Ever feel like despite all the recent competitive tools flying onto the market that somehow you're still missing the "big picture"?
RoboCrush plans to fill this gap.
Sure it's great to know what keywords a competitor is using and for how long, but ultimately isn't what really matters their overall strategy. And even then what many companies still fail to track is "clusters of competition" and their relationship to trends in their markets and segments of those markets.
That's why at RoboCrush what you see isn't necessarily "what you get". Sure, when you look at our pre-upgrade data you may think you know what you're seeing.
But what if we told you that the keywords shown do not not necessarily "belong" to the company listed. In fact what if we told you that company "numbers" don't even designate "specific" companies, but instead are uniquely determined clusters determined by our proprietary RC Factor algorithm?
Although we have started publishing our data, we are still in our test cycle and will announce our formal launch date as soon as we can. Our number 1 priority is data reliability so at this point we do not have a concrete launch timeline.
We will keep the status of beta testing and all launch information updated on the RoboCrush blog.
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It’s been an alarmingly fast past June and we blew right past Fathers’ day without a nod.
New models of aggregate trend analysis are unfolding from our initial beta testing and we’ve garnered a bit of underground media interest.
We are attempting to analyze the effects of various variable constraints when applied to model overlays across market [...]
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Just a quick greeting to all the great mom’s out there to wish you a happy mother’s day - including mine of course - happy mother’s day!
We’ll have some interesting updates a bit later this month, so definitely stay tuned.
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Sorry for the lack of updates recently. It’s not for lack of productivity.
As you know we’re beta testing traffic channel specific implementations of RoboCrush and hope to be able to work on merging some of the aggregate trending data in order to create super-aggregrate trending model overlays, although the complexity of that project has grown [...]
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As discussed previously, while model overlays are typically most useful for analyzing the growth pattern and potential strategies of specific businesses or within more localized market segments, aggregate trending models tend to be most useful for identifying potential model anomolies within related market sectors and predicting the likely future existence of breakthroughs that could lead [...]
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OK. We’re going to “geek out” on you a bit here. There’s been a lot of buzz recently about model-independent overlays when it comes to collecting and organizing data for feeds into aggregate trending models. As in any good system the separation of data from the mechanism for manipulating the data is key although in [...]
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