Archive for the 'reviews' Category

5 Ways to Simplify Mobile Reviews

You can never have too much data – especially when it comes to local reviews.  So for developers of local, mobile applications its worth looking for ways to simplify the process of capturing reviews.

So, here’s a list of 5 ways mobile application developers can simplify how a user identifies the business they want to review.  Here’s the scenario I’ll explore: I’ve just had a meal at a restaurant and want to quickly identify the business and give it a review.

1. Use a photograph of the menu

Take a picture of the menu and use software to automatically recognize the restaurant based on the picture.  The SnapTell iPhone application which provides ‘visual product search’ is a good example of this principle in action.   Now, just take that technology and apply it to local reviews.

Also uses: geo-location (GPS, cell-towers, wi-fi) as a hint to the image processor.

The challenge: photographing and tagging all those menus.  The crowds can help you out on this.  Restaurant owners might even be motivated.

2. Use a photograph of a code on the menu

Take a picture of a special code (likely a 2 dimensional bar code) somewhere on the menu.  Probably much more reliable.   You also get to engage the restaurant owner as an active participant in the process.  Google recently issued a patent on this idea.

Also uses: probably doesn’t need much help, a 2-D bar code would probably be reliable by itself.  That’s an advantage.

The challenge: getting restaurant owners to re-print their menus with 2 dimensional bar-codes.

3.  Use the restaurant’s wi-fi or blue-tooth signature

The restaurant could be identified by it’s wi-fi or blue-tooth signature.  You could even have the restaurant owner install a device explicitly for the purpose of being identified.

When the user opens the review application, you automatically present them with the restaurant based on the detected signature.  In a dense urban area, you might present them with a few different options on the screen.

Also uses: presents options to the user and gets confirmation/feedback from them.

The challenge: tagging all those signatures.  But others might be doing that anyway.  This might just become part of the general ‘geo-location’ infra-structure.

4.  Use location assisted auto-complete

The review app could use location-assisted auto-complete to quickly pick the restaurant to review.  Location is determined using GPS, cell-tower location, wi-fi or bluetooth signatures.  The user starts typing name of the restaurant and it auto-completes based on knowledge of place.  In most cases, the user will only have to type a few characters.

Also uses: The keyboard for input and a variety of geo-location technologies.

The challenge: geo-location information sometimes isn’t very accurate, so you need to make sure the auto-completion algorithm casts a wide enough net.  You also need geo-references for all the businesses.  But this one feels ready to implement now.

5.  Use augmented reality

Point your video camera at the outside (or possibly the inside) of the restaurant – see the name of the restaurant on the screen – pick it and enter your review.  Augmented reality is a hot-topic right now.  This one has sizzle, but I’m not sure it’s as practical as some of the other approaches.

Also uses: depends on accurate geo-location and a compass.

The challenge: accurate geo-location and tagged photographs of all those places.

More Reading

All of these suggestions are made possible by exploiting the array of new sensors available on mobile phones – which, as I’ve written previously, is turning them in to the Remote Control for Our Lives.

Recently, Tim O’Reilly has been promoting the idea of Web Squared – the evolution of Web 2.0 made possible (in part) by the sensors in phones.  These five suggestions are  an application of these principles to local reviews.

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Google Patent’s My Invention to Simplify Reviews

Google has just published a patent for a process to simplify creating reviews using a smart-phone.  Bill Slawski describes the patent on his SEO by the Sea blog.

In simple terms, the idea would be to have UPC codes printed on something like restaurant menus.  Then you use the camera on your phone to photograph the code which automatically identifies the restaurant and lets you link your review to the restaurant.  The use of the code and the camera is intended to be faster and more convenient than having to enter the name of the restaurant manually.  The broad goal is to make it very easy for users to provide feedback.

And as Mike Blumenthal pointed out in a tweet, one nice thing about this process is that you would actively engage local merchants in the process.  Of course, that’s also the biggest hurdle — you have to get all those businesses to use your code.   Fortunately, there are alternative ways to simplify the process.  More on that in a future blog post.

Here’s the funny thing.  I remember discussing this concept with a colleague sitting in an airport in the fall of 2007.  Google filed their patent in March of 2008.  Of course, I didn’t disclose anything and I didn’t file a patent of my own.  So, Google wins.  And my generally ambiguous feeling about the worth of these kinds of patents continues.  I guess I need to either write my own patents or disclose the ideas on my blog in sufficient detail to prevent patents.

Netflix Prize has lessons for local search

The Netflix Prize seeks to substantially improve the accuracy of predictions about how much someone is going to love a movie based on their movie preferences.

So what does this have to do with local search? Researchers working on this problem have found that you should ignore everything you know about the movies (the genres, the actors, etc.) and base your predictions on how people have rated them.  For local search this means we should base recommendations on people’s preferences – the businesses they like and have used – rather than categorical data about businesses.

Lessons from the Netflix Prize

From a New York Times article on the Netflix Prize:

“You can find things like ‘People who like action movies, but only if there’s a lot of explosions, and not if there’s a lot of blood. And maybe they don’t like profanity,’ ” Volinsky told me when we spoke recently. “Or it’s like ‘I like action movies, but not if they have Keanu Reeves and not if there’s a bus involved.’ ”

So, you can’t base movie recommendations on a simple categorization like ‘action movie’.  Its difficult for most people to articulate what they like or dislike about a movie. So, its better to base predictions on what you know about which movies the person likes or dislikes. In fact, researchers have consistently found that adding in categorical information about the movies doesn’t help with making predictions at all. (And there have been numerous attempts.)

Applying it to Local

The research from the Netflix Prize shows us that you shouldn’t recommend a pizza place to someone just because it’s a pizzeria (i.e. it’s category) and it’s ‘close enough’ to you.  That’s because the best choice can be influenced by many factors:

  • Am I a person who likes my pizza ’straight-up’ or exotic?
  • Am I in a rush and looking for the quickest option?
  • Am I bored and looking for something new?
  • Have I just come back from an exotic location and looking for an old favorite?

Today,  local search engines continue to rank results based primarily on  factors like category and location.  Even sites such as Yelp with extensive reviews rank and present results to users without considering the preferences of the searcher.  This is akin to simply presenting movies ranked by popularity alone.

Research coming out of the Netflix Prize shows the way towards a different way of thinking about local.

RELATED:

Forget search: local is a recommendation problem

5 ways to re-frame Yellow Pages

At the recent YPA (Yellow Pages Assocation) conference Malcolm Gladwell set the stage from some productive industry discussion by urging participants to re-frame the Yellow Pages.  Neg Norton has a great summary on the YPA blog.

So, in the spirit of continuing the conversation, I humbly submit the following five suggestions:

1. Proof is even better than research

Yellow Page advertising has always been (rightly) sold on the basis of a proven ROI.  Why not build on this position by making EVERY print, online and mobile ad track-able using tracking numbers.  Then you can definitively prove the ROI to EVERY one of your advertisers.  Do it for all your advertisers – even, perhaps especially for – subscription products.

2. Be the mobile maven

Mobile audiences are exploding.  But mobile advertising is slow to catch up.  They really need local advertisers but don’t have access to them.  You do – why not get together?  (And of course, continue to develop your own branded mobile experiences, but also look at how you can reach the mobile audience in other ways.)

3. Be the social connector

People are talking about your advertisers on twitter and Facebook.  What are you doing to help them join the conversation?

4. Recommendations rather than results

Be the matchmaker by helping consumers figure out which business is the right one for them.  Utilize tools like ratings and recommendations but also leverage your reputation.  Make it really easy to use.

5. Yellow pages connect

Unleash innovation by providing software developers with access to your data — and a share of the revenue from the leads they generate.  Wouldn’t you rather be sharing some revenue with an innovator using your data rather than buying your leads from Google?  You’ll make more money and be further ahead strategically.

What would you add to the list?  What would you delete or change?

The problem with local reviews

I love local reviews.  And local review sites like Yelp.  And I’m delighted to see reviews becoming increasingly commonplace – expected really – at local search sites from Google to yellow page publishers.

My problem is that I don’t know any of these people, so I don’t know if they like the same things as me.

My parents are small town people.  When they are looking for a place to eat they want value for money.  They want good food but nothing too exotic — and they don’t want to spend a lot of money.

I usually want something exotic — a bit unusual and out of the way.  But not too expensive.  And not TOO exotic.

So, my problem is that I don’t know if a reviewer is me or my mom.  Sure, if they’ve written enough reviews and I spend enough time reading them, I can probably get a sense of it.  But really, I was just looking for something to eat.  That shouldn’t need to be a major research project.