You need reliable Amazon data. You need to know how your competitors are positioned and if and where you can invest into the marketplace. But you don’t want to pay out the nose for it. While it’s a bit weird to bring up pricing at the beginning, but it’s such a differentiator that we have to bring it up. Profitero is a tool focused on enterprise level brands. Signing year long deals with monthly fees of well over $5k a month. SmartScout is a fraction of that with plans from 10-20% of Profitero. But why?
First off, they have to bring in the revenue to justify the huge acquisition. But what does that mean for reliability of the data?
Little to none. SmartScout was founded by sellers who have been building tools for over a decade on the marketplace. With over $300m in revenue under their belts, their perspective on how data science can impact decision making make the tool competitive with anything out there. Their coverage of categories, brands, sellers and products has to be seen. As a bootstrapped analytics tool, we can afford to get this into as many hands as possible.
Don’t want to take our word for it? Profitero is “very expensive compared with other suppliers”.
Now before we get too far into the weeds we have to figure out who is the winner here in accuracy. As inaccurate data will lead to bad decisions. When it comes to data accuracy, it’s kind of a black box. Sure they might be accurate for one brand, but how are we to know that the models are being updated over time and consistent with trends?
SmartScout’s approach is to show as much information as possible. There’s a full article here on what we do. We show our work. What do we mean by showing our work? We break down every product, variation and then show how it all adds up. You can click through and see more data in every part of the SmartScout platform. What type of stuff can you see by zooming in? An organized product list with sales rank, average price, average number of FBA sellers, 1p vs 3p breakdown, average product size, review rating and we do this for a category, a seller, a brand, a product and search terms.
Look at this image as an example of the data coverage. We won’t blame Profitero for not covering all these data points. They’ve been building tools. We’ve been busy selling on Amazon for the past decade.