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Marketing Analytics in Emerging Markets: Evaluating the Impact of Access to Analytics for Micro Entrepreneurs in Rwanda
Last registered on June 17, 2020

Pre-Trial

Trial Information
General Information
Title
Marketing Analytics in Emerging Markets: Evaluating the Impact of Access to Analytics for Micro Entrepreneurs in Rwanda
RCT ID
AEARCTR-0005591
Initial registration date
March 24, 2020
Last updated
June 17, 2020 6:46 PM EDT
Location(s)
Region
Primary Investigator
Affiliation
Stanford University
Other Primary Investigator(s)
PI Affiliation
PI Affiliation
PI Affiliation
Additional Trial Information
Status
Completed
Start date
2019-06-01
End date
2020-03-31
Secondary IDs
Abstract
The key idea of our research project is – “How can knowledge of analytics have an impact on small scale entrepreneurs and their business?” Specifically, we seek to improve the growth of small firms in emerging markets by addressing a significant constraint they face: access to marketing information & marketing analytics. Few micro and small enterprises formally record their marketing data (e.g. sales, products, customers) which hampers their ability to extract meaningful insights from business information. The lack of knowledge of metrics and analytics (business intelligence) needed to use business information, limits firms’ ability to overcome constraints or take advantage of opportunities. Our research uses a randomized controlled field experiment (RCFE) to measure the impact on business performance of an easy-to-use, mobile app-based information and analytics tool (conceptualized by us) that increases an entrepreneur’s ability to track, access and take actions on key marketing information. Our aim is to better understand the role of marketing information and analytics in improving firms’ ability to derive useful insights. We also intend to study how it can be used to change the mind-set of the entrepreneurs and unlock the potential of emerging-market enterprises in a cost-effective, scalable way.
Keywords: Information, Growth, Marketing, Analytics, Entrepreneurship
External Link(s)
Registration Citation
Citation
Anderson, Stephen et al. 2020. "Marketing Analytics in Emerging Markets: Evaluating the Impact of Access to Analytics for Micro Entrepreneurs in Rwanda." AEA RCT Registry. June 17. https://doi.org/10.1257/rct.5591-2.0.
Experimental Details
Interventions
Intervention(s)
The key idea of our research project is – “How can knowledge of analytics have an impact on small scale entrepreneurs and their business?” Specifically, we seek to improve the growth of small firms in emerging markets by addressing a significant constraint they face: access to marketing information & marketing analytics. Few micro and small enterprises formally record their marketing data (e.g. sales, products, customers) which hampers their ability to extract meaningful insights from business information.
Intervention Start Date
2019-07-01
Intervention End Date
2020-03-31
Primary Outcomes
Primary Outcomes (end points)
Main effect is measured on - sales and profits (firm growth), in addition we will also try to identify the mediating mechanisms leading to the effect (if any).
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Our sample consists of 550 growth-oriented entrepreneurs. The baseline data was collected and verified for this set of firms (n=550),and the participants were randomly assigned into one of three experimental groups:

1. Group 1 (treatment): 250 entrepreneurs receive a smartphone with the “MARKETmanager” tool, a mobile app tool that is focused on tracking key business metrics related to entrepreneurs’ management of marketing activities (e.g. products and customers, and related policies/practices).

2. Group 2 (pure control): 250 entrepreneurs form a counter-factual group that does not receive any intervention during the project (note: they will be given access after the project ends).

3. Group 3 (placebo): 50 entrepreneurs form a second comparison group that receives only a smart phone and data plan (they will not be given any marketing analytics apps, tools, intervention, etc.)
Experimental Design Details
Our sample consists of 550 growth-oriented entrepreneurs. The baseline data was collected and verified for this set of firms (n=550),and the participants were randomly assigned into one of three experimental groups: 1. Group 1 (treatment): 250 entrepreneurs receive a smartphone with the “MARKETmanager” tool, a mobile app tool that is focused on tracking key business metrics related to entrepreneurs’ management of marketing activities (e.g. products and customers, and related policies/practices). The tool prompts entrepreneurs daily or weekly to complete a series of simple and straightforward questions about their business. Entrepreneurs are visited weekly by a data analyst who can assist with usage of the tool. On a monthly basis, entrepreneurs are also provided with ‘marketing analytics’ reports specific their firm, that compares current to past performance. Overall, this solution aims to increase an entrepreneur’s ability to pay attention to, and act on, key marketing and sales information. 2. Group 2 (pure control): 250 entrepreneurs form a counter-factual group that does not receive any intervention during the project (note: they will be given access after the project ends). 3. Group 3 (placebo): 50 entrepreneurs form a second comparison group that receives only a smart phone and data plan (they will not be given any marketing analytics apps, tools, intervention, etc.). This is to rule out potential alternative explanations in our study results due to exposure to smartphone or the internet.
Randomization Method
Randomization done in office using stata
Randomization Unit
The randomization unit is a firm.
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
550 firms, 3 experimental groups - Treatment, Control and Placebo
The design is not clustered
Sample size: planned number of observations
550 firms, 3 experimental groups - Treatment, Control and Placebo (The design is not clustered)
Sample size (or number of clusters) by treatment arms
250 firms in Treatment group, 250 in Control group and 50 in Placebo group
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
Intervention
Is the intervention completed?
No
Is 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