Map Based Search Booklet Cover

Spatial Search Dynamics and E-commerce Conversion

£17.50

Formal Bibliography of Research Sources Adam, S., Mukasa, K.S., Breiner, K., & Trapp, M. (2008). An apartment-based metaphor for intuitive interaction with ambient assisted living applications. Proceedings of the 22nd British HCI Group Annual Conference on People and Computers, 1, 67–75. Agarwal, R., & Venkatesh, V. (2002). Assessing a firm’s web presence: A heuristic evaluation procedure for the measure ment of usability. Information Systems Research, 13(2), 168-186. Ahlström, D., Cockburn, A., Gutwin, C., & Irani, P. (2010). Why it’s quick to be square: Modelling new and existing hierarchical menu designs. Proceedings of the SIGCHI Conference on Human Factors in Computing…

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Everyone’s Adding a Map to Their Store. Almost Nobody Should Be. (Here’s How to Know If You’re the Exception)

“Airbnb has a map. Zillow has a map. Uber Eats has a map. Maps are clearly the future of product discovery, so let’s put one on our site.”

Eighteen months and one agency invoice later, conversion hasn’t moved. Sometimes it’s gone backwards.

Here’s the uncomfortable part: the case for map-based search is real. It’s backed by genuine, credible research. It’s just pointed at three or four specific industries, and almost everyone borrowing the idea is borrowing it for the wrong one.

This article and its companion audio breakdown exist to save you the eighteen months. In under 20 minutes of reading, or one commute’s worth of listening, you’ll know exactly whether a map belongs on your product pages, and if it doesn’t, what actually does.

  • The real reason a map lifted bookings on Airbnb, and why it has almost nothing to do with the map itself
  • Why one of the biggest names in UX research found that most travel sites are hiding their own best feature from users, and what happens the moment they stop hiding it
  • The specific point in the booking journey where a map stops being a discovery tool and starts being something else entirely
  • Why a well-known study found that people’s stated preference for visual browsing and their actual measured behaviour flatly contradict each other
  • The counterintuitive fix three separate engineering teams landed on, independently, after their maps got more crowded, not less useful
  • A peer-reviewed study that pitted a traditional shop menu against a completely different way of organising products, and the margin by which it won will make you question your entire category structure
  • The one question that predicts, more reliably than any feature checklist, whether an interface will convert

This booklet synthesises findings from:

  • Adam, S., Mukasa, K.S., Breiner, K., & Trapp, M. (2008). An apartment-based metaphor for intuitive interaction with ambient assisted living applications. Proceedings of the 22nd British HCI Group Annual Conference on People and Computers, 1, 67–75.
  • Agarwal, R., & Venkatesh, V. (2002). Assessing a firm’s web presence: A heuristic evaluation procedure for the measurement of usability. Information Systems Research, 13(2), 168-186.
  • Ahlström, D., Cockburn, A., Gutwin, C., & Irani, P. (2010). Why it’s quick to be square: Modelling new and existing hierarchical menu designs. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’10), 1371–1380.
  • Airbnb Engineering. (2021). Beyond A/B Test: Speeding up Airbnb search ranking experimentation through interleaving. Airbnb Tech Blog.
  • Baymard Institute. (2026). Accommodations split view: The optimal layout for hotel & property rental search results. Research Report. ———. (2026). E-commerce cart abandonment rate statistics. Industry Benchmark. ———. (2026). E-commerce search UX benchmark: Large-scale study of 100+ sites. Industry Report.
  • Brooke, J. (2013). SUS: A retrospective. Journal of Usability Studies, 8(2), 29–40.
  • Chiu, T.-P., & Yang, Y.-C. (2024). A hybrid horizontal+vertical menu structure outperforms uniform horizontal menus for viewing efficiency. SSRN.
  • Cockburn, A., Gutwin, C., & Greenberg, S. (2007). A predictive model of menu performance. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’07), 627–636.
  • Djamasbi, S., Siegel, M., & Tullis, T. (2010). Generation Y, web design, and eye tracking. International Journal of Human Computer Studies, 68(5), 307-323. ———. (2011). Visual hierarchy and viewing behaviour: An eye tracking study. HCI 2011, Springer LNCS.
  • Findlater, L., Moffatt, K., McGrenere, J., & Dawson, J. (2009). Ephemeral adaptation: The use of gradual onset to improve menu selection performance. CHI 2009, 1655–1664.
  • Golledge, R.G. Wayfinding behaviour: Cognitive mapping and other spatial processes. Foundational Geography/Psychology.
  • Griffith, D.A. (2005). An examination of the influences of store layout in online retailing. Journal of Business Research, 58(10), 1391–1396.
  • Haldar, M. (2021). Improving search ranking for Maps. The Airbnb Tech Blog.
  • Han, S., et al. (2022). Mapping consumers’ cross-device usage for online search: Mobile- vs. PC-based search in the purchase decision process. Journal of Business Research.
  • Hart, S.G., & Stavenland, L.E. (1988). Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. Human Mental Workload, 139–183.
  • Hearst, M.A. (2006). Clustering versus faceted categories for information exploration. Communications of the ACM, 49(4), 59–61.
  • Huang, M.H. (2003). Designing website attributes to induce experiential encounters. Computers in Human Behaviour, 19(4), 425-442.
  • Iyengar, S.S., & Lepper, M.R. (2000). When choice is demotivating: Can one desire too much of a good thing? Journal of Personality and Social Psychology, 79(6), 995-1006.
  • Just, M.A., & Carpenter, P.A. (1976). Eye fixations and cognitive processes. Cognitive Psychology, 8(4), 441-480.
  • Katz, M.A., & Byrne, M.D. (2003). Effects of scent and breadth on use of site-specific search on e-commerce websites. ACM Transactions on Computer-Human Interaction, 10(3), 198–220.
  • Larson, K., & Czerwinski, M. (1998). Web page design: Implications of memory, structure and scent for information retrieval. CHI 1998, 25–32.
  • Laugwitz, B., Held, T., & Schrepp, M. (2008). Construction and evaluation of a user experience questionnaire. USAB 2008, LNCS, 5298, 63–76.
  • McKinsey & Company. (2024). The attention equation: Winning the right battles for consumer attention. Industry Insights Report.
  • Nielsen Norman Group. (2024). E-commerce user experience research report. (11th ed.). ———. (2024). Touch targets on touchscreens. UX Design Guidelines.
  • Parhi, P., Karlson, A. K., & Bederson, B. B. (2006). Target size study for one-handed thumb use on small touchscreen devices. MobileHCI ’06.
  • Prathipa, B., Alston, S., & Salathiyan, S. (2025). Decision fatigue significantly mediates the link between choice-overload interfaces and purchase abandonment. IJSREM, 9(9).
  • Resnick, M.L., & Sanchez, J. (2004). Effects of organisational scheme and labelling on task performance in product-centred and user-centred retail websites. Human Factors, 46(1), 104–117.
  • Robertson, G., et al. (1998). Data mountain: Using spatial memory for document management. UIST 1998, 153–162.
  • Scarr, J., Cockburn, A., Gutwin, C., & Bunt, A. (2012). Improving command selection with commandMaps. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 257–266.
  • Schmutz, P., Roth, S.P., Seckler, M., & Opwis, K. (2010). Designing product listing pages—Effects on sales and users’ cognitive workload. International Journal of Human Computer Studies, 68(7), 423-431.
  • Speicher, M., et al. (2017). VRShop: A mobile interactive virtual reality shopping environment. Proc. ACM Interact. Mob. Wearable Ubiquit. Technol., 1(3). ———. (2018). A virtual reality shopping experience using the apartment metaphor. AVI 2018, 17:1–17:9.
  • Townsend, C., & Kahn, B. E. (2014). The “visual preference heuristic”: The influence of visual versus verbal depiction on assortment processing, perceived variety, and choice overload. Journal of Consumer Research, 40(5), 993-1015.
  • Tuch, A.N., Bargas-Avila, J.A., & Opwis, K. (2009). Visual complexity of website: Effects on users’ experience, physiology, performance, and memory. International Journal of Human Computer Studies, 67(9), 703-715.
  • Vrechopoulos, A.P., et al. (2004). Virtual store layout: An experimental comparison in the context of grocery retail. Journal of Retailing, 80(1), 13–22.
  • Wang, Q., et al. (2014). An eye-tracking study of website complexity from a cognitive load perspective. Decision Support Systems, 62, 1-10.
  • Wood, R.E. (1986). Task complexity: Definition of the construct. Organisational Behaviour and Human Decision Processes, 37(1), 60-82.
  • Zaphiris, P., Kurniawan, S.H., & Darin Ellis, R. (2003). Age-related differences and the depth vs. breadth tradeoff in hierarchical online information systems. UI4ALL 2002, LNCS, 2615, 23–42.
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