Show HN: Online Reputation Management for Restaurants
bistro.is
bistro.is
Looks good otherwise, and seems like a really useful service.
> Unable to connect to MongoDB: connecting to mongodb://web:###plaintextpassword###@dawson.mongohq.com:10036/bistro_production failed: Operation now in progress
Hmm, as the site is down I don't even know how to contact them. Hope they'll see it here very fast.
Is this more of an alert system on reviews being placed?
Currently, when a negative review comes in, we notify the user and provide advice on how to properly handle it. In the future, we will be incorporating some more advanced sentiment analysis to notify users of negative mentions on sites that don't offer a star-rating system (Twitter, Facebook, etc).
Having a family in the restaurant industry, I can say that most negative reviews and rants can be diffused with a little discussion and an offer to make it right. With Bistro, we just want to find every mention (from review sites or even personal blogs) and just start that conversation.
Thanks!
Doesn't sound like too much work given that you've said the system works on either web scraping or with API's of other review sites? Obviously you wouldn't want to jeopardize Bistro in it's current format through generalizing the platform for other "industries", but if done right, looks like a good opportunity to me!
That being said, you are absolutely right. It is very confusing. In the event that happens in the future, we will leave that field blank so users (such as yourself) can manually enter a location.
As for the "i.e." versus "e.g.," I was honestly not aware of the difference. You've prompted me to Google it, and the results are super interesting! Thanks for pointing it out! I'll make sure to get that updated.
Removing the city selection is something we've talked about, since it is less necessary, but it sounds like something we should move forward with.
You are right, though, that is very confusing. In the event that happens in the future, we will need to leave that field blank so users (such as yourself) can manually enter a location.
I tried doing this before with SquidCube but it was a bit too broad, and lacked the required focus to be compelling.
Thanks
For the reply, do you just link to the original site? Or do you let users reply through your interface?
What's the benefit of telling people that it's built with ST2?
I design (dead tree) books for a living. In the colophon, I always include information about the typefaces I’ve used (font families for print are usually quite costly — $1-3k — so I mention it to gloat about my purchase as well as wanting to give credit where it’s due), the paper it’s printed on (usually FSC certified), and the eco-inks (if used.) I also mention in which country the book is printed.
I don't mention it’s laid out in InDesign on a Mac and that the copy is styled in InCopy — that’s standard. For programming, there are more options. I use BBEdit and Coda, but I respect your choice and I appreciate you letting us know what you use.
It isn't necessary to the end user, but it is fun to show to designers and developers that we might want to work with.
Put it in http://humanstxt.org/
2c
Checking and updating the large list of review sites and social networks took more time than he had, so Bistro was originally created as a way for him to keep a pulse on his family's restaurant's online reputation.
We showed it off to a number of marketing managers of local restaurants in Boulder, CO and have since sold subscriptions to a number of restaurants in the area. Since the launch, we've gone through a number of tweaks and actually end up removing "features" fairly often. We know that restaurant owners are busy, but we continue to understand what they care about and what information we should drop to make their days easier.
What was the thinking behind current pricing structure? I think they are underpriced, but then again I know nothing about restaurant industry.
[Edit] Are you also doing sentimental analysis of mentions and reviews?
As for sentiment analysis, we were performing a rudimentary analysis on all non-rated mentions (Twitter, Facebook, etc.), however the algorithm we were using was providing too many wrong sentiments, so we removed it for the time being. We are currently evaluating new algorithms and APIs, and may bring it back in if we can find one that can comfortably handle sarcasm (a favorite of the review sites) and mentions with no sentiment attached to it (the phrase "I am eating at <restaurant name>" is neither positive, nor negative).
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