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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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• Twitter Works to Improve Location ID Service (marketingpilgrim.com)
• Google Gives Sentiment Analysis a Multistar Rating (mikemoran.com)

Tagged: monitoring, orm, postrank, radian6, ranking, sentiment analysis, social engagement, socialmention, twitter