Brandwatch Beta review and Web Journal June 6-June 15th, 2013

I’ve often used platforms for social listening interchangeably even though they perform many of the same tasks differently, provide a different set of results with similar of identical input (for a variety of reasons) or have a different workflow altogether.

Just want to state that’s new Beta, which is now available as a link from their main page is a refreshing change of pace, is a “breath of fresh air”  and  a big jump forward for team Brandwatch forward from their original listening platform which was discussed in my Social Media Analytics book (mainly in Chapter 10).

I have been using the platform for advocacy as part of an  in-depth project at Rutgers University Social Media for the Arts class this Spring and Summer which crowd sourced students to find influential people (mostly via their Twitter accounts) in areas they are majoring in (such as music, fashion, food cuisine, graphic design/illustration/cinematography/fine arts, dance, environmental sciences, etc ) using tools such as Follwerwonk (now part of MOZ analytics), the Tweet Archivist tool and Twitter Search (not to mention the now available Twitter Analytics) .

I’m getting ready to release the result of this study to my students and the world at large but in the process of putting it together and I found the use Brandwatch invaluable. The project also gave me a chance to “kick the tires” of Brandwatch and find what was new, and how it worked in depth, in a real project.

Move over, this project I can talk about, as opposed to others that I’m not able to  – building advocacy is very important  – as you can’t display the work of clients without their permission, at least in university work, there is an ability which certain limits to share the work (thank God for that – otherwise no one would be able to talk about anything much of value except in very vague generalities – your typical business situation today – ie: Salesforce, Oracle, Adobe brochure / governmental , think typical NSA, situation.  It’s a wonder that anyone goes to conferences or listens to presentations to learn anything – almost all the good stuff is stripped out – ha!) and I have a lot to share here, most which hasn’t been presented anywhere yet.

Maybe a small peak at it near the end of the post.

So what has Brandwatch, in my opinion, improved on from what they had over the last 3 or so years?  Here’s a list of aspects I have noted, but I’m sure they’re not all-inclusive, a platform as rich in capabilities as Brandwatch takes time to fully learn and leverage.  Often features of a platform are unused because we’re not aware of them OR we have not yet found a reason to make use them.  To fully test out a platform you need to make an investment of time in it as the learning won’t come overnight.

  • The Interface and Workflow are much, much more streamlined and easier to use.  Even simple tasks such as saving queries and dashboards, which sometimes I used to forget to do, no longer are a problem – the platform makes sure you save every step (if you want to).
  • New functionality on Earned, Owned and Paid Media through defining Channels (mostly Facebook business pages or Official Twitter accounts).  The readouts on these channels can be added to your listening reports and are similar in nature to functionality that Simply Measured and SocialBakers provides at no additional cost.  I think this new functionality is a hat tip to Brand Managers that needed that functionality but didn’t have it embedded in their listening platforms.   Whilst Sysomos and a few others have let users peek at their Twitter/Facebook accounts, there’s no direct integration with the rest of the listening effort.
  • Brandwatch already had robust Content Tagging capabilities, but these are augmented and straightened with a powerful rule-set automation and classifications that improved on what was there.
  • The interface responds much more quickly than before, is more intuitive and data is updated and made available much quicker than it originally was when I first worked with the platform.
  • Data Groups were always supported but now have been strengthened to fit in with VoC and SoV, and can be further broken down via earned, owned and paid for media.
  • Extensive language support for foreign languages as well as a query engine that has sentiment analysis via industry categories (this was available before) but now is at the query level, and is much more transparent than it was before.


Now, in this Social Media Analytics space, many of the platforms have consolidated (the whole “Salesforce/Oracle/Adobe” Cloud concept) and in doing so have become mammoth whales of platforms, that are pretty much now useless except to other mammoth whale clients (as a friend of mine recently put it).  The original base Radian6 is next to useless and hasn’t improved much at all.  With without the augmented R6 Insights and BuddyMedia platforms, not to mention the newer acquisitions, the platforms, in and of themselves, were OK for 2007 but didn’t really evolve that much except via acquisition.

But the acquisitions made the platforms too expensive and unwieldy to use except for MDM applications for the few Enterprise clients that could still afford to use the new “whales”  – the type of client that a Salesforce, Oracle, IBM and Adobe always wanted – but that left anyone smaller without the means to pay for or use the new Clouds.    Brandwatch, to it’s credit, saw a gap left by the “cloud whales” and tried, as best it could, to fill it; I think they did an excellent job at filling the gap and being a best in breed listening platform that is also a pleasure to use.


So what’s left for Brandwatch to improve on?

It would not be a WebMetricsGuru INC post if I did not say what I also think about what Brandwatch could improve on.  I’m known as an industry independent (a role I really enjoy) and so I have to make sure that if I give some positives, I also pepper it with realism.  So here goes.

  • The implication of all of these new features (esp the earned, owned and paid media, channels, rule set automation, categories, etc) is that a business is willing to spend the time to  refine and annotate their listening efforts on a continual basis.  But that’s not at all clear that will happen in a satisfactory way, or will always be the case (as I mentioned in my book).  
    • There’s a significant amount of  time and effort in “tuning” and annotation (a better word would be “curating”) of the content that’s needed for Brandwatch to prove it’s full business value.  Based on my own experience and insights with the platform the design and workflow of Brandwatch assumes there is a commitment to this work, that analysts will be tasked within the business to support this effort.
    • Brandwatch has/had an opportunity to play here (Big Data), to my thinking  focused more on becoming  the better Radian6/Sysomos/Socialbakers/Simply Measured.  So far, that strategy has worked well for them and played into a gap occurring in the industry created by the various marketing, sales and social clouds from Salesforce/Oracle/Adobe and IBM, etc.
    • For a longer term play focus on the data itself and the process of working with it; Brandwatch has made strides there.    


Revenge of the Nerds – just what Omnicom is experiencing now! – Wikipedia  (by the way, I bet Omnicom and Annalect would not see what I just said in the same light as I do – but then again – look what happened in Davos a few years ago, when I debated Paul Holmes).  After all, if there ever was a person that represent Mar-com at its best, its Paul Holmes – but read what he said after we talked in 2011.

Paul Holmes and Marshall Sponder debate in Davos, Ch, February 2011

    • Might I add, the changes in PR/Mar-com are just inevitable though somewhat disconcerting and ludicrous to see Mar-com creatives and fluff at Omnicom  witness their businesses being taken over by the Quants that  they hate so much (even though the Quants are are powered by the Salesforce whale, itself  partaking of Mar-com fluff  – still).  
    • By the way, the feeling is mutual –  many of us, in the past, but not now, slaved in the back rooms of various  agencies that constantly talked out of both sides of their mouth and pimped themselves out, then had the analysts be slaves of an ever moving target that could never be satisfied (because it consisted mostly of hot air) – but times are a changing and clients now need something more robust than they have been given (and see through the agencies own bluffs).  See the quote from the article below:
    • “…Scott Hagedorn, CEO, Annalect, a Omnicom Media Group company, said the move will create a new type of advertising platform supporting services from planning to analytics, as well as the ability to trade media as stocks. It will also give the agency a new physical infrastructure he calls “physical data centers and social cloud rooms.” They will make clients feel “immersed in mission control centers” that demonstrate how the agency activates campaigns and combines transactional data.

    • Every millisecond, the agency bids on 1 billion opportunities to serve ads, Hagedorn said.

    • The agency will reorganize resources to create a new practice unit. The restructure and integration should take about 45 days to complete, he noted. Fortunately, most of the Omnicom companies use Salesforce technology, such as Buddy Media, and Radian6. Protecting that aggregate, anonymous data requires combining device ID or cookie data associated with a specific market segment. It then brings together client first-party data with Analects’.

Also, note that in many organizations, the CMO is becoming the CIO, and that the CMO is often being replaced by the CIO!

That’s reality – mar-com fluff all aside – good creative, good storytelling is paramount and always will be - but I don’t expect the storytellers to be good Data Custodians.    Nor can they be, their focus is telling the story – what we need(ed) was a true collaboration between both – something that both Creatives and Quants can live with and highlights the strengths of both – not a Creative throw the Quants under the bridge- because the Creatives get the business but then end up having the Quants do the lion share of the work, sort of steam engine room mentality, what we typically see in many agencies today that claim to work with data.

I know that’s changing. Even agencies like Droga5 are talking about Big Data like they own it now.  What is less clear is whether to me is if the gut level DNA of the  management of  Droga5 and agencies like it have really changed much, or are they just doing a “Big Data” mantra to the public and their clients, but in the back room, it’s business as usual with the quant marginalized by the creatives.

I guess we’ll just have to wait and see.  So far, what I have seen and heard sounded pretty good, actually – so maybe there’s hope to find some middle ground between the Right and Left Brain.

In fact, for corporations now, the big challenge has gone way, way past listening and largely in to MDM (Master Data Management) – the Corps are worried about “bad data” contaminating everything else they have.  It’s a data architects nightmare and a vendor solutions “wet dream” to solve that problem.  The issue now isn’t so much about listening data for the larger entities.. they want to know if the data the data they are collecting is  good data … and if it will sit with the rest of the data they have, and where they are going to store it, clean it, use it, etc.

And they are looking at the big fish – the one’s on the upper right hand corner in the charts below, for the solutions.  That’s where Salesforce wants to be – unless I’m missing something, they aren’t there – ha!  Not now and not in 2014-2015.  Well, well…

MDM 2012-2013 Gartner Comparison

Source: (chart from year over year Gartner Magic quadrant on MDM )

Summary on Brandwatch

    • In short, in focusing, over the last two years or so, on making a better listening tool, Brandwatch succeeded.  
    • Now, Brandwatch should focus on improving the listening process to further streamline and automate it (perhaps automating it somewhat more than rule-sets can do, alone)  – because the time it takes to make that listening tool work as well as it needs to,  might be more time than someone has or is willing to spend.
  • There’s also room for Brandwatch to further automate, based on some of their clients and third-party data, the categorization of paid, earned and owned media.  
    • To some extent a client can do this for themselves using the rule sets feature in Brandwatch, provided they can agree on what is “paid for” vs. “owned” vs. “earned” (you’d think a client would know this – but I’m not so sure they always do, or can always keep the definitions up to date) and go back and constantly update the rules – this will make the readouts more meaningful for people who use the information, but it may be too much to ask many organizations to maintain such a system.
    • However, in all fairness, I bet many of Brandwatch’s clients do spend the time to keep the their queries, query groups, categories, rule-sets and partial automation up to date, and for those who can or are willing to do this, the platform provides fantastic value for the price.
  • Finally, the Query Editor of Brandwatch is pretty finicky – many of listening platforms that use Query Editors are, but the editor could be more helpful in telling you exactly what things it doesn’t like.  In that respect, I would wish for a more “tolerant”, or perhaps a more intelligent Query Editor – as going back and trying to find mixed “AND” and “OR” statements that turn out to be “Quotation Marks” using sightly off character sets (values) can be a very time-consuming task for maintaining your queries.

So, to sum it all up, I’m really grateful for the use and continued use of Brandwatch that has now become my new favorite Listening Platform – I know they have what it takes to go yet further up the food chain and take on a bigger piece of the business and I’m always there to help and offer my advice (to any platform that is willing to work with me).    And Brandwatch has been a great sponsor to some events I’ve been connected with in the past, I know a couple of people who work there and so, I’m always keen to both use the platform and help, as I can, to add value (whilst remaining independent, and expressing a voice of the analyst).

A quick peak at what I’m working on at Rutgers based on the Crowd Sourced study:


Source: Brandwatch Twitter Data that is run via TwiAngulate


My thought process is informed by hands on work. As I work with the data I see things (in my gut) that make sense to me – such as network theory and the use of social network mapping.  Perhaps finding the right “nodes to approach” is a network mapping feature that could be developed (and even have students perform in a simple way – so as to streamline outreach efforts).

Source: Facebook Graph Search and WebMetricsGuru Social Intelligence INC

 Notice that last part…

By the way, notice this “beauty crowd” isn’t into technology much, or media for that matter – all of this will be released on a date not far off.


Web Journal

Just a couple of links to end this long, but overdue post:


Well that’s it – making up for not enough writing! Enjoy.




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