leveraging surveys in patent litigation: demonstrating consumer...

Leveraging Surveys in Patent Litigation:

Demonstrating Consumer Perception,

Avoiding Errors That Impact Damages Best Practices for Developing, Presenting and Challenging Surveys

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THURSDAY, JULY 10, 2014

Presenting a live 90-minute webinar with interactive Q&A

Chris Larus, Partner, Robins Kaplan Miller & Ciresi, Minneapolis

Bryan J. Mechell, Robins Kaplan Miller & Ciresi, Minneapolis

Dr. Shankar Iyer, Vice President, Cornerstone Research, Washington, D.C.

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Using Surveys and Other Quantitative Analyses

In Patent Litigation

Developing, Presenting and Challenging Surveys and Regression Analyses

July 10, 2014

“Determining a fair and reasonable royalty is often . . . a difficult chore, seeming often to involve more the talents of a conjurer than those of a judge.”

ResQNet.com v. Lansa, 594 F.3d 860 (Fed. Cir. 2010)

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Using Surveys and Other Quantitative Analyses In Patent Litigation

OVERVIEW

1. The Evolving Patent Damages Landscape

2. Economic Analyses Applicable to Patent Valuation

3. Recent Uses of Economic Analyses in Patent Litigation: Effective Uses and Rejected Attempts

4. Avoiding Common Challenges to Economic Analyses

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PATENT DAMAGES LANDSCAPE: INCREASED SCRUTINY 1. Damage awards in patent infringement cases

must be supported by sound economic theory and tied to the patented invention’s “footprint in the marketplace.” Uniloc (Fed. Cir. 2011)

2. Damage awards have been rejected if based on “speculative and unreliable evidence divorced from proof of economic harm linked to the claimed invention.” ResQNet (Fed. Cir. 2010)


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PATENT DAMAGES LANDSCAPE: INCREASED SCRUTINY ResQNet.com v. Lansa:

Expert testimony as to reasonably royalty “must

carefully tie proof of damages to the

claimed invention’s footprint in the marketplace.”

IP Innovation v. Red Hat:

Damages must

reflect “economic reality.”

Uniloc v. Microsoft:

Damages based on the entire market value of the

accused product are appropriate only where

the patented feature creates the “basis for

consumer demand” or “substantially creates the value of the component

parts.”


i4i Ltd. P’ship v. Microsoft:

Consumer survey demonstrating real-

world consumer behavior provided

evidence to demonstrate an

appropriate royalty base.

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PATENT DAMAGES LANDSCAPE: INCREASED SCRUTINY Oracle v. Google:

Consumer surveys not “inherently

unreliable” but can become so when expert “artificially

forced” participants or data to desired

outcome.

TVI v. Sony: Survey deemed “fundamentally

flawed and unreliable” but

court ruled criticism more appropriate

for jury determination.

NetAirus v. Apple: Survey results

unreliable where sought to value

something “significantly broader than the claimed invention without adequate

justification.”

Apple v. Motorola:

Damages experts’ testimony

excluded for lacking

“intellectual rigor” – case dismissed with prejudice.


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PATENT DAMAGES LANDSCAPE: INCREASED SCRUTINY 1. Detailed economic analyses can help isolate and

demonstrate patent value, but must be tied to the patented technology.

2. Consumer surveys and regressions are increasingly used to quantify the economic value of the invention in support of a reasonable royalty rate analysis.


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ECONOMIC ANALYSES APPLICABLE TO PATENT VALUATION

1. Consumer Surveys A. Ranking-Based Conjoint Analysis B. Choice-Based Conjoint Analysis C. Direct Queries

2. Regression Analysis A. Price Premium / Hedonic Analysis B. Market Share Premium C. Merger Analysis


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CONSUMER SURVEYS: BACKGROUND

• Consumer survey evidence can demonstrate the evidentiary link between the patented invention and consumer demand.

• Consumer survey evidence must be tied to the patented technology.


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CONSUMER SURVEYS: TYPES OF SURVEY ANALYSES

Ranking-Based Conjoint Analysis

Choice-Based Conjoint Analysis

Direct Queries

Methodology Allows ranking of products within a group

Presents groups of products to choose

Queries directed at patented feature/demand

Outcome Relative comparison of consumer preferences for product features & combinations

Relative comparison of consumer preferences for product features & combinations

Demand for patented feature and relative strength of any such demand

Details Participants can rank choices. Potential issues if participants oversimplify.

Participants must make choices.

Allows for multiple choice, yes/no, ranges, rankings. Must be carefully crafted to avoid bias


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• Ranking-Based Conjoint Analysis – 4 step process 1. Identify product attributes. 2. Conduct a survey where respondents rank the

importance of specific attributes in products. 3. Analyze data using statistical analysis to determine

relationship between rankings and attributes. 4. Conduct a simulation in which the results of step 3

determine additional value of the target attribute.

CONSUMER SURVEYS: RANKING-BASED CONJOINT ANALYSIS


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CONSUMER SURVEYS: RANKING-BASED CONJOINT ANALYSIS

• Example:


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• Choice-Based Conjoint Analysis – 4 step process 1. Identify product attributes. 2. Conduct a survey where respondents choose among

products with different combinations of different attributes.

3. Analyze data using statistical analysis to determine relationship between choices and attributes.

4. Conduct a simulation in which the results of step 3 determine additional value of the target attribute.

CONSUMER SURVEYS: CHOICE-BASED CONJOINT ANALYSIS


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CONSUMER SURVEYS: CHOICE-BASED CONJOINT ANALYSIS

• Example:


Appendix A, Survey Expert Report filed in Convolve v. Dell, Inc. (E.D. Tex. 2011).

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CONSUMER SURVEYS: CHOICE-BASED CONJOINT ANALYSIS • Example: Apple v. Samsung (N.D. Cal. Feb. 25, 2014)

• Choice-based conjoint model allowed where respondents chose which of four hypothetical smartphones they preferred. (Dr. Hauser, Apple’s survey expert)

1. The use of conjoint survey to quantify decreased demand is supported by literature.

2. Studies have demonstrated that conjoint surveys are able to quantify consumer demand with respect to complex products.

3. Dr. Hauser’s approach has peer support. 4. Description of the claim was not overbroad.


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CONSUMER SURVEYS: DIRECT QUERIES

• Direct Queries can be used to query the extent to which there is demand for a patented feature and the relative strength of any such demand.

• Include: Multiple choices, yes/no questions, “unaided” questions, range of choices, rankings.

• Must be carefully crafted to avoid potential bias.


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• Example: Multiple Choice


Day Decl., Lucent v. Microsoft (S.D. Cal. Dec. 13, 2010).

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• Example: Unaided questions


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CONSUMER SURVEYS: KEY TAKE-AWAYS

• Serious flaws in survey design and implementation can lead to exclusion of survey evidence.

• Surveys must be directed to the patented technology.

• Courts will likely examine literature in the field to determine whether a particular methodology can be used to quantify benefits of the invention.


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• Regression analysis is a set of statistical techniques that uses data to estimate the relationship between a dependent variable (e.g., product price) and an independent variable (e.g., features).

• Allows for “random error” that represents other things that could influence the dependent variable not included in the model.

• Useful in determining whether the value of a patented feature drives price, market share, or profitability, and what that value is.

REGRESSION ANALYSES: BACKGROUND


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• Example: Multiple Regression

1. Identify relevant features in product that likely affect price.

2. Hold other features constant and measure impact patented feature has on the price.

3. Estimate value of patented feature to overall product price.

REGRESSION ANALYSES: BACKGROUND


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REGRESSION ANALYSES: TYPES OF MODELS

Price Premium Market Share Prem. Merger Analysis

Dependent Variable (patented technology)

Price Market Share Change in Profits (price & market share)

Method Use price hedonic analysis to estimate how prices co-move with product characteristics.

Eliminate all other influences on market share & product success to estimate premium.

Calculate demand for product with technology.

Outcome Price premium enjoyed when using patented feature vs. same product using alternative technology.

Measure market share premium enjoyed when using patented feature.

Percentage change in product profitability when incorporate patented technology.


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• Price Premium Example: Multiple Regression

1. Identify relevant features in product that likely affect price.

2. Hold other features constant and measure impact patented feature has on the price.

• Result: price premium for a set of products that utilize patented technology over a second set of otherwise identical product that do not use patented technology.

REGRESSION ANALYSES: PRICE PREMIUM


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• Stragent v. Intel (E.D. Tex. March 6, 2014) (Fed. Cir. Judge Dyk)

• Multivariate hedonic regression used to estimate value of accused feature’s contribution to product price.

• 19 relevant features were either collectively present or not at all in Intel processors. Combination of features was 42% average selling price Each feature assigned identical weight.

• Methodology relied on arbitrary assumptions not tied to facts.

• Need to have data points where patented feature is not always part of the same bundle of other features.

REGRESSION ANALYSES: PRICE PREMIUM


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• Market Share Example:

1. Identify relevant influences on product that likely affect market share.

2. Hold other influences constant and measure impact patented feature has on market share.

• Analysis is similar to price premium / hedonics analysis, but the dependent variable is now market share.

REGRESSION ANALYSES: MARKET SHARE PREMIUM


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• Merger Analysis Example:

1. Calculate initial demand for product with patented feature.

2. Turn off patented feature to create new “equilibrium” – picture of the product’s market without the patented technology.

3. Quantitative end result is the % change in profits (product profitability) without patented technology.

REGRESSION ANALYSES: MERGER ANALYSIS


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REGRESSION ANALYSES: KEY TAKE-AWAYS

• Regression-based expert testimony has been tested for years in the antitrust context.

• Courts in the antitrust context have tended to carefully scrutinize specific variables and assumptions.

• Recent Federal District Court case law indicates importance of sound methodology and discredits arbitrary assumptions lacking factual basis.


• TV Interactive Data v. Sony (N.D. Cal. Mar. 1, 2013)

Admitting use of conjoint analysis in patent case regarding autoplay feature of DVD player, Blu-Ray player, and PlayStation 3 console.

Conjoint analysis, which measured the market’s willingness to pay for the patented technology, found reliable for providing a principled basis for choosing the non-patented features.

Conjoint surveys can provide reliable insight into consumer choice and willingness to pay for patented technology.

USES OF ECONOMIC ANALYSES IN PATENT LITIGATION: RECENT EFFECTIVE USES


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• Apple v. Samsung (Apple II) (N.D. Cal. Feb. 25, 2014)

Admitted conjoint survey used to quantify the hypothetical reduction in sales of accused products had noninfringing alternatives been developed.

Conjoint technique was sufficiently supported by the marketing research literature, indicating an acceptance of the technique used by the survey.

New conjoint techniques allowed if sufficiently supported by literature.



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• Criticisms relating to under-inclusiveness and clarity of survey can survive a Daubert challenge.

– Microsoft v. Motorola (W.D. Wash. 2012)

Admitting conjoint survey in a case concerning calculation of RAND royalty rates for video decode and Wi-Fi capabilities of Xbox 360.

Clarity of questionnaire and argument as to under-inclusiveness best resolved at trial through cross examination.

– Apple v. Samsung (Apple I) (N.D. Cal. June 30, 2012)

Admitting willingness-to-pay surveys relating to smartphones and tablets.

Defendant’s dissatisfaction with the description of the patented features in the survey and appropriate universe of potential purchasers goes to weight, not admissibility and does not render survey testimony unreliable.



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• Survey not tied to asserted patent claims rejected as flawed.

– NetAirus Techs. v. Apple (C.D. Cal. Oct. 23, 2013)

• Portions of survey found unreliable; survey questions were about all Wi-Fi use on accused phone, while asserted patent narrowly focused on email usage while connected to Wi-Fi.

– Apple v. Motorola (N.D. Ill. May 22, 2012), rev’d on other grounds, (Fed. Cir. April 25, 2014)

• Pertinent evidence excluded because damages model relied on survey designed to estimate value of a cellphone’s notification window but survey not designed to determine the relative value of the patented technology to Motorola’s customers.

USES OF ECONOMIC ANALYSES IN PATENT LITIGATION: RECENT REJECTIONS


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• Survey not tied to asserted patent claims rejected as flawed.

– Rembrandt v. Facebook (E.D. Va., Dec. 3, 2013), pet denied for interlocutory appeal, (Fed. Cir. April 7, 2014)

• Expert had improperly used surveys about importance to users of various features of the Facebook service; equated survey-result percentages reflecting importance with percentages of advertising revenue received by Facebook, without adequate analysis or explanation.

• Conjoint surveys are rejected for illogical results.

– Oracle v. Google (N.D. Cal. March 13, 2012)

• Excluding conjoint analysis for its illogical results, noting that testing only a portion of the total number of features may have caused the problem.



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• Survey cannot be stretched beyond its intended purpose.

– VirnetX v. Cisco (E.D. Tex. March 1, 2013)

• Expert precluded from simply substituting a survey result for actual sales data to show apportionment because the expert made no attempt to remove sales of noninfringing items from the sales data.

• But see Apple II, where new conjoint technique that was sufficiently supported by literature was allowed.



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• NetAirus retained two experts to conduct surveys regarding consumer use of the accused iPhone 4 products.

• Portions of one survey struck as unreliable under Daubert because the survey asked questions that had no reliable basis and were tied to functionality that was far beyond the asserted claims.

• Other survey struck in its entirety:

– (1) Expert made no effort to shield survey participants from the goals of the survey; (2) the gender of the survey participants was not balanced; and (3) the study asked prospective purchasers questions that required present use of the product.

Key Take-Away: Tie the survey to the asserted patent claims and retain an experienced survey expert.

USES OF ECONOMIC ANALYSES IN PATENT LITIGATION: NETAIRUS V. APPLE


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(C.D. Cal. Oct. 23, 2013)

• Expert conducted conjoint analysis determination of market share that measured the relative importance to consumers of seven smartphone features, three of which were covered by the patented technology, four of which were not.

• The expert offered no principle basis for selecting the four non-patented features for inclusion in the analysis.

• Survey found unreliable because the features selected to be surveyed were purposefully few in number and omitted important features that would have played an important role in real-world consumers’ preferences.

• Exclusion was required because the chosen features led to irrational results that indicated the study participants failed to hold all other non-tested features constant.

Key Take-Away: Choose nonpatented features reliably.

USES OF ECONOMIC ANALYSES IN PATENT LITIGATION: ORACLE V. GOOGLE


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(N.D. Cal. Mar. 13, 2012)

• Expert precluded from substituting a survey result for actual sales data to show apportionment because the expert made no attempts to remove sales of noninfringing items from the sales data.

• The expert reduced the revenue of entire products by 70% apportionment factor; a factor derived from a single survey which found 70% of customers valued VoIP security.

• “This apportionment factor is a poor substitute for the type of analysis one should undertake when parsing an alleged infringer’s profits for patented versus unpatented features.”

Key Take-Away: Avoid making a survey something that it is not.

USES OF ECONOMIC ANALYSES IN PATENT LITIGATION: VIRNETX V. CISCO


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(E.D. Tex. Mar. 1, 2013)

• Apple I: Samsung moved to exclude the willingness-to-pay opinions of expert hired by Apple to design and conduct two surveys (one for smartphones, one for tablets) to determine what price premium, if any, Samsung customers are willing to pay for the features associated with the patents at issue.

– Expert’s failure to disclose written records of underlying interviews used to select appropriate “distraction features” does not render survey testimony unreliable.

– Under-inclusiveness and clarity of the survey goes to weight, not admissibility.

• Apple II: Samsung moved to exclude the survey expert who designed and performed the conjoint surveys to determine the demand for the patented features at issue in the case.

– First step in expert’s analysis was same as in Apple I and although conjoint technique in the expert’s second step had not been used in the same way before, it was adequately supported by marketing research literature indicating acceptance of the technique used by Apple’s survey.

USES OF ECONOMIC ANALYSES IN PATENT LITIGATION: APPLE I & APPLE II


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(N.D. Cal. Jun. 29, 2012)

(N.D. Cal. Feb. 25, 2014)

• Properly-constructed consumer surveys can provide highly persuasive evidence of patent value.

• Serious flaws in survey design and implementation can lead to exclusion of survey evidence.

• Vulnerable to attack if not tied to the patented technology and consumer demand for the inventive feature.

• Surveys conducted for litigation purposes often are very different than those conducted by a company for non-litigation marketing purposes.

AVOIDING COMMON CHALLENGES TO ECONOMIC ANALYSES


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• Trial courts may choose to exclude direct testimony by the survey expert when the damages expert will be relying on survey data.

• The party’s damages expert should be in the position of presenting evidence about the consumer survey, and, in describing the underlying methodology used in the survey.

• The survey expert should provide detailed information as to the design of the survey instrument, implementation of the survey, and analysis of the survey data.

AVOIDING COMMON CHALLENGES TO ECONOMIC ANALYSES: ENSURE EXPERT FAMILIARITY


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• The damages expert should be familiar with details necessary to ensure the validity and reliability of the survey data.


• The Braun Corp. v. Vantage Mobility Int’l (N.D. Ind. Jun. 21, 2010)

– Defendant’s damages expert relied on a histogram that was derived from a consumer survey.

– District court struck portions of testimony by defendant’s damages expert relating to the histogram.

• The damages expert’s report failed to disclose details of the underlying survey.

• The expert did not independently establish the validity and reliability of the underlying survey data.


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• Proponents of survey evidence should carefully consider how such evidence might be used against the proffering party.


• Lear Automotive v. Johnson Controls (E.D. Mich. Feb. 7, 2011)

– Defendant provided its damages expert with a survey directed to assess the frequency of use of patented feature in accused garage door systems.

– Defendant’s damages expert relied on the survey to calculate the royalty rate.

– The plaintiff used the same survey to meet its burden of proof on direct infringement.

– Over Defendant’s objection, the District court found the data admissible as an adoptive admission.


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AVOIDING COMMON CHALLENGES TO ECONOMIC ANALYSES: DIRECT THE SURVEY TO THE PATENTED TECHNOLOGY


• Consumer survey evidence is frequently challenged on ground that it does not specifically address the issues in dispute.

• Fractus, S.A. v. Samsung Electronics (E.D. Tex. Apr. 29, 2011)

– District court excluded testimony re: survey of internal vs. external antennas, because survey was not directed at specific features of claimed technology.

– Patent-in-suit did not address internal antennas, but rather multi-band functionality and reduced size.

• LaserDynamics v. Quanta Computer (E.D. Tex. Jan. 7, 2011)

– District court excluded expert testimony re: survey of royalty rates in computer component industry, because survey was not limited to comparable technologies.

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AVOIDING COMMON CHALLENGES TO ECONOMIC ANALYSES: PROPERLY DEFINE THE SURVEY POPULATION


• Ensure that survey participants are selected from a population encompassing the correct survey participants.

• Example: if the goal of the survey is to determine business attitudes regarding an accused product . . .

– Survey is over inclusive if it includes non-business purchasers.

– Survey is likely under inclusive if it fails to include certain types of business purchasers.

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AVOIDING COMMON CHALLENGES TO ECONOMIC ANALYSES: PROPERLY DEFINE THE SURVEY POPULATION


• Case examples:

• Hodgdon Powder Co. v. Alliant Techsystems (D. Kan. 2007)

– Survey population consisting only of plaintiff’s customers was too narrow and should have included purchasers of competing products across the industry.

• Leelanau Wine Cellars v. Black & Red (S.D. Ind. 2003)

– Survey conducted by plaintiff in shopping malls was overbroad. Although plaintiff sold products through variety of channels, defendant only sold product through specific, narrow trade channel. District court gave the survey minimal weight.

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AVOIDING COMMON CHALLENGES TO ECONOMIC ANALYSES: PAY ATTENTION TO DETAIL


• Utilize Procedures to Ensure a Fair Sample of the Population.

– Ensure that the chosen sample accurately reflects a cross section of the total population.

• Clearly Define the Survey Objectives.

– When commissioning a survey, carefully define survey objectives and tailor questions to squarely address those objectives.

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AVOIDING COMMON CHALLENGES TO ECONOMIC ANALYSES: PAY ATTENTION TO DETAIL


• Determine an Appropriate Mode of Data Collection for the Survey.

– In-person interviews

– Telephone surveys

– Mail surveys

– Internet surveys

• Use Clear, Precise, and Unbiased Questions.

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AVOIDING COMMON CHALLENGES TO ECONOMIC ANALYSES: CHECK YOUR WORK


• Employ Appropriate Controls to Ensure the Objectivity of the Survey.

– Attorneys should avoid direct participation in interview and results tabulation process.

– Courts may exclude survey data where attorneys have undue influence.

– United States v. Southern Indiana Gas & Electric Co. (S.D. Ind. 2003)

• District court “troubled” that defense counsel sent letter that “could be interpreted as pressure or guidance” to survey participants before receiving the survey.

• Conduct a Post-Survey Validation of Data.

• Employ Procedures to Ensure that Survey Methodology and Data are Properly Recorded.

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AVOIDING COMMON CHALLENGES TO ECONOMIC ANALYSES: KEY TAKE-AWAYS


• Federal Circuit trend: damages awards must be supported by evidence that is firmly rooted in sound economic theory and tied to the patented invention’s “footprint in the marketplace.”

• Economic analyses can be used to demonstrate or refute the evidentiary link between the patented invention and consumer demand.

• Economic analyses must be tied to the patented technology at issue.

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Christopher K. Larus Chair, Minneapolis IP Litigation Group

[email protected] 612.349.0116

Q & A


Bryan J. Mechell IP Litigation Group

[email protected] 612.349.0172

Shankar Iyer Vice President,

Cornerstone Research [email protected]

202.912.8924

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