MGMT 5500 Strategic Marketing AnswerDash Case Study Review the Dove Case:AnswerDashAnalyze the case using the sample case study analysis. For the exclusive

MGMT 5500 Strategic Marketing AnswerDash Case Study Review the Dove Case:AnswerDashAnalyze the case using the sample case study analysis. For the exclusive use of Y. Wang, 2020.
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REV: AUGUST 3, 2017
ELIE OFEK
JEFFREY D. SHULMAN
AnswerDash
On a cold, rainy afternoon in early 2014 Dr. Jacob O. Wobbrock, cofounder and CEO of
AnswerDash, met with the company’s other cofounder and CTO, Dr. Andrew J. Ko, to discuss the
company’s future plans. AnswerDash had developed a product that, in Wobbrock’s mind, was nothing
short of a revolution in how users could easily find answers to the questions they had while browsing
websites. Moreover, the cofounders firmly believed that their innovation had the potential to be highly
attractive to many businesses – allowing them to increase revenues, decrease customer support costs,
and improve the consumer’s online experience. In the year and a half since the September 2012
founding, the company had meticulously gathered evidence of the benefits their novel technology
generated for early adopter clients. As Wobbrock and Ko had hoped, these clients raved about the
amount of costly customer support tickets that had been reduced by AnswerDash’s customer selfservice support solution, which allowed web users to find answers to their questions with less effort
and without contacting the customer support staff of the company’s site they were on. Several of these
early clients also experienced increased revenue by using AnswerDash to ensure users had the
information they needed to complete a transaction. Quick self-service answers for web users were
translating into more successful online transactions for online businesses.
Although these results were encouraging, two situations related to customer acquisition and
retention spurred Wobbrock and Ko to think about making strategic changes to their go-to-market
approach that would allow scaling the business. First, despite selecting a pricing scheme intended to
encourage widespread adoption, the rate of new customer acquisition did not meet expectations. As of
April 2014, they had only four paying customers, and most of these customers were cultivated from
the team’s professional network. Even then it took months for potential customers to move from initial
contact to signing up. Second, Ben Bridge Jeweler, AnswerDash’s very first paying customer, had
recently decided to discontinue the service. This was disconcerting to the cofounders and caused them
to question whether they were targeting the right companies. While not ready to hit the “panic button”
just yet, Wobbrock and Ko realized that they had to do something differently.
Up to this point, the young startup had basically talked to anyone willing to listen to it and pursued
any contact supplied by a colleague or friend. But Ko began to question this “shot-gun” approach: “We
need more clarity on who we are trying to target. That will frame our strategy for how we want to
continue to build the product, how we should communicate it, and how we should price it.”
HBS Professor Elie Ofek and Professor Jeffrey D. Shulman (University of Washington, Foster School of Business) prepared this case. It was reviewed
and approved before publication by a company designate. Funding for the development of this case was provided by Harvard Business School
and not by the company. HBS cases are developed solely as the basis for class discussion. Cases are not intended to serve as endorsements, sources
of primary data, or illustrations of effective or ineffective management.
Copyright © 2016, 2017 President and Fellows of Harvard College. To order copies or request permission to reproduce materials, call 1-800-5457685, write Harvard Business School Publishing, Boston, MA 02163, or go to www.hbsp.harvard.edu. This publication may not be digitized,
photocopied, or otherwise reproduced, posted, or transmitted, without the permission of Harvard Business School.
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AnswerDash
Wobbrock agreed, but noted, “We’ve seen AnswerDash create value for both E-Commerce and
software service firms across various industries. Each of our customers has a unique application that
solves a different problem, yet we are still able to boost the bottom line of all of them. Before we proceed
with a sharper focus, we need to carefully weigh our alternatives. And we certainly don’t want to lose
any more of the precious customers we have managed to sign on.”
Industry Background
In general, support solutions designed to help online users find answers to their questions can be
classified into two categories: self-service and assisted-service. In self-service support solutions, users
worked within the user interface to find the answers themselves. Examples included Frequently Asked
Questions (FAQ) pages, knowledge bases, and Q&A forums. In assisted-service support solutions, users
connected with a company representative who could provide answers. Examples included email, live
chat, and phone calls.
Several companies offered a suite of both self-service and assisted-service solutions. Two major
players in the industry included Salesforce’s Desk.com and Zendesk. Both companies offered selfservice solutions allowing their customers to publish a knowledge base and to let end-users solve each
other’s problems in forums on company-branded support sites. Both companies also allowed customer
support agents to view and respond to support tickets from email, phone, web, live chat, and social
media channels through a coordinated universal inbox that was integrated with the knowledge base.
Zendesk launched in 2007 and had its IPO in May 2014, the same year it earned $127 million in revenue
from more than 51,000 customers. Zendesk charged between $5 and $99 per month per customer
support agent (so-called “seat-based pricing”) who accessed the system. Larger companies, who had
many customer support agents to respond to high ticket volumes, would therefore pay substantially
higher than a small company with a single customer support agent who could generally handle
roughly 40 customer support tickets per day. The higher-priced plans offered ticket management tools,
self-service help centers, community forums, and analytics tools. Salesforce.com Inc., an enterprise
software firm that offered a popular suite of customer relationship management tools, launched
Desk.com in January 2012 after acquiring customer support company Assistly for $80 million in
September 2011. Desk.com charged between $30 and $135 per support agent, per month. Higher-level
packages allowed for integration with Salesforce.com’s customer relationship management software
so that companies could seamlessly merge customer support information with sales contact
information. Salesforce.com had over 100,000 customers at the time of Desk.com’s launch.
The industry was experiencing a shift in end-user preferences. Research by Forrester found a
growing desire for, and usage of, web and mobile self-service options over speaking to agents on the
phone. In 2009, a survey of 4,653 individuals found that 36% of surveyed consumers strongly preferred
to be self-reliant online and that percentage jumped to 46% when considering only 18- to 29-year-olds.1
In fact, web self-service use increased from 67% to 76% from 2012 to 2014.2 A 2013 report by
eDigitalResearch surveyed customers to find how the preferred method of contact for assisted-service
solutions depended on the situation (see Exhibit 1).
AnswerDash Company History
The Problem
Jacob O. Wobbrock and Andrew J. Ko were accomplished professors in the field of humancomputer interaction (HCI) at the University of Washington’s Information School. The genesis of their
2
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AnswerDash
516-106
idea, upon which they would later found their business, was a research project the two had
collaborated on with doctoral student Parmit Chilana. The team of scholars was fascinated with what
became known in human-system communication as the vocabulary problem, whereby different users
provided different words to describe the very same issue or goal. For example, in a seminal study,
researchers gave more than one thousand pairs of participants the following instructions: “On a piece
of paper write the name you would give to a program that tells about interesting activities occurring
in some major metropolitan area (e.g., ‘this program would tell you what is interesting to do on Friday
or Saturday night’). Make the name 10 characters or less. Try to think of a name that will be as obvious
as possible, one that other people would think of.”3 The researchers found that fewer than a dozen
pairs agreed, leading to the conclusion that less than 1.2% of participants could have accessed the
command directly had it been named by their partner. Another way to interpret the results was that
given the variance in how people referred to the very same command, a particular command would
need to have multiple names, or “aliases,” associated with it to guarantee a “match” by someone else
(see Exhibit 2 for the number of optimally selected names an object must have in order to yield a
particular success rate by users).
Previous research had found that the vocabulary problem was one of several reasons why web
users could not locate useful answers from existing self-service support solutions. In fact, individuals
seeking information rarely knew what information might actually be useful to them and therefore had
difficulty specifying what they needed retrieved.4 As a consequence, users were often frustrated by
being directed to a FAQ page and having to sift through reams of irrelevant text or type in a query,
only to get a list of answers with limited applicability to their interest or actual question.
The Solution
Chilana, Ko, and Wobbrock’s research grew out of this user-centered problem. Wobbrock
explained, “People around the world struggle to get the most out of the web because they cannot
always understand the functionality of various components on the webpages they visit, for example,
‘What does this button do?’ Moreover, the ability to receive answers to content-related queries, such as
‘Can I return this item to the store?’ or ’Can I get a discount if I buy more than one item?’ was
inconvenient and often frustrating.”
Chilana, Ko, and Wobbrock hypothesized that if they could directly embed answers into the web
experience, right where the questions arose in the first place, users could get answers quickly and move
forward successfully. As Wobbrock explained, “What a user does with any tool is try to map their
intention to the tool’s operation. A simple example is a hammer: If I want to drive a nail, I don’t care
about the hammer itself. The hammer is the way to achieve my goal, but I have to map my intention
for nail-driving to the hammer’s motion. It’s the nail I care about. Similarly, the vocabulary problem
arises when you are trying to match your intention to ‘get help’ into the help tool’s operation. You often
end up searching for help with different terms than the help authors anticipated. You might write ‘How
do I upload a picture?’ and I might write ‘How do I add an image?’ Someone else might say ‘How do
I insert a photo?’ People use different verbs and nouns, which becomes problematic for query-based
help solutions. We reasoned the vocabulary problem could be resolved if people can get help by
clicking on the objects they have questions about in the interface itself. No more typing search terms.”
They envisioned a platform that would allow the user to simply click on text or objects on a webpage
and immediately receive clarifications and answers to FAQs directly related to that text or object. As
Wobbrock and Ko put it, “Such a solution would remove the need for the user to engage in trial and
error in an attempt to guess what keyword to enter or having to sift through a laundry list of irrelevant
answers.”
3
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AnswerDash
They originally dubbed the approach they had developed LemonAid, conceived as a method to
“allow users to ask for help by selecting a label…or other user interface (UI) element, rather than
choosing keywords.”5 Wobbrock expanded on the solution they had in mind: “The idea is to
automatically link every element on a webpage (text or object) to a set of Q&A that are pertinent to that
element and then provide the user the ability to simply point and click on any element and receive
answers. Pointing-and-clicking on an element triggers a search—but without typing search terms—
that brings forth the most relevant Q&A for that object.” The researchers built a prototype and tested
its efficacy with a simulated community of users online who were compensated for their participation
in the study. The study found LemonAid provided relevant information to more than half of the
queries, which was much better than the performance of text-based queries for which users need to
exert much more effort. The researchers were pleased with the findings and conducted field studies to
corroborate the results. For further studies, the researchers subsequently added features that improved
the discovery of existing help content, allowed for moderation of help content, offered analytics to
show the relevance of information, and made external implementation and setup possible. The
improved version of LemonAid was piloted by four groups within the University of Washington6
where over 70% of survey end-users indicated they were likely to use it again (see Exhibit 3 for the
findings from these pilots). The feedback from the groups that piloted LemonAid was also very positive
as they experienced a decline in redundant questions asked via email or in person. The team was
thrilled with the results.
Although the project was borne out of academic curiosity and a genuine desire to understand how
to improve user experience on the web, the research team got an initial indication that they had created
something commercially viable in the fall of 2010. At this time, Chilana presented the research to a team
of design engineers and tech support staff at Facebook who showed keen interest in her work. Chilana,
Ko, and Wobbrock approached the University of Washington’s Center for Commercialization for
guidance on how to protect the intellectual property. In the process, they were assigned an
entrepreneur-in-residence, Ken Myer, to evaluate whether there might be a market for their technology.
Myer had served as an executive at several successful technology organizations and, as entrepreneurin-residence, had looked at many early stage ventures to see which could be turned into profitable
businesses.
Myer was convinced that a successful company could be built around LemonAid. He was struck by
the ease with which he understood the potential value proposition. He personally related to the
frustration of not being able to find relevant answers to questions or having to spend time with
customer support. He also viewed Wobbrock as a highly credible expert in this domain with the
personal characteristics of an entrepreneur who could take the technology to the next level. In fact,
prior to earning his Ph.D. in Human-Computer Interaction at Carnegie Mellon University in 2006,
Wobbrock had worked as an engineer in a Silicon Valley software startup, so he had direct experience
of what a startup life entailed. Myer saw in him an excitement about commercializing the technology
and reconnecting to those startup days, only this time from the vantage point of being the founder.
From Concept to Company
The three researchers faced a unique dilemma. They had all begun the project in hopes of furthering
their academic careers. However, early indications of its commercial viability gave them reason to
ponder pursuing a different path. For Wobbrock, who was already tenured and about to enter his
sabbatical, this would represent an opportunity to return to the startup scene he had enjoyed
previously; he felt a strong urge to try and ‘go big’ and establish a highly profitable firm. For Ko, who
was not yet tenured and would be going up for promotion to associate professor soon, it was more
about using a commercial company as a vehicle to disseminate his academic discoveries. However,
4
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AnswerDash
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Chilana had sought a Ph.D. in hopes of launching her academic career. They each needed to make a
tough decision.
Ultimately, Wobbrock and Ko decided to found a company, which they initially named Qazzow
Inc., in September 2012, and Chilana decided to pursue her passion for academic research, joining the
University of Waterloo after obtaining her Ph.D. Chilana would be a named founder of Qazzow but
was never operational in the company. The University of Washington approved Wobbrock’s sabbatical
on the premise that he would take charge as CEO of the company and engage in translating research
from the lab to the field. Ko would serve as CTO of the company while continuing his position as a
professor at the university. Wobbrock and Ko settled on a deadline to raise capital by the end of
Wobbrock’s yearlong leave, which would be the trigger for Ko to take a leave of absence and join
Qazzow Inc. full time.
The two operational founders were eager to find out how potential customers would respond to
their concept before they invested heavily in improving upon the prototype. Hence, they decided to
make their early customer pitches with just a demo video based on their research and the pilots they
had done at the university. Even so, their first pitch was a success in that the company that saw the
video enthusiastically agreed to try the product. In preparing the prototype for the live demo,
Wobbrock and Ko realized they faced a challenge. LemonAid was built appropriately crudely to prove
the efficacy of providing contextual answers to web users, not with any commercial customer and its
IT ecosystem in mind. Wobbrock and Ko now had to worry about details such as user interface and
browser compatibility, customizability, security, scalability, and other concerns that lay beyond the
initial research investigations. In short, they had to turn a research project into a commercial product. They
immediately got to work building the first commercial version.
Energized by the successful customer pitch, Wobbrock sought help from Myer in making
introductions to other potential customers. By the end of 2013, Qazzow had achieved several
milestones: in August, Matt Blythe became their first employee as Director of Customer Development;
in September, Andrew Ko began a leave of absence to dedicate himself full-time to the company; in
November, Qazzow raised a seed round of $500,000; and in December Qazzow raised $2.54 million in
venture capital. Ken Myer and Bill McAleer, from Voyager Capital, joined the board of directors.
Investors had concerns that the name Qazzow was difficult to pronounce and customers may have
trouble remembering how to spell it when attempting to access the site. So at the first board meeting
in January 2014, it was resolved that Qazzow would be renamed AnswerDash.
AnswerDash Initial Marketing and Sales Strategy
Product
AnswerDash created a self-service customer support so…
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