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`Case 6:21-cv-00569-ADA Document 185-3 Filed 01/19/23 Page 1 of 24
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`Case 6:21-cv-00569-ADA Document 185-3 Filed 01/19/23 Page 2 of 24
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`UPSTREAM
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`PARTNERS
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`IN THE UNITED STATES DISTRICT COURT
`FOR THE WESTERN DISTRICT OF TEXAS
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`Case 6:21-cv-00569-ADA Document 185-3 Filed 01/19/23 Page 3 of 24
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`SUPPLEMENTAL EXPERT REPORT
`OF MARK J. CHANDLER
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`Table of Contents
`
`OVERVIEW ........................................................................................................................ 1
`I.
`II. QUALIFICATIONS AND INFORMATION CONSIDERED ....................................... 1
`III. SUPPLEMENTAL OPINIONS ......................................................................................... 2
`A. Additional Documents Provided by Google on Usage Data are Unreliable, Inconsistent
`and Contain Limitations ................................................................................................ 2
`i.
`GOOG-TST-00217555 ........................................................................................ 3
`ii.
`GOOG-TST-00217556 ........................................................................................ 6
`iii. GOOG-TST-00217557 ........................................................................................ 9
`iv. GOOG-TST-00217558 ...................................................................................... 15
`IV. EXHIBITS ......................................................................................................................... 18
`V.
`POSSIBLE REVISIONS TO THIS REPORT ............................................................... 18
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`SUPPLEMENTAL EXPERT REPORT
`OF MARK J. CHANDLER
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`SUPPLEMENTAL EXPERT REPORT
`OF MARK J. CHANDLER
`
`
`I.
`
`OVERVIEW
`
`1.
`
`In the matter of Touchstream Technologies, Inc. v. Google LLC (the “Litigation”)1,
`
`I submitted an expert report dated November 14, 20222 (my “Original Report”)
`
`which provided my expert opinions on certain damages and other matters relevant
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`to this case.
`
`2.
`
`Since submitting my Original Report, Google produced and I received and had the
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`opportunity to review four (4) additional documents. 3 In this report I will provide
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`my comments and opinions with regard to the information provided in those
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`documents, and with regard to how the information and documents relate to the
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`analysis and opinions I set forth in my Original Report.
`
`3.
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`This report supplements my opinions as presented in my Original Report based on
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`certain new information that has become available since the date of that report. I
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`may further supplement my opinions in light of any additional information that may
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`become available prior to, or during, trial.
`
`II.
`
`QUALIFICATIONS AND INFORMATION CONSIDERED
`
`4.
`
`5.
`
`In my Original Report, I provided a detailed summary of my experience.
`
`In arriving at the conclusions outlined below, I have based my opinions in this case
`
`on my extensive experience with damages analysis, patent valuation, negotiations,
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`
`1 Complaint for Patent Infringement, June 4, 2021 (the “Complaint”).
`2 Expert Report of Mark J. Chandler, November 14, 2022.
`3 GOOG-TST-00217555, GOOG-TST-00217556, GOOG-TST-00217557, GOOG-TST-00217567.
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`Case 6:21-cv-00569-ADA Document 185-3 Filed 01/19/23 Page 5 of 24
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`and licensing; independent research and analysis of publicly available information;
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`interviews with experts and Touchstream executives; and my review of various
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`documents, deposition testimony, and pleadings produced to date by Touchstream
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`and Google. In forming the opinions expressed in this report, I considered the
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`documents identified in Exhibit 2 to my Original Report and Exhibit 22 to this
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`report.
`
`III.
`
`SUPPLEMENTAL OPINIONS
`
`A.
`
`Additional Documents Provided by Google on Usage Data are Unreliable,
`Inconsistent and Contain Limitations
`
`6.
`
`Since the submission of my Original Report, I have received and had the
`
`opportunity to review the following four (4) documents relating to usage data:
`
`• GOOG-TST-00217555
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`• GOOG-TST-00217556
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`• GOOG-TST-00217557
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`• GOOG-TST-00217567
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`7.
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`In addition to the documents listed above, I have also received and reviewed the
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`Responses to Plaintiff Touchstream Technologies, Inc.’s Interrogatories (Nos. 7-8,
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`13), dated December 1, 2022.
`
`8.
`
`The documents listed above, specifically the four (4) documents produced by
`
`Google relating to usage data, are unreliable, inconsistent, and contain limitations.
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`I address each of these documents individually below.
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`i. GOOG-TST-00217555
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`9.
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`GOOG-TST-00217555 appears to be an Excel spreadsheet file containing “WT
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`hours” data for June 2013 through October 2022. The file contains rows and
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`columns that contain amounts corresponding to dates from June 2013 through
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`October 2022. It is unclear what the amounts under “YM US WT hours” and “YTV
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`US WT hours” represent. There is also no description of what the amounts under
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`“Overall US WT hours” represent.
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`10.
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`Google does not provide any description as to the context or definition of the terms
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`used in this document or in any of its Responses to Interrogatories. Google also
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`does not identify whether these amounts relate to casting, or to non-casting, or to
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`what devices, services or applications the “Overall” category includes.
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`11.
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`It is my assumption that these amounts relate to YouTube Watch Time hours and/or
`
`YouTube TV Watch Time hours, but the document does not provide sufficient or
`
`complete data to apply to my analysis. For example, in July 2015, the document
`
`reports 28 “YTV US WT hours,” 162 “YM US WT hours” and 3.1 billion “Overall
`
`US WT hours.” Furthermore, it is impossible to reconcile the relatively small
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`number of 28 “YTV US WT hours” and 162 “YM US WT hours” with the
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`3.1 billion “Overall US WT hours.” I cannot determine what these metrics represent
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`without making unfounded assumptions.
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`12.
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`The information included in GOOG-TST-00217555 does not include, for example,
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`casting versus non-casting usage and revenues associated with casting versus non-
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`casting usage on cast-enabled Alphabet applications.
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`13. Without further explanation or detail, I cannot verify the relevancy of this data to
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`determine whether the data may be, or may not be, appropriate for my intended use
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`in conducting analysis. The completeness of the data, in other words, whether the
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`data has missing values or missing data records, cannot be assessed without
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`understanding what amounts are included in the “Overall” category.
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`14.
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`Furthermore, I am limited in comparing or analyzing this data against previously
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`produced documents due to the lack of consistency in the metrics (column headers)
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`used. For example, Google produced documents provide data usage in terms of
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`“playback_min,” 4 “num_playback_seconds,” 5 “total_app_time_hours,” 6 “per_
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`device_playback_hours,” 7 “total_playback_time_hours,” 8 “playback_per_day_
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`minutes,” 9 and “MPD.”10 Without an explanation of the definition of these metrics,
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`it is not clear whether a playback min or app time includes active usage time only
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`or idle usage time as well. It is also not clear whether metrics such as
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`“playback_per_day_minutes” or “MPD” represent actual minutes per day or
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`average minutes per day.
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`15.
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`The metrics and the way in which the metrics are measured can significantly skew
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`the resulting data. As an example, an episode of a TV show may be casted from a
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`mobile device to an AndroidTV. The viewers may watch successive episodes which
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`are automatically played after the first casted episode. One way to measure casting
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`
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`4 GOOG-TST-00207268.
`5 GOOG-TST-00217367.
`6 GOOG-TST-00217557.
`7 GOOG-TST-00217557.
`8 GOOG-TST-00217557.
`9 GOOG-TST-00217557.
`10 GOOG-TST-00207270-GOOG-TST-00207284.
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`minutes in this example would be to include from the start of the first episode up to
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`the end of the last episode watched given that these are successive episodes,
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`initiated and enabled through casting technology. Another metric may include only
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`minutes from the first episode. The resulting data will be significantly different.
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`16.
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`Such measuring standards may have changed over time with the change of
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`functionalities and service offerings. However, Google has not provided any
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`explanation of the standard or standards in which casting time is measured, making
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`it impossible to make any reasonable assumptions with the provided data.
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`17.
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`As another example, I calculated the average monthly session length for Sabrina
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`using “total_playback_time_hours,”11 and attempted to compare this to the original
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`production showing “num_playback_seconds”12 by application for 2019 through
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`2022. As summarized in Table 1 below, the average monthly session length for all
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`applications for Sabrina drops from 15.15 minutes to 6.48 minutes from 2021 to
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`2022. This may be partially impacted by the sudden drop for (a) YouTube from
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`35.39 minutes to 3.81 minutes and (b) YouTube TV from 57.80 minutes to 0.62
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`minutes, in the same time frame. However, the dramatic drops from 2021 and 2022
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`may also reflect a change in the way that session length is determined for YouTube
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`and YouTube TV. 13 In my opinion, it would be inappropriate to rely on a
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`comparison of the newly provided usage data with other data sets without a
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`thorough analysis of such variances.
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`
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`11 GOOG-TST-00217557.
`12 GOOG-TST-00217367.
`13 Based on my review and analysis of GOOG-TST-00217367, the top 3 application for Sabrina by casting sessions
`Netflix (34%), YouTube (30%), and YouTube TV (23%), while casting time for the same apps were YouTube (25%),
`YouTube TV (4%) and Netflix (0.06%).
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`Case 6:21-cv-00569-ADA Document 185-3 Filed 01/19/23 Page 9 of 24
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`Table 1. Sabrina Usage Data - Average monthly session length in minutes
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`All Applications14
`YouTube15
`YouTube TV16
`2019
`7.28
`8.78
`25.25
`2020
`10.41
`28.27
`42.23
`2021
`15.15
`35.39
`57.8
`2022
`6.48
`3.81
`0.62
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`18.
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`As described in the example above, I have no basis to assume that the measuring
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`standard is consistent throughout the different applications. Some applications
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`allow for automatic playing of related media, while other applications do not have
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`this function. Some applications and devices allow multi-screen playing, while
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`others do not. If Google is using varying measuring standards for the different
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`devices and applications, without a description of such metrics and measuring
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`standards, I cannot use the provided data for any reliable analysis.
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`19.
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`As of my submission of this Supplemental Report, Google has not produced
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`sufficient additional data that would allow me to compare casting versus non-
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`casting usage. The foregoing missing information is important and necessary for
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`calculating with any reasonable degree of accuracy the total amount of benefits and
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`value Google has received from its use of the Patents-in-suit through its deployment
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`of Chromecast technology.
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`ii. GOOG-TST-00217556
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`20.
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`GOOG-TST-00217556 is an Excel spreadsheet file containing two sheets (tabs)
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`which Google describes as showing “metrics related to Google TV and Android
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`
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`14 GOOG-TST-00217557.
`15 GOOG-TST-00217367.
`16 GOOG-TST-00217367.
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`TV”. 17 Google has responded that Sheet 1 shows “monthly U.S. aggregate time
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`metrics
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`in
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`applications per device
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`across
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`all
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`applications where
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`daily_mins_per_device is the average daily time,” 18 and Sheet 2 shows “monthly
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`U.S. metrics associated with applications, the daily_minutes per application (refers
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`to daily average usage for that month), daily_device (refers to daily average number
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`of devices in use for that month), and min_per_device (refers to daily average use
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`per device). 19 The average use refers to all activity, including cast-initiated
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`sessions.”20
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`21.
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`The information provided by Google in this document is insufficient, inconsistent
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`and contains errors. Google’s description of the document is unclear and confusing.
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`For example, Google states that Sheet 1 shows “monthly U.S. aggregate time
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`metrics,” however, Sheet 1 includes only one set of data which represents
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`“daily_mins_per_device.” In the same Interrogatory Response, Google states that
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`“daily_mins_per_device” represents “the average daily time.” Google’s description
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`is confusing and unclear as to whether the amounts presented in Sheet 1 are monthly
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`aggregate amounts or daily average amounts for each month. Furthermore, and
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`critically, the document does not offer an explanation of which devices are included
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`in the provided metrics in Sheet 1 or Sheet 2.
`
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`17 Google LLC’s Supplemental Objections and Responses to Plaintiff Touchstream Technologies, Inc.’s Interrogatories
`(Nos. 7-8, 13), p.17.
`18 Google LLC’s Supplemental Objections and Responses to Plaintiff Touchstream Technologies, Inc.’s Interrogatories
`(Nos. 7-8, 13), p.17.
`19 Google LLC’s Supplemental Objections and Responses to Plaintiff Touchstream Technologies, Inc.’s Interrogatories
`(Nos. 7-8, 13), p.17.
`20 Google LLC’s Supplemental Objections and Responses to Plaintiff Touchstream Technologies, Inc.’s Interrogatories
`(Nos. 7-8, 13), p.17.
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`22.
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`In my attempt to determine and review the accuracy and consistency of the provided
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`data, I compared the numbers contained in Sheet 1 and Sheet 2. Assuming that the
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`amounts shown in Sheet 1 represent total average daily minutes, I compared the
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`listed amounts in Sheet 1 to the calculated monthly totals from Sheet 2 and found
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`that none of the amounts matched for the provided period. In other words, there are
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`discrepancies between the numbers provided in each of the sheets.
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`23.
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`For example, the aggregate “daily_mins_per_device” across all applications is
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`167.74 minutes for November 2020 according to Sheet 1. According to Sheet 2 the
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`total for the same time period is 93.98 minutes.
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`24.
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`Furthermore, and critically, it is unclear which Google TV and Android TV devices
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`are included in the provided metrics.
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`25.
`
`In addition, the metric used in this document, “daily_mins_per_device,” is not
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`consistently used in other produced documents which limits my ability to compare
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`and analyze across documents.
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`26.
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`The conflicting amounts in the metrics provided by Google show the lack of
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`accuracy of this information. Also, the completeness of the data cannot be
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`determined given the lack of explanation of devices, services, or applications
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`considered in the amounts in Sheet 1. Without further explanation or detail, I am
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`limited in comparing or analyzing this data against previously produced documents
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`due to the lack of consistency in the metrics used.
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`Case 6:21-cv-00569-ADA Document 185-3 Filed 01/19/23 Page 12 of 24
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`27.
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`This information provided by Google is unreliable for calculating with any
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`reasonable degree of accuracy the total amount of benefits Google has received
`
`from its use of the Patents-in-suit through its deployment of Chromecast technology.
`
`iii. GOOG-TST-00217557
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`28.
`
`GOOG-TST-00217557 appears to show device and application usage metrics by
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`product and device type. Data is included from March 2015 through November 1,
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`2022. Google does not provide any description of the context or any definition of
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`the terms that are used, in this document or in any Responses to Interrogatories.
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`Google also does not identify whether these amounts relate to casting versus non-
`
`casting, or U.S. versus Worldwide. Furthermore, the information provided in this
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`document is lacking in context, is inconsistent, and is therefore unreliable.
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`29.
`
`For example, the provided data contains several outliers which significantly skews
`
`the data. Critically, this also puts into question and raises doubts about the reliability
`
`of the accuracy of the dataset as whole. As one example, noted in Table 2 below,
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`the annual average total app time for the 2017VIZIOTV ranged between 320 to 870
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`hours in 2017 through 2022. However, the average app time hour in 2019 was 7.69
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`trillion hours which is equivalent to 877 million years of app time.
`
`Table 2. Annual Average “total_app_time_hours” for the 2017VIZIOTV21
`2016
`2017
`2018
`2019
`In millions of hours
`Average "Total_app_time_hours"
` 18.7
` 320.3
` 870.6
` 7,687,123.0
`
`2020
` 460.5
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`2021
` 384.8
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`2022
` 294.8
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`
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`21 GOOG-TST-00217557.
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`30.
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`There are also entries which appear to be duplicative or incorrect. For example, the
`
`Vizio TV products report significant larger hours compared to the more than 2,000
`
`other products included in this document and appear to have duplicate categoric
`
`fields. For example, there are differing values for each month for both “2018 VIZIO
`
`TV” and “2018VIZIOTV.” It is not clear if these amounts are intentional and
`
`should be additive or if they are duplicative and should deducted. Therefore I
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`cannot see how it would be possible for anyone to draw valid and reliable
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`conclusions from the data provided in GOOG-TST-00217557.
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`31.
`
`These outliers put into question the validity and accuracy of the entire data set, as
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`it makes it likely that there are no quality checks, and there may be unaccounted
`
`outliers further skewing the data.
`
`32.
`
`Furthermore, an explanation of the listed metrics is necessary for my analysis of
`
`Google’s use of the Chromecast technology. There is no explanation of the
`
`definition or method in which of “app_time” versus “playback time” was measured
`
`within the context of functionally different devices and products. It is unclear how
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`the range of devices are interpreting and measuring these metrics.
`
`33.
`
`Given the issues identified above, it is not possible to determine the accuracy and
`
`completeness of this data. Without further explanation or details on what is being
`
`displayed, I am limited in my ability to compare or analyze this data against
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`previously produced documents, due to the lack of consistency in the metrics used
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`to measure data usage. The stated deficiencies prevent further usefulness of this
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`information in any such analysis.
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`34.
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`Furthermore, in attempting to interpret the new data produced by Google and the
`
`intended meaning of the various column headers, it also became apparent that
`
`Google’s decisions about how to aggregate and organize the data could materially
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`skew the results that could be obtained if one were to compare data that was
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`purported to reflect cast time as compared to data that was purported to reflect
`
`application time. I have detailed some of these issues below:
`
`• Google has not provided any details about how it determines the start or end
`
`time of a casting session, or the length of a casting session. Using
`
`YouTube/YouTube Music as an example, a user searches for content on
`
`their smartphone, selects content to be cast, selects the cast button on the
`
`phone, and then selects the target Chromecast device which displays or
`
`plays the content using the technology covered by Touchstream’s patents.
`
`Typically, after the selected content is played, additional related content will
`
`be displayed or played, and Google generates revenue from the sale of
`
`advertisements during the entire casting session. In addition, Google may
`
`insert advertising content as commercials within a video or between videos.
`
`Google has provided no information to explain whether the casting time
`
`reflected in the report includes the entire casting session or only the first
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`selected content. Google also has not explained whether it included time for
`
`inserted advertisements in its reporting of casting time.
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`• Google has not explained whether content selected with the Chromecast
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`“virtual remote” is included in casting time.22 Google has provided no
`
`information as to whether the content provided subsequent to that selected
`
`from within the initial casting session is included in the casting time it has
`
`provided.
`
`• Google has not provided information on the applications that are included
`
`in the application time data and certain applications could result in very
`
`significant amounts of time with very limited user interaction. For example,
`
`Chromecast devices include ambient mode (previously called backdrops)
`
`which run during periods of inactivity.23 If ambient mode or backdrop time
`
`is included in applications, application time would be increased during
`
`periods when a Chromecast device is simply acting as a screen saver.
`
`Similarly on devices with Google Assistant, Google provided no
`
`information on how it determines the amount of time, if any, associated with
`
`operating Google Assistant or even if Google Assistant is included in
`
`application time.
`
`• Using Touchstream’s patented technology, a user can search and select
`
`videos and other content of interest on their smartphone and then cast the
`
`
`22 See, e.g., “Use your phone as a virtual remote control,” Chromecast Help,
`https://support.google.com/androidtv/answer/6122465?hl=en; “How to use an Android phone as a Google TV remote,”
`androidcentral, December 14, 2021, https://www.androidcentral.com/how-use-android-phone-google-tv-remote; “Cast it:
`The Chromecast tips and tricks you need to know,” The Ambient, August 24, 2022, https://www.the-
`ambient.com/guides/google-chromecast-tips-tricks-1152.
`23 See, e.g., “Ambient Mode for Chromecast and Chromecast Ultra,” Chromecast Help,
`https://support.google.com/chromecast/answer/6080931?hl=en; “How to customize Ambient Mode on Chromecast with
`Google TV,” androidcentral, June 22, 2021, https://www.androidcentral.com/how-customize-ambient-mode-chromecast-
`google-tv; “Cast it: The Chromecast tips and tricks you need to know,” The Ambient, August 24, 2022, https://www.the-
`ambient.com/guides/google-chromecast-tips-tricks-1152.
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`Case 6:21-cv-00569-ADA Document 185-3 Filed 01/19/23 Page 16 of 24
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`
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`selected content to a target device and, while searching, Google typically
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`presents ads to the user. However, Google has provided no information on
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`whether Google’s data picks up any of the search time in its casting time
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`data. With respect to Google’s tally of application time, it is likely that all
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`search time and idle time for apps such as YouTube and Netflix are included
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`in application time. Similarly, there may be substantial amount of idle time
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`included in application time if a user starts an app but is not actually playing
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`content. These differences could result in application time being heavily
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`overweighted relative to cast time making any such comparison unreliable,
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`at least in part due to the fact that apportionment based solely on the
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`difference in play time would not fairly compensate Touchstream for the
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`use made by Google of Touchstream’s patented inventions.
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`35.
`
`Aside from the examples provided in the paragraph above of this Supplemental
`
`Report, there are numerous other ways in which data could be impacted based on
`
`the way in which Google determines the amount of cast time as opposed to the
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`amount of application time. Google has not provided any explanation of how it has
`
`determined what to include or whether the same methodologies for selection and
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`aggregation were consistent across the various spreadsheet data files.
`
`36.
`
`As described in my Original Report, had I been provided with accurate, reliable,
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`consistent and complete data, I would have compared and analyzed total casting
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`and non-casting hours against previously produced casting hours24 to further assess
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`the appropriate apportionment of value related to Chromecast Technology.
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`24 See, e.g., GOOG-TST-00207268.
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`Case 6:21-cv-00569-ADA Document 185-3 Filed 01/19/23 Page 17 of 24
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`Assuming the provided data appropriately determines casting and non-casting
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`times, taking into account the examples noted above, I would be able to further
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`determine an appropriate apportionment percentage for each device or model in my
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`damages approaches by comparing the casting usage versus total (casting and non-
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`casting) usage by device.25
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`37.
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`In order to conduct this analysis, I would need to review data files that contain
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`consistent metrics that are measured under the same standards. However, the
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`documents that were produced prior to the submission of my Original Report, for
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`example, GOOG-TST-00207268 and GOOG-TST-00217557, use varying metrics
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`without any explanation preventing analysis with any reasonable degree of
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`accuracy. For example, according to GOOG-TST-00207268, “playback_min” for
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`estelle products on December 1, 2021 is 94,931,393, however, according to GOOG-
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`TST-00217557, “playback_per_day_minutes” for estelle products on the same date
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`is 20.9 and 7.6. Without additional explanation, there is no way to reconcile the
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`significantly varying amounts for the same date and same product across these two
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`documents.
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`38.
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`Furthermore, there are inconsistencies and outliers in the data preventing a reliable
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`analysis. Attempting to use the produced information, given its deficiencies, would
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`require making unwarranted assumptions, ignoring data errors, and not taking into
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`account the inconsistent data metrics used across the Google produced documents.
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`25 See, Original Report, §XI.
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`Case 6:21-cv-00569-ADA Document 185-3 Filed 01/19/23 Page 18 of 24
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`39.
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`As of my submission of this Supplemental Report, Google has not produced the
`
`requested data necessary for my analysis. The foregoing missing information is
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`important and necessary for calculating with any reasonable degree of accuracy the
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`amount of total benefits Google has received from its use of the Patents-in-suit
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`through its deployment of Chromecast technology.
`
`iv. GOOG-TST-00217558
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`40.
`
`GOOG-TST-00217558 is titled “U.S. Play App Revenues.” This file appears to
`
`include subscription and in-app revenue for January 2013 through June 2022 for
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`the following applications:
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`• air.com.vudu.air.DownloaderTablet
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`• com.bamnetworks.mobile.android.gameday.atbat
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`• com.bydeluxe.d3.android.program.starz
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`• com.clearchannel.iheartradio.controller
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`• com.facebook.katana
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`• com.nbcuni.nbc
`
`• com.pandora.android
`
`• com.pandora.android.atv
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`• com.soundcloud.android
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`• com.univision.univisionnow
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`• com.viacom.betplus
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`Case 6:21-cv-00569-ADA Document 185-3 Filed 01/19/23 Page 19 of 24
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`• com.viki.android
`
`•
`
`•
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`•
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`radiotime.player
`
`tunein.player
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`tv.twitch.android.app
`
`41.
`
`Google was initially requested to provide all Play App Revenue, to which it refused.
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`Then Google agreed on October 13, 2022, and was ordered on November 29, 2022,
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`to provide only a small subset of the U.S. Play App Revenue, for only dozens of
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`cast-enabled content providers whereas the number of such providers number in the
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`thousands.
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`42.
`
`As noted in my Original Report, the revenue associated with the initial production
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`of approximately 17 applications was $363.36 million for June 2015 through June
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`2022. 26 The additional revenue associated with the second production of
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`approximately 15 applications was $272.67 million for the same time period.
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`43.
`
`The total revenue data we have received associated with Play App Fees for June
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`2015 through June 2022 is $636.03 million.27 As mentioned in my Original Report,
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`this amount is still much less than the total one would expect to see, based on a
`
`review of publicly available data. For example, worldwide gross application
`
`revenue from Google Play has been reported to have grown from $15 billion in
`
`
`26 Original Report, Exhibit 21; GOOG-TST-00207293-GOOG-TST-00207302.
`27 See Exhibit 23.
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`Case 6:21-cv-00569-ADA Document 185-3 Filed 01/19/23 Page 20 of 24
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`2016 to $48 billion in 2021.28 In 2020 alone, the App Store generated $72.3 billion
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`with Google Play revenue reaching approximately $38.6 billion.29
`
`44.
`
`The additional information provided by Google is informative, but is still limited
`
`for the purposes of my analysis. The file does not include information on all the
`
`cast-enabled applications , and it is evident, based on public sources, that the total
`
`Play App revenue is significantly greater than what has been produced by Google
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`as of the submission of this report.
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`45.
`
`The foregoing missing information is important and necessary for calculating, with
`
`any reasonable degree of accuracy, the total amount of benefits and value that
`
`Google has received from its use of the Patents-in-suit through its deployment of
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`Chromecast technology under the Revenue Approach.30 I have included an updated
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`table showing the increase in Play App revenue in Exhibit 23, however, the lack
`
`of information from Google, the lack of accuracy, consistency, and overall
`
`completeness of the information prevents me from determining the total amount of
`
`benefits Google has received from its use of the Patents-in-suit through its
`
`deployment of Chromecast technology.
`
`
`28 See, e.g., “Worldwide gross app revenue of Google Play from 2016 to 2021,” Stati