Peter Nieforth
Peter Nieforth is the Chief Executive Officer and Co-Founder of Vitrium Systems. Mr. Nieforth was instrumental in bringing together the founders who designed Vitrium’s business model based on Narayan Sainaney’s research and protected pdf technology. Mr. Nieforth specializes in financing, organizing and commercializing promising start-ups, most recently acting as Director of Investment for The Loreto Bay Company, where he raised 18 million US dollars for the development of the world’s largest sustainable resort community, in the Mexican Baja. Mr. Nieforth has also served as an investment specialist for BMO Bank of Montreal, a Financial Advisor for Yorkton Securities and a Financial Consultant for Merrill Lynch Canada Inc.
Mr. Nieforth studied Political Science at Acadia University and graduated from Mount Saint Agnes Academy in Hamilton, Bermuda.
Interview Transcript
Eric Enge: Can you give us a definition of document analytics?
Peter Nieforth: Well, document analytics is a phrase that we are coining with the release of our latest product, docmetrics. If you do a Google search on document analytics you are not going to find many hits, so we are really trying to be one of the first to step through the door on this. We’ve opened up this notion of the ability to measure what happens to your electronic content. Millions and millions of documents are created and sent out into the wild every day. No one really knows what goes on with this electronic content. What we have developed here in our technology is the ability to understand what is happening to it. How many pages are read and how much time is spent reading each page? Is it printed? Who are your readers and who are they sending your content to? And so on. So, we’re really opening up this whole space of document analytics.
Eric Enge: Right. And what do people need this information for?
Peter Nieforth: If you think about the millions of electronic documents that are created each day and sent out, whether it would be a sales proposal that you’re sending off to an organization or a white paper, the inability to measure what’s happening to that content is not a good thing. So, if I’m spending fifty thousand dollars on developing fifty pages of lovely white paper, but no one reads past page 25, wouldn’t that be interesting information for me to know? A lot of publications are created and produced, and a lot of money is being spent on this. Yet, there is very little knowledge or information about how that content is consumed; how the readers are engaging with it. Say I send a sales proposal to an organization, maybe I believe I’m dealing with the decision maker, but maybe I’m not. It’s interesting to know where that sales proposal goes; who is reading it in the organization. That gives you just a tremendous amount of data that you otherwise would not have had.
Eric Enge: Right, so is it possible to tell if someone gets down to page 25 vs. does not open your paper at all?
Peter Nieforth: Absolutely. We can also tell how much time they spent reading each page if they printed it, and who they sent it to. And you can actually now see how documents and white papers travel within an organization. I was at a conference in Boston recently, and Michael Stelzner said up to 56% of white papers are passed along to colleagues via online content sharing. At the same conference, David Meerman Scott spoke and said that un-gated content gets viewed by 20 times as many readers. So think about that: if I have a white paper on my website today and I’m gating that white paper with a web form, I’m missing out on 95% of my readers. I’m probably going to get bogus data from the 5% of people that actually fill out the web form. And those few readers I do receive data on will pass the document on up to 56% of the time but I have no visibility or knowledge as to who they are passing it to. So, I think that document analytics or metrics is a better way to know if your content is being engaged with, because, clearly, gating content isn’t the solution. You want to get your content out there, and of course, when you get your content out there, it is nice to know if it is being read and who is reading it.
Eric Enge: Right, so who are the people that can benefit from using this kind of analytics?
Peter Nieforth: Well, for example, companies will benefit from knowing whether or not their marketing content gets read because it allows them to begin to measure return on investment and discover if they should continue putting money into electronic content. And this kind of activity is increasingly coming under scrutiny, so executives and CEOs would be very interested in seeing this information. We’ve found, since we launched our solution just seven weeks ago, that organizations are coming to us from all different market segments, folks that produce free and paid content, looking to learn more about how it is being consumed. We had an organization out of Europe recently contact us. They’re funded by the G30 and they produce 170 publications a year that they distribute to their membership. They want to know if this stuff is being read, and who is reading it. If you think about web analytics for a moment, every website you go to today is tracking your behavior: which pages you go to, what pages you go to next, everything. All of that is now being measured on the web, and so, if you think of the value that web analytics has brought to the web world, I think that you could easily make the comparison with document analytics. If you care about web analytics you should care about document analytics and document metrics.
Eric Enge: So, how does document analytics differ from web analytics?
Peter Nieforth: When you come to my website I have tools, I have the ability to measure and optimize my site, making sure that it’s performing at its best and that I’m getting a good return on my investment in that website. The same can be said about document analytics.
Eric Enge: Are there certain kinds of things that you are able to measure on a web page and then you can measure in a document?
Peter Nieforth: Yes, I think they are very similar actually. I don’t know anything that you can do with the web that you can’t do in a document. However, with document analytics, we have the ability to put something like a chat widget inside a document. Let us say I’m in a customer service manual and I have a question. Potentially, the publisher of the manual could embed a widget within the document, allowing the reader to start a conversation in real-time with someone at the other end.
Eric Enge: Yeah, so let’s talk a little bit about how this works. With web analytics, there are two kinds of methods of tracking: one is by reading log files and the other is if you put JavaScript tags on the pages of the site. So what is the principle type of technology used in and how do they work in order to be able to collect this data?
Peter Nieforth: I’m sure there are many ways to do it, but the technology that we have developed is Flash-based. We are actually using a Flash application inside a PDF, and that Flash application is collecting the information and reporting it back to the publisher, in real-time. In web analytics, there is often a delay in actually getting the data. That data is aggregated together and usually reported back the next day. One of the advances that we’ve made with our Flash-based application is the ability to actually report that data in real time, so you could actually get pinged if someone had just opened up your document.
Eric Enge: What are the issues in terms of being able to identify users as unique people? Do you rely on cookies to do that or some other mechanism? So, for example, someone gets a document downloads it and, they do a certain amount of things with it. Then they email that document to someone else, and they do a certain number of things with it, and your Flash application is communicating that back to your server so they can collect all of that data. So you must be doing something to tell the first user from the second user.
Peter Nieforth: Yes, in fact, we have just filed a patent on that. We now have the ability to differentiate who the original recipient of a document was from the subsequent readers of that document.
Eric Enge: So in the web analytics world, the user gets cookied, and there is this whole notion of session tracking.
Peter Nieforth: We are doing something very similar. We make sure the document does create the session with the user, so we do collect such things as IP addresses. We can actually identify one particular user’s machine from all other machines. As a result, we know where a document came from and where it gets passed to.
Eric Enge: Right, so is that data stored in the Flash application itself or it’s stored in a cookie?
Peter Nieforth: It is actually stored in the Flash cookie container and then, the next time the user engages with the docmetrics document, that information is communicated back to the server.
Eric Enge: What are examples of some key performance indicators people might want to focus on?
Peter Nieforth: I think some of the KPIs that folks might be interested in are how many pages are read, how much time is spent reading each page, whether the document was printed… I think those are sort of the core analytics that you would want about how the reader is engaged with the content. The other technology that we’ve introduced with this is the ability to put forms in front of readers and get them to answer questions about the content or collect other data such as personal information if they’re willing to provide it. The second group of metrics that we are really collecting here is reader responses. If I put four questions in front of someone, I can actually now measure how many of these questions they answer. I can make them mandatory or skippable. So, if I make them skippable, another metric I may be collecting is how many people skipped each of the questions that I put in front of them.
Eric Enge: Right. I think it would be interesting to measure the relationship between downloaders and readers. For example, how many times it was forwarded and actually read by someone else, so you can see a situation where you actually get two readers or three readers per download.
Peter Nieforth: That’s a good point, because now you can begin to marry web analytics with document analytics; I can see how many people have downloaded and taken this file away from my website, then I can look on the other side and see how many people actually read the file.
Eric Enge: Right, you can treat a white paper download as a lead if you will. You could potentially set a monetary value to see what the results are from your campaigns. It may be worth a dollar that someone downloaded the document, it may be worth a little more money if they get to page 25, and some more money if they forward it to someone. It is a structure you could set up to compare the value of one white paper versus another.
Peter Nieforth: I think this is powerful because now you can really get into AB testing.
Eric Enge: Is this currently limited to PDF files or are there other kinds of file formats that you can process?
Peter Nieforth: Our docmetrics technology is focused on PDF files at the moment, and we transform standard PDF files into what we call enhanced docmetrics documents. That’s not to say that we cannot expand that into other areas.
Eric Enge: Is there something inherent about the PDF format that makes it more trackable say than a Word document can be or is there really no inherent limitation in terms of expanding?
Peter Nieforth: When you think about what is produced and what is distributed today, quite often the end file output is PDF. It’s rare that you’d go to a site and find a white paper in a Word document. It’s a pretty standard practice that when you produce a publication it ends up as a PDF. When you produce a sales proposal, typically you are going to turn that into a PDF before you send it out. It’s just pretty standard practice. Adobe Reader is installed on nearly 99% of all machines in the world, so it is pretty ubiquitous and it’s a very well-used file format. But that’s not to say that we can’t go into other file formats as well. Our technology is Flash-based, so obviously a natural extension for us is to move into the area of videos. And so, let’s say you have a Flash video on your website, and you want to measure specific metrics about that, I think that would be interesting as well.
Eric Enge: You can collect the data even when the person isn’t connected, and then you can store that in a cookie until they are connected, and then transmit the data at a later date. So there is really no difference in the data that you can collect whether they are online or offline.
Peter Nieforth: Correct. Setting this up is really quite easy. You just upload a PDF file to our server, we crack it open, inject our smart document technology, put the document back together and give it back to you. And now, wherever that PDF goes, it’s collecting and reporting the information and data back to you.
Eric Enge: Great, well thanks a lot Peter, I appreciate your time today.
Peter Nieforth: Thank you Eric!
