Chapter 7 - Searching and Finding

Search engines are the tool that most Internet users use to find things in which they are interested - but the mere phrase "search is used to find" reveals something very important: searching and finding are two different things. Searching represents the effort, and finding represents success.

And in spite of decades of research and refinement, search engines aren't particularly good at finding things, as users often have to carefully craft their inquiry and still have to scroll and page through possible results to get to what they wanted in the first place.

On the mobile platform, users do not have that kind of time and patience - so a key to success on this platform is designing the tools and services that lead more quickly to success in delivering exactly what is wanted without a great deal of effort.

The New Mobile Search

The author also suggests another difference between internet and mobile searching: he believes that internet searches are "premeditated" in that the user has an idea of the kind of information he is seeking. He feels that mobile search is less deliberate, and more in terms of discovery: the user doesn't know what he needs to find and looks to the platform to help him discover what is relevant to him.

(EN: I think he is onto something about the degree to which a person knows their needs at the onset of conducting a search, but I don't have much faith in his assertion, without any supporting evidence, that the mobile user is less focused in their search, nor can I conceive of an example for which this would hold true as a general statement for either platform. I also have the sense that it may be splitting hairs to draw a distinction - as a user has some idea, however vague, of what they want. They may not be able to name a specific retailer, but an internet user is just as likely to be looking for "a clothing store" or "an Indian grocery" in their vicinity, and a mobile user is just as likely to be looking for a specific product and model.)

There are a number of search parameters that are either unique to mobile, or at least more important to mobile, than they are to internet searching in some instances:

In all, the mobile user is more likely to be seeking something that he needs right here, right now, and germane to what he is doing at the moment than is an Internet user. He is also more willing to accept compromise for the sake of convenience - to pay a little more to have something from a vendor on the same block where he is standing than to save a little money getting it from one that's a few miles away.

(EN: All good information, but most of the author's speculations presume a commercial intent. For many users, mobile is a distraction that is used for less mercenary purposes - they wish to entertain themselves during a few spare moments, or avoid making social contact with others in their environment. This leisure activity is likely of little interest to the book's intended audience, but it is important to consider the mobile user's actual behavior - rather little of which matches what sellers want it to be.)

Leveraging User Behavior

Second-generation Internet search engines did not merely match the user's query against the text content of a Web site, but began to consider evidence of what users really valued: the last (and presumably best) thing one user clicked after searching was weighted as more relevant for the next user who searches for the same phrase, and crawlers indexed sites by the words or phrases surrounding links to them from other sites. In this way, the intelligence of human users augmented the cold logic of text-matching algorithms.

The author suggests that the same thing is happening in mobile, and further suggests that search engine developers are "moving to mobile" because it presents a much greater opportunity than Web. (EN: No evidence is provided for either assertion, but it stands to reason search engine creators would not start over with text-matching, and likely see mobile as an area without an established winner.)

He then goes into a case study of "Phone Tell," a company that is attempting to become the phone book for the mobile platform, which intends to provide relevant results by considering the behavior of other users: the company began by aggregating information from other online phone directories as well as each user's personal contact databases - but then improved search results by considering the numbers that users actually call, given the day, time, and location in addition to the search query. By leveraging additional information from public databases (such as business hours) other irrelevant results are suppressed or de-emphasized. As an added benefit, the service integrates with the native phone application to display the names of incoming callers who are not in the customer's address book.

What's good for the user is likely to be good for the marketer as well: a service that enables and advertiser to be more specific about the kinds of users they are seeking can make advertising (and ad spending) more efficiently focused on prospects who have the greatest potential to become buyers.

Barcodes and QRC

The author is also enthusiastic about the use of codes to "find" information - traditional bar codes and the newer "quick-response" codes provide mobile users with the ability to retrieve information without the need for typing.

(EN: this pops up every couple of years, and it has not caught on. The QRC has been thoroughly abused by advertisers. Users who were eager became quickly disillusioned when scanning codes rendered nothing of value, and they learned to ignore them in most instances. It's going to take time to undo the damage, and because there is no central authority, it means many independent firms must all choose to act responsibly and provide genuine value so that the stigma of past abuses is overcome, which seems very unlikely.)

Universal Product Codes (UPCs) are already in use by retailers, whose point-iof-sale systems scan merchandise. The same codes are being adopted by search engines to enable users to scan the barcode to retrieve product and pricing information.

(EN: the use of UPC has been successful only in the context of specific applications. A user may scan a bar code for shopping purposes, or they may do so to retrieve the nutritional information about foodstuffs. The person who scans a UPC has a definite purpose in mind and seldom does so out of free-floating curiosity - so this is more in line with "searching" rather than "finding" by the author's definitions.)

The author provides a number of examples of code-reading applications, most of which simply return the best price for a given product, but others of which use codes to enable users to quickly visit Web sites for more information, to add a product to a shopping list, to enter a contest, to register for a product warranty, etc. Since the code is translated to a URL or other specific information, it is merely a method of data-entry that can trigger any number of responses. The author predicts that QR codes will be more widely used in future.

(EN: My sense is that codes will be abandoned in favor of technologies such as optical character recognition [OCR] and even image analysis, which associates data to ordinary objects visible to the human eye. In future, the customer will be able to retrieve information by taking a picture of something like a logo, a package, a product, or even a random object in their environment. There's a lot of effort in developing and perfecting these products at the present time.)

The Reality of Augmented Reality

Augmented reality is a technology that overlays the view through a smartphone camera with various data layers, which provides information about objects in the user's physical environment.

There is currently a wealth of data available that can be displayed: point the smart phone at a building and the data overlays can tell you the building's architecture and history, its street address, the names and phone numbers of everyone who is inside presently, as well as the names of everyone who has ever been there, the name of the architect, the building materials, a catalog of crimes committed in the building, the average income of residents, the cost at which it was last sold, the current and past year's property taxes, a gallery of photos taken on a historical timeline, streaming updates of anyone using social media from within, the last time the elevator was inspected, the average power and water consumption, and many other things that most people simply do not care to know.

Naturally, this is largely theoretical: the ability of smart phones to recognize an object through the camera lens, download and display it in real time, and cut the clutter to present on a small screen only those details the mobile user might find value in knowing have prevented AR from becoming a reality. Current applications pale in comparison to the hype: experimental applications offer the same information that is presented on a two-dimensional map is used (landmarks and areas) and it does not jibe with the actual view but may be off by several yards.

The author speculates about other potential uses for AR when the technology is ironed out, adding pop-up information about historic locations for tourists, retrieving statistics about athletes while viewing them in action at a sporting event, getting additional information about an advertisement shown on television, or finding out where to purchase virtually any item that can be viewed.

The author speculates that this will be sorted out in time, and especially if Google's augmented-reality eyepiece catches on, there may be increased demand and more practical uses.