LexaBlog: Our Sentiment about Text Analytics and Social Media
The Customer is Right
I’ve seen many postings advising companies on listening to their customers, especially as new voice of the customer outlets such as Twitter (can we really still call Twitter “new”) evolve and grow in usage and maturity. We’ve discussed it on our own blog in the past, and Chris Brogan has some excellent postings about “café-shaped conversations”. The underpinnings of these conversations is listening for feedback from your customers or the public at large, hearing what they are saying, and nurturing your dialogue with this audience. But the audience for these articles is generally businesses establishing themselves in the social web. I want to talk to a different audience in this article, the customers, and share some of my experiences in listening to you and hearing your feedback. The quotes are taken from actual emails; names have been withheld to protect the innocent.
“Do you ever sleep?”
Hearing this from a customer is great, because it means that we’ve been responsive to you on your timeline, regardless of what timezone you are in. The truth is, yes, we do sleep…sometimes…with a Blackberry or laptop nearby. But we are a small company, and we don’t have 24×7 support. Realistically, there will be times when we can’t respond immediately, and there may be cases where that delay is going to make the issue more of a problem for you. Our commitment is to respond to feedback, comments, questions, problems as quickly as we can, and as thoroughly as we can.
“I feel as though I’m bugging you.”
There’s one occasion I saw this comment and another occasion I saw something like it, and I’ve responded to it immediately in the same way both times. Absolutely not. Not every piece of feedback from a customer (or potential customer) will turn into actionable changes in our products. But, each and every piece of feedback, in the form of a comment or an issue raised or a question, gives us the opportunity to see our products through the eyes of an end-user. This comment may indicate that a customer is not getting the answers they need, or the response they need. We pay attention to that too, it means we need to try harder to understand your situation and help you.
“Thanks.”
We love hearing this one (doesn’t everyone?). We’ve gotten this when a customer, or even someone engaged in a trial of our software, has come to us with a question or problem, and we’ve been able to show them how the software can be used to solve their business problem. And with that support from us, they are able to use our product, use our product better, understand their data, or understand a different approach to their data than they might have considered before. That’s progress, and that is what product support is about.
Conclusion
Why did I write this? Because at the end of the day, we can write all the cool software we want. But it’s our customers, and the business problems they are applying our software to, that make it worth doing. And having the dialogue with you, the customer, is a vital part of us understanding your need and knowing we’ve helped be part of a solution. Companies are being told that listening to their customers is more important than ever, I wanted the customers to know we are hearing them.
- Carl Lambrecht's blog
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Comments
Mike, this is a good idea.
We do recognize that the questions are tailored to a particular vendor’s feature set, even if responses are fair. For instance, your questions 1 & 2 are not relevant for OpenCalais, which is delivered as a Web service.
I am, however, skeptical of self ratings. For instance, Lexalytics doesn’t run on Unix or MacOS, right? So I’d give you two stars. A rating point is foreign-language support, but Lex has none so you get no stars, and Lex is less open than open-source GATE or RapidMiner or open-code LingPipe so I’d reduce you to two stars. But this is nibbling at the edges on my part. It’s a nice effort.
I do have three significant questions.
1) Your point 4 is “Flexibility of entity extraction” but what you show is annotation, not extraction. What are Lex’s extraction capabilities, either into XML possibly including RDF triples or into a database or some other format?
2) Do we not need to look at accuracy, performance, and throughput?
3) Ecosystem: Some vendors have alliances with vendors whose applications consume text-analytics output, for instance, BI or e-discovery or search tools. Some vendors offer visualization or data mining capabilities. All this matters for some users.
These are just off-hand thoughts. Good start.
Thanks for the feedback Seth, I actually agree with most of what you say especially around the star ratings, with hindsight no stars for language support is perfectly correct. I’m not sure that I would agree with you on the Open Calais issue though, surely it is of utmost importance to know if you can install the software on your own stack or have to use a webservice with all the latency issues that involves.
Answering your specific questions
1) The screenshot is of a tool that we are releasing alongside our 4.1 release that will enable you to annotate your own data with what you consider entities and then make a trained model that will exist alongside our existing ones, giving you complete flexibility in what you recognize as an entity, and thus what you can extract. To your other point, this write up focuses solely on Salience, which of course is an SDK so entities are returned as structures / objects in whatever lanaguage you are using. It is a simple task to turn those into XML, insert them into a DB etc.
2) Yes we do, though as discussed in other places accuracy is very hard to judge, hopefully one day someone will produce a base line test set that we can all run against.
With regards to performance I wrote something about that a few weeks ago http://blog.lexalytics.com/2009/02/17/every-little-bit-helps/
3) Yep it does, our own partnership with the Enterprise Search vendors or various VoC companies for example help bring text analytics into a more mainstream market. Not sure how you would rate that on a meme however, number of partnerships?