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Some tips about optimizing the IA for retail web sites.
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Information Architecture in Retail:
Lessons from the Field
Nick Berry
- Overview and definitions- How IA manifests in retail- Challenges and opportunities- Questions
Definitions
Information architecture is a practice that takes into account… 1) all potential uses of information 2) the primary users of information 3) principles of information organization
…to build a communication model (web site, application, map).
Taxonomy is a knowledge organization paradigm that uses… 1) entities 2) attributes 3) relationships …to codify knowledge of a complex topic.
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knowledge & information
taxonomy filter
design filter
information consumer
Information architecture uses other knowledge organization paradigms besides taxonomy.
For instance, interaction design uses cognitive principles of learning to make machines more intuitive to use.
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Taxonomy is how we make sense of complex topics. It’s a way to break up big ideas into components.
Music follows a taxonomy:
rhythm
meter
tempo
timbre
pitch
key/mode
Each of these facets (components) can be used to identify a particular segment of music.3
These components, and their strictly defined relationships with each other, enable us to communicate because we are using a common information model.
part of speech
punctuation
tense
case
Grammar is another type of taxonomy:
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“the cat the dog is chasing”
Customers have to understand your IA
“The appreciation we have for music is intimately related to our ability to learn the underlying structure of the music we like – the equivalent to grammar in spoken or signed languages – and to be able to make predictions about what will come next.”
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Big questions information architects ask themselves
• How do people interact with content?– Make the IA flexible enough to deliver on changing usability
requirements– Use the Lego model of content architecture for easier revisions
• How does information affect business decisions?– Make the back end data meaningful enough to draw conclusions
• How can I make business owners support information architecture?– Developing KPIs that turn heads– Listening for pain points and easy wins: CVLs, bounce rates
• How can the principles of information architecture best serve the company and our customers?
– Constant analysis of goals– Constant research into customers – Make your initiatives match company initiatives and strategic
imperatives
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information architecture’s place in retail
• Retail is the most complex ecosystem for information architecture
• Same backend (intranet) organization problems as government, academia, etc
• Added complexity of persuasiveness
• If the IA is bad, they won’t buy your stuff
• IA contributes to trust
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IA and the customer experience
CX
preconceived notions
cost vs. quality
state of mind
information architecture
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information architecture in stores
• Signs, labels, directories, tags, charts = metadata
• What the staff is trained to say = content
• Store layout, directories = categories, navigation
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what do these signs mean?
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information architecture’s 3 goals in retail
goal #1: filtering out the noise & illuminating the target
goal #2: enabling reusability & consistency
goal #3: developing a common language & making sense of data
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Vendors and merchandisers provide a rich, complex set of product data and features.
Information architecture seeks to overcome complexity for the “average” customer.
This person is understood via testing.
goal 1: filtering & illuminating
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goal 1: filtering & illuminating
This goal is about finding stuff.
IA provides ways to filter out the noise in a large information ecology.
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goal 1: filtering & illuminating
• innovations in meaningful simplicity
• intuitive modeling paradigm that always works = holy grail of IA
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goal 1: filtering & illuminating
Retailer wants to get a specific message to each customer.
“Right information, right time, right place”
“Targeted customer communications”
“What we want to tell you”
Requires personas, segmentation, understanding of customer types
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1
2
3
4
goal 2: enabling reusability & consistency
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goal 2: enabling reusability & consistency
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1
2
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5
67
8
10
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goal 2: enabling reusability & consistency
this is the “Lego model”
of content architecture
goal 3: developing a common language…
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Camping Backpacking Family & car campingClimbing Rock climbing Ice climbing Mountaineering
Cycling Bike commuting Mountain biking Road cyclingSnowsports Backcountry skiing Cross-country skiing Downhill skiing Snowboarding Snowshoeing…etc
acti
vit
y
<meta name=“activity”>Mountain biking</meta>
goal 3: developing a common language…
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1
2
goal 3: developing a common language…
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goal 3: developing a common language…
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4
goal 3: developing a common language…
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5
goal 3: developing a common language…
6
24
goal 3: developing a common language…
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goal 3: …and making sense out of data
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gross margin (finance) = [net sales - cost of goods sold + annual sales return] – taxes –
employee salaries – litigation costs
vs.
gross margin (retail) = net sales - cost of goods sold
+ annual sales return – damages/shrinkage
gross margin (marketing) = net sales
finance division reporting system
retail division reporting system
marketing division reporting system
goal 3: …and making sense out of data
27 taxonomy as semantic backbone of enterprise
Gross margin (master definition)
Finance reporting systems
Marketing reporting systems
Other BI systems
goal 3: …and making sense out of data
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document management
systems
supply chain management
HR systems
product lifecycle
management
digital asset management
systems
document management
systems
CRM systems
goal 3: …and making sense out of data
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REI.com
Camping dept.
Clothing dept.
Cycling dept.
Travel dept.
Skiing dept.
Large
Lge
L
Lrg.
LG.
goal 3: …and making sense out of data
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REI.com
Camping dept.
Clothing dept.
Cycling dept.
Travel dept.
Skiing dept.
L
taxonomyor
master data team
Tower of Babel:
no taxonom
ist on staff
• Challenge #1: overcoming technology • Challenge #2: overcoming politics• Challenge #3: overcoming yourself
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challenges for information architects
• not enough resources (staff, servers, software)• bad architecture (systems, information)• poor information collection methodologies (info quality going out depends on quality going in)• bad modeling technique (same)• undefined processes or “black leaps”
Which leads me to….
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challenge #1: overcoming technology
• competition over ownership of data• competition over attribution of sales• competition over attention of customer (“green vest syndrome”)• competition for attention of leadership• competition for scarce resources (IT, money, staff/interns)• stress on someone else’s deadlines (making them look bad)• closing the feedback loop on research (the “you didn’t tell me/you didn’t include me” hissy fit)
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challenge #2: overcoming politics
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challenge #3: overcoming yourself
• never assume your perspective is the customer’s perspective. if you’re a taxonomist or an IA, you’re already too complex of a thinker. • don’t take things too seriously. it’s easy to lose credibility that way.• keep learning. IA doesn’t change much but its language does. • assume your viewpoint is limited. learn from other taxonomies and job roles. incorporate them into an ever widening world view and an ever more informed taxonomy.• be humble, not arrogant. Most other divisions and job roles think they are the center of the customer experience. treat them as though they are and suddenly they trust you and call on you.• listen to people sympathetically. they will tell you interesting stuff.• don’t win the battle but lose the war…
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allies
Develop relationships with the following key people:
• leadership• IT architects• DBEs/DBAs• UX professionals• search specialists• business analysts• analytics professionals• business process owners: find places where you can pick the low-hanging fruit, improve or streamline processes, and reach a wider audience.