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Posts Tagged ‘Data’

‘Experience’ has gained a prime status in the past decade — everything seems to revolve around experience in the universe of management, marketing, and even more specifically with respect to relationship marketing. It has become like a sine qua non of operating in this universe. There can be multiple contexts for framing experience — customer experience, brand experience, user (or product) experience, and also employee experience. Nevertheless, these concepts are inter-linked, and customer experience could be the central point-of-reference just because all other forms of experience eventually contribute to the customer’s experience. After all, this is the age of experience economy (cf. Pine and Gilmore).

This focus on the role of experience and primarily customer experience (CX) in contemporary marketing surely has not escaped the attention of companies involved with data-based marketing particularly on the service side (e.g., technology, research, consulting). In mid-November 2018 enterprise information technology company SAP announced a stark move of acquiring research technology firm Qualtrics for the sum of $8 billion in cash (deal expected to materialise during the first half of 2019). Qualtrics started in 2002 by specialising in survey technology for conducting consumer and customer surveys online, and has later on broadened the spectrum of its software products and tools to address a range of experience domains, put in a framework entitled Experience Management (XM).

However, less visible to the public, Qualtrics made an acquisition of its own of Temkin Group — an expert company specialising in customer experience research, training and consulting — about two weeks before announcing the SAP-Qualtrics deal. Qualtrics was reportedly engaged at the time of these deals in preparations for its IPO. Adding the knowledge and capabilities of Temkin Group to those of Qualtrics could fairly be viewed as a positive enforcement of the latter prior to its IPO, and eventually the selling of Qualtrics to SAP. Therefore, it would be right to say that Qualrtics + Temkin Group and SAP are effectively joining forces in domain knowledge, research capabilities and data technologies. Yet since the original three entities (i.e., as before November 2018) were so unequal in size and power, it raises some major questions about how their union under the umbrella of SAP will work out.

SAP specialises in enterprise software applications for organisational day-to-day functions across-the-board, and supporting software-related services (SAP was established in 1972, based in Germany). It operates today in 130 countries with 100+ innovation and development centres; its revenue in the 2017 financial year was $23.46 billion. Many of the company’s software applications can be deployed on premises, in the cloud, or hybrid (SAP reports 150 million subscribers in the cloud service user base). The two product areas of highest relevance to this story are CRM & Customer Experience solutions and the Enterprise Resource Planning (ERP) solutions & Digital Core (featuring its flagship platform HANA). The two areas of solutions correspond with each other.

The S4/HANA platform is described as an intelligent ERP software, a real-time solution suite . It enables, for example, delivering personally customised products ordered online (e.g., bicycles). For marketing activities and customer-facing services it should require data from the CRM and CX applications. The ERP platform supports, however, the financial planning and execution of overall activities of a client organisation. The CRM & Customer Experience suite of solutions includes five key components: Customer Data Cloud (enabled actually by Gigya, another acquisition by SAP in 2017); Marketing Cloud; Commerce Cloud; Sales Cloud; and Service Cloud. The suite covers a span of activities and functions: profiling and targeting at segment-level and individual level, applicable, for instance, in campaigns or tracking customer journeys (Marketing); product order and content management (Commerce); comprehensive self-service processes plus field service management and remote service operations by agents (Service). In all these sub-areas we may find potential links to the kinds of data that can be collected and analysed with the tools of Qualtrics while SAP’s applications are run on operational data gathered within its system apparatus. The key strengths offered in the Customer Data Cloud are integrating data, securing customer identity and access to digital interfaces across channels and devices, and data privacy protection. SAP highlights that its marketing and customer applications are empowered by artificial intelligence (AI) and machine learning (ML) capabilities to personalise and improve experiences.

  • At the technical and analytic level, SAP’s Digital Platform is in charge of the maintenance of solutions and databases (e.g., ERP HANA) and management of data processes, accompanied by the suite of Business Analytics that includes the Analytics Cloud, Business Analytics, Predictive Analytics and Collaborative Enterprise Planning. Across platforms SAP makes use of intelligent technologies and tools organised in its Leonardo suite.

Qualtrics arrives from quite a different territory, nestled much closer to the field of marketing and customer research as a provider of technologies for data collection through surveys of consumers and customers, and data analytic tools. The company has gained acknowledgement thanks to its survey software for collecting data online whose use has so expanded to make it one of the more popular among businesses for survey research. Qualtrics now focuses on four domains for research: Customer Experience, Brand Experience, Product Experience, and Employee Experience.

  • The revenue of Qualtrics in 2018 is expected to exceed $400 million (in first half of 2018 revenue grew 42% to $184m); the company forecast that revenue will continue to grow at an annual rate of 40% before counting its benefits from synergies with SAP (CNBC; TechCrunch on 11 November 2018).

Qualtrics organises its research methodologies and tools by context under the four experience domains aforementioned. The flagship survey software, PER, allows for data collection through multiple digital channels (e.g., e-mail, web, mobile app, SMS and more), and is accompanied by a collection of techniques and tools for data analysis and visualisation. The company emphasises that its tools are so designed that use of them does not require one to be a survey expert or a statistician.

Qualtrics provides a range of intelligent assistance and automation capabilities; they can aid, guide and support the work of users according to their level of proficiency. Qualtrics has developed a suite of intelligent tools, named iQ, among them Stats iQ for statistical analysis, Text iQ for text analytics and sentiment scoring, and Predict iQ + Driver iQ for advanced statistical analysis and modelling. Additionally, it offers ExpertReview for helping with questionnaire composition (e.g., by giving AI-expert ‘second opinion’). In a marketing context, the company offers techniques for ad testing, brand tracking, pricing research, market segmentation and more. Some of these research methodologies and tools would be of less relevance and interest to SAP unless they can be connected directly to customer experiences that SAP needs to understand and account for through the services it offers.

The methods and tools by Qualtrics are dedicated to bringing the subjective perspective of customers about their experiences. Under the topic of Customer Experience Qualtrics covers customer journey mapping, Net Promoter Score (NPS), voice of the customer, and digital customer experience; user experience is covered in the domain of Product Experience, and various forms of customer-brand interactions are addressed as part of Brand Experience. The interest of SAP especially in Qualtrics, as stated by the firm, is  complementing or enhancing its operational data (O-data) with customer-driven experience data (X-data) produced by Qualtrics (no mention is made of Temkin Group). The backing and wide business network of SAP should create new opportunities for Qualtrics to enlarge its customer base, as suggested by SAP. The functional benefits for Qualtrics are less clear; possible gains may be achieved by combining operational metrics in customer analyses as benchmarks or by making comparisons between objective and subjective evaluations of customer experiences, assuming clients will subscribe to some of the services provided by the new parent company SAP.

Temkin Group operated as an independent firm for eight years (2010-2018), headed by Bruce Temkin (with wife Karen), until its acquisition by Qualtrics in late October 2018. It provided consulting, research and training activities on customer experience (at its core was customer experience but it dealt with various dimensions of experience beyond and in relation to customers). A key asset of Temkin Group is its blog / website Experience Matters, a valued resource of knowledge; its content remains largely in place (viewed January 2018), and hopefully will stay on.

Bruce Temkin developed several strategic concepts and constructs of experience. The Temkin Experience Rating metric is based on a three-component construct of experience: Success, Effort and Emotion. The strategic model of experience includes four required competencies: (a) Purposeful Leadership; (b) Compelling Brand Values; (c) Employee Engagement; and (d) Customer Connectedness. He made important statements in emphasising the essence of employee engagement to deliver superior customer experience, and in including Emotion as one of the pillars of customer experience upon which it should be evaluated. The more prominent of the research reports published by Temkin Group were probably the annual series of Temkin Experience Rating reports, covering 20 industries or markets with a selection of companies competing in each.

Yet Temkin apparently has come to a realisation that he should not go it alone any longer. In a post blog on 24 October 2018, entitled “Great News: Temkin Group Joins Forces With Qualtrics“, Temkin explained as the motivation to his deal with Qualtrics a recognition he had reached during the last few years: “it’s become clear to me that Qualtrics has the strongest momentum in CX and XM“. Temkin will be leading the Qualtrics XM Institute, built on the foundations of Temkin CX Institute dedicated to training. The new institute will be sitting on top of Qualtrics XM platform. In his blog announcement Temkin states that the Qualtrics XM Institute will “help shape the future of experience management, establish and publish best practices, drive product innovation, and enable certification and training programs that further build the community of XM professionals” — a concise statement that can be viewed as the charter of the institute Temkin will be in charge of at Qualtrics. Temkin has not taken long to adopt the framework of Experience Management and support it in writing for the blog.

The teams of Temkin and Qualtrics (CEO and co-founder Ryan Smith) may co-operate more closely in developing research plans on experience for clients and initiating research reports similar to the ones Temkin Group produced so far. Bruce Temkin should have easy and immediate access to the full range of tools and technologies of Qualtrics to continue with research projects and improve on them. Qualtrics should have much to benefit from the knowledge and training experience of Temkin in the new XM institute at Qualtrics. It seems easier to foresee beneficial synergies between Temkin Group and Qualtrics than their expected synergies with SAP.

However, there is a great question arising now, how all this vision and plans for Temkin and Qualtrics working together, and particularly their project of Qualtrics XM Institute, will be sustained following the acquisition of Qualtrics by SAP. One cannot overlook the possibility that SAP will develop its own expectations and may require changes to plans only recently made or modifications to Qualtrics CX Platform and XM Solutions so as to satisfy the needs of SAP. According to TechCrunch (11 Nov. 2018) Qualtrics will continue to function as a subsidiary company and will retain its branding and personnel (note: it may be gradually assimilated into SAP while keeping Qualtrics associated names, as seems to be the case of Israel-based Gigya). Much indeed can depend on giving Qualtrics + Temkin Group autonomy to pursue with their specialisations and vision on XM while they share knowledge, data and technologies with SAP.

Bill McDermott, CEO of SAP, is looking high in the sky: as quoted in the company’s news release from 11 November 2018, he describes bringing together SAP and Qualtrics as “a new paradigm, similar to market-making shifts in personal operating systems, smart devices and social networks“. But it is also evident that SAP still sees the move through the prism of technology: “The combination of Qualtrics and SAP reaffirms experience management as the ground-breaking new frontier for the technology industry“.

Temkin’s viewpoint is much more customer-oriented and marketing-driven vis-à-vis the technology-driven view of McDermott and SAP, which may put them in greater conflict with time about priorities and future direction for XM. Qualtrics headed by Ryan Smith will have to decide how it prefers to balance between the marketing-driven view and technology-driven view on experience. Temkin, for example, has reservations about the orientation of the technology known as Enterprise Feedback Management (EFM), suggesting instead a different focus by naming this field “Customer Insight and Action (AIC) Platforms”. In his comments on the acquisition of Qualtrics by SAP (16 November 2018) he explains that organisations “succeed by taking action on insights that come from many sources, combining experience data (X-data) and operational data (O-data)“. In his arguments in favour of joining SAP with Qualtrics, Temkin recollects an observation he made in an award-winning report from 2002 while at Forrester Research: he argued then that “widespread disappointing results of CRM were a result of a pure technology-orientation and that companies needed to focus more on developing practices and perspectives that used the technology to better serve customers”; he claims that much has changed in the field since that time. Yet it is hard to be convinced that technology has much less influence now in shaping organisational, managerial and marketing processes, on both service side (e.g., SAP) and client side.

  • As a note aside, if SAP gets the upper hand in setting the agenda and does not give sufficient autonomy to Qualtrics as suggested earlier, the first sector at risk of having most to lose from this deal would be ‘marketing and customer research’.

SAP and Qualtrics are both involved in development and implementation of technology, yet SAP is focused on information technology enabling overall day-to-day operations of an organisation, whereas Qualtrics is focused on technology enabling experience and marketing research. Qualtrics and Temkin Group are both engaged in domains of experience: Qualtrics specialises in the technology that enables the research, while Temkin Group brought strengths in conducting research plus strategic thinking and training (education) on customer experience. In order for their joint forces to succeed they all will have to find ways to bridge gaps between their viewpoints, to ‘live and let live’, and at the same time complement one another in areas of shared understanding and expertise.

Ron Ventura, Ph.D. (Marketing)

 

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Revelations about the Facebook – Cambridge Analytica affair last month (March 2018) invoked a heated public discussion about data privacy and users’ control over their personal information in social media networks, particularly in the domain of Facebook. The central allegation in this affair is that personal data in social media was misused for the winning political presidential campaign of Donald Trump. It offers ‘juicy’ material for all those interested in American politics. But the importance of the affair goes much beyond that, because impact of the concerns it has raised radiates to the daily lives of millions of users-consumers socially active via the social media platform of Facebook; it could touch potentially a multitude of commercial marketing contexts (i.e., products and services) in addition to political marketing.

Having a user account as member of the social media network of Facebook is pay free, a boon hard to resist. Facebook surpassed in Q2 of 2017 the mark of two billion active monthly users, double a former record of one billion reached five years earlier (Statista). No monetary price requirement is explicitly submitted to users. Yet, users are subject to alternative prices, embedded in the activity on Facebook, implicit and less noticeable as a cost to bear.

Some users may realise that advertisements they receive and see is the ‘price’ they have to tolerate for not having to pay ‘in cash’ for socialising on Facebook. It is less of a burden if the content is informative and relevant to the user. What users are much less likely to realise is how personally related data (e.g., profile, posts and photos, other activity) is used to produce personally targeted advertising, and possibly in creating other forms of direct offerings or persuasive appeals to take action (e.g., a user receives an invitation from a brand, based on a post of his or her friend, about a product purchased or  photographed). The recent affair led to exposing — in news reports and a testimony of CEO Mark Zuckerberg before Congress — not only the direct involvement of Facebook in advertising on its platform but furthermore how permissive it has been in allowing third-party apps to ‘borrow’ users’ information from Facebook.

According to reports on this affair, Psychologist Aleksandr Kogan developed with colleagues, as part of academic research, a model to deduce personality traits from behaviour of users on Facebook. Aside from his position at Cambridge University, Kogan started a company named Global Science Research (GSR) to advance commercial and political applications of the model. In 2013 he launched an app in Facebook, ‘this-is-your-digital-life’, in which Facebook users would answer a self-administered questionnaire on personality traits and some personal background. In addition, the GSR app prompted respondents to give consent to pull personal and behavioural data related to them from Facebook. Furthermore, at that time the app could get access to limited information on friends of respondents — a capability Facebook removed at least since 2015 (The Guardian [1], BBC News: Technology, 17 March 2018).

Cambridge Analytica (CA) contracted with GSR to use its model and data it collected. The app was able, according to initial estimates, to harvest data on as many as 50 million Facebook users; by April 2018 the estimate was updated by Facebook to reach 87 millions. It is unclear how many of these users were involved in the project of Trump’s campaign because CA was specifically interested for this project in eligible voters in the US; it is said that CA applied the model with data in other projects (e.g., pro-Brexit in the UK), and GSR made its own commercial applications with the app and model.

In simple terms, as can be learned from a more technical article in The Guardian [2], the model is constructed around three linkages:

(1) Personality traits (collected with the app) —> data on user behaviour in Facebook platform, mainly ‘likes’ given by each user (possibly additional background information was collected via the app and from the users’ profiles);

(2) Personality traits —> behaviour in the target area of interest — in the case of Trump’s campaign, past voting behaviour (CA associated geographical data on users with statistics from the US electoral registry).

Since model calibration was based on data from a subset of users who responded to the personality questionnaire, the final stage of prediction applied a linkage:

(3) Data on Facebook user behaviour ( —> predicted personality ) —>  predicted voting intention or inclination (applied to the greater dataset of Facebook users-voters)

The Guardian [2] suggests that ‘just’ 32,000 American users responded to the personality-political questionnaire for Trump’s campaign (while at least two million users from 11 states were initially cross-referenced with voting behaviour). The BBC gives an estimate of as many as 265,000 users who responded to the questionnaire in the app, which corresponds to the larger pool of 87 million users-friends whose data was harvested.

A key advantage credited to the model is that it requires only data on ‘likes’ by users and does not have to use other detailed data from posts, personal messages, status updates, photos etc. (The Guardian [2]). However, the modelling concept raises some critical questions: (1) How many repeated ‘likes’ of a particular theme are required to infer a personality trait? (i.e., it should account for a stable pattern of behaviour in response to a theme or condition in different situations or contexts); (2) ‘Liking’ is frequently spurious and casual — ‘likes’ do not necessarily reflect thought-out agreement or strong identification with content or another person or group (e.g., ‘liking’ content on a page may not imply it personally applies to the user who likes it); (3) Since the app was allowed to collect only limited information on a user’s ‘friends’, how much of it could be truly relevant and sufficient for inferring the personality traits? On the other hand, for whatever traits that could be deduced, data analyst and whistleblower Christopher Wylie, who brought the affair out to the public, suggested that the project for Trump had picked-up on various sensitivities and weaknesses (‘demons’ in his words). Personalised messages were respectively devised to persuade or lure voters-users likely to favour Trump to vote for him. This is probably not the way users would want sensitive and private information about them to be utilised.

  • Consider users in need for help who follow and ‘like’ content of pages of support groups for bereaved families (e.g., of soldiers killed in service), combatting illnesses, or facing other types of hardship (e.g., economic or social distress): making use of such behaviour for commercial or political gain would be unethical and disrespectful.

Although the app of GSR may have properly received the consent of users to draw information about them from Facebook, it is argued that deception was committed on three counts: (a) The consent was awarded for academic use of data — users were not giving consent to participate in a political or commercial advertising campaign; (b) Data on associated ‘friends’, according to Facebook, has been allowed at the time only for the purpose of learning how to improve users’ experiences on the platform; and (c) GSR was not permitted at any time to sell and transfer such data to third-party partners. We are in the midst of a ‘blame game’ among Facebook, GSR and CA on the transfer of data between the parties and how it has been used in practice (e.g., to what extent the model of Kogan was actually used in the Trump’s campaign). It is a magnificent mess, but this is not the space to delve into its small details. The greater question is what lessons will be learned and what corrections will be made following the revelations.

Mark Zuckerberg, founder and CEO of Facebook, gave testimony at the US Congress in two sessions: a joint session of the Senate Commerce and Judiciary Committees (10 April 2018) and before the House of Representatives Commerce and Energy Committee (11 April 2018). [Zuckerberg declined a call to appear in person before a parliamentary committee of the British House of Commons.] Key issues about the use of personal data on Facebook are reviewed henceforth in light of the opening statements and replies given by Zuckerberg to explain the policy and conduct of the company.

Most pointedly, Facebook is charged that despite receiving reports concerning GSR’s app and CA’s use of data in 2015, it failed to ensure in time that personal data in the hands of CA is deleted from their repositories and that users are warned about the infringement (before the 2016 US elections), and that it took at least two years for the social media company to confront GSR and CA more decisively. Zuckerberg answered in his defence that Cambridge Analytica had told them “they were not using the data and deleted it, we considered it a closed case”; he immediately added: “In retrospect, that was clearly a mistake. We shouldn’t have taken their word for it”. This line of defence is acceptable when coming from an individual person acting privately. But Zuckerberg is not in that position: he is the head of a network of two billion users. Despite his candid admission of a mistake, this conduct is not becoming a company the size and influence of Facebook.

At the start of both hearing sessions Zuckerberg voluntarily and clearly took personal responsibility and apologized for mistakes made by Facebook while committing to take measures (some already done) to avoid such mistakes from being repeated. A very significant realization made by Zuckerberg in the House is him conceding: “We didn’t take a broad view of our responsibility, and that was a big mistake” — it goes right to the heart of the problem in the approach of Facebook to personal data of its users-members. Privacy of personal data may not seem to be worth money to the company (i.e., vis-à-vis revenue coming from business clients or partners) but the whole network business apparatus of the company depends on its user base. Zuckerberg committed that Facebook under his leadership will never give priority to advertisers and developers over the protection of personal information of users. He will surely be followed on these words.

Zuckerberg argued that the advertising model of Facebook is misunderstood: “We do not sell data to advertisers”. According to his explanation, advertisers are asked to describe to Facebook the target groups they want to reach, Facebook traces them and then does the placement of advertising items. It is less clear who composes and designs the advertising items, which also needs to be based on knowledge of the target consumers-users. However, there seems to be even greater ambiguity and confusion in distinguishing between use of personal data in advertising by Facebook itself and access and use of such data by third-party apps hosted on Facebook, as well as distinguishing between types of data about users (e.g., profile, content posted, response to others’ content) that may be used for marketing actions.

Zuckerberg noted that the ideal of Facebook is to offer people around the world free access to the social network, which means it has to feature targeted advertising. He suggested in Senate there will always be a pay-free version of Facebook, yet refrained from saying when if ever there will be a paid advertising-clear version. It remained unclear from his testimony what information is exchanged with advertisers and how. Zuckerberg insisted that users have full control over their own information and how it is being used. He added that Facebook will not pass personal information to advertisers or other business partners, to avoid obvious breach of trust, but it will continue to use such information to the benefit of advertisers because that is how its business model works (NYTimes,com, 10 April 2018). It should be noted that whereas users can choose who is allowed to see information like posts and photos they upload for display, that does not seem to cover other types of information about their activity on the platform (e.g., ‘likes’, ‘shares’, ‘follow’ and ‘friend’ relations) and how it is used behind the scenes.

Many users would probably want to continue to benefit from being exempt of paying a monetary membership fee, but they can still be entitled to have some control over what adverts they value and which they reject. The smart systems used for targeted advertising could be less intelligent than they purport to be. Hence more feedback from users may help to assign them well-selected adverts that are of real interest, relevance and use to them, and thereof increase efficiency for advertisers.

At the same time, while Facebook may not sell information directly, the greater problem appears to be with the information it allows apps of third-party developers to collect about users without their awareness (or rather their attention). In a late wake-up call at the Senate, Zuckerberg said that the company is reviewing app owners who obtain a large amount of user data or use it improperly, and will act against them. Following Zuckerberg’s effort to go into details of the terms of service and to explain how advertising and apps work on Facebook, and especially how they differ, Issie Lapowsky reflects in the ‘Wired’: “As the Cambridge Analytica scandal shows, the public seems never to have realized just how much information they gave up to Facebook”. Zuckerberg emphasised that an app can get access to raw user data from Facebook only by permission, yet this standard, according to Lapowsky, is “potentially revelatory for most Facebook users” (“If Congress Doesn’t Understand Facebook, What Hope Do Its Users Have”, Wired, 10 April 2018).

There can be great importance to how an app asks for permission or consent of users to pull their personal data from Facebook, how clear and explicit it is presented so that users understand what they agree to. The new General Data Protection Regulation (GDPR) of the European Union, coming into effect within a month (May 2018), is specific on this matter: it requires explicit ‘opt-in’ consent for sensitive data and unambiguous consent for other data types. The request must be clear and intelligible, in plain language, separated from other matters, and include a statement of the purpose of data processing attached to consent. It is yet to be seen how well this ideal standard is implemented, and extended beyond the EU. Users are of course advised to read carefully such requests for permission to use their data in whatever platform or app they encounter them before they proceed. However, even if no information is concealed from users, they may not be adequately attentive to comprehend the request correctly. Consumers engaged in shopping often attend to only some prices, remember them inaccurately, and rely on a more general ‘feeling’ about the acceptable price range or its distribution. If applying the data of users for personalised marketing is a form of price expected from them to pay, a company taking this route should approach the data fairly just as with setting monetary prices, regardless of how well its customers are aware of the price.

  • The GDPR specifies personal data related to an individual to be protected if “that can be used to directly or indirectly identify the person”. This leaves room for interpretation of what types of data about a Facebook user are ‘personal’. If data is used and even transferred at an aggregate level of segments there is little risk of identifying individuals, but for personally targeted advertising or marketing one needs data at the individual level.

Zuckerberg agreed that some form of regulation over social media will be “inevitable ” but conditioned that “We need to be careful about the regulation we put in place” (Fortune.com, 11 April 2018). Democrat House Representative Gene Green posed a question about the GDPR which “gives EU citizens the right to opt out of the processing of their personal data for marketing purposes”. When Zuckerberg was asked “Will the same right be available to Facebook users in the United States?”, he replied “Let me follow-up with you on that” (The Guardian, 13 April 2018).

The willingness of Mark Zuckerberg to take responsibility for mistakes and apologise for them is commendable. It is regrettable, nevertheless, that Facebook under his leadership has not acted a few years earlier to correct those mistakes in its approach and conduct. Facebook should be ready to act in time on its responsibility to protect its users from harmful use of data personally related to them. It can be optimistic and trusting yet realistic and vigilant. Facebook will need to care more for the rights and interests of its users as it does for its other stakeholders in order to gain the continued trust of all.

Ron Ventura, Ph.D. (Marketing)

 

 

 

 

 

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