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Search Engine Optimization: What Drives Organic Traffic to Retail Sites?

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  • Michael R. Baye
  • Babur De los Santos
  • Matthijs R. Wildenbeest

Abstract

The lion's share of retail traffic through search engines originates from organic (natural) rather than sponsored (paid) links. We use a dataset constructed from over 12,000 search terms and 2 million users to identify drivers of the organic clicks that the top 759 retailers received from search engines in August 2012. Our results are potentially important for search engine optimization (SEO). We find that a retailer's investments in factors such as the quality and brand awareness of its site increases organic clicks through both a direct and an indirect effect. The direct effect stems purely from consumer behavior: The higher the quality of an online retailer, the greater the number of consumers who click its link rather than a competitor in the list of organic results. The indirect effect stems from our finding that search engines tend to place higher quality sites in better positions, which results in additional clicks because consumers tend to click links in more favorable positions. We also find that consumers who are older, wealthier, conduct searches from work, use fewer words, or include a brand name product in their search are more likely to click a retailer's organic link following a product search. Finally, the quality of a retailer's site appears to be especially important in attracting organic traffic from individuals with higher incomes. The beneficial direct and indirect effects of an online retailer's brand equity on organic clicks, coupled with the spillover effects on traffic through other online and traditional channels, leads us to conclude that investments in the quality and brand awareness of a site should be included as part of an SEO strategy.

Suggested Citation

  • Michael R. Baye & Babur De los Santos & Matthijs R. Wildenbeest, 2016. "Search Engine Optimization: What Drives Organic Traffic to Retail Sites?," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 25(1), pages 6-31, March.
  • Handle: RePEc:bla:jemstr:v:25:y:2016:i:1:p:6-31
    DOI: 10.1111/jems.12141
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    Cited by:

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    3. Jang, Sungha & Kim, Alex Jiyoung & Yoon, Jiho, 2022. "Multiple keywords management in sponsored search advertising with interrelated consumer clicks," Journal of Business Research, Elsevier, vol. 140(C), pages 459-470.
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    6. Patrick Winter & Paul Alpar, 2020. "Effects of search engine advertising on user clicks, conversions, and basket choice," Electronic Markets, Springer;IIM University of St. Gallen, vol. 30(4), pages 837-862, December.
    7. Dimitrios K. Nasiopoulos & Dimitrios A. Arvanitidis & Dimitrios M. Mastrakoulis & Nikos Kanellos & Thomas Fotiadis & Dimitrios E. Koulouriotis, 2023. "Exploring the Role of Online Courses in COVID-19 Crisis Management in the Supply Chain Sector—Forecasting Using Fuzzy Cognitive Map (FCM) Models," Forecasting, MDPI, vol. 5(4), pages 1-23, November.
    8. Harris, Mark N. & Novarese, Marco & Wilson, Chris M., 2022. "Being in the right place: A natural field experiment on the causes of position effects in individual choice," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 24-40.
    9. De los Santos, Babur, 2018. "Consumer search on the Internet," International Journal of Industrial Organization, Elsevier, vol. 58(C), pages 66-105.
    10. Artur Strzelecki, 2020. "Google Medical Update: Why Is the Search Engine Decreasing Visibility of Health and Medical Information Websites?," IJERPH, MDPI, vol. 17(4), pages 1-13, February.
    11. Kim, Alex Jiyoung & Jang, Sungha & Shin, Hyun S., 2021. "How should retail advertisers manage multiple keywords in paid search advertising?," Journal of Business Research, Elsevier, vol. 130(C), pages 539-551.
    12. Nagpal, Mayank & Petersen, J. Andrew, 2021. "Keyword Selection Strategies in Search Engine Optimization: How Relevant is Relevance?," Journal of Retailing, Elsevier, vol. 97(4), pages 746-763.
    13. Martin Reisenbichler & Thomas Reutterer & David A. Schweidel & Daniel Dan, 2022. "Frontiers: Supporting Content Marketing with Natural Language Generation," Marketing Science, INFORMS, vol. 41(3), pages 441-452, May.
    14. Charlson, G., 2020. "Searching for Results: Optimal Platform Design in a Network Setting," Cambridge Working Papers in Economics 20118, Faculty of Economics, University of Cambridge.
    15. Damianos P. Sakas & Ioannis Dimitrios G. Kamperos & Panagiotis Reklitis, 2021. "Estimating Risk Perception Effects on Courier Companies’ Online Customer Behavior during a Crisis, Using Crowdsourced Data," Sustainability, MDPI, vol. 13(22), pages 1-26, November.
    16. Peter Landry, 2021. "Keywords, limited consideration, and organic product listings," Quantitative Marketing and Economics (QME), Springer, vol. 19(3), pages 505-566, December.
    17. Intaka Piriyakul & Shawanluck Kunathikornkit & Montree Piriyakul & Rapepun Piriyakul, 2022. "Facial Skincare Journey: Consumer Needs Identification to Enhance Online Marketing," International Journal of Business Intelligence Research (IJBIR), IGI Global, vol. 13(1), pages 1-19, January.
    18. Darius Schlangenotto & Dennis Kundisch & Nancy V. Wünderlich, 2018. "Is paid search overrated? When bricks-and-mortar-only retailers should not use paid search," Electronic Markets, Springer;IIM University of St. Gallen, vol. 28(4), pages 407-421, November.

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    More about this item

    JEL classification:

    • L0 - Industrial Organization - - General
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets

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