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1/ Thanks @enidmagari
They are great with high precision data. That’s the quality dimension their customers have been trained on. Precision is very helpful for some use cases- especially for the largest public Co's. They focus on descriptive analytics (“what” is happening).
They are great with high precision data. That’s the quality dimension their customers have been trained on. Precision is very helpful for some use cases- especially for the largest public Co's. They focus on descriptive analytics (“what” is happening).
2/ The challenges they face are the same everyone in consumer faces:
Information Advantage: The data has been commoditized. Meaning if all of your competitors are looking at the same set of data and the data isn’t that complex….it's not much of an Info Adv.
Information Advantage: The data has been commoditized. Meaning if all of your competitors are looking at the same set of data and the data isn’t that complex….it's not much of an Info Adv.
3/ Breadth: Retail sales providers get data by forming partnerships with large retailers. Typically they don’t even get all the products/brands in those large retailers. Then they sell the data to Coke, P&G etc. The data focused on large brands and large retailers.
4/ It misses the long-tail of innovation completely. It always will because the way they collect the data isn’t economic for long tail of retailer or brands.
5/ Predictive Power: Everyone in consumer is trying to understand what innovation is going to take off. Predictive analytics not just descriptive analytics.
