This document describes a user persona and user stories for an online record store called Interstellar Records. The user persona is Rick "Rocky" Smops, a 43-year-old professor and DJ. Rocky's user stories involve finding albums that are unavailable or needed urgently. The document then estimates the user population size at around 20,000 users based on sales data and trends in vinyl sales. It outlines typical user session durations and describes a strategy to get users to opt-in to telemetry by offering early access to pre-orders. Finally, it proposes top analytic questions around user search, playlist usage, checkout abandonment, streaming, and interactions with curated selections.

1. Alison Kozol
User Experience Engineering
Assignment 7
What is your user persona and stories?
My user person is Rick “Rocky” Smops, a 43 year old professor at a community college in northeast Ohio.
Rocky runs a record label and djs in his spare time.
● Rocky wants to buy an album from a band that he cannot find.
● Rocky is unable to find a record in his local record store that he needs ASAP for a present.
● Rocky needs suggestions for records for his upcoming DJ gig
○ Rocky organizes his past searches for upcoming gigs.
What is the approximate size of your user population?
The approximate size of the user population is difficult to distinguish. Interstellar Records is based
on music distribution company Forced Exposure, which houses media from around 500 independent
labels. Almost half of these labels are exclusively distributed through Forced Exposure, so FE can
account for all sales of records on these labels. When Forced Exposure is not the exclusive
distributor of a label, they acquire anywhere from 1% to 80% of the records.
Notably, there were 94 albums that sold at least 10,000 copies on vinyl in 2014 ­­ up tremendously
from 46 titles in 2013. 57 percent of all vinyl albums sold in 2014 were purchased at independent
stores, while another 36 percent were shifted through non­traditional retailers (such as Web­based
stores like Amazon.com and clothing/lifestyle chains like Hot Topic and Urban Outfitters).
((​http://www.billboard.com/articles/columns/chart­beat/6422442/vinyl­album­sales­hit­historic­high­20
14​)).
Note that Forced Exposure distributes to Urban Outfitters, though this does not apply as part of the
user population, because those figures are considered to be distribution sales, not customer sales.
With vinyl sales increases more than steadily every year and no indication of slowing down,
Interstellar is in a great place. Not only can they rely on their return customers who have been
ordering records from them since the 80’s, but now they can look forward to obtaining a new
generation of millennial users who are learning to love vinyl. This is not even including the other
media Interstellar offers ­­ CDs, cassettes (also on the rise), apparel, DVDs, magazines, books, art,
and other collectibles. While they may serve a niche market, Interstellar is one of the few premier
names in this particular industry, so they have one of the larger user populations. Considering their
sales from last quarter (which I am unable to disclose due to promised confidentiality) were much
higher than expected, I would say that their potential user population is approximately 20,000 users.
What is your expected frequency and duration of user sessions, approximately?
I was unsure about this, so I did an informal poll of 10 friends who buy records at least once a month from
an online distributor. From my research I gleaned there are two main types of user sessions. The first is
really quick ­­ under 3 minutes. This is when the customer is familiar with the web app and knows the exact
item they would like to purchase: they will sign in, locate the record, make the purchase, and then log out.

2. The other type of user session is approximately 35­45 minutes. This session does not necessarily end in a
sale, as my research indicates that the main point of this type of session is not to buy, but to browse. That
said, there are certainly outliers of much longer periods of time. A friend reported that he could spend hours
on one site, clicking around with occasional jaunts to Wikipedia or Discogs to find additional information.
Describe your strategy for getting users to grant permission for telemetry. What percentage do
you think will sign up? In what ways might this population skew from the centroid, and how will
you attempt to detect and control that situation? (10 pts.)
My strategy for getting users permission for telemetry offers users a no­cost incentive. Interstellar has the
ability to offer pre­orders on specific records. A preorder is the option to reserve a copy of an album that has
not yet been released. This is very attractive to my persona and general user base because the rarest
records are usually pressed in small batches, so it can be difficult to reserve a copy of a particularly rare
record.
There will be a banner right below the menu bar on top of the page that will read something along the lines
of “Help Interstellar and gain early access to new releases.” Clicking the banner will send the user to a new
page that provides information about the offer.
“Hi Interstellar family!
We are working on making our new online store even better, and we could use your help! If you join us,
information from your sessions will be sent to us to optimize the store. The only thing you need to do is click
“Yes” below! And as a thank you, we can offer a month of Pro Preorder.
Yes or Ask Later”
My centroid user does not like to have his activity tracked, but my centroid user trusts the Interstellar name
after being a loyal customer for so many years. Additionally, not only does my centroid user have interest in
the incentive, but he has a vested interest in improving the online store, as he would benefit the most. My
secondary user is much younger and does not see harm or intrusion from sharing their session information.
The secondary user is also interested in the incentive.
This strategy appeals to the exact population I’d like to examine because a recurring customer is a. more
likely to see the banner than a one­time user b. care about the incentive. I will keep track of this by removing
outliers ­­ customers that have never bought anything or have just created an account in the past month. I
will also consider including a very brief demographic survey to ensure accuracy.
Describe the top 5 analytic questions that you want to answer. Provide the answer that you
expect, and explain under what circumstances your guess would be right and wrong. (20 pts.)
1. How do users search for albums?
I am interested in two answers from this question:
1) What is the most common search filter/field?
2) Which search methods yield the most sales?
I expect that users simply type in an artist or album (etc) name into the search bar and then use the results
to find what they are looking for. I can image my guess being wrong if purchases revolve more around new
releases or current events than they do around their own idea.

3.
2. What does a typical user created playlist look like and how often are they altered?
One function of the app is the ability to create lists similar to Amazon wish lists. Users are able to readily
store any album, song, or artist on the site in customized lists.
My guess is that users have 1­3 lists that they maintain regularly. Users may have additional lists that are
not often altered. I could be wrong if lists are rarely used due to poor UX (hopefully not!), or if the user
deems them worthless. Additionally, I could be wrong if users utilize multiple lists and maintain all of them. I
essentially want to know how to optimize the playlist based on the user's’ interactions with it.
3. Does the design of the checkout page make users cancel purchases?
I think that users may cancel or leave during a purchase mainly due to cost. They either find it more cost
efficient to purchase multiple items at once (to save on shipping), or they decide they cannot afford the item
they are considering. I would be wrong if the checkout is unintuitive and annoys the customer enough to
make them leave. This is crucial.
4. How often do users utilize the free streaming service in­site?
I want to know how much the streaming function affects purchases and searches, as well as the general
workflow of a session. My guess is that users will almost always stream before purchasing. The centroid
user is an audiophile and wants to ensure he is getting exactly what he wants. This guess could be wrong if
there simply is no indication of a trend between streaming and sales, searches, and session flow.
5. What interaction do users have with Interstellar curated selections?
On many pages of the site, Interstellar curates selections of records to display. For example, on any given
day, the Interstellar home page might have a small selection of “favorite holiday albums” or “Library Music of
the 50’s”. These are created to spark interest in records that users may not know about. The question here
should tell us how effective these selections are in comparison to a user’s own search pattern.
I expect that users will click on the curated selections at least once a session when the session is longer
than approx. 5 minutes. I could be wrong ­­ users may actually have very little interaction with the curated
selections and they prefer to navigate the site on their own.
For the previous section, where would you place your measurement points in your program to
find out what you want to know? (20 pts.)
1. How do users search for albums?
I will put measurements points in the search box and on the various filters the user can customize during the
search (ex. search by artist, album, etc.). I can then find out what average searches look like by examining
the most searched terms and filters. I would also put a measurement point on scrolling and clicking after a
search to measure the time it takes for users to get from search to purchase. I could examine this further by
running a t­test of search terms and purchases for a given time period. I could also look specifically at
high­frequency customers’ searches (i.e. those that purchase more than once/month over the course of 6
months) and their purchases to gain insight into successful search/purchase combinations.
2. What does a typical user created playlist look like and how often are they altered?
I would put a measurement point on the “playlist” button on the header bar as well as scrolling on the playlist
page, which would measure the frequency that users tend to their playlists. If possible, I would compare

4. random playlists from ~50 users. While the content of the playlists matters somewhat, the question of
whether or not users make use of the playlist function is more important.
3. Does the design of the checkout page make users cancel purchases?
For my project, the development of a new online store is rooted in possible financial gain, so I need to pay
close attention to the effect of design on frequency of purchases.
From an accessibility perspective: I could put measurement points on the checkout page and add a timer, so
I could measure how long the user spends on the checkout page. If it’s longer than the average length of
time needed to checkout in development mode (which I plan to measure), there are serious issues that need
to be resolved. I’d also like to compare the length of time spent on the checkout page with whether or not the
customer made a purchase (clicked the “submit purchase” button) to see if that sheds light on my question.
From a financial perspective I think a good strategy would be to pay attention to the cart after the user logs
out: Does the user delete the item from the cart before navigating away from the site? Or is it more likely that
the item remains in the cart, and if so, for how long will it remain inactive (not removed or purchased) in the
cart? I could compare that to more frequent customers’ cart activity.
4. How often do users utilize the free streaming service in­site?
This one is simple: I would put measurement points on the “play” button on the music player and also
measurements of page views of the albums. Then I could compare the number of plays to the number of
visits. I understand that the second measurement could confound my results, as some customers may
choose to listen to one song several times while only visiting a page once.
5. What interaction do users have with Interstellar curated selections?
I would place measurements on the curated selections section on the front page. I would also add
measurement points to the “add to cart” button on all of the albums included in the curated section to see if
they are added at a higher frequency than other albums.
How will you detect changes in user behavior over time? (For example, beginners do [this], but as
they gain more experience, they start doing [that] instead.) (15 pts.)
As users become more and more familiar with the Interstellar store, they will have an easier time finding
exact titles. Thereby, instead of searching for something and clicking through all the results to find what they
want, they will instead make use of the various filters to save themselves time. I will track this change by
looking at their searches and filters (using measurement points), and by creating a script that will compare
their time spent by some time interval, probably 6 months. The second measurement, the comparison of
time spent, will influence future tweaking of the site, as I can use data from seasoned users to help make the
interface more accessible to new users and more precise for all users.
Beginners may not create playlists, or they may not make playlists that are useful to them. Users that are
familiar with the site after half a year or so are far more likely to make use of the playlists. They will use them
to remember records they want to buy, which may lead to more sales. I will track this by measuring
frequency and extensiveness of the lists over time.
Essentially, measuring the amount of time users spend per session over time will be of great use, as I will be
able to quantify if, in fact, the search tool becomes more effective over time, as the user becomes more
comfortable with it. I believe that returning customers, over time, will spend more money per purchase than

5. beginners. This is because the additional features of the site, over time, will become more comfortable for
the user to enjoy, such as playlists, streaming, and customer/employee interaction.
Of the commercial telemetry providers that you can find, which do you think would be best for
your application and why? Or if you insist on rolling your own framework, explain why, and where
you would start doing that. (15 pts.)
http://www.sparringmind.com/best­web­analytics/
Piwik:
● Exit page analytics is crucial
● Site search and visitor log is exactly what I’m looking for ­­ love this layout
● Open source, so I could trick one of the developer’s I work with to help me add cool features :­)
● I like how it combines “campaigns” with all the other measures. I’ve used campaigns before with
MailChimp, so it’d be helpful to see how emails relate to traffic.
Google Analytics
● I use Google Analytics at work, and I don’t think it includes enough visitor information
Clicky
● Real­time is cool, but I’m not sure if it’s necessary
● Very extensive user insights ­­ almost intrusive!
● Lots of detail.
HaveaMint
● One time cost of $30 which is good for the company
● Almost all the same features as Piwik
Church Analytics
● Doesn’t stand out
Kissmetrics
● The most luxurious! This one has everything.. “track visitors not page views”. Lots of options here
● $200 ­ $700/month wouldn’t fly with such a small company
Open Web Analytics
● Free and differs from GA because it’s open source
● Not as elegant or extensive as others.
Clicktale
● Very deluxe. Can ​replay​ entire sessions!
● Includes site health ­­ not just if site is offline or not
● Drop report: shows exactly when users leave the site.
Crazy Egg
● Really obsessive with heatmaps.. not for me..
Bit.ly
● I think they should stick with their link shortening… their analytics are kind of weak
Piwik is the clear winner. Not only does it have incredible features, but it is free and open source. A free
analytics tool is crucial for such a small company. It’s also easy to use and gives an absurd amount of
insight.

6. Produce an imaginary data set from your measurements. Apply it to your analytical questions.
Explain why you think you were right about the ones you got right, and wrong about the ones you
got wrong. Explain how you would modify your program in response. (20 pts.)
1. How do users search for albums?
MIE 028LP
Mark Fell
Pelt
We The American People
We The American
The results show the varied ways that users can search for albums. Something that came to my attention
with these results is the last result, We The American People. Presumably, the user was looking for “We The
People/American Zoo”, a band that first went by “We The People” and then by “American Zoo”. The user
would not be able to find the artist they are looking for with that search term, although they should be able to
due to keywords. This sheds light on how creative the search engine needs to be to provide the correct
results.
“Pelt” is another example of properties the search engine must have. Pelt is the name of a band but it is also
the name of a label and catalog number. So this user could be looking for the band, the label, or an exact
title. Accessible filters like “artist” or “Catalog number” need to be readily available.
2. What does a typical user created playlist look like and how often are they altered?
User 224 ­ 3 lists
Roy
Ralph Carney ­ This is Ralph Carney!
Sikikojwirgpoejgms
Save
The Nomads ­ Stagger in the Snow
Bank ­ True Tempo
User 43 ­ 0 lists
User 929 ­ 1 list
To buy
TCB ­ Rather Happy Songs
Max Durante ­ Black Light
In Embrace ­ The Initial Caress
Rocks Throe ­ Legion EP
Lonely Walk ­ Teen

7. Baby Ford ­ Fabric 85
Clay Rendering ­ Snowthem
This user data would prove me wrong in that users do not seem to alter their playlists often. The first user
has some messy lists, one without anything on it! But they are still using the playlist function. The second
user doesn't have any playlists. The third user has one playlist, but it is well­maintained as there are only
brand new titles on the list. This would prove wrong my theory that newer users are less likely to have
well­maintained playlists.
I would want to gather more specific user data to see more details about the interactions to improve the UX.
I would want to add more indications of playlists around the site, such as implementing more “add to playlist”
buttons and the option to rename or create a new playlist on the same page as the album information. I
would also consider adding the list of playlists on a sidebar so it would show up on all pages, making it more
easily accessible.
3. Does the design of the checkout page make users cancel purchases?
User 599
2:15 minutes on page
Left at “Enter credit card information” step
User 1040
4:54 minutes on page
Left at “Enter credit card information” step
User 3920
4:03:49 hours on page
Left at “pick shipping method” step
From these results, I would infer that the credit card information step needs to be dramatically altered. I
would want to do extensive user testing to see the problem. I would hypothesize that users do not want to
enter their credit card information ­­ they would prefer to use Amazon or PayPal payments. I also assume
that the third user just left the tab open and forgot about the purchase.
4. How often do users utilize the free streaming service in­site?
Taken from best sellers of the month:
SUN CITY GIRLS​ ­ ​Torch of the Mystics
14,039 plays
COIL​ ­ ​Backwards
930 plays
VA​ ­ ​[Cease & Desist] DIY! Cult Classics from the Post­Punk Era (1978­1982)
8,002 plays
These results would indicate that exclusive titles get many more plays than non­exclusive titles. The first and
third titles on the list are exclusives, and it would be difficult to find a place to stream these albums

8. elsewhere. The second title is not exclusive and is fairly easier to find. I would want to make the exclusive
streams more prominent on the site, and perhaps encourage an email campaign to advertise.
5. What interaction do users have with Interstellar curated selections?
Week 6 ­ 6,003 clicks
Week 7 ­ 5,332 clicks
Week 8 ­ 8,338 clicks
These results would indicate that perhaps the content of the lists have more weight than their location, as
they have healthy activity for all three weeks.