CopyDiva

Here’s a data point. I was at a Business Marketing Association meeting last week, talking to an agency principal who’s recently started using a social media monitoring service — the name of which I frankly can’t remember (I hadn’t heard of them before anyway). He had also demo’ed one of the bigger players in the space as well, but chose this new vendor because he liked the user interface better. In his mind, the actual data collection were comparable amongst all the vendors he looked at.

His need was not focused on real-time data — he needed brand-related data, which any of the vendors have, some of it real time, some not, some more robust and complete, some with more sources available.
What I wonder, from this very unscientific singular data point: Are measurement and social media monitoring services losing differentiation? Are they all delivering the same promise, or is it time for these folks to really work on that differentiation among the brands?

Certainly, there are differences — in everything from data quality to the analytics. But, are the vendors in this space doing a good job of letting the market know their differences? Do they need to at this point, or is the market big enough for continuing generic explanations of what social media monitoring or listening services offer?

Here’s my every now-and-again list of posts that’s I’ve liked and followed recently:

• I have heard many people talk about how every company should have a blog, which I really disagree with. Seems BL Ochman and I follow the same line of thinking.
• Discussions of measurement and ROI abound, both in the context of scalability (and here) and justification of paying for social media engagement.
• And yet others on measuring Word-of-Mouth and standardizing metrics there as well.
• Ways to bucket social media technologies.
• Should corporate communications people show their true colors when engaged online, or does that deflect from “the brand?”

Pat LaPointe takes some folks to task about the nebulous metrics of social media measurement tools. Now, I don’t necessarily agree with the ultimate premise — that social media measurement shouldn’t get money because ROI is fuzzy. However, it does bring up the issue for me that measurement of social media ought to have specific goals, such as:

• Baseline understanding: what’s our competitive position or share-of-voice?
• Location: where are the conversations happening that are important to the company, brand, industry, etc?
• Sentiment: are there glaring issues with perception of us?
• Trends: what’s the general context of the conversations? Do participants talk about us the way we expect?

Based on initial baselines, you’ve got somewhere to go — somewhere to move the needle. Can you make a difference through some kind of tangible engagement? What will have the greatest impact? If we change the way we talk about us to be more like what people say about us in social media, will it have a positive result on some other metric?

Interesting posts I read this week, so far:

• Improving your website as a business asset and lead generator: This post at conversation marketing gives you concrete steps to take for a 3-hour improvement on your site (probably good for sites that don’t have 100’s of pages).
• WOM moneyback guarantee: WOM agency BzzAgent is challenging themselves by pitting their efforts against a typical interactive shop — if they don’t do 20% better than an agency, your WOM campaign is free. Kudos to them on that challenge, its very compelling.
• Top 50 Women Bloggers: Want to know which women bloggers have the most influence (granted, as per usual, this is a subjective analysis)? What really intrigued me about this story was the incredible diversity of topics of these women, from knitters to sex therapists to techno-geeks.
• Alisa Leonard has great, cheeky insights when I remember to read them. She added to her list of things to do when you want to get social.

As someone who’s worked on the sales and client services side of marketing companies, Jim Sterne’s post today on Metrics Insider really resonated with me. What he talks about is that sometimes it is difficult to get a decision about contracted metrics goals for online marketing, because there are so many things to measure — you can really get off track quickly, trying to resolve organizational goals with what the metrics are hoping to achieve. Meaning, there can be a disconnect between how you are compensated (as a project leader) and the organizational goals. Case in point: organizational goals for a web site are to increase inbound leads by 10%. But, your bonus, or the metrics you’re being measured against are to improve the lead-to-conversion rate, or to cut the cost-per-lead.

The point is that its key to align the metrics on both sides — the organizational ones and the manager bonus ones as well.

Another good point to remember is that you can measure so granularly on a web site now, that you need to be careful not to get too hung up on measuring so many pieces. Measure and analyze within reason so that the metrics are trackable, but don’t get too bogged down in the endless details.

Alisa Leonard put out an interesting post today on the heels of getting demos from both Collective Intellect and Radian6, two competitors in the social media measurement space, and probably some others as well. (Disclaimer: I used to work for Collective Intellect). As someone who used to work in the measurement space, as well as a marketer, I find it interesting that the measurement piece wanted most by brands and PR folks alike is post-level tonality. Specifically, the ability to decipher whether a post, video, tweet, etc. is positive or negative towards the brand or whatever subject at hand.

Just to be perfectly clear: I also think it would be great, however, measuring tonal sentiment is difficult - for humans and machines. So, even if you are currently using a manual approach (ie, you’ve got a dark room full of low-paid interns reading posts and viewing videos, then categorizing for tonality) — you’re getting very inaccurate information.

Why? Plenty of reasons, here are a few:

• All people do not score a post in the same way: I might think a post is really negative, you might think its neutral
• Sarcasm: some people are sarcastic, others are not, but again, depending on the reader, sarcasm could be inferred when there is none

Basically, what I am getting at here is that particularly for written forms of social media, humans are not going to agree on tonality because how they read something is reflective of many things: comprehension, state of mind, attention level, etc.

So, is automated tonality better? Yes, but with a major caveat: Its better only in the aggregate. Anyone who tells you that they can measure sentiment at the post level with high accuracy is really pulling a number on you. Here are some reasons why:

Associations: determining tonality is complicated by the language used (how exuberantly negative or positive) and also how many different subjects are discussed in either a positive or negative way. For example, if a blogger writes about Coke, Pepsi and Diet Rite, and is positive about Coke and Diet Rite but negative about Pepsi, how is the post ranked? Even if you are only interested in posts about Pepsi, the automated tonality engine is looking for text that indicates tonality, so if it sees more positive than negative language, guess what? The post is scored as positive.

BUT, again, if you are looking for an aggregate view of all social media postings, then some of those misses become less important (unless you are measuring such a small number of posts that there is no real aggregate).

Social media measurement tools are very helpful in measuring certain things at a granular level, but tonality isn’t on that list. For anyone out there investigating these tools, you will be greatly helped by having realistic expectations of the accuracy of tonality from any of these vendors.