 If you're a great marketer in the building material space, you're looking at your data. You're seeing what that data is telling you about where you're getting customers, how you're driving leads, and what issues people may have with finding information that they're looking for. But there's a cost to dirty data, and what I mean there is that if you're not collecting data the right way, if your data is actually reporting it correctly, you can be making decisions off the data that's completely false. One thing we always do with our clients, and this is not a plug, but one thing we always do is we're checking the data to make sure that we are collecting it the right way, and there's nothing out there that's skewing it, whether that's bots from Amazon or that's some Russian website trying to hack into our site. 99% of the time we go and we audit an analytics setup, we're finding an issue with collection of data. I'm not making that up. So one thing you need to do to make sure that you're not running into issues with dirty data is look at the bots. You can see if you see anomalies with places like Ashburn, Virginia, which sounds crazy, but that's where there's a lot of Amazon farms. If you're seeing spikes in traffic at weird times or weird countries, filter that out within your analytics. You may find that this will drop the overall traffic on your site. What you're going to get out of it is a much cleaner picture of what's happening across the board with your true actual customers. One example of this was we had a client who had a bunch of traffic at one metropolitan area. They thought that, wow, we're just killing it in this one area. What they found that there was a dealer that was looking at their site over and over and over throughout the day, and this data was not filtered out from the reporting. So they're making decisions thinking that people wanted their product in this one area, but it was just one dealer. This impacted the overall strategy, and if we didn't get in there and take a look at that and solve that for them, they would have gone a complete different direction. So when you're thinking about cleaning your data, the most important thing to think about is assessing is what I'm looking at true and clean, and do I feel confident in the reporting and if I'm going to move in the direction that it's telling me to go?