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 This specific case study is about improving the sales of a consultancy firm by attracting more clients through its website. The project follows the define-measure-analyze-improve-control (DMAIC) phases, as prescribed by Lean Six Sigma. See the file below for the case study. 

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Quality Engineering

ISSN: 0898-2112 (Print) 1532-4222 (Online) Journal homepage: www.tandfonline.com/journals/lqen20

Quality Quandaries: Improving Revenue by
Attracting More Clients Online

Inez M. Zwetsloot &

Ronald J. M. M. Does

To cite this article: Inez M. Zwetsloot & Ronald J. M. M. Does (2015) Quality Quandaries:
Improving Revenue by Attracting More Clients Online, Quality Engineering, 27:1, 130-138, DOI:
10.1080/08982112.2014.968668

To link to this article: https://doi.org/10.1080/08982112.2014.968668

Published online: 21 Dec 2014.

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Quality Quandaries: Improving Revenue by
Attracting More Clients Online

Inez M. Zwetsloot ,

Ronald J. M. M. Does

Institute for Business and

Industrial Statistics (IBIS UvA),

Department of Operations

Management, Amsterdam

Business School, University of

Amsterdam, The Netherlands

INTRODUCTION

“A website offers a business . . . another avenue to generate revenue by
attracting more customers. Unfortunately, not all websites successfully turn visi-
tors into customers” (Chiou et al. 2010, p. 282). Fortunately, websites can be
improved, and the quality profession offers some guidelines for improvement.
This “Quality Quandary” provides an example of a Lean Six Sigma project with
respect to online marketing. Lean Six Sigma deals with improving processes on
a project-by-project basis (cf. De Mast et al. 2012).

This specific case study is about improving the sales of a consultancy firm by
attracting more clients through its website. The project follows the define–mea-
sure–analyze–improve–control (DMAIC) phases, as prescribed by Lean Six
Sigma. We first provide a brief background on the case study. Next, we describe
how the project has been executed following the five phases. Finally, we
conclude.

CASE STUDY

In 2014, a project aimed at increasing the number of clients was carried out at
a consultancy firm. The consultants of the firm give courses and training to pro-
fessionals within The Netherlands. In addition, they perform academic research
in the topics taught. The courses with open enrollment take 8 to 16 days dis-
tributed over a period of 4 to 6 months and start in February and September.

The objective of the project was to increase the number of participants (i.e.,
clients) in these courses by attracting more leads through the website. A project
team was formed (a project leader and two team members). The team also hired
two web designers from an external agency.

Define

In the define phase, the project leader described the process to be improved
and formulated the project objectives and their potential benefits.

The process to be improved is the acquisition process through the firm’s
website. The input to this process is a potential client searching online for a
course. The acquisition process can be described in four main steps and is dis-
played in Figure 1:

Edited by Ronald J. M. M. Does

Address correspondence to Ronald J.
M. M. Does, IBIS UvA, Amsterdam
Business School, University of
Amsterdam, Plantage Muidergracht
12, 1018 TV Amsterdam, The
Netherlands. Email: r.j.m.m.does@uva.
nl

Color versions of one or more of the
figures in the article can be found
online at www.tandfonline.com/lqen.

130

Quality Engineering, 27:130–137, 2015
Copyright� Taylor and Francis Group, LLC
ISSN: 0898-2112 print / 1532-4222 online
DOI: 10.1080/08982112.2014.968668

� A potential client has to find the firm’s website. An
initial analysis, of September 2013 through March
2014, showed that there were 74 visitors per day.
The definition of a “visit” is somewhat arbitrary and
will be discussed in the measure phase.

� Secondly, the potential client looks at the website
and the courses; an average visit consisted of scroll-
ing 3.2 webpages in 2.42 minutes.

� Next, the potential client has the option to request a
brochure through an online form. On average 1.7
persons request a brochure per day and they are
added to the firm’s client relationship management
(CRM) system as a lead.

� The final step is the registration for a course. On
average 7.8% of the leads register for a course.

It was estimated that 50% of the firm’s clients origi-
nated from a lead in the CRM system and the other
50% come from preferred supplier contracts and other
sources. The goal for this project was to increase the
number of clients, originated online, by 15%. This
implies a direct increase in revenues for the firm of
about €55,000.

Measure

The first step in the measure phase includes the
selection of clearly defined, measurable characteristics,
which are called critical to quality characteristics and
abbreviated by CTQs. We can schematically illustrate
how the CTQs relate to the project goal and strategic
focal points of the organization by means of a CTQ
flowdown (cf. De Koning and De Mast 2007).

A modified version of a CTQ flowdown discussed
by De Koning et al. (2010) is used for this project and
is illustrated in Figure 2.

In this project, we select two possible ways to
improve revenue: by identifying more prospects and
by improving the conversion rate from prospect to lead
with an online request for a brochure. Hence, the two
CTQs in this project are traffic and the conversion rate.
Traffic is the number of visitors to the website and the
conversion rate equals the number of leads as a percent-
age of the total traffic. Recall that a lead is a potential
client who requested a brochure online and is stored in
the firm’s CRM system.

FIGURE 1. Main process steps.

FIGURE 2. CTQ flowdown of the project.

Quality Quandaries 131

For both CTQs we need operational definitions. For
the CTQ traffic we define a prospect as a single user
who has a number of interactions on the website within
a given time frame. An interaction can be a page view, a
brochure request, or even registration for a course. Cli-
ents from the latter category will be handled differently
(cf. Figure 2). A visit ends if the user is inactive for 30
minutes. The CTQ traffic is defined as the total num-
ber of visits of single users in a given time frame.

Data on traffic were retrieved from the web analytics
program of the website and the number of leads was
obtained from the CRM system. Initially, the CTQs
were measured per day. However, it was discovered
that traffic displays a weekly pattern: on the weekend
traffic is lower than during the week. Figure 3 shows
this pattern for traffic in November and December
2013. Because the project leader was not interested in
this weekly pattern, she decided to measure the CTQs
on a weekly basis.

The measurement period was set from September
2013 to March 2014. This period includes 30 weeks
and the start of a training cycle (September) when
acquisition efforts are low, as well as the buildup period
toward a new training cycle (February) when acquisi-
tion efforts are high.

The last step of the measure phase is the validation
of the data in the system; that is, ensuring that the data
reflect the definitions. This was done by checking the
definitions as used by the web analytics program and
by checking the firm’s CRM system again.

Analyze

In the analyze phase, the current performance of the
CTQs is determined. A thorough analysis leads to a
diagnosis of the problem and a list of potential influ-
ence factors.

The CTQ traffic equals 520 visits a week on average,
with a standard deviation of 209. Figure 4 shows the
total traffic split up by type: 44.6% of the traffic origi-
nates from a search engine (organic); 26.7% of the traf-
fic comes in through online advertisements (paid);
16% of visitors use the URL to go to the website
(direct), 12.2% comes from links in mailing, news
items, and links on other websites (referral); and 0.5%
are from other sources.

The team was surprised by the large standard devia-
tion but realized that this could originate from a time
effect; traffic depends on the online advertisement bud-
get, which varies according to the intensity of the
acquisition process. From this budget, online advertise-
ments are bought to attract people to the website. The
line plot in Figure 5 shows that online campaigns dou-
ble the number of visits per week.

The current performance of the CTQ conversion
rate is on average 2.4% with a standard deviation of
1.0%. A control chart of the conversion rate is shown
in Figure 6. It shows that the conversion rate was
around 3.2% before the online campaign and then
dropped to 1.9% during the online campaign and
stayed at that level until March 2014. Note that during
the online campaign the number of visits per week was
around 800 and when there was no online campaign it
was around 400 (see Figure 5).

To find relevant influence factors for the CTQs, the
project leader performed a brainstorm session with the
project team, asked for advice from the web designers,

FIGURE 3. Control chart of traffic per day.

FIGURE 4. Bar chart of the types of traffic.

132 I. M. Zwetsloot and R. J. M. M. Does

searched the literature, performed a failure modes and
effect analysis, benchmarked with websites from com-
petitors, and spoke to clients about why they chose this
course. This resulted in a long list of potential influ-
ence factors.

Improve

In the improve phase, the project team selected the
most important influence factors and provided evi-
dence of their effects on the CTQs. Based on these
influence factors, they designed improvement actions
that would result in large improvement of the CTQs.
The team used a so-called priority matrix to categorize
the influence factors based on effect size and change-
ability. Influence factors that were thought to be large
in both effect and changeability were the following:

� Design of the website
� Content quality

� Accessibility
� Online marketing budget

An overview of these factors is presented in Table 1.
A core principle of Lean Six Sigma is evidence-based

improvement actions. Every influence factor was stud-
ied, and evidence was gathered, in order to understand
the effect of the influence factor on the CTQs. Next,
the project team designed a number of improvement
actions. In the following we discuss the evidence for
each influence factor as well as the related improve-
ment action.

The first influence factor “design of the website”
influences the conversion rate. Design is a creative pro-
cess and it is difficult to provide strong evidence for
the effect on the CTQs for something so broad as
design. The team decided to redesign the old website
and hired two professional web designers to help. To
focus the redesign process the team proceeded accord-
ing the following steps:

1. Using a so-called sitemap, navigability was made as
easy as possible. Ranganathan and Ganapathy
(2002) pointed out that ease of navigation of the
website is an important principle for business-to-
customer

website.

2. A Pareto analysis revealed which webpages, from the
old website, were visited most often. Using this
knowledge the team decided that four so-called
wireframes were needed. A wireframe is a functional
layout and design of a webpage. In order to save
time, and resources, the less popular webpages
would not get their own wireframe design and
would be made to fit the standard frame.

3. An analysis of the traffic data showed that 32% of
the traffic comes from tablets and mobile devices.
Therefore, it was decided that the website would be
optimized for all possible screen sizes—so-called
responsive web design.

4. The web designers made a new design for each wire-
frame and built the new website.

To show the effectiveness of redesigning the website
retrospectively, the team studied the bounce percent-
age: the percentage of paid visitors already leaving the
website on the entry page. Assuming that the bounce
percentage is a proxy for interest and ultimately also
conversion ratio, Figure 7 shows that people engage
more on the new website.

FIGURE 5. Line plot of traffic per week.

FIGURE 6. Control chart of the conversion rate per week.

Quality Quandaries 133

Another proxy used to evaluate the effect of rede-
signing the website is the duration of a visit. Data anal-
ysis showed that the average duration of a visit for
organic traffic increased from 2.42 minutes to 3.07
minutes after the redesign of the website, an increase of
15%.

The second influence factor, “content quality,” con-
cerns the relevance of the information provided by the
firm on the website (Hern�andez et al. 2009). The team
discussed the position of the firm in the market and
talked to clients to ask why they chose this course. Fur-
thermore, the unique selling points of the firm were
discussed. A conclusion was that the combination of
research and consulting is an important strength. This
was accentuated on the new home page. Furthermore,
some of the texts on the old website were reused in
condensed form.

The third influence factor, “accessibility,”mostly has
an effect on the CTQ traffic; the higher the position on
search engines, the more potential customers will find
the firm’s website; that is, the higher the traffic will be.
Accessibility is also one of the recommendations by

Hern�andez et al. (2009). As an improvement action the
team first defined five keywords for which it is impor-
tant that the firm is found. In December 2013 the rank-
ing of the website, on all five keywords, was in the first
10 hits on Google. To ensure that this ranking would
be maintained the new website was designed according
to search engine optimization rules (cf. Su et al. 2010).

Finally, for the influence factor “online marketing
budget,” the project leader used regression analysis to
study the effect on the CTQ traffic. The results are
graphically displayed in Figure 8 and show that the
budget spent on online campaigns strongly determines
(paid) traffic; every euro spent yields on average three
extra visitors. This effect is statistically significant.

Furthermore, the online marketing budget has a sta-
tistically significant effect on organic traffic. Figure 9
shows a rise in organic traffic of 52 visitors if the online
marketing is used. It can be concluded that some paid
traffic returns to the website through the search engines
later that week.

FIGURE 8. Fitted line plot of paid traffic versus cost.

FIGURE 7. Box plot of bounce percentage, old versus new

website. Connected symbols are the group

averages.

TABLE 1 Influence Factors that are Large in Both Effect and Changeability

Influence factor Evidence Effect on CTQ traffic Effect on CTQ conversion rate

Design of the website Client and expert interviews,

literature

No effect Positive effect

Content quality Literature, clients No effect Positive effect

Accessibility Expert interview, literature

on SEO (search engine

optimization)

High ranking on the

keywords has a positive

influence

No effect

Online marketing budget Analysis of proces data Three visitors per extra euro No effect

134 I. M. Zwetsloot and R. J. M. M. Does

Online marketing might increase both paid and
organic traffic, but that does not guarantee that it also
increases the number of clients. To be able to provide
better data for decisions regarding the marketing bud-
get, a special piece of software was programmed into
the website. This software tracks all paid traffic and
registers if a paid visitor requests a brochure; that is,
becomes a lead. In an 11-week period after the new
website was launched, 68 brochures were requested, of
which one was a paid visitor. Based on the data from
September 2013 through March 2014 we have an aver-
age conversion rate of 2.4% and know that 7.8% of the
leads register for a course. The average fee for a course
is €7,100. Hence, an extra lead and the additional
organic traffic if the online marketing is used resulted
in an expected return of €8,157. The cost in this period
were €1,079. This implies a return on investment of
756%; it was decided to keep the campaign budgets at
the current level.

Control

The improve phase resulted in improvement actions
that aim to change processes for the better. In the con-
trol phase the project team created a control plan to
deal with irregularities in the process and organized
continuous improvement and assigned roles and
responsibilities. Furthermore, the benefits of the proj-
ects were calculated and, finally, the project was closed.

In the control plan an important part is monitoring.
Monitoring can lead to insights and is useful for detect-
ing changes in performance and understanding the
CTQs’ behavior over time. It can also be used to quan-
tify the extent to which improvement initiatives have

been successful. The team set up monitoring tools for
both CTQs. The data from the analyze phase were
combined with 11 weeks of data starting a month after
the new website went live. This initial period of one
month was ignored in the data because the data were
contaminated by all of the work on the website done
by the team in the first weeks.

It is not possible to look at the average traffic before
and after the launch when quantifying the effect of the
new website. This would give a distorted conclusion
because traffic is very volatile and is dependent on
other factors apart from the website, as can be seen in
Figure 10.

The project team used regression analysis to control
for the factors influencing traffic in order to find the
effect of the new website on traffic. It was found that
there are four statistically significant factors to explain
traffic:

� Cost of advertisement
� Number of referral visits
� Old or new website
� Trouble with the server host

These four factors are explained below. The results
of the regressions analysis are displayed in Table 2.

The estimated transfer function equals

TrafficD 232C 3:4£CostC 2:2£Referral

C 123£Newsite¡ 206£ ServerCResiduals:

The cost of advertisement has a coefficient of 3.4,
which is approximately equal to the effect determined
in the analyze phase (see Figure 8). Referral traffic has a

FIGURE 10. Control chart of traffic split for old and new

website.

FIGURE 9. Individual value plot of organic traffic split by

online marketing campaign. Connected symbols are the group

averages.

Quality Quandaries 135

coefficient of 2.2, meaning that a visitor coming
through a link tends to come back a second time. The
term “New site” shows that traffic increased 123 on
average after the new website was launched. The term
“Server” is added because in the last 3 weeks of the data
gathering period there were problems with the server
host. An unexpectedly changed security setting resulted
in a situation where no brochures and forms could be
downloaded, quickly resulting in a drop in the search
engine rank and thus in the traffic.

A provisional conclusion is that the new website
attracts, on average, 123 extra visitors compared to the
old website. This is an increase of 23%. Because there
are only 11 observations (weeks) for the new website, of
which 3 are affected by the trouble with the server
host, this conclusion has to be verified when more data
become available.

Regarding the CTQ conversion rate, a Shewhart
control chart shows that the rate dropped significantly
after the new website was put online (see Figure 11).

The project team hypothesized that the reason for
this is that on the old website, potential customers who
were looking for the price of the courses had to request
a brochure and hence increased the conversion rate.
On the contrary, the new website displayed all informa-
tion on the price of courses. The team decided to
experiment with the online prices. Only part of the
price information was put online and the conversion
rate increased to a normal level. Figure 11 shows this
development of the conversion ratio. More data are
needed to draw a conclusion about the improvement
of the conversion rate. Preliminary results show that
the conversion rate is on the same level as in November
2013 to March 2014, which is around 1.8%. As traffic
increased by 20% and the conversion rate remained
constant, the number of clients from online marketing
will increase with about 20%, leading to a €70,000
increase in revenue (as opposed to the original goal of
€55,000). Note that the number of participants in the
open enrollment courses in September 2014 was 58,
which was 13 participants more than in September
2013. The increase in revenue was actually more than
€90,000.

CONCLUSION

This study demonstrates how Lean Six Sigma can
help increase revenues through improving online mar-
keting and sales. It illustrates how the DMAIC road-
map helps in providing focus and structure to an
improvement project. Core principles of Lean Six
Sigma, such as problem structuring with the help of
the CTQ flowdown and gathering evidence for pro-
posed influence factors, helped a great deal to manage
and focus the process of designing the new website.
The project improved the effectiveness of the online
acquisition process by approximately 20%, leading to
potentially 10% more clients per year. Finally, the
visual management system helped to secure that the
new website is retained.

ABOUT THE AUTHORS

Inez M. Zwetsloot obtained her master’s degree
(MPhil) in econometrics from the University of

FIGURE 11. Control chart of conversion ratio after the launch

of the new website.

TABLE 2 Regression Output for Traffic Related to Cost, Refer-

ral, Visits, Website, and

Server

S R-sq R-sq(adj) R-sq(pred)

68.9329 95.49% 94.98% 93.85%

Term Coef SE Coef T-Value P-Value

Constant 355.8 42.6 8.35 0.000

Cost 3.379 0.166 20.35 0.000

Referral 2.240 0.368 6.09 0.000

Website

Old ¡123.8 31.4 ¡3.94 0.000

Server

Yes ¡205.8 52.7 ¡3.91 0.000

136 I. M. Zwetsloot and R. J. M. M. Does

Amsterdam in 2013. Currently, she works for the Insti-
tute for Business and Industrial Statistics as a Lean Six
Sigma Consultant and is a Ph.D. student at the Univer-
sity of Amsterdam. Her current research interests include
robust exponentially weightedmoving average charts.

Ronald J. M. M. Does is Professor of Industrial Sta-
tistics at the University of Amsterdam; Director of the
Institute for Business and Industrial Statistics, which
operates as an independent consultancy firm within
the University of Amsterdam; Head of the Department
of Operations Management; and Director of the Insti-
tute of Executive Programmes at the Amsterdam Busi-
ness School. He is a Fellow of the ASQ and ASA and
Academician of the International Academy for Qual-
ity. His current research activities include the design of
control charts for nonstandard situations, health care
engineering, and operations management methods.

REFERENCES
Chiou, W. C., Lin, C., Perng, C. (2010). A strategic framework for web-

site evaluation based on a review of the literature from 1995–
2006. Information & Management, 47(5):282–290.

De Koning, H., De Mast, J. (2007). The CTQ flowdown as a conceptual
model of project objectives. Quality Management Journal, 14
(2):19–28.

De Koning, H., Does, R. J. M. M., Groen, A., Kemper, B. P. H. (2010).
Generic Lean Six Sigma project definitions in publishing. Interna-
tional Journal of Lean Six Sigma, 1(1):39–55.

De Mast, J., Does, R. J. M. M., De Koning, H., Lokkerbol, J. (2012). Lean
Six Sigma for Services and Healthcare. Alphen aan den Rijn, The
Netherlands: Beaumont Quality Publications.

Hern�andez, B., Jim�enez, J., Mart�ın, M. J. (2009). Key website factors in e-
business strategy. International Journal of Information Manage-
ment, 29(5): 362–371.

Ranganathan, C., Ganapathy, S. (2002). Key dimensions of business-to-
consumers web sites. Information & Management, 39(6):457–465.

Su, A. J., Hu, Y. C., Kuzmanovic, A., Koh, C. K. (2010). How to improve
your Google ranking: Myths and reality.Web Intelligence and Intel-
ligent Agent Technology (WI-IAT)IEEE/WIC/ACM International Con-
ference, 1: 50–57.

Quality Quandaries 137

Student Name:

Case Study Title:
[What is the title of the case study article?]

1. Issue:
[What is the major issue that the case study is about? Tell us about the company, organization, or industry]

2

. Discussion Questions:
[Type in the discussion questions below and then provide your detailed analysis and observations]

a.

b.

c.

d.

e.

3. Opinions & Suggestions:
[Any other observations in your analysis?]

4. References/Sources:
[List the articles, videos, or other sources you reviewed in this case study]

a.

b.

c.

Use the above format for your case study, including the section headers in bold. The main text (sections 1, 2, & 3) should fill a minimum of 3 full pages. Do not add extra spaces between paragraphs. Do not indent paragraphs. All text flush with left margin.

[
NOTE: Red italicized text in brackets is for your instructions only. Please delete this text as you complete your paper.]

2

This specific case study is about improving the sales of a consultancy firm by attracting more clients through its website. The project follows the define-measure-analyze-improve-control (DMAIC) phases, as prescribed by Lean Six Sigma. See the file below for the case study.

Quality Quandaries Improving Revenue by Attracting More Clients Online

Actions

Discussion Questions: Summarize the case study, in your own words, by answering the following questions. DO NOT use AI or any other prior or present student’s work.

A. Explain the purpose of each quality tool in the case study. Name each tool and then talk about why the tool was used.

B. What metrics were used to quantify the process?

C. What were the results/solutions that were implemented and why? 

D. What challenges were faced by the project team? How did they resolve them?

E. How would you use one of the quality tools referenced in another industry or topic?

Attached you will find two files containing source information for this case study and a basic template for you to complete and submit your work.

Each case study involves current events related to quality improvement tools applied to processes.  I will provide you with the topic and articles that can be found on the internet.  This will be followed by discussion questions that I expect you to address in your paper.

You will have two weeks to work on this assignment.  The deadline to submit your paper is shown in the syllabus.

1. Download the Case Study and the template and rename it [Student Name]_Case_Study_2 x.

2. Review the related material provided and focus on how they relate to the discussion questions.

3. Use your own initiative to seek out other sources of information related to this issue to develop further information for your response.

4. Develop your paper on the template provided and respond to the discussion questions in essay format.  Do not use cover sheets, table of contents, or any other pages not included in the template.

5. MINIMUM paper length is 3 full pages. (Note: reference list does not count for paper length) 1 inch margins.  Arial 12 point font.  Double Spaced.  All sections included in the template addressed.

6. Submit your completed paper in MS Word format before the due date.

Grading: 15 Points possible

Format – 5 points (1/2 point each)

Met the minimum page requirement (3 pages of case analysis); All pages numbered; Double spaced; 1 in. margins on all sides; Uses Arial font; 12 pt. font; Includes all required sections; No extra spacing between paragraphs; No indentations.  All text flush with left margin.; Student name single line in the header margin

Content – 10 points

1-4 points – Poor

5-6 points – Satisfactory

7-8 points – Good

9-10 points – Excellent