider the following. An xml file has a field named ICN, among others. We will read the file and update a SQL database. First, we get a file handle.

< cffile variable="gmrXML" file=" “wits.xml" action="read">

Then a ColdFusion XML Document Object datatype, using our file handle and the ColdFusion xmlParse() function:

< cfset myxml=" xmlParse(gmrXML)">

When we use cfoutput to see what we have, all is well:

<cfloop to="#arrayLen(myXML.incidentList.Incident)#" from="1" index="i">


The output on our Web page shows the ICN value we expect:


Good enough. We now add it to our database with the following code:

<cfquery datasource="SMC" name="loadSMC">
Insert into aIncident(ICN)
< /cfquery>

and when we look, the value in the ICN column in the database is not 200458431 but instead is

<?xml version="1.0"?>

This disappointing result is because in the cfquery above, we were treating the ICN reference as a value. cfouput helped in this deception because we could treat it as a value with this sophisticated function. A look at cfdump shows what happened.

Here is a dump of the reference:

It is not a value but a structure. To get to the value we want, we need to add .xmlText to the end of the reference we used so that the query now looks like:

<cfquery datasource="SMC" name="loadSMC">
Insert into aIncident(ICN)

This works as expected.

Monday, July 20, 2009

ColdFusion Program to Read XML File

Markup encodes and transfers metadata about information such as its structure and format. XML is a markup language, derived from the much earlier SGML, which uses strings of short words to surround the data it is describing. These strings of short words are known as tags. An example would be <name>George</name> <phone>555-1212</phone>.

With XML, a structural model of the data in a file can be encoded along with the data. The structure can be as simple as name and phone or much more complex, with fields like name and phone embedded in other fields like employee. A style sheet, an XSL, can be used to transform the tagged data in an XML file into a Web page. Likewise, a schema file, an XSD, can communicate database information in database operations.

ColdFusion provides a subset of functions that enable a programmer to operate on XML files. A typical operation would be to read an XML file, work on it and write it, perhaps to a database. A datatype in ColdFusion has been created for XML and is known as the XML document object. By doing this, Adobe extends the reach of its already existing ColdFusion structure functions to encompass XML data as well.

Structures consist of objects, properties, and objects embedded in other objects. Name and phone embedded in employee is an example. The dot operator is used to delimit what object in a structure you want to access. The general syntax is <object>.<object>, <object>.<property>. These can be combined to get for instance <object>.<child object>.<property>, so to access my phone number, we would use the dot operator: <employee>.<phone>

The following ColdFusion code uses some of the XML functions to read an XML file. It starts by validating the XML data file to ensure that it is consistent with its schema.

<cfset myResults= XMLValidate ("wits.xml", "wits.xsd")>
<cfoutput> Is Valid? #myResults.status#!

Next, a file handle is obtained.

<cffile variable="gmrXML" file=" “wits.xml" action="read">

Then we get a ColdFusion XML Document Object datatype using our file handle and the xmlParse() function:

<cfset myxml=" xmlParse(gmrXML)">

Now we are ready to loop through the data, and display different field values. This test file consists of a series of incidents embedded in an incident list. In addition to its own properties, an incident will have an embedded list, or object, of one or more incident types. In addition to this, it will have, an embedded facilities list, of zero or more facilities involved in the incident. These embedded lists correspond to embedded objects or to child tables in a database.

<cfloop index="i" from="1" to="#arrayLen(myXML.incidentList.Incident)#">
Event Type<br>
<!---Here is an inner loop to get all Event Types for the Incident--->
<cfloop index="j" from="1" to=
"#arrayLen(myXML.incidentList.Incident[i]. EventTypeList.EventType)#">
<cfif StructKeyExists(myXml.incidentlist.incident[i].FacilityList,"Facility")>
<!---Here is an inner loop to get all Facilities for the Incident--->
<cfloop index="j" from="1" to
"#arrayLen(myXML.incidentList.Incident[i]. FacilityList.Facility)#">
No facility for this one

The ColdFusion arraylen is used in the “To” parameter of our loop to return the number of Incidents in this incidentlist. There is one incidentlist per file. Our dot operator starts with the file handle, then refers to the incidentlist we know to be in file (because we validated), and the particular incident is referenced with our index variable [i]:


The incident number property, ICN, is accessed from the record just read from the file. For EventType, it is very similar. Since we know we will have at least one Event Type in every incident (one or more), the following code is sufficient:


On the other hand, we may not have a facility (zero or more) and will get a null pointer exception if we try to dereference a facility in an empty facilitylist. We need to use the ColdFusion StructKeyExists function to test if a facility object is embedded in the facilitylist for the current record.

<cfif StructKeyExists(myXml.incidentlist.incident[i].FacilityList,"Facility")>

If so, then we loop through the facilities involved in the incident, else we indicate no facility.

Sunday, July 19, 2009

The Marketing Research Report: Now and in 1964

The information obtained from marketing research is useful for analysis and decision-making. McDaniel and Gates (2008, pp 5-7) state that research is a fundamental means of understanding the environment, and how organizations and individuals exist, work, compete and make decisions. They go on to say that research provides data on the effectiveness of organizational actions, and insights into organizational changes needed to change the outcomes in the environment.

Furthermore, research is the basis for exploring new opportunities in the environment. Research helps segment the environment, and match segments with the characteristics or the product or action. Reporting research findings is an essential part of making it actionable. Johnson (2009, p. 1) advises us “the research report, the final step in the research process, requires thoughtful preparation and presentation.”

What are the key components to a research report?
With one interesting exception, the key components of a research report have not changed much since Boyd and Westphal published their Marketing Research text in 1964. Some forty years on, McDaniel and Gates (2008, p. 468-9) still have the following elements:
  • Title Page: The name of project.

  • Table of contents: A list of major sections.

  • Executive summary: Key findings and recommendations.

  • Background: Strengths, weaknesses, opportunities and threats.

  • Methodology: although Boyd, et al organize this with three major subsections, the research design, collections methods, and sampling.

  • Findings: A summary of results for every question in the survey.

  • Appendices

Boyd and Westphal have these same sections but also include a major section on Limitations. They note (1964, p. 575) that “A good report sells the results of the study, but it should not oversell. Every project has limitations.”

McDaniel and Gates (p. 470) tell us that the report interprets findings to arrive at conclusions using induction and then deduces recommendations from the conclusions. Induction starts (pp 470-2) by examining one-dimensional tables and then it cross tabulates to see how characteristics both independently and in tandem affect the dependent variable. A recommendation explains how a differential advantage can be obtained (p. 472). Finally, contrary to popular belief, the report does use pictures and graphs.

How would you incorporate those components into an effective research presentation?
Rubin and Babbie (2005, p. 661) admonish us to know our audience. They emphasize that the report writer must distinguish between professional colleagues and business readers. It is critical to not make assumptions about the existing knowledge of business readers. They go on to say that with business readers it is best to keep terminology simple and clear.

Furthermore, summaries and visuals appeal to business readers as does expressing the implications for their area of operations. Neal (1998, p. 23) recommends that we take time to explain complex analysis and data to our business audience. Doing so will build confidence in the research.

Boyd and Westfall (1964, p. 570) say that to make the report effective, start at the beginning. The report writer must keep the study objectives in mind when writing the report. The writer should be selective of what is included in the report, making sure it is related to the objectives. McDaniel and Gates (2008, p. 468) likewise suggest keeping the report strictly oriented to the objectives. They say, “The genesis of the report and the researcher’s thinking are the objectives provided by the client….”

McDaniel and Gates further tell us to be storytellers (p. 468). With mountains of information, the challenge to the report writer is how to package it into a coherent message. Story telling helps. They finally inform us that Microsoft PowerPoint is not only used for the oral presentation but often for the written report (p. 470). This has been my experience at work. Vendors, including prestigious firms like Booz Allen, submit final reports as PowerPoints. It is fitting with our over burdening workloads.

How does the written report differ from the presentation in terms of its function and format?
Boyd and Westphal (1964, p. 579) say the oral presentation demands “greater use of dramatics”, in other words more use of visual aids. They also suggest that transparencies, what we now call PowerPoint slides, make greater use of “headline style” writing. McDaniel and Gates (2008, p. 473) note that the presentation is an assembly of stakeholders who need to get “reacquainted with the research objectives and methodology.” They say that a copy of the full report along with the visual presentation should be handed to the participants.

The presentation must succinctly express the following (p. 475) as part of the persuasion process. First, interpret what the data mean and the impact on the organization. Next, we have learned something and does this new knowledge reveal new opportunities? Finally, what could be done better? This last point goes to the Boyd and Westphal inclusion of a Limitations section in the report itself.

McDaniel and Gates (2008, p. 476) offer the possibility of using Web technology to publish the presentation. We have done that at work. It is easy to publish a PowerPoint as a self-contained Web page or as an attachment to a blog. The blog allows for community feedback and commentary. We deal with an organization of lawyers, so we still need the face-to-face and the cross-examination in person, even if we post on a Web page


Boyd, Harper and Ralph Westfall (1964). Marketing Research Text and Cases. Richard Irwin.

Johnson, E. (2009). Communicating Research Results & Managing Marketing Research. Retrieved on July 11, 2009 from

McDaniels, C and R Gates (2008). Marketing Research Essentials. John Wiley.

Neal, William D (Spring 1998). The Marketing Research Methodologist. Marketing Research.

Rubin, Allen and Earl Babbie (2005). Research Methods for Social Work. Thompson/Brooks/Cole.

Saturday, July 4, 2009

The HERI College Senior Survey

The Higher Education Research Institute (HERI) at UCLA executes a national survey every year to better understand the college experience so that higher education can be improved. They use a meticulously laid out questionnaire and this year’s version is available at: GSEIS. Christian and Dillman (2004, p. 78) found that the amount of space and how it is apportioned can affect response. The HERI questionnaire has evenly apportioned and pleasing spaced formatting.
They exclusively use close-ended questions with a mix of dichotomous, multiple choice, and mostly scaled response. While their questionnaire is highly organized, it does not always reflect the principles of questionnaire design espoused by marketing research. Applying these principles would improve their instrument.

McDaniel and Gates (2008, p. 298) note that dichotomous questions are often subject to measurement error because they offer only black and white choices when many times shades of gray are needed. This is not the case with the HERI questionnaire. Question 6 is the only set of dichotomous choices and they are truly yes/no.

The first three pages of the HERI instrument are mostly scaled response questions. They not only allow seniors to express an opinion about a subject but also calibrate the intensity of that feeling (p. 299). A potential problem with scaled response, remembering category options, is avoided in this questionnaire by its careful design.

The fourth page introduces multiple choice questions. McDaniel and Gates (p. 299) warn that the choices may not cover all alternatives but this may be mitigated by offering an ‘other’ choice. HERI does not do this. They should to improve the questionnaire over time. In addition, Question 27 may have positioning bias. The two positive answers about colleges are positioned where they are most easily seen.

The next question reveals another common problem in the questionnaire. McDaniel and Gates (p. 301) say that words should have the same meaning to all respondents and that, additionally, words used in questions should have a precise meaning. In Question 28 both flaming liberals and draconian conservatives could indicate themselves as moderate. This same issue occurs in Question 13 about drinking frequently or occasionally. What I consider occasional, someone else may consider frequent. Finally, in Question 5, what does the word regularly mean in “regularly communicated with professors?” Specific guidance about how many for frequent, occasional and regular is needed.

Sensitive or embarrassing questions are handled by HERI in a robotic manner. In Question 13 students are directly asked about mental depression, the need for professional counseling, and alcoholic drinking habits.

Question 19 asks about marijuana, same sex marriage, denial of services to undocumented immigrants, and affirmative action. Many may be sensitive to these issues and McDaniel and Gates (p. 327) recommend using one of two techniques in such cases: 1.) Counterbiasing; or 2.) 3rd person voice. HERI does not. This is not an anonymous survey.

McDaniel and Gates (p. 301) also admonish us not to ask questions the respondents could not answer correctly. In Question 14, HERI asks students to guess what quintile they are in for various aptitudes or domain knowledges. Ambrose and Anstey (2007, p. 28) state that an important topic category in a survey is measuring the knowledge of the population. By this they mean discovering the levels of understanding. However, in the HERI survey, the students would have no frame of reference for knowing the answers to the various parts of Question 14 and so McDaniel and Gates apply with full force.

McDaniel and Gates (p. 302) also recommend that time periods be kept recent. They highlight a question as poorly worded because its time period is a year. In Question 9 of the HERI instrument, the time period of a year is used in twenty parts to that question. As McDaniel and Gates ask, unless the students kept an accurate diary of each of the twenty activities, how would they know? A better approach is to ask how much the respondent has done in the past two weeks and then if that is more or less than average (p. 302).

All in all, I found the HERI questionnaire to be well done but a few questions could be fine tuned to get more complete and more accurate results.

Ambrose, David and John Anstey (March 2007). Better Suvey Design is Stick for an Answer. ABA Bank Marketing. Retieved from on July 4, 2009.

Christian, L and D DIllman (Spring 2004). THE INFLUENCE OF GRAPHICAL AND SYMBOLIC LANGUAGE MANIPULATIONS ON RESPONSES. Retieved from on July 4, 2009.

McDaniels, C and R Gates (2008). Marketing Research Essentials. John Wiley.