Google has acquired retail coupon marketing platform Incentive Targeting for an undisclosed sum.
In an announcement on their homepage, Incentive Targeting noted that they had originally set out to do for retail couponing what Google had done for online advertising: “Make it simple, relevant, measurable and effective.”
As part of Google, said Incentive’s leadership, they will have the resources and expertise needed to transform coupons from a discount tool to a way to build businesses.
A Google spokesperson issued this statement: “We look forward to working with Incentive Targeting in our ongoing efforts to help consumers save time and money and enable retailers deliver relevant discounts to the right customers.”
Mike Dudas, Emerging Business Lead in Google’s Mobile Commerce division, tweeted yesterday that the purpose of the acquisition is to “power highly targeted manufacturer and private label coupons.”
Incentive Targeting was founded in February 2007, by Ben Sprecher and Joshua Herzig-Marx. Interestingly, the company was granted a patent for a “Computer-implemented method and system for conducting a search of electronically stored information,” in July this year. The patent describes an “interactive targeting rule editor,” which enables users to create a targeting rule to identify desired search results.
What is it for? The patent indicates that,
“In the case of the targeted marketing service described above, those activities can be, e.g., transaction line items representing purchases of products at a retailer. However, various other activities can also be searched by making appropriate changes to the targeting rule grammar. Some other exemplary applications of the techniques described herein can include, identifying website/e-commerce users by their behavior, identifying possible criminals or terrorists based on specific behaviors from a database of activities, identifying students who need additional assistance/instruction, identifying top-performing sales people, identifying outliers in drug or therapy trials, detecting suspected fraud, waste, or abuse from records of financial transactions (such as a credit card or bank account transaction log), medical records, insurance claims, etc., and finding computational or communication bottlenecks from collected usage data, log files, network diagnostics, and/or benchmarking results.
The techniques described herein are also generally applicable in situations where users, particularly non-technical business users, are configuring settings or parameters for constrained problem spaces. These can include domain-specific search applications such as, e.g., document archive searching; file searching on a computer or network; company or individual searching; real estate searching; price comparison searching; reference, book, and article searching; travel searching (e.g., flights, hotels, cars, vacation packages, rental properties, cruises, etc.); and product feature searching (such as for a store or website selling products with many attributes such as, e.g., computer parts or automotive parts).
The patent goes on to describe “hinting mechanisms” that seem designed to allow searchers to preview results and edit their query based on these hints.
This technology would obviously be of interest to Google, especially in the Google Shopping and Wallet spaces.
Imagining how this could be employed within Google, one can picture a retail shopping search, whether in paid listings or organic, where users could preview results and edit their query in real-time to see different products and set of results. Rather than searching, reviewing results, and searching again, shoppers could change the parameters of their search as they shop, honing in on just the right product by becoming more and more specific within that one search.
It will be interesting to see just how and where Google chooses to use this technology.
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