I spoke with Scout Labs earlier this week and got access to their platform for an extended period of time so I might evaluate it and compare it to other Social Media Monitoring platforms (see More Analytics Platforms I’m looking at right now) – so far, I like what I seeing and the price is right (between 100-200 per month for the full functionality).  I must say that parts of Scout Labs remind me of Sysomos Map, and I like what Sysomos does with keyword and phrase mining.

I’ll list what I noticed in this first testing of Scout Labs in no particular order as I’ll be using it more over the next few months.

I’m using a case study of  the Cuban Restaurant – pretty much the same test I’m running in Viralheat,  I set up a similar profile in Scout Labs.

Here’s what I set up for Scout Labs and the local Cuban Restaurant chain, Havana Central.

Required = AND while Relevant=OR and Excluded = NOT – the interface to enter queries is very simple and seems to cover all you would need to enter a complex search query, yet very simply.   In this case I went with “Havana Central” but NOT “Old Havana”, the same exact query I put into Viral Heat and the same one I’ll put into Sysomos Map now.

The first thing I noticed is my saved searches are ranked by the amount of change (Buzz) that took place over the last two weeks.

I wrote last night (this post is updated) that Scout Labs can look at only one month at a time – but that’s not true – actually – it has a window of up to 6 months (not sure if you can look back further than 6 months as your profiles continue to run or not – maybe Scout Labs can weigh in on that).

Note: there is an assumption with several monitoring platforms – as your monitoring Buzz, what your monitoring is fairly current and offering historical data is not necessary.

I’m happy that Scout Labs provides 6 months of historical data to begin with.

I’ll make my point again – a historical database is really almost a  necessity for some of the work I do.

Volume of Social Media Mentions

Still, comparing Scout Labs to the competition in terms of volume of mentioned brings us some interesting things

Scout Labs

Radian6

Sysomos MAP

Notice how different these 3 platforms are in just picking up data – Scout labs has far less data it picked up over the last month and I’m not sure why,  but I will ask.  One possibility is noise filtering and spam lists – Sysomos is pretty good at filtering out noise – maybe Scout Labs is too, but maybe it’s filters are different

- (I think that all the platforms are different in this respect, Volume and you will not get an identical results in any of them – not unless there is one crawler/data source for all the Social Media Monitoring platforms use as their primary source – and they equally draw upon it – a idea no one has yet proposed that I’m aware of).

IDEA: Having said that, I did propose “plug and play” modules was part of the future of Social Media Monitoring when I spoke in London last November (see slide 20)- and maybe the “plug and play” module is the data itself – let’s have one or two companies supply the data the rest of them use – that would make the comparisons a lot better in my opinion – as well as the collection of data.

The idea of a single data collection process for all vendors has merit, and it fact, is somewhat similar to what ATM machines do now – when it comes to money, people are lot more particular about who has what … but isn’t information now more valuable than money? – esp if its the right information.

We want a clean, accurate data collection process and that’s clearly a problem for all the vendors as they are pooling the data together and storing it as best the can – but it causes interoperability issues  - no one’s data essentially agrees with one another, for the most part – sorta like Quantum Physics - but do we really want that in Analytics?   Do we really want to have 10000 vendors with 10000 versions of reality to pick from – because that’s more or less, what we have now.

Radian6

Sysomos Map

Scout Labs

As usual, the numbers don’t come close to each other – the same thing I found recently when I compared the first set of platforms.

Radian6 Blogs =   15%       60 blog posts

Sysomos Blogs =  13%      40 blog posts

Scout Labs Blogs=64%    30 blog posts

See what I mean – no standards at all – it’s totally up to the vendor and they are making their own rules based on what is easier for them to aggregate.

Also, I notice Scout Labs has a functionality very similar to Sysomos Map in that it captures significant phrases; in addition it also displays the sentiment of the phrase – very nice.

Scout Labs Quotes

Sysomos MAP

The Sysomos quotes  are   chosen using by a different algorithm than the Scout Labs quotes  and I’m not surprised – if you read the rest of this post it’s obvious none of these platforms will agree on anything the majority of the time- but  I like the quotes Scout Labs picked up.

Radian6 does not have this functionality, no point comparing them  on it.

WorkFlow Management

Scout Labs

Scout Labs is roughly comparable with Radian6 in Workflow Management as you can assign a tweet or blog post to someone on the team to answer.

Radian6

Sysomos MAP doesn’t have workflow management, nor does Viralheat,  not point in comparing them to such.  It’s possible that Sysomos Heartbeat does have features that Sysomos Map does not – there may be Workflow management there – but I haven’t explored Heartbeat much yet – so I’ll leave it out of this discussion for the time being.

My next post in this series will measure sentiment analysis Scout Labs vs. Radian6 and Sysomos – plus anything else I can pull in – I’d do the sentiment analysis but for a notice the data takes 24 hours to have sentiment.