Product searching capabilities are of course not new for Google. Google Product Search has been available since 2002 (back then it was still called "Froogle"). A mobile version of Google Product Search has been available since 2005. Google Product Search for Android added barcode scanning last year, enabling users to scan bar codes in the store and instantly search for product ratings and reviews on the internet.
Now they've added a significant new capability to their mobile shopping application. On March 11th 2010, Google announced a new feature for its Google Product Search for mobile application that lets users search for products that are available and in stock at nearby stores. Google said that participating retailers include Best Buy, Williams-Sonoma, West Elm, Sears Pottery Barn, and others.
How It Works -- The User Experience
The new capability is available to users of phones based on Google Android, Palm WebOS, or Apple iPhone that have enabled the "My Location" feature. When they use Google Product Search, any product for which local inventory data is available will have a blue dot next to it and the label "In stock nearby." Tapping the blue dot or in stock label brings the user to a page listing the nearby locations that are selling the product. Each listing displays the price, availability, contact info, and link for directions (Figure 1). It may be coincidence, but the initials for Google Product Search ("GPS") are a good fit for this location-based feature.
Figure 1 - Google Product Search for Mobile Screen Shots
YouTube has an excellent video of Vic Gundotra, vice president of engineering for Google mobile, demonstrating this new capability back in December, 2009 (as well as talking about a whole bunch of other cool new developments from Google).
Some Challenges: Data Normalization, Accuracy, Completeness
Though not unique to mobile search, one of the challenges is normalizing product data from thousands of different retailers and hundreds of thousands of different manufacturer/suppliers for potentially millions of different products. Each of the major product search engines has its own standards for categorizing products, which are already putting a huge burden on retailers and manufacturers that would like their products to be found by these engines. And these existing categorization standards don't necessarily go to the right level of detail in defining product attributes. For example, a successful TV search needs details such as screen size, resolution, features, etc.; all of which are needed for a successful search. This means that many retailers, especially smaller ones without dedicated resources, will struggle to provide that all the data be cleansed, normalized and in the right format that is needed for them to participate and show up in the searches. Besides their lack of manpower, smaller specialty retailers often have unique items such as custom clothing, handmade goods, arts and crafts, many of which lack a UPC. For the boutique retailer, significant manual data entry is required, increasing the challenge of cataloging and normalizing their product data.
What is the impact of low participation rates by retailers on the shoppers' experience? If the search misses 19 out of 20 real-world available instances of the product that the shopper is seeking, then its usefulness is limited. In the early stages, it will be the large retailers that adopt. If enough major retailers embrace this enthusiastically, it may reach that critical mass of usefulness before too long. It's also possible that adoption of POS SaaS offerings by small to mid-sized retailers helps that sector to participate, though still at a later stage than the larger and more technically sophisticated retail chains.
The data also needs to be accurate. If the shopper drives all the way to the store, only to find that the item actually in stock is a different size, or color, or version than what they were told was in stock, then they will be pretty disillusioned with the service. Data accuracy and cleanliness is still a huge issue and challenge, even in many larger companies with reasonable IT budgets.
Displaying the Right List of Alternatives
A good web search engine like Google (we're talking about regular web search now, not product search) is not rigid about the search parameters you entered and is able to handle misspellings and suggest alternatives "did you mean: ..... ." This is not yet the case for product search. Testers of this early version from Google mentioned the fact that searches are too restrictive and literal, not displaying good alternatives that are actually available nearby.
Google Not the First to Offer Location-Based Product Search
The first mobile phone location-based product search application that I'm aware of was Slifter, from GPShopper, introduced in 2006. TheFind.com has also provided mobile location-based product search for several years. Shop Savvy provides Android-based phone users with the ability to scan barcodes of products, and then by leveraging the Krillion network, searches the inventory of local stores.
In addition, there are many related shopping applications for mobile phones. For example, with StoreXperience and similar applications, you can use your cell phone to take a picture of a product barcode and use it to obtain competitive price information, or go directly to that product's web page, or automatically launch a Google search for more product information. Or take Yelp, which has over eight million reviews of local businesses like dentists, hair stylists, mechanics, allowing users to find local events and special offers on their mobile phone or PC. The list goes on and on -- here's one list of mobile retail apps for those who are interested.
Google's Entry is Challenging for Competitors, but Great for the Mobile Shopping Sector
While GPShopper and TheFind.com might not be so happy about the entry of such a formidable competitor, the arrival of Google is great news for location-based product inventory search. It will likely cause retailers to start putting more serious effort into cleaning up and categorizing their data so that they can participate. It might also lead to the establishment of de facto or even de jure standards for sharing product data, reducing all the non-value-add effort spent conforming to the myriad proprietary formats that currently exist. This would ease some of the burden on retailers and manufacturers, thereby encouraging more of them to participate, and lowering the barrier for smaller retailers.
Google usually does a very good job building clear and easy-to-use user interfaces and functionally rich applications. If they continue to make a significant investment in this area, we expect the physical inventory feature of Google Product Search for mobile to get much better. When combined with so many other amazing capabilities in location-based and visual mobile computing (not just from Google), we should see mobile phones that can do even greater really amazing and useful things in the coming years.
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