Babur De los Santos

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

The lions 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 retailers 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 greater the brand equity 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 better-branded sites in better positions, which results in additional clicks, since 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 retailers organic link following a product search. Finally, the brand equity of a retail site appears to be especially important in attracting organic traffic from individuals with higher incomes. The beneficial direct and indirect effects of an online retailers 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.

What's in a Name? Measuring Prominence, and Its Impact on Organic Traffic from Search Engines

Organic product search results on Google and Bing do not systematically include information about seller characteristics (e.g., feedback ratings and prices). Consequently, it is often assumed that a retailer’s organic traffic is driven by the prominence of its position in the list of search results. We propose a novel measure of the prominence of a retailer’s name, and show that it is also an important predictor of the organic traffic retailers enjoy from product searches through Google and Bing. We also show that failure to account for the prominence of retailers’ names—as well as the endogeneity of retailers’ positions in the list of search results—significantly inflates the estimated impact of screen position on organic clicks.

Search with Learning

This paper provides a method to estimate search costs in an environment in which consumers are uncertain about the price distribution. Consumers learn about the price distribution by Bayesian updating their prior beliefs. The model provides bounds on the search costs that can rationalize observed search and purchasing behavior. Using individual-specific data on web browsing and purchasing behavior for electronics sold online we show how to use these bounds to estimate search costs. Estimated search costs are sizable and are found to relate to consumer characteristics in intuitive ways. The model outperforms a standard sequential search model in which the price distribution is known to consumers.

Search With Learning for Differentiated Products: Evidence from E-Commerce

This article provides a method to estimate search costs in a differentiated product environment in which consumers are uncertain about the utility distribution. Consumers learn about the utility distribution by Bayesian updating their Dirichlet process prior beliefs. The model provides expressions for bounds on the search costs that can rationalize observed search and purchasing behavior. Using individual-specific data on web browsing and purchasing behavior for MP3 players sold online we show how to use these bounds to estimate search costs as well as the parameters of the utility distribution. Our estimates indicate that search costs are sizable. We show that ignoring consumer learning while searching can lead to severely biased search cost and elasticity estimates.

Do MSRPs Decrease Prices

The nature of manufacturer’s suggested retail prices (MSRP) and whether their effect is pro or anticompetitive is not well understood. Opposing theories suggest that manufacturers may attempt to reduce retail prices to deter double marginalization or increase retail prices to foster upstream or downstream collusion. We exploit a policy experiment in South Korea in which MSRPs were banned and then reinstated one year later to estimate their impact on prices. The ban increased prices by 2.3 percent and the reinstatement decreased prices by 2.6 percent, demonstrating the pro-competitive effect of MSRPs. Based on a lack of evidence that recommendations act as binding price ceilings, we offer an alternative explanation in which MSRPs provide information to searching consumers. We demonstrate that the removal of recommendations can reduce search and increase prices.