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Being able to properly identify your customers is the cornerstone of a successful and rigorous go to market strategy. It lays out the foundation on which you can afterwards perform a segmentation of the outlets, define the territories, the sales infrastructure required to cover this territory, in terms of distributors, sales rep, etc. Traditional trade in Africa is made up of small shops that operate on small capitalisation, and can therefore go bankrupt, or close because of seasonality effect (agents closing to go harvesting for example). While some companies will contract an external agency to do a one-time census exercise, we believe it is better to run it internally leveraging a software solution provided to the field agents to be able to constantly update it. The only justification of having an external eye on it is if the current sales teams are too busy focusing on sales, and need to be challenged with an external objective view on the universe size.
Obviously, it is much simpler to capture all those details directly through a mobile application to have accurate information and to ensure the captured information reflects on the cloud-stored version of the overall database. Once synchronised, this data can be seen online through the FieldPro web app by the manager or by all field users and exported onto an excel format or through an interactive map on FieldPro.
From our experience, these are the key dimensions that need to be collected when identifying a retailer on the field:
Shop name
Outside / Inside picture
Type of shop. Use the classification that makes sense to you with specific options
Product categories sold. This is useful to make sure these outlets sell similar products as yours.
GPS localization. Make sure the accuracy is below 10 meters
Shop owner contact details: email address, phone, name
Shop assistant contact details: email address, phone, name
Unique identifier. It can be an agent code, or a number specific to your business to be used as a primary key
Address description. Plain text indication of where to find the shop as the street address might not be accurate
District / City
Equipment presence, such as fridge, cooler, etc.
Branding / Shelves / Hanger picture
Best practices that can be enforced with the FieldPro app to ensue data quality
Define Regex Rules
Regex refers to constraints you can put on the data inputted to make sure it fits certain formats, like a phone number to start with a particular number and be 10 digits long. This is essential if you want to use these numbers to pay mobile money incentives for example. Or asset codes to match the required format used internally. This is to ensure there is only quality data inputted in the system that can be exploited after.
Put some fields as mandatory
Each attribute can be marked as mandatory or optional based on their importance in your database. We recommend putting as mandatory at least these :
Picture
GPS
Outlet Name
Unique identifier. Agent code or phone number
Define some these attributes as unique
This is to prevent the user to register a retailer twice and generating duplicates. Typically a phone number or agent code can be used as primary keys.
Create conditions on the attributes to capture
Make some information conditioned to the response, such as the type of shop or whether there are assets in the shops. This is to ensure you have relevant information for each outlet profile.
