How to induce workers to sell high-margin products? A field experiment

Last registered on December 21, 2020

Pre-Trial

Trial Information

General Information

Title
How to induce workers to sell high-margin products? A field experiment
RCT ID
AEARCTR-0005347
Initial registration date
February 05, 2020

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
February 07, 2020, 1:56 PM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated
December 21, 2020, 3:35 AM EST

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Region
Region

Primary Investigator

Affiliation
University of Cologne

Other Primary Investigator(s)

PI Affiliation
University of Cologne
PI Affiliation
University of Cologne
PI Affiliation
University of Cologne

Additional Trial Information

Status
In development
Start date
2020-02-01
End date
2020-12-31
Secondary IDs
Abstract
We collaborate with a retail company and investigate changes in the salesworkers' compensation system. In an RCT, we study the effect of assigning higher weights to high-margin products in the determination of workers' compensation. We compare two compensation systems. The first system is solely based on workers' individual performance (i.e., their revenue). In the second system, revenues of high-margin products are assigned higher weights than revenues of low-margin products, and the commission is based on weighted revenue. We study how the different compensation systems affect revenues from the different types of products, turnover, conversion rates (i.e., the rate at which customers being served by salesworkers buy the firm's products), and granted discounts.
External Link(s)

Registration Citation

Citation
Gürtler, Oliver et al. 2020. "How to induce workers to sell high-margin products? A field experiment." AEA RCT Registry. December 21. https://doi.org/10.1257/rct.5347-1.1
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2020-02-01
Intervention End Date
2020-05-31

Primary Outcomes

Primary Outcomes (end points)
Revenue (from different types of product)
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Conversion rate by product type, discounts, turnover
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We collaborate with a retailer operating 69 stores in Australia and New Zealand. The retailer employs salesworkers whose main task is to sell the firm's products in the stores. In an RCT, two (new) compensation systems are implemented in (about) half of the firm's stores, respectively, and the company has agreed to keep the treatments in the field for at least four months (i.e., until the end of May). The first system is solely based on workers' individual performance (i.e., their revenue). In the second system, revenues of different types of products are assigned different weights, and commission payments are based on weighted revenue. Both compensation schemes are piecewise linear; they have kinks at two pre-specified targets and become steeper once a target is reached. The commission systems are designed such that the average commission is about the same across systems (as calibrated with the 2019 revenue distribution).

Treatment A: Salesworkers' monthly compensation depends on their (unweighted) revenue in that month.

Treatment B: Salesworkers' monthly compensation depends on their weighted revenue in that month. Different weights are assigned to revenues of different types of products, with high-margin products receiving higher weights than low-margin products.

We study how the different compensation systems affect revenues from different types of product, turnover, conversion rates (i.e., the rate at which customers being served by salesworkers buy the firm's products), and granted discounts. We also study heterogeneous treatment effects with respect to workers’ pre-treatment performance (high- vs. low-performers) and tenure. We further conduct employee surveys to measure employee attitudes.

Due to the Covid-19 pandemic the travel agency unfortunately had to close their stores in spring 2020 and the RCT had to be stopped.
Experimental Design Details
Randomization Method
Pairwise matching by revenues in 2019
Randomization Unit
The randomization was implemented on the store level.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
69 stores (51 stores in Australia and 18 stores in New Zealand)
Sample size: planned number of observations
Actual headcount on the 1st of February (we do not yet have the precise data)
Sample size (or number of clusters) by treatment arms
About half of the stores (35 and 34) in each of the two treatments, respectively
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials