MarketDial, Inc. v. Applied Predictive Technologies, Inc.

CourtDistrict Court, D. Utah
DecidedJune 20, 2024
Docket2:23-cv-00477
StatusUnknown

This text of MarketDial, Inc. v. Applied Predictive Technologies, Inc. (MarketDial, Inc. v. Applied Predictive Technologies, Inc.) is published on Counsel Stack Legal Research, covering District Court, D. Utah primary law. Counsel Stack provides free access to over 12 million legal documents including statutes, case law, regulations, and constitutions.

Bluebook
MarketDial, Inc. v. Applied Predictive Technologies, Inc., (D. Utah 2024).

Opinion

IN THE UNITED STATES DISTRICT COURT FOR THE DISTRICT OF UTAH

MARKETDIAL, INC., a Delaware MEMORANDUM DECISION & ORDER corporation, ON THE PARTIES’ MOTIONS TO DISMISS Plaintiff, Case No. 1:23-cv-00477-JNP-CMR v. District Judge Jill N. Parrish APPLIED PREDICTIVE TECHNOLOGIES, INC., a Delaware corporation,

Defendant.

Through this action, MarketDial, Inc. (“MarketDial”) seeks a declaration that U.S. Patent No. RE49,562 (“‘562 patent”) is invalid or unenforceable. In response, the owner of the ‘562 patent, Applied Predictive Technologies, Inc. (“APT”), answers and asserts a counterclaim against MarketDial for infringement of the ‘562 patent in violation of 35 U.S.C. § 271 et seq. Before the court are the parties’ motions to dismiss the complaint and counterclaim, respectively. For the reasons set out below, MarketDial’s motion to dismiss APT’s counterclaim is GRANTED, and APT’s motion to dismiss the complaint is DENIED AS MOOT. FACTUAL BACKGROUND A. Previous patent This case turns on the validity of the ‘562 patent. The ‘562 patent is a reissue of U.S. Patent No. 8,571,916 (“‘916 patent”), which issued in 2006. The ‘916 patent “relate[d] to business initiative analysis systems, and more particularly, to methods, systems, and articles of manufacture for performing a segmented initiative analysis for initiatives implemented at selected business locations in order to identify in which other locations to implement the initiative.” ‘916 patent at 1:18-23. As a previous order of this court explained, the ‘916 patent was directed to a problem that can be characterized in the following terms: While retailers have traditionally relied upon their business instincts or anecdotal evidence to determine whether an initiative is worth launching, some have more recently sought to adopt a more structured and analytical approach. Rather than relying solely on intuition, retailers may test a business initiative by implementing it at one or more locations, collecting performance metrics from those locations, and analyzing the collected data using “conventional software products.”

Applied Predictive Techs., Inc. v. Marketdial, Inc., 2020 U.S. Dist. LEXIS 221981, at *7-*8 (D. Utah Nov. 25, 2020) (“‘916 Order”). The ‘916 patent sought to resolve this issue by reducing human error. The patent recited a process by which retailers decided categories of performance metrics to collect (for example, gross profit margins, changes in average sales, or number of products sold) and business locations from which to collect such data. These decisions are referred to as a test’s parameters. Id. at *8. “These parameters form the crux of the problem identified by the ‘916 patent. In particular, the patent notes that the parameters selected for a business initiative test may influence the results of that test, [] skewing the test’s findings.” Id. at *8-9. Thus, the ‘916 patent identified that “there is a need for a system and method that automatically identifies one or more analytical parameters that filter out the most inconsistent data to maximize a retailer’s ability to analyze the results of an initiative test.” Id. at *9. The ‘916 patent sought to respond to this need by claiming a process of performing virtual tests on virtual test sites in an attempt to identify parameter settings that would create the least “noise” and thus optimize parameter settings for business initiative testing. Independent claim 1 of the ‘916 patent laid out this process, explaining the basis of the virtual testing by claiming 2 [a] method for determining optimal parameter settings for business initiative testing software used for testing initiatives for business locations included in a business network, comprising: [a] identifying, by a computer, a business initiative testing model having a set of parameter settings; [b] selecting a first parameter setting set for performing the virtual test, the first parameter setting set including a set of selected parameter setting options each respectively corresponding to one of the parameter settings for the business initiative testing model; [c] performing, by a computer, a virtual test on a set of virtual test sites, each virtual test site reflecting a selected business location in the business network, wherein each virtual test is a simulated business initiative test performed on test sites where no actual initiative test has been implemented at those test sites, and wherein the virtual test is performed on the virtual test sites using a variation of each parameter setting; [d] determining, by a computer, actual performance data associated with the set of virtual test sites; [e] determining, by a computer, actual performance data associated with a set of control group sites reflecting second selected business locations in the business network using the tested parameter settings; [f] determining a noise value for the first parameter setting set, the noise value reflecting an inconsistency between performance data associated, with the set of virtual test sites and performance data associated with the set of control group sites reflecting second selected business locations in the business network using the tested parameter settings; [g] determining, by a computer, a set of optimal parameter settings for the business initiative testing model based on results from the virtual test whereby the optimal parameter settings best minimize noise from the results; and [h] configuring, by a computer, the business initiative testing model using the optimal parameter settings to test a business initiative for application in the business network.

‘916 patent at 25:60-26:33 (bracketed letters added for organizational ease). In layman’s terms, the process provided for in the ‘916 patent begins with choosing a business initiative testing model with a selected set of parameters, such as the type of performance data collected, the geographic locations of the stores, or the time of year that the test is performed. Then, rather than merely implementing this test, as a retailer would traditionally do, the patent provides a process for ‘testing’ parameter settings to determine whether they are the optimal parameter settings for the business initiative testing model.

3 ‘916 Order at *11-12.1 Performance metrics for virtual test sites are compared against the historical performance data of control sites, and discrepancies in results between the two are attributed to “some influence present in the parameter settings options selected. This inconsistency is referred to as ‘noise.’” Id. at *12.2

“The patent then consists of storing this noise value and iteratively ‘testing’ a large number of parameter setting options in this same way. The noise values for these different tests are also stored and the optimal parameter setting, or the parameter setting that creates the least ‘noise,’ can be identified.” Id. at *13. “As can be seen in [c]laim 1,” however, “the specifics of this analysis are not provided for in the patent. Rather, the process articulated in the patent appears to consist of any process that permits the patent-user to analyze the data and obtain the relevant performance metrics and, as a result, ‘noise.’” Id. at *12 n.3.

1 Or, as this court explained elsewhere in its order, [the] method consists of selecting a set of parameter settings to test, performing a virtual test on virtual test sites, determining the performance data at those sites, and comparing that data with the performance data from a set of control group sites. This process is performed iteratively, testing a range of parameter settings. Once the testing is complete, the noise values for the different parameter settings are compared and the optimal setting can be identified.

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MarketDial, Inc. v. Applied Predictive Technologies, Inc., Counsel Stack Legal Research, https://law.counselstack.com/opinion/marketdial-inc-v-applied-predictive-technologies-inc-utd-2024.