00:00When you were having those early conversations, deciding like okay what
00:03are the actual pain points here, what were some of those that you guys came
00:06upon that you started to innovate for? So the really big thing in the early days
00:09was speed, right? So right now the research process, if you use humans for
00:13the whole process, which most brands do, it takes about four to eight weeks to
00:16get from, I have a problem, I have an information gap, and then I now have the
00:20insight to go and act on that. For us that takes about 24 to 48 hours and that
00:24was a step two process. Like we started out, like I was saying, with Tesco and
00:28Diageo, and we were able to turn around data in kind of seven to ten days just
00:32because we had three engineers who were nerds and wanted to automate things and
00:36didn't want to take lots of time and they were like don't worry about that
00:39panel thing, you guys can deliver insight to seven to ten days, that's amazing, double
00:43down on that. And so yeah really stepping up the automation and then stepping up
00:47the AI was like the early innovation to that speed. And I think the speed is
00:51almost like the Trojan horse, like speed gets us in the door with brands but
00:54actually coming back to the idea that people are buying comfort, now there's a
00:58real drive to the quality of insight and what that isn't, that's not just like
01:02the quality of the consumers who are giving their opinion and it's actually
01:05like the first principles understanding of what is the original problem and then
01:09tying that to the inside at the end. Because I'm using a lot of analogies now
01:13but the people want a quarter-inch hole not a quarter-inch drill. So when
01:16someone comes to you with a problem they don't care how you really get you get
01:19them there. So we like 24 to 48 hours is exceptional, it's taken us years to get to
01:23that level of speed. But actually it's 24 to 48 hours too slow. People say like
01:28if you asked our clients now they would say I want to be in a meeting, get asked a
01:32question as to what should we do and be able to pull the insight from what we
01:37already know. Like there's so much research out there already, there's so
01:40much data out there already, the speed at which we can access and understand that
01:44data and then only run new research on where there is gaps. That's the way
01:48research has to go if it's going to have any chance of competing at the highest
01:53kind of decisions in these brands. Yeah and that's why there's a lot of
01:56excitement around our retrieval engine, so that kind of secondary data analysis
01:59knowledge management piece because you don't need to waste to go and gather data
02:02and wait for the turnaround for those responses. You can just mine your existing
02:06data and get an answer to a question in that meeting with that stakeholder.
02:09Right.
Comments