Some tips about optimizing the IA for retail web sites.

1. Information Architecture in Retail: Lessons from the Field Nick Berry

3. 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. 1 1

4. 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. 2

5. Taxonomy is how we make sense of complex topics . It’s a way to break up big ideas into components. Music follows a taxonomy: Each of these facets (components) can be used to identify a particular segment of music. 3 rhythm meter tempo timbre pitch key/mode

6. These components, and their strictly defined relationships with each other, enable us to communicate because we are using a common information model . Grammar is another type of taxonomy: 4 “ the cat the dog is chasing” part of speech punctuation tense case

10. IA and the customer experience preconceived notions cost vs. quality state of mind information architecture 8 CX

12. what do these signs mean? 10

13. 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 11

14. 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 12

15. goal 1: filtering & illuminating This goal is about finding stuff. IA provides ways to filter out the noise in a large information ecology. 13

17. 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 15

18. 1 2 3 4 goal 2: enabling reusability & consistency 16

19. goal 2: enabling reusability & consistency 17

20. 1 2 3 4 5 6 7 8 10 18 goal 2: enabling reusability & consistency this is the “Lego model” of content architecture

21. goal 3: developing a common language… 19 Camping Backpacking Family & car camping Climbing Rock climbing Ice climbing Mountaineering Cycling Bike commuting Mountain biking Road cycling Snowsports Backcountry skiing Cross-country skiing Downhill skiing Snowboarding Snowshoeing …etc activity <meta name=“activity”>Mountain biking</meta>

22. goal 3: developing a common language… 20 1 2

23. goal 3: developing a common language… 21 3

24. goal 3: developing a common language… 22 4

25. goal 3: developing a common language… 23 5

26. goal 3: developing a common language… 6 24

27. goal 3: developing a common language… 25 7

28. goal 3: …and making sense out of data 26 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

29. 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

30. goal 3: …and making sense out of data 28 document management systems supply chain management HR systems product lifecycle management digital asset management systems document management systems CRM systems

31. goal 3: …and making sense out of data 29 REI.com Camping dept. Clothing dept. Cycling dept. Travel dept. Skiing dept. Large Lge L Lrg. LG.

32. goal 3: …and making sense out of data 30 REI.com Camping dept. Clothing dept. Cycling dept. Travel dept. Skiing dept. L taxonomy or master data team

33. Tower of Babel: no taxonomist on staff

39. Questions? [email_address] 37