Fletcher Berryman, Head of Sales at dataPlor, is a seasoned geographer and salesperson experienced in navigating the location intelligence space and spatial technology, including GIS, spatial analytics, cartography, remote sensing and satellite imagery.
We asked Fletcher to spend a few minutes chatting with us about the unique challenges of helping multinational companies apply location data insights in developing markets. Along the way, we touched on applications for financial institutions, retail site planning and selection, geosciences companies, and a growing list of global food unicorns.
Tell us a little about yourself and dataPlor and what you want to be for customers.
Sure, I am Fletcher Berryman, head of sales at dataPlor. Our mission is to be the global provider of point of interest (POI) data, specifically, small business point of interest data in emerging markets. In developed markets, such as the UK or the United States, it is easy to find small businesses like retailers, or the private practice of an attorney. But in the vast majority of markets there is very little POI data, or it is of disparate quality. We solve for that through a combination of technology and human beings.
Can you provide an example for how the value of data exploration may play put in a typical client engagement?
Sure. Knowing where one taco place in Mexico is located is somewhat useful. Knowing where every taco place in all of Mexico is and being able to compare when they have been opening and closing against all of the cafes and hardware stores and how they all do economically from one quarter and one year and one region to the next -- that’s really useful. It allows the client to get a much clearer picture of what is actually taking place in a given part of the world than can be gleaned from standard macroeconomic indicators, which tend to be skewed in the first place. The value is solving for that lack of clarity, more frequently, covering areas that aren’t normally covered, and validating data with real humans to make sure it is reliable.
So your clients are most of your clients US-based or foreign companies?
That's a good question. You would think for selling in these emerging markets we are going to go after companies that are based there. In fact, the majority of our client book is comprised of American, Canadian, and Western European companies. Why? Because they tend to be more focused on sophisticated analyses that can be run across more than one country or region. As a caveat to that, I’ll add that there is an increasing trend towards data analysis among the Mercado Libres and Rappis and iFoods of the world, which I think is helping the tech ecosystem as a whole adopt.
Which industry categories have the greatest growth opportunity for your business?
For us, there are three verticals that have particular pertinence -- financial institutions, site selection and planning, and the whole geosciences realm. When I say financial institutions, that’s vague because it really can mean a lot of things; a multinational bank, an investment bank or some form of asset management business. Then there are adjacent businesses, like large consultancies or accounting firms or what have you. In each case, they want to understand how to measure the economic viability or lack thereof of parts of the world that are hard to measure. They have so many questions, and the metrics that spin out of answering those questions can sometimes supplant more traditional macro, guidelines like GDP even.
The next would be site planning or site selection. Simply, if I am going to buy commercial real estate, or invest in real estate somewhere, or expand my network to a particular part of the world, I want to know what is in a given area and who is moving around. These are not questions that are that hard to answer in America or the UK but if Walmart, to use a made up example, wants to open an extra 100 stores in Mexico, they are going to care deeply about where thousands of Mom and Pop shops people already shop at are located. There is more to it than that, but that is generally speaking how site planning and site selection look at what we do.
The final one of our core three is a little harder to label, but you can just call it mapping or geosciences or spatial analytics. These companies care about a problem that, at least in terms of understanding, is very simple, but executing on it technically is very hard. but they just want as much data as possible and they want the best of it. So, if you open your phone in America and you go to a map you are probably expecting them to have not just a location but up to date hours, even in the midst of a global pandemic, yet, it is the most technical problem we solve when working with some of the largest mapping companies in the world.
Can you share some client names, or talk about specific projects?
When it comes to financial institutions, which extends actually beyond even the examples I gave into fringe cases like payments, we work with American Express among others. Amex has a pressing need to understand where luxury retailers and fine dining establishments are located because if those locations exist and are not taking American Express cards, there is a disconnect between the business and what Amex would like to be taking in. They worked with us, I believe, all over Mexico, but particularly cared about Mexico City and wanted to identify gaps in coverage and then from there, execute on expanding their coverage network amongst retailers.
Uber Eats would be another example. They are relying on the same type of data as Amex but Uber Eats cares for a very different reason -- they want not just more folks in their system but also more accurate data because they do not want someone, whether it is a delivery person or a user to go to a POI that is 150 meters off. Because all of our stuff is geo-coded obsessively, Uber Eats can lean into our data in ways that they cannot with other providers who just scrape the web and put a bow on it. That is really where the human element comes in at dataPlor. There is no one else that human verifies every record and we are very proud of that.
How do Unacast and dataPlor complement each other and work together?
Unacast helps to articulate to a customer where human beings are moving around. dataPlor helps to understand the points of interest that they are moving around in relation to. One absent the other, you have some somewhat useful basic data. Together, we can form a complete picture of not just how but why someone is moving through a space and the potential economic impacts of that movement. It could be for a store, or a brand, or a building, or some arbitrary block in a major city… it’s the depth of vision we can provide together that insights and value spring from. I’ll say it again: this is pretty easy to do in New York or London, not so much in emerging areas like San Paulo or Chiapas State. But businesses in emerging areas still care about on the ground truths. Together, we help surface and make sense of those truths.
dataPlor provides enterprises highly accurate point of interest(POI) data to grow in emerging economies, particularly Latin America. SMBs inthese regions are volatile, yet provide valuable insights into economic healthand activity. dataPlor is U.S. based and venture-backed by leading investmentfirms including Quest Venture Partners, ffVC, Space Capital, and MagmaPartners.