PhilGo20

I’d be hard pressed to guess if social media monitoring tools have finally crossed the chasm but they’ve clearly been riding a solid buzz for the last 18 months. Looking at the client list of Radian6, Sysomos or ScoutLabs  you soon realize that many major brands have jumped on the bandwagon to be able to monitor the buzz and sentiment that their brand, products and competitors generate.

Some voices are questioning the real value and possible ROI of these platforms, sometimes in opposition with free solutions. And it totally make sense when monthly fees easily range in the 500-1000$/month for the main solutions with a decent set-up.

One of these, entititled “The problems with Social Media Monitoring technologies“, seems to have decent web findability as it was sent to me a couple times by friends and clients in the past weeks. I’ll take a moment to go over these particular points one by one.

1. The technology is fairly stupid. It either don’t do what it says on the tin or do it quite badly. It is supposed to be simple: based on keyword configuration, the software scrolls the social web and collect mentions of your keyword(s). It then supposes to analyse themes and influence ranking and sentiment etc, which it does with limited accuracy . For example, will pick up any header, ad sense or footer mentions of your keywords even if it’s in the totally irrelevant context. If your brand name is pretty generic you are in deep sh*t. Hours of configuration and exclusions awaiting you.

You have the same problem when you search with Google. Building up good search queries takes time, analysis, trial & error and a good understanding of the brand, product and industry . Nobody said social media monitoring would be easy or obvious. The web is getting noisier everyday and good queries are more valuable than ever.

Unreliable data. The most important thing to understand is that the software simply provides you with piles of data. Before you can extract anything meaningful from this data you have to go through hours and hours of spam filtering which can be very tedious if you are dealing with 1000s of mentions every week/month. In some occasions I had over 50% irrelevant data coming through my dashboard. Additionally, the spiders cannot access all social spaces and sometimes the most important conversations are blocked.

There’s a clear need to be able to classified results by social engagement, source, language, sentiment and geo-demographics.  There’s spam in Google results as well obviously and you need good tools and techniques to cut through the noise.

Sentiment analysis is flawed. Again, this is part of the limitation of the technology. The software analyses keywords, not human emotions and, on average, the software gets it wrong 30% of the data because human emotions are subtle and complex and not easily categorised by software – we are not there yet.

I agree. And one of the reason is that we are usually measuring the message instead of the effect. Sentiment analysis should be mainly used as an extra filter. 60-70% reliability is better than nothing and probablu much higher for tweets.

Good monitoring tools allows for user to overwrite the results of sentiment analysis. Results needs to be reviewed, but it’s still much faster than evaluating everything manually.

Region specific data: for global brands, social media have very strong global element as well as clear regional bent (forums, blogs, networks etc). This is tricky especially if you are working with a regional client (e.g Huggies UK). Problem is for the software it’s not about where you are but which domain are you using. So reliable geo / regional analysis is, in many cases imposible to carry or not complete so need to be complemented with manual search.

True, Twitter localization is only based on what the user enters as location in but will soon be changed by the new API opt-in feature.
The ability to drill down the query with localization-related keyword helps obviously.

Influence analysis is flawed. Well, the concept of influenced is flawed so of course technologies of measuring it are flawed as well. Similar to sentiment, the technology is just not as clever as they want you to believe. It is based either on bogus metrics or just irrelevant, obsolete ranks .

Agrred, most implementation are. That’s why I always ask before evaluating or using. Sysomos has their own Postrank-style ranking. Social Mention (free) as added PostRank to their results.

If I were to design a full platform, I’d be using Postrank to rank results.

Time consuming. Because all of the above, the reality is that while thess companies provide you with piles of data and funky visualisations the profound unreliability of the software means you have to sit for hours and days and configure the dashboard, refine the data, correct the scores, filter the spam, get rid of irrelevant data AND THEN, AND ONLY THEN you can start making some meaningful analysis.

It does take quite a lot of time to set-up and it’s not easy. After a lengthy initial process, the work involved somewhat decrease but  you will still have to filter out some spam.

The analysis will always take time. That’s why many brands work with analysts to help them make sense of it.

Price. This varies significantly but the fact is that you pay just for the data and license fees to use the software. For the level of service you don’t get value for your money.

I’d expect to have access to an API to integrate with client workflow and platforms or to customize views and results, the ability to query on past period and modify queries at any time.

Conclusion

Social Media Monitoring platforms are not be-all end-all solutions, more of a building block of brand’s modern tool set for effective market research, marketing and customer support. They require investment both in time and money and more often than not, some support from people who have done it before and are comfortable using these particular tools.

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Ranking social media users can be seen as an ego trip, but with communication and information channels growing and evolving so fast, it simply make sense to use a somewhat automated way to filter out users based on their influence. While PostRank gives me a nice way to evaluate social engagement around content, many apps are starting to express the need to use a similar filter to evaluate Twitter users by interest and activity.

Getting a score for a user is not so useful in itself, but is (we’ll be) a building block and filter-classifier of many upcoming tools and services.

I haven’t yet found a tool that fully satisify my needs but here’s the best of what I’ve tried so far.

The Tested Ranking Tools

1. Twitterank
2. Twitter Grader
3. Retweetrank
   

The References

To perform a real test, I needed some kind of references, so I used the following profiles:

The Normal Guy

@PhilGo20 : My own profile. I consider myself a fairly active Twitter user, with an ok following (around 560) and a close to 1:1 follower/following ratio. I retweet, been retweeted a couple times and am mentionned a couple times a week in reply.

The VIP

@SebProvencher : Seb is a Praized.com co-founder (Mtl startup) and Product Development Manager. I like his tweets and read all of them (thxs for TweetDeck group feature). He has close to 1500 followers,  but he’s only following 480 persons, giving him what is seen as an excellent follower/following ratio.

The Popular

@Caterina : Caterina is Cofounder of Flickr and Hunch and a  social media startup star. She has over 9000 followers but just over 200 tweets.

The Not-So Active

@PhilipBoum : Philippe is one of the NOFOLO/Percute Technologies guy in Quebec City, involved in the business side of these web services small companies. I don’t know if he’s using an automated follow back script but he has over 1000 followers with only 14 tweets and have not tweetted once in the last month. I am guessing he has a life outside Twitter, and that’s good !

The Spammer

@entrepreneur949: Sorry if you read this and you are not, but by your tweets and your link, if I were to design a spam tool for Twitter, you would be targeted.

The Inactive (used as a reference for the test)

@philippegauvin : I am squatting my own name domain. Only 2 tweets redirecting to my real account. 0 followers / 0 following.

Each reference is pretty self-explanatory, except the difference between Caterina and SebProvencher. I wanted to have both because I think they have different type of influence. To me most of SebProvencher influence comes from his activity on Twitter while Caterina’s comes from who she is. Without being very active, she has an important following. Praized is not know on the street while Flickr is (pick your street).

The Results (on August 27th 2009)

Retweetrank (0-100 percentile)

• PhilGo20 : 91.4
• SebProvencher : 98.59
  
• Caterina : 98.6
  
• PhilipBoum : 0:0
  
• PhilippeGauvin : 0.0
  
• Entrepreneur949 : 0.0
  

Twitter Grader (0-100 I suspect it’s a percentile)

• PhilGo20 : 95.7
  
• SebProvencher : 99.7
  
• Caterina : 99.4
  
• PhilipBoum : 96
  
• PhilippeGauvin : 25
  
• Entrepreneur949 : 89
  

Twitterank (not normalized, 0-200+)

• PhilGo20 : 16.93
  
• SebProvencher : 94.97
  
• Caterina : 32.17
  
• PhilipBoum : 0
  
• PhilippeGauvin : 0
  
• Entrepreneur949 : 0

First, despite the usefulness of TwitterGrader and some well thought features (I like the tag cloud), it is no yet usable in my sense as it rank inactive and spam account way to high.

Retweetrank does a pretty good job, but it’s very harsh if you haven’t tweetted in the last month. I would think PhilipBoum deserves better than 0. Having read the way they rank users, it seems to be only looking at the last month of activity. There is pros and cons to that approach in my mind. It does a very good job at filtering out Spam account though. What I am wondering is this : Could only one spam supporter account  retweeting the main account be sufficient to put Retweetrank at wrong ? Have not tested it yet. Also, it does not really separate significantly me, Caterina, and SebProvencher. That’s why you cannot be using a percentile as an actual rank.

TwitterRank does a good job too, but also harsh on PhilipBoum account. Maybe that’s the way it should be, but maybe the guy took a month off Twitter ! On the other hand, this is the only tool, that seems to normalize the value (not using the percentile as a rank) and the only one that shows the difference between Caterina and SebProvencher’s influence.

Conclusion

I think TwitterRank is doing the best job by far here and their simple API is also a big plus. There’s is going to be a large number of ranking tool for social media users coming up in the next months, so it’s futile to bet on the future of this service but the need for it is obvious to me. Mash it !

The Online Reputation Monitoring tools market is growing at a fast pace as more and more company understand and express the need to listen to what’s being said about their market, products and competitors online, evaluate the influence of these conversations and analyze the sentiment expressed.

There’s now a gazillion way to do it, from free mash-up techniques like the one described in my previous post to uber-expensive solutions from media company.

Before evaluating the solutions, one would need some parameters to do so. Here’s a short list half-mine, half-borrowed

• Efficient filtering of queries based on language, country, source, date, topic
• Depth of coverage
• Real-time monitoring
• Duplicate elimination
• Smart Sentiment analysis (learning with time)
• Ability to modify sentiment analysis
• Sentiment plus (point in time, trend over time, compared with competitor, overlay with another issue etc.)
• Ability to associate timeline with events
• Identification, ranking and monitoring of influencers on multiple networks
• Ranking based on “social popularity” or social engagement (PostRank)
• Comparison to competitive information
• Identification of entity and events within the conversation
• Easy, dynamic ability to chart and graph analysis of queries
• Self-service set up of queries
• Multiple User Management
• Backward trending (and not just for 30 days!)
• Real-time threshold monitoring
• Integration with CRM system
• Analysis services by experts

I tend to put an heavy emphasis on the last point as so far from my experience, monitoring tools are only used as a first step to decipher the whole conversation and identify influencers while the real value lies in the results of the analysis services offered afterward. Despite great progress in technology, we still need a human with social science skills to make some sense out of all this.

I have evaluated a few software in this field and was preparing some kind of report for a client when I stumbled on a coveted Forester Report : The Forrester Wave™: Listening Platforms Q1 2009. With my limited resources, I could hardly do better than their evaluation and I was lucky enough to get it for free. And you can get it too, courtesy of Visible Technologies, evaluated in the report.

Only top-tier applications with a minimum of 75% of entreprise-level clients are evaluated in the report. Although they see listening platforms has being in their infancy, I was surprised to see the much-talked about Radian6 platform at the bottom of the ladder. According to Forester’s report, this is due to a lack of

sentiment analysis, NLP, insight generation, and integration and consulting services.

Nielsen BuzzMetrics and Cymfony are given as industry leaders based on

sophisticated sentiment analysis capabilities, strong international coverage, and
multilingual support

for the former and on

comprehensive reporting and analysis capabilities [...] well complemented by
a strategic and consulting services organization that offers advanced support for understanding
sentiment and influence

for the second.

A slightly older but well-done and complimentary report (with pricing info) on 10 leading online conversation monitoring tool can be found on Ryan MacMillan blog.

What do the actual users/customers of these tools have to say about them ? The best place to look for this might be on … a blog. Read the comments following ReadWriteWeb : The Future of Social Media Monitoring post for some great insights.

The conclusion seems to be that no tool yet offers a complete solution and I would be tempted to think that the greatest tool would be a giant mash-up of many smaller tools and technologies out there. More to come…

Have a good read !

DISCLAIMER : Many of the evaluation points mentionned above come from Anna B. at Organic.

I had been postponing to write this for a couple weeks, but a link shared on PostRank Twitter account left me no choice but to hurry up.

Social Media Monitoring is now an essential part of any brand, corp or product marketing plan. Between tools like Radian6, BuzzMetrics, TechRigy, one can also use free tools like Google Alerts to monitor mentions of keywords or brand name in the news. It’s way too late to get any decent readership with a “How to Monitor Your Brand With Google Alerts” but add a SocialMention.com feed to the mix and you just spiced up an old recipe, allowing monitoring of social media platforms. And everybody likes good free online reputation monitoring tools.

Btw, SocialMention is a great social media search engine developed by Jon Cianciullo in Ottawa.

Social Mention monitors 80+ social media properties directly including: Twitter, Facebook, FriendFeed, YouTube, Digg, Google etc.

SocialMention also uses Backtype API to monitor blog comments.

So that’s what this guy did and he created a video tutorial to show how to do it. Super simple.

So what I am adding to this ?

Well, one problem with this method (and with most monitoring services) is that you can rapidly get an avalanche of alerts and you will most likely spend a good amount of time flying through the list to see what could be relevant. On top of that, that does not tell you the reach or range of influence of these results. You’ll have to look it up yourself to see if these links where bookmared on delicious, shared on twitter, if they have comments and so on. Lengthy process.

The magic trick ? PostRank by AideRSS.

PostRank is a scoring system developed by AideRSS to rank any kind of online content, such as RSS feed items, blog posts, articles, or news stories. PostRank is based on social engagement, which refers to how interesting or relevant people have found an item or category to be. Examples of engagement include writing a blog post in response to someone else, bookmarking an article, leaving a comment on a blog, or clicking a link to read a news item.

Available as a GreaseMonkey Script or a FireFox extension, it will basically gives a 0 to 10 ranking score to any item in your Google Reader List and allows you to filter out result based on their PostRank score. Look at your Google Alerts + SocialMention feed in list mode and instantly know which one are worth looking at, based on the social engagement they generated.

That’s it, a cheap and manageable Online Reputation Management tool. Not perfect, but worth trying.

If you need more info about integrating PostRank with Google Reader, look at this.

EDIT:

Both (mine and Intelligendo) explanation kinda skimp over what you should be monitoring.

Marty Weintraub create a great tutorial on how to do this and how to choose search terms for monitoring