1
00:00:00,000 --> 00:00:02,680
And we've got a special guest with ourselves. Would you like to introduce yourself?

2
00:00:02,800 --> 00:00:06,460
Sure. I'm Travis Vann. I'm the co-founder of a company called IT Database.

3
00:00:06,540 --> 00:00:10,480
I think IT Database has actually been working for a while now, and you've sort of been in stealth mode, if you will.

4
00:00:10,600 --> 00:00:19,020
IT Database, we're a new startup. We're focusing on the problem that there's a lot more IT news that comes out than people actually have time to read.

5
00:00:19,720 --> 00:00:28,580
If you work for an IT vendor, you know, chances are that you've only got enough time to maybe configure your RSS reader for certain publications or authors you like.

6
00:00:28,900 --> 00:00:34,340
You might go to places like Tech Meme on a daily basis to look at kind of what's hot, dig, Reddit.

7
00:00:34,840 --> 00:00:37,540
There's a number of aggregators that, of course, you're familiar with.

8
00:00:37,640 --> 00:00:48,040
If you're into something specific like your virtualization vendor, for example, you really want to narrow in on kind of the cumulative coverage of virtualization in a single day.

9
00:00:48,660 --> 00:00:54,340
You don't want to go digging through each publication or manually sifting through, you know, various lists and so forth.

10
00:00:54,340 --> 00:01:00,840
You just want to kind of hone in on all the virtualization coverage and see, you know, who are the top 10 virtualization vendors mentioned today?

11
00:01:00,940 --> 00:01:03,780
Which authors produce the most content about virtualization?

12
00:01:03,780 --> 00:01:10,280
We're interested in providing sort of more metadata about what's being discussed and who's producing that content.

13
00:01:10,280 --> 00:01:20,400
So we're aggregating the most IT news that we can and only IT news, and then we're putting a lot of tagging and references on this stuff so that the user can slice and dice it.

14
00:01:20,400 --> 00:01:31,020
From a marketing background like you have and also coming from the work that I do day to day, it's, you know, it sounds like more so than just sort of like, you know, Yahoo Tech News or whatever's going on.

15
00:01:31,020 --> 00:01:44,000
There's sort of tools that you would use, you know, over this library that you guys have built up for people who are basically looking at this data as more than just information that they're curious about, but they're really like doing something professionally with it, right?

16
00:01:44,080 --> 00:01:50,460
And I wonder, like, what are the types of people who are sort of like going above and beyond just keeping up with it?

17
00:01:50,460 --> 00:01:58,120
I mean, I think that is a really good distinction between sort of the general enthusiast searching for news versus someone who actually needs to use that data to make decisions.

18
00:01:58,120 --> 00:02:07,320
And we're really focused on the in-house people at the large IT vendors and small IT vendors who have a specific marketing task.

19
00:02:07,460 --> 00:02:18,420
The PR person is sort of the low-hanging fruit for us because they make their money by following the influencers in different topic domains and participating in these discussions.

20
00:02:18,580 --> 00:02:26,960
Another area of particular interest to us is sort of the personalization aspects of when someone's interacting with this data, they have a research session.

21
00:02:27,160 --> 00:02:29,940
They may have decided to contact some of these people.

22
00:02:30,500 --> 00:02:33,880
They may have decided that they want to stay away from certain people because they're dangerous.

23
00:02:34,080 --> 00:02:38,480
There are some authors that are kind of, you know, a little bit scary that you want to stay away from.

24
00:02:38,600 --> 00:02:38,740
Right.

25
00:02:38,740 --> 00:02:41,520
I don't think there are very many, but I'm just kind of playing around.

26
00:02:41,920 --> 00:02:46,800
But I think that when you get out of that research session and you go away, well, the next time you come in,

27
00:02:46,840 --> 00:02:49,680
the system should be smart enough to recognize what you did the last time.

28
00:02:49,680 --> 00:02:52,380
Yeah, just sort of be adaptive and learn for what you're not interested in.

29
00:02:52,380 --> 00:02:59,080
So, you know, we want to do some really fun stuff that makes it intuitive for people to remember the people they like or don't like

30
00:02:59,080 --> 00:03:04,160
or that they know or don't know or keep track of information that's gone on in the past.

31
00:03:04,220 --> 00:03:07,360
Sounds like there's a large sort of human element involved as well, right?

32
00:03:07,360 --> 00:03:12,100
I mean, how does that play into the sort of library that you guys have built up?

33
00:03:12,280 --> 00:03:20,560
Yeah, well, you know, a big problem with, you know, finding everything related to IT and staying on top of it is that there's new authors popping up all the time, new blogs.

34
00:03:20,900 --> 00:03:26,100
Of course, there's a lot of churn within the IT trade publications, business press, anyone who covers IT.

35
00:03:26,600 --> 00:03:27,840
They're hopping around quite a bit.

36
00:03:27,900 --> 00:03:35,540
If you're just pointing machines at, you know, different links to look for content, you're missing a lot of these transitions and new things popping up.

37
00:03:35,680 --> 00:03:40,680
So that's sort of the human edge of, you know, searching and looking in all these different places.

38
00:03:40,960 --> 00:03:44,000
And we're doing a lot of the search so that the user doesn't have to.

39
00:03:44,520 --> 00:03:50,300
The user, when they do searches, they're finding the most targeted, comprehensive information that they possibly can.

40
00:03:50,480 --> 00:03:57,140
So we're taking away that sort of roll-up-your-sleeves drudgery that anyone would have to do when they're effectively researching any topic

41
00:03:57,140 --> 00:04:01,680
to find out who they want to contact or who their competitors are, what their competitors are saying, and those types of questions.

42
00:04:01,680 --> 00:04:09,140
Right, I mean, on the analyst side of things, you know, I'm always interested what goes on, you know, our side of the client as far as their information and everything.

43
00:04:09,340 --> 00:04:14,300
And it seems like the better ones, they sort of generate sort of like a crib sheet about sort of, you know,

44
00:04:14,340 --> 00:04:16,780
whenever we're meeting with someone, they might have a little information about a monk.

45
00:04:16,780 --> 00:04:18,000
Briefing notes, right.

46
00:04:18,060 --> 00:04:18,860
Yeah, something like that.

47
00:04:18,900 --> 00:04:24,780
And it seems like there's a chance of, you know, obviously there's a distinction between someone's just, you know,

48
00:04:24,820 --> 00:04:28,680
someone you work with is telling you what they know about something or the relationship they have with someone.

49
00:04:28,860 --> 00:04:34,680
But there is sort of like all of that information out in public where you could sort of start to build up a profile and what this person, you know,

50
00:04:34,700 --> 00:04:38,860
various people who are interested in different topics that you might be interested in talking about.

51
00:04:38,860 --> 00:04:44,520
You know, 10 years ago, Bacon's Media Guide was sort of the print Bible for, you know,

52
00:04:45,100 --> 00:04:49,600
trying to find any journalist in any technology subject matter or any industry for that matter.

53
00:04:49,860 --> 00:04:56,400
But they would go out, you know, once a year or however many times a year and canvas all these people that worked at these different news agencies

54
00:04:56,400 --> 00:05:01,860
and ask them for their feedback on what they cared about and how they prefer to be contacted and all these things.

55
00:05:01,940 --> 00:05:08,240
And they'd come up with little, you know, biographical information that you would then use to determine, you know,

56
00:05:08,260 --> 00:05:09,640
if they were appropriate to contact or not.

57
00:05:09,960 --> 00:05:14,640
You know, where we're evolving and what we're interested in is what does your bio mean, you know,

58
00:05:14,800 --> 00:05:21,760
for Michael Coté, what, you know, some bio that you gave to someone on the phone when you were multitasking and doing other things.

59
00:05:22,100 --> 00:05:26,260
I don't think that means as much about you as all the stuff that you're saying in your blog every day.

60
00:05:26,340 --> 00:05:31,240
I mean, you're writing about Adobe and IBM and Sun and all your different clients.

61
00:05:31,340 --> 00:05:35,380
You like, you know, RIA technologies and open source and software development trends.

62
00:05:35,540 --> 00:05:38,420
And these are things that I know because I've worked with you in the past.

63
00:05:38,580 --> 00:05:44,040
But to someone who's just fresh in this industry, they're not going to know that you're one of those people that matter in that

64
00:05:44,040 --> 00:05:45,740
until they've gotten their feet wetting.

65
00:05:45,740 --> 00:05:49,920
You mentioned reporting in the briefing notes earlier, and I neglected to mention,

66
00:05:50,200 --> 00:05:52,900
but it's actually a pain to pull those briefing notes together.

67
00:05:53,160 --> 00:05:53,540
Right, right.

68
00:05:53,540 --> 00:05:59,080
Because you have to research all those articles that that person that your executive may be meeting with the next day,

69
00:05:59,180 --> 00:06:06,100
and that entails finding the articles, reading them, extracting certain things that you can surmise that they're interested about

70
00:06:06,100 --> 00:06:08,080
based on what you've read and making recommendations.

71
00:06:08,500 --> 00:06:14,820
And, you know, we give people kind of a one-click, you know, way to automatically explore a lot of that information,

72
00:06:15,340 --> 00:06:18,960
and then they can overlay their own sort of analysis on that about their company.

73
00:06:19,300 --> 00:06:20,960
And it just really simplifies the process.

74
00:06:20,960 --> 00:06:25,160
I don't think it's very respectful, if you're asking for a journalist's time to meet with you,

75
00:06:25,480 --> 00:06:28,040
to go into an interview and not know what they write about.

76
00:06:28,160 --> 00:06:28,400
Sure.

77
00:06:28,620 --> 00:06:31,120
I mean, that's, and I think that happens far too often.

78
00:06:31,280 --> 00:06:36,180
You know, people look at an interview opportunity as their chance to impress something upon this person,

79
00:06:36,300 --> 00:06:39,140
and that may be part of what you're trying to accomplish.

80
00:06:39,140 --> 00:06:41,280
But you're also just trying to connect with another person,

81
00:06:41,760 --> 00:06:46,640
and nothing says that you're a jerk more, in my opinion, than not even taking, you know, 10 minutes to read it.

82
00:06:46,640 --> 00:06:47,660
Right, not really knowing about them.

83
00:06:47,700 --> 00:06:48,060
Exactly.

84
00:06:48,300 --> 00:06:50,700
It's like the low-hanging fruit of knowing about them, right?

85
00:06:50,720 --> 00:06:51,160
I agree.

86
00:06:51,500 --> 00:06:51,860
Yeah, yeah.

87
00:06:51,980 --> 00:06:57,540
And all the good guys out there and women in interviews, they do that extra homework,

88
00:06:57,660 --> 00:06:58,580
and I think it's very important.

89
00:06:58,580 --> 00:06:58,740
Right.