Offline Search Engine Findyr Aims To Be The Postmates Of Hyperlocal Data

The technology platform fulfills businesses’ data requests on-demand — and it’s striking a series of analytics partnerships in a bid to deliver better location insights.

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Findyr’s Anthony Vinci

Findyr, a technology platform that fulfills requests for hyperlocal data, recently struck an analytics partnership with First Mile Geo in a bid to give brands better location insights — and CEO Anthony Vinci says a series of similar integrations are on the horizon as the company looks to give brands better location insights on-demand.

Findyr’s platform operates as an “offline search engine” of more than 1000 markets worldwide, allowing users to task “Findyrs” with collecting data, performing surveys, and taking custom photos and videos on-demand. Once a data request is made, “Findyrs,” local citizens who have downloaded the Findyr app and who have access to the information needed, answer the request, usually within 48 hours. Findyr, through its app and technology, validates the data or content provided to the user.

“Findyr democratizes the data collection process in the sense that even small companies can do a $100 research project,” Vinci says. “But the other point is that I think it also gives businesses a different type of information than beacon or online surveys or virtual panels can give you, in that you can actually send somebody to that location and receive an incredibly diverse set of real-time information.”

Tell me about Findyr’s origins. How did the idea of creating an offline search engine for data collection come about?

I started out in the tech industry here in New York. But then, about 10 years ago, I went in the opposite direction: I did a PhD in International Relations at the London School Economics, and I did all my field work in sub-Saharan Africa. I was interviewing people and doing surveys and traditional pen and paper fieldwork the same way people did field work 200 years ago. And it was really gratifying and it was really interesting work.

And then I realized at some point, “there’s a way I can combine these two interests and backgrounds.” There’s a way to technologically enable the type on the ground research that I was doing – to get information from all kinds of places and view it in a scalable, technologically driven way, and I think it was the smart phone that really allowed for that.

With smartphones, all of a sudden we have this data collection capability in the hands of people that can go anywhere. That’s where the idea came from, and that’s what we ran with.

We did our angel round in Winter 2014, so we built Findyr in 2014. We were already doing projects actually, paid projects for clients that we’d brought in from different places while we were in beta.

How did Findyr’s abilities evolve?

What Findyr does now is to address, for businesses or individuals, how you can get offline, real-world, collected data or information or content from anywhere in the world. How would you go about solving that problem?

What we built, and the way we address that problem, is through an information marketplace approach. We’re similar in a way to other marketplaces like Uber, or Airbnb, or TaskRabbit — but applied specifically to obtaining data and information. On one side you have a web app where you can make a request for information. It almost works like an offline search engine. So you enter into the text field, “This is where I want my information. I want it at 220 E 23rd St.”

How do these requests for information work? And how does it provide businesses with insights that they might not be able to get through other types of data collection?

On one side, businesses can make a request for information through Findyr. You enter into the text field, “This is where I want my information. I want it at 220 E 23rd St.”

You could say, “I want you to survey 20 people between the ages of 18 and 34, who are college educated, and ask them these 10 questions about my company’s brand. What are they think of this product? Have they every bought this product in the last 30 days?” You can do all kinds of surveys.

It’s specific to each brand’s audience. It enables requests for data from very highly localized locations. You can get a lot of on-the-ground data, find out what’s happening in specific retail locations, and not only what is for sale — you can request to find out what the street traffic looks like in front of a certain store’s location. Essentially, it gives businesses of any size — even a company of just one person — the ability to have a global market research capability.

Because it’s efficient and cost effective, it democratizes the data collection process in the sense that even small companies can do a $100 research project, which is impossible when using a large research company.

But the other point is that I think it also gives businesses a different type of information than beacon or online surveys or virtual panels can give you, in that you can actually send somebody to that location. You can say, “Give me a photograph of the front of the store inside the store. Give me a video of the street traffic.”

A Placed or PlaceIQ is going to tell you how many people went into a specific retail location, of course, and then you can pair that with other data, in terms of what was purchased. With Findyr, you can literally say something like, “I want to know how many people went into this retail location wearing a hat and had a beard, and what they did once they got to the store.” So, the perimeters are very wide open in terms of what you can get out of it.

What kind of reach does Findyr have, both in terms of users and “Findyrs?”

We have android and iOS app, and more than 50,000 people at this point have this app, globally. It’s in 138 countries and over 1,000 cities. When you make the request for information, the “Findyrs” will see those requests in their local area and they can answer and fulfill the request.

It works similarly to [Postmates and its couriers, but] our users tend to be a little more tailored to the information collection industry in the sense that we’ve purposely recruited among people who have an interest or background in social science in these kinds of market research areas.

And then when they’ll collect the data, typically it’s not just performing the survey, but it’s also gathering objective information — photos and videos and things like that. Qualitative information. And then the app will help to verify the information by the data collection itself in that we’re collecting GPS coordinates. We’re collecting time-date stamps. We’re collecting also pattern of life activity and data about our data collectors over time to validate them as well.

Putting all that together it helps verify the data collection information that you’re getting. And it also helps to structure that information. So everything, every data point that we provide, is geo-tagged. It’s “Where was that photo take? Where was that survey performed?” And then it’s presented in a geo-spatial format through our dashboard where businesses can access of download it. We also have an API, so people can integrate it into an existing data dashboard instead of using our self-service platform, if they prefer.

It comes back into our dashboard, and then users can access it there. Or they can download the data. If it’s a survey, you can download it into Excel. If it’s a photo or video, you can download it into a zip file and have that information. We also have an API, so you can also integrate, instead of using our self-service platform, you can actually integrate it into, if you have a data dashboard.

Tell me more about the partnership with First Mile Geo. What are users of Findyr and FMG able to do that they couldn’t before?

We were all in the market research and emerging markets research space, and it was really kind of a no-brainer in that what First Mile is bringing is this data analysis capability, data dashboard, and ability to integrate different forms of data collection. What they didn’t have… was an actual data collection capability — people in the world who can go collect data. And really that’s what we do. We called it on-demand business intelligence, in that we could feed in the data that they needed, these new proprietary data sets, and then they can use their system to then perform analysis on that and answer questions for their clients. It’s a perfect example of a great partnership and it’s highly complementary.

Now, we’re forming more and more of those affiliate style arrangements where we find companies that have complementary products where we think we could kind of essentially revolutionize how they do what they’re doing. So if you’re doing business intelligence, now you can do it in an integrated way, combining the analysis and the data collection. That’s the plan for the near future.

Can you give an example of how a brick-and-mortar business has used this data to boost in-store visits and/or sales?

One small business here in New York City, for example, was a provider of office products. They needed to be able to perform surveys in lots of different types of offices about what people needed, and they didn’t want to get skewed results by just talking to friends or a few old customers, which was the traditional way of small businesses doing this.

Another general example is that ad verification is a big part of Findyr’s business. For small businesses that are doing outdoor advertising, either they walk around to those locations to make sure that their ad or digital ad is up, and they stand there all day — or they could utilize Findyr to actually verify that what they paid for is appearing. There are so many different applications for small businesses, once they begin to consider how something like this can be utilized.

At the end of the day, what Findyr represents is not only an interesting new application that democratizes market research, but this emerging area of alternative data. So much of what has been talked about is big data and how granular it is, but the reality is that between big data and traditional search there are some serious gaps that exist. And a lot of that comes down to the hyper-local level in terms of really understanding the human intelligence in the real world.

About The Author
Lauryn Chamberlain Lauryn Chamberlain @laurynchamberla

Lauryn Chamberlain is the Associate Editor of A New York City based journalist, she specializes in stories related to retail, dining, hospitality, and travel.