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Field
Abstract
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Before
Small and micro enterprises are the foundation of emerging market economies. Despite their aggregate importance, these firms often operate with limited market information. A small merchant may observe her own performance, but she rarely observes the performance of comparable nearby peers. This lack of peer information may prevent merchants from accurately assessing their market position and from making effective business decisions. This study uses a randomized field experiment to examine whether providing merchants with peer benchmark information affects their future decisions and performance. Eligible stores are randomly assigned to either a control group or an informational treatment group. Treated stores receive weekly in-app access to peer-information (revenue and relative standing) based on comparable stores in the same industry category and within a 3-kilometer radius. We then compare treated merchants with control merchants to estimate whether access to peer benchmark information improves revenue and other business outcomes. We also examine whether the effect of peer information depends on the competitive environment in which it is deployed. Overall, the study estimates the causal impact of peer information on the future decision-making and performance of small and micro stores.
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After
Small and micro enterprises are the foundation of emerging market economies. Despite their aggregate importance, these firms often operate with limited market information. A small merchant may observe her own performance, but she rarely observes the performance of comparable nearby peers. This lack of peer information may prevent merchants from accurately assessing their market position and from making effective business decisions. This study uses a randomized field experiment to examine whether providing merchants with peer benchmark information affects their future decisions and performance. Eligible stores are randomly assigned to either a control group or an informational treatment group. Treated stores receive weekly in-app access to peer-information (revenue and relative standing) based on comparable stores in the same industry category and within a 3-kilometer radius. We then compare treated merchants with control merchants to estimate whether access to peer benchmark information improves revenue and other business outcomes. We also examine whether the effect of peer information depends on the competitive environment in which it is deployed. Overall, the study estimates the causal impact of peer information on the future decision-making and performance of small and micro stores.
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Field
Trial Start Date
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Before
June 29, 2026
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After
July 06, 2026
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Field
Trial End Date
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Before
August 31, 2026
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After
August 16, 2026
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Field
Last Published
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Before
June 23, 2026 08:38 AM
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After
July 03, 2026 03:17 AM
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Field
Intervention (Public)
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Before
The intervention provides small and micro stores with weekly peer-performance information through the Shouqianba app. Peers are defined as stores in the same industry category, and within a 3-kilometer radius of the focal store. Treated stores receive an in-app message notifying them that a new peer-information feature has been launched.The main experiment randomly assigns 100,000 vendors to euqal sized treatment and control groups: 50,000 vendors to the control group and 50,000 vendors to the treatment group. Treated vendors receive weekly peer-information (revenue and relative standing) displays through the app. Vendors in the control group receive no change to the app interface and do not receive access to the new peer-information feature. Outcomes are measured using administrative data from the platform at the store-week level.
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After
The intervention provides small and micro stores with weekly peer-performance information through the Shouqianba app. Peers are defined as stores in the same industry category, and within a 3-kilometer radius of the focal store. Treated stores receive an in-app message notifying them that a new peer-information feature has been launched. The main experiment randomly assigns 100,000 vendors to equal-sized treatment and control groups: 50,000 vendors to the control group and 50,000 vendors to the treatment group. Treated vendors receive weekly peer information (revenue and relative standing) displays through the app. Vendors in the control group receive no change to the app interface and do not receive access to the new peer-information feature. Outcomes are measured using administrative data from the platform at the store-week level.
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Field
Intervention Start Date
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Before
June 29, 2026
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After
July 06, 2026
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Field
Intervention End Date
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Before
August 31, 2026
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After
August 16, 2026
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Field
Experimental Design (Public)
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Before
The intervention provides small and micro stores with weekly peer-performance information through the Shouqianba app. Peers are defined as stores in the same industry category, and within a 3-kilometer radius of the focal store. Treated stores receive an in-app message notifying them that a new peer-information feature has been launched.The main experiment randomly assigns 100,000 vendors to euqal sized treatment and control groups: 50,000 vendors to the control group and 50,000 vendors to the treatment group. Treated vendors receive weekly peer-information (revenue and relative standing) displays through the app. Vendors in the control group receive no change to the app interface and do not receive access to the new peer-information feature.Outcomes are measured using administrative data from the platform at the store-week level.
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After
The intervention provides small and micro stores with weekly peer-performance information through the Shouqianba app. Peers are defined as stores in the same industry category, and within a 3-kilometer radius of the focal store. Treated stores receive an in-app message notifying them that a new peer-information feature has been launched. The main experiment randomly assigns 100,000 vendors to equally sized treatment and control groups: 50,000 vendors to the control group and 50,000 vendors to the treatment group. Treated vendors receive weekly peer information (revenue and relative standing) displays through the app. Vendors in the control group receive no change to the app interface and do not receive access to the new peer-information feature. Outcomes are measured using administrative data from the platform at the store-week level.
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Field
Randomization Method
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Before
Eligible stores in the main experiment will be randomly assigned at the store level to the control or treatment groups using computer-Eligible stores are randomly assigned at the vendor level to either the control group or the treatment group using computer-generated random assignment. Assignment is fixed for the duration of the experiment.
Randomization is stratified by industry, city, and market-intensity level. These variables are central to the research design because the effect of peer information may depend on the competitive environment in which the information is provided. Vendors in different industries face different demand conditions, pricing structures, and customer-retention strategies. Vendors in different cities operate in different local markets, with different consumer bases and business environments. Market intensity captures the degree of local competition and the density of comparable peers, which may shape how vendors interpret and respond to peer benchmarks.
Stratifying on these three dimensions helps ensure balance between the treatment and control groups across key determinants of vendors’ future decisions. It also allows us to examine heterogeneity in treatment effects across different competitive environments.
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After
Prior to the experiment, we will randomize firms into control and treatment groups. We begin with all firms subscribing to Shouqianba's service and apply the following eligibility filters before randomization. First, we require that a firm open the Shouqianba app at least once during the week immediately preceding the experiment to ensure the merchant’s engagement with the platform. The condition is analogous to McKenzie and Woodruff (2017), who restrict their sample to actively operating firms at baseline, since their treatment (i.e., management consulting) requires an active firm to receive it. Our treatment, which is peer information deliver, similarly requires an engaged merchant to be exposed to it. Second, we require firms to have at least 5 peers within a 3 km radius, ensuring a stable and reliable peer benchmark. Finally, we exclude firms with extreme performance, those earning more than 10 times or less than 1/10th of their peer median. All filters are based on the week immediately prior to the experiment.
We conduct block randomization within each stratum to assign 100,000 merchants into equal-sized treatment and control groups. Strata are defined based on the level of competition. Randomization is conducted at the merchant level within each stratum.
We define competition strata based on the number of firms operating in the same secondary industry category within a 3-kilometer radius. We use 3 kilometers based on evidence on short-distance urban mobility in China. Survey-based studies of retail catchment areas find that Chinese shoppers at neighborhood-scale retail centers are drawn overwhelmingly from within a 2–3km radius (Wang, Zhang, and Wang 2006). Consistent with this, e-bikes (the dominant mode for short local trips in Chinese cities) average round-trip distances of roughly 5–6km, implying a comparable one-way local travel radius (Weinert, Ma, Yang, and Cherry 2007). We classify markets into high-, medium-, and low-competition based on the distribution of the strata. This stratified randomization serves two purposes. First, it guarantees that the treatment and control groups are comparable in their competitive environment, preventing competition intensity from confounding our estimates of the benchmark information effect. Second, it provides the variation we need to test our hypothesis that the strategic response to benchmark information differs across market competition levels.
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Field
Intervention (Hidden)
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Before
Control group:
Stores in the control group receive no change to the app interface and do not receive access to the new peer-information feature.
Treatment: Peer revenue information, relative standing, and top-performer benchmarks
Stores receive weekly information on: their own revenue in the previous week; the median revenue of peer stores in the previous week; their percentile rank within the peer group; and the revenue of a peer store in the top 10 percent of the peer revenue distribution. Information is updated every Monday using the previous week’s performance.
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After
Control group:
Stores in the control group receive no change to the app interface and do not receive access to the new peer-information feature.
Treatment: Peer revenue information, relative standing, and top-performer benchmarks.
Stores receive weekly information on: their own revenue in the previous week; the median revenue of peer stores in the previous week; their percentile rank within the peer group; and the revenue of a peer store in the top 10 percent of the peer revenue distribution. Information is updated every Monday using the previous week’s performance.
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