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Fern Halper

Top 5 Challenges of Text Analytics

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mnorth
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The Top of the Top Five
mnorth   10/19/2012 8:36:52 PM
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Great post! A timely topic, becoming even timlier.  In my view, the taxonomy is the biggest of the five you've listed.  There are so many variations on ways to create a taxonomy, because the data are unstructured, so there's little embedded guidance as to how to structure your taxonomy.  This, I believe, is why organizations absolutely must commit to documentation, standards, and repeatable measures in their text analytics activities.  Otherwise it's going to be very difficult to meet the other challenges (such as believing/trusting the data and results).

MDMconsult
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Re: Great Post
MDMconsult   10/19/2012 7:39:15 PM
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Interesting. Text Analytics software used for ROI should be deployed and compete with other methods to solve problems. Organizations can select Text Analytics if it can produce a better result or better problem solve versus other analytics methods

lscagliarini
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Re: Great Post
lscagliarini   10/19/2012 8:19:25 AM
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Yes, it's true that turning the soft benefit of text analytics into an ROI is difficult, as Beth mentioned. Or that today, most text analytics projects do not have ROI as Fern says, but in at least 2 of the 5 reasons Fern lists in her post http://www.allanalytics.com/author.asp?section_id=2013&doc_id=242200& (customer service routing or deflection and lead generation), it is pretty common to use ROI models to evaluate the investment in text analytics. Obviously, this is more difficult in voice of the customer or customer experience optimization projects. This is unfortunate because these are probably the initiatives that bring the highest ROI to organizations, as usually they contribute to both revenue growth and cost reduction. However, I think this is more because predictive models accounting for "soft" variables are still in development. I think the analogy with weather forecasting that I wrote about here http://www.expertsystem.net/blog/?p=266 is valid. When these new models are developed, it will be a great day for text analytics because adoption will grow significantly. We'll see if I'm right :). In any case, thanks to both of you for the high quality work you      are doing on this site.

Fern Halper
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Re: Great Post
Fern Halper   10/18/2012 3:17:54 PM
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Thanks @lscaqlarini for your kind words about the post.  You bring up a good point about ROI.  Interestingly, a large number  of the companies I speak to don't have to do an ROI analysis for their text analytics software.

BethSchultz
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Re: Great Post
BethSchultz   10/18/2012 10:51:01 AM
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@lscagliarini, first off, thanks for jumping onto the AllAnalytics.com message boards. Welcome, and I'm glad you found value in Fern's post! You raise a great point, as well as a potential difficulty, I'd say. The soft benefits associated with being able to analyze text quickly and efficiently are fantastic. But wouldn't you say they're awfully difficult to work into a formal ROI statement? 

lscagliarini
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Great Post
lscagliarini   10/18/2012 9:07:59 AM
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Perfect analysis. I would add, from my experience, that ROI calculation for text analytics projects, especially the most strategic ones, often requires accounting for the cost of ignorance (i.e. loss of potential revenue or cost savings) that cannot be easily calculated using traditional data based financial models. What are the costs of not interjecting a complaint about your product in time or finding out late (and too late) about an existing patent in an area related to your R&D project, or not being able to immediately identify an employee with the right skill set to address an urgent organizational issue?  This is not so different from what was happening to supply chains 15-20 years ago before the right models to deal with their complexity were developed.  In any case, this is a great post, one that I'm sure to refer to again.  

Fern Halper
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Re: Sarcasm
Fern Halper   10/16/2012 3:55:36 PM
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I guess that would depend on a)what tool was used and how finely tuned the sentiment was and  b)who the analyst was that was doing the analysis and whether they tuned the sentiment.  I would be suspicious of anyone making the claim that mentions somehow equates to who won a debate in any event - I'd have to see the other part of the analysis!  Goes to show you how someone can use an analysis and say what they want from it.........

PredictableChaos
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Data Doctor
Re: Sarcasm
PredictableChaos   10/16/2012 2:36:06 PM
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The morning following the first presidential debate, a twitter analysis showed that Romney had significantly more mentions than Obama -  and this was cited as part of the evidence that Romney won.

Given the widespread use of sarcasm and irony around the topic of presidential politics, is this data even 70% reliable?

PC

BTW - The second presidential debate is tonight.

BethSchultz
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Re: Access Control
BethSchultz   10/16/2012 2:10:41 PM
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Alexis, right -- lots of front end work required to make sure you're working with quality data. In a way, that's no different with text analytics than any other sort of analytics, at a basic level, at least.

BethSchultz
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Re: Access Control
BethSchultz   10/16/2012 2:08:52 PM
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@Noreen, for some reason I'm having a hard time reconciling the idea that a grocer than lets a store become a "nasty, dirty place" would be bothering with text analytics. That seems a disconnect to me -- why invest in measuring measure customer sentiment using advanced analytics tools if you can't even bother to pick up a broom and a mop?

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