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[Idea/Concept Not Complete]: SoCon Malawi - Customer Segment Testing - July 2018

by
Seif Zakri Stacey
Seif Zakri Stacey | Jul 17, 2018 | in Knowledge Base

Introduction

We have designed a customer segment using assumptions based on research of the Malawian Government's National Survey and other statistical analysis’ of the nations financial sector such as FinScope. The target customer for this experiment is young women in fringe rural/ urban villages with limited income and limited access to finance. This is just one of 3 customer archetypes we are currently validating, and hope to develop a profile for by the end of July.

How we came to our assumptions

We chose this fringe rural/ urban area because the national survey (2016) stated that 38% of all loans issued in Malawi came from village banks and that of these loan 39% were from village banks in rural areas and 35% were from village banks in urban areas. This led us to believe that these in-between area’s (like Nancholi for example) were where demand for loans were most prevalent. Women were our focus demographic in these areas due to having a higher tendency to borrow loans from village banks than men (39% > 37%, respectively). The national survey stated that 90% of the population engages in subsistence farming/ fishing, but only 8% of crop families could be considered farm entrepreneurs. It also states that 90% of the population lives on less than $US 2 a day and 75% lives on less than a $US 1.25 a day. This information cross referenced with the FinScope Survey statistics that 86% of the population live in rural areas, 41% have an income of less than 10,000 Kwacha/ month (> $US 13.7/ month), only 10% of the population receive regular income, and 54% of Malawians do NOT save led us to the assumption that most people in Malawi had limited/ irregular income. These assumptions were clarified after seeing their quality of life first hand. The national statistics also stated that 18% of households interact with the credit market, and of this 18%  only 13% actually get approved for a loan. This and the fact that 46% of all financial service access points are located in Lilongwe and Blantyre led us to the assumption that there was limited access to capital in our target demographic.

How to validate these assumptions?

We surveyed the local population around Blantyre and evaluated whether their answers confirmed our identified assumptions relating to the customer segment, associated problems, and potential value proposition. These assumptions will be validated by displaying a correlation between the problems and value propositions attributed to the customer segments we have developed. If there is a high correlation between these variables then we know that the problems we have assumed are reality.

Testing Methods

  • In person Survey

  • This will be the primary method to validate the assumed customer segment because it gives us more detailed answers to the problems experienced by Malawians as well as the values they hold, and that we can deliver. The survey design will be essential to ensuring consistent and reliable qualitative results.  (details below).

  • USSD Survey

    • This will be a secondary method to validate the assumed customer segment. It gives us slightly less clarity on the ‘Pain Points’ experienced by the people of Malawi but this will be offset by the large sample size we can reach

 

Customer Segment Assumptions

Questions that validate our assumptions

Females make financial decisions in households

Q: What gender are you?

Q: Do you manage the funds in your house?

Hard to Save Money

Q: What is your daily/weekly income? (if judged appropriate to ask)

Q: How much do you save in a month?

Hard to access capital

Q: Do you find it difficult to obtain a loan?

Age 18-35

Q: How old are you?

Agriculture is their Main Occupation

Q: What is your main source of income?

Inconsistent Occupation

Q: Do you have another source of income?

Uneducated (business/ finance)

Q: What is the highest level of education you have completed?

Q: Have you ever borrowed money for your business or farm?

Q: Did this loan improve your business?

Q: How many businesses have you had? Q:Were they successful?

Paid Monthly (continuous stream of informal income)

Q: How often are you paid?

Q: Do you have a bank account?

Fringe Urban/Rural

Q: where is the closest city to you?

Q: If you do not live in the city how long does it take you to reach the closest city Center?

Informal Banking system used

Do you have a formal bank account?

Additional validation covered in Survey (Problems and value proposition)

 

Lack of Access to capital (Problem)

Q: If you are given a loan what would you invest in?

Financial Security (value prop)

Q: How often are you paid?

Opportunity to grow business (value prop)

Q: If you are given a loan what would you invest in?

Note: These are the formal questions we want to ask and that they will be adjusted to match the flow of conversation (i.e. level of engagement and amount of respect conveyed)

 

  • Customer Information from Energy team Sales

    • This will give us both qualitative and quantitative data about our customer segment. We can validate our customer segment by assessing whether the payment plan in place was an effective way to finance the product, as well as solving the problems and value proposition we identified. We can identify whether this customer segment is the character archetype we want to pursue as a target customer by analysing factors like default rates, fluctuations in repayments and correlation to income, differences in wealth (and wealth distribution) between villages etc.

 

We may find that there is an another issue that is stopping our customer segment from accessing capital or that there is an issue that requires us to change our customer entirely, we can validate this through another experiment - this will be shown if we cannot find any clear link or pattern within this survey data.

 

Survey Practicality Assessment

 

USSD (digital) Survey

 

Pros

Cons

  • Targets a large sample size which gives us a more accurate picture of the situation here in Malawi and in particular our target demographic

  • Requires a fee (~50 Kwacha)

  • Relatively quick and easy to answer questions

  • Only allows a limited amount of questions which means we can’t expand on some questions and certain problems or values experienced by Malawians can go amiss

  • Scalable: which means there is opportunity to expand it to a larger scale when possible

  • Only allows for basic answers (users pick options 1-6 on their brick/smartphone), which means we cannot gauge the emotional response to the answers

  • Doesn’t require human resources therefore it can be run when Trekkers are not in country

 



Interview/In-person Surveying

 

Pros

Cons

  • Doesn’t cost PEV anything

  • Requires human resources, which means it cannot be run when Trekkers are not in country

  • Information is more detailed and allows for open-ended qualitative questions/answers

  • More time intensive process, especially when a translator is required (as well associated costs)

  • Allows us to gauge the emotional responses to the answers provided

  • Smaller sample size

 
  • Not scalable



Customer information (Energy sales)

 

Pros

Cons

  • Gives quantitative data of the financial environment of the rural villages around Blantyre (income, default rates, cash flow cycle etc.)

  • Smaller sample size

  • Is free and detailed information

  • Information about the customers attitude towards microfinance (through the payment plan) doesn’t effectively gauge emotional response

  • Requires human resources but it can be gathered out of country

  • Questions cannot expanded upon so certain problems and values of Malawians might go amiss

  • Not a time intensive process (at least not for the So-Con team)

  • Information has room for error because factors affecting loan repayment/ satisfaction may revolve around the product being sold (in this case a solar battery which has a large social impact) and not the process of microfinancing itself

  • Gives a decent sample size (54 so far and growing)

 
edited on 8th January 2019, 10:01 by Ella Grier

William Lee Jul 17, 2018

This is really great - as you might or might not know, I do have access to the underlying data (n=3,000) from the FinScope Survey so hit me up if you want me to analyse something specific, or that may help you prove different assumptions.

Reply 1

Seif Zakri Stacey Jul 17, 2018

That would be awesome man! I’ll consult the team and get back to you with a list of specific questions

Reply 0

Justin Hakeem Sep 3, 2018

Status label added: Idea/Concept Not Complete

Hi Zak, Just wondering what would qualify this experiment as a success. Were there any key metrics needed to qualify the customer segment? Additionally did this experiment end up happening? If so what were the results and can you update this post/ make a new post with them. Thanks

Reply 0