This is part of my library of evergreen notes. It is continually updated as I refine my thinking around a particular topic.
Data Strategy
Data strategy can be likened to Data Product Management. It’s important that data activities align with business strategy to create truly meaningful data products.
B2B vs B2C Firm Characteristics
As much as industries influence what kinds of people exist in an industry (consumer businesses attract marketing types, fintech businesses attract numerate types, and tech companies attract techies), B2B vs B2C is probably the first principal component in differentiating different kinds of jobs. Although there is much to be said about the B2B world eventually resembling more B2C, there are still some key differentiators.
Aspect | B2B | B2C |
---|---|---|
Product Range | Typically one product, with a few variations across pricing and add-on features. A high degree of bundling and cross-selling (sometimes giving the customer no choice on bundling). | Lots and lots of SKUs, there is a wealth of choice and it is expected by the customer. Normally would sell multiple products with promotional bundling. |
Data Volumes | Lower volumes (less rows) and more nuanced data (more columns). Some rows are vastly more important than others (usually a few anchor clients that are very important) | Higher volumes and less nuanced data |
Customer Experience | Definiing the jobs to be done is very important; customers are very deliberate and specific about what they want. | Surprise and delight are very importance; there is a degree of exploration and wandering involved in the experience. |
Sales | Apart from a few standard terms, most stuff is going to be custom. There is an "account manager" managing each customer account and making sure that it's fit for purpose. | As standard as possible, the default is no human interaction. Customer support is then needed to save the people who do not have a good experience. |
Data Problems | Compliance of operational personnel with call logs, meeting logs, and other information that would normally be unstructured and require judgment | Adblockers and other technological blockers to proper data collection. |
Product Development | More of a consulting model, it's more important to get direct feedback and work on those, especially for the larger clients. | Going to be based off of data and hunches, as consumers do spend a lot of time thinking about what they should ideally consume. There is more room for moonshots. |
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