Social Media Return on Investment and Performance Evaluation in the Hotel Industry Context Dimitrios Buhalis and Emmanouil Mamalakis
Abstract Marketing has been impacted by social media platforms and the Internet developments. To survive fierce competition, corporations have to take advantage of all the opportunities provided by Social Media (SM). Marketers need to evaluate the effectiveness of different SM channels and Return on Investment (ROI) measurement is critical in the management of SM marketing campaigns. This paper assesses SM ROI using Princess Andriana Hotel in Rhodes, Greece as a case study. It clarifies complicated concepts related to SM ROI measurement. A comprehensive framework, built around the landscape of SM ROI assessment supports measurability. A netnographic observation revealed suitable metrics for the evaluation of the SM activities. Five SM channels and a set of analytics tools were combined to measure SM ROI. The result identified both financial and non-financial returns. Finally, recommendations for future assessment of SM campaign are provided. Keywords Social media • Return on investment • Metrics • Case study • Hotel • Marketing
1 Introduction The Internet and SM have dramatically changed the way people communicate, by providing channels that contribute to the interactions and transactions between consumers and businesses (Gay et al. 2007). SM platforms host over two billion users monthly (Statistic Brain 2014), who are actively participating in content creation in communities, blogs, social networking, wikis. SM have been characterized as the hybrid of marketing and communications (Orsburn 2012). Measuring SM performance and ROI have become increasingly important. Hitherto, measurement efforts and tools have been insufficient and methods undeveloped (Powell et al. 2011). Web 2.0 released innovations in communications, marketing, and promotion. However marketers are unable to precisely calculate the performance D. Buhalis (*) • E. Mamalakis eTourismLab, School of Tourism, Bournemouth University, Poole, UK e-mail:
[email protected];
[email protected] © Springer International Publishing Switzerland 2015 I. Tussyadiah, A. Inversini (eds.), Information and Communication Technologies in Tourism 2015, DOI 10.1007/978-3-319-14343-9_18
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of their online marketing activities. Managers need justifications for escalating SM budgets and promotion and for making the right high-level decisions. Investments in online promotion need to be measured and evaluated to assess any form of return. The purpose of this paper is to explore online marketing measurement practises and to create a framework that assists the measurability of SM ROI. The research used the SM activity of the Princess Adrianna Resort and Spa Hotel, in Rhodes, Greece to develop a framework of techniques and measurements to evaluate effectiveness.
2 Theoretical Background The development of Web 2.0 strengthened the communication between consumers and companies through a variety of online channels. These interactions enhance marketing, attracting new customers by superior value and satisfying existing customers. Marketing is entering into a new era where the power of influence moves from marketers to consumers. This requires new marketing tools and methods for measurement of ROI in promotional activities. ROI fulfils business need for a tangible profit from an investment (Kaske et al. 2012). In finance, ROI is simply calculated by the following formula (Lenskold 2003; Ambler and Roberts 2008, cited in Rautio 2012; Sheehan 2010): ROI ¼ ðGain from Investment Cost of InvestmentÞ=Cost of Investment ROI is the relationship between profit and the investment that generates that profit, and is widely used to examine the performance of an investment (Franklin and Plewa 1996). However, there are differences between calculating the ROI in financial terms, and in terms of marketing; especially in online marketing where there are increased levels of complexity. In marketing ROI equations, there is a variety of different metrics replacing traditional ones. The early history of SM ROI measurement has presented negative opinions about measurement (Powell et al. 2011). Companies have dropped the idea of ROI as a success measurement for SM (Crosti 2013). The debate rise around the types of SM ROI that can be measured. Therefore, it is critical to investigate the different opinions around online marketing measurement (Table 1).
2.1
Metrics
Ultimately, there are financial and non-financial measurements of ROI (Perdue 2010). In the past, measuring the performance of online advertising used simple metrics such as unique visitors, page visitors, page views or cost per clicks (Fisher 2009). Web 2.0 applications brought a further advance of e-metrics. E-metrics are defined as performance criteria that measure the success of Internet sites (internal and external) and e-business and e-commerce (Fisher 2009). Metrics could be divided into marketing,
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Table 1 The SM ROI debate Financial arguments
Author
Inability in measuring traditional media. Conversely, ability in measuring SM The key through hard metrics and financial ROI is Web analytics Trusts the three categories of metrics: qualitative, quantitative, ROI It is possible to measure by taking two important steps Financial metrics win the battle against non-financial metrics Non-financial arguments Businesses realised that there is no financial metrics to measure, there is only soft metrics Marketers will never be able to measure every single financial lead, thus SM is about impression The metrics to be measured are often unknown SM financial ROI: Measuring the immeasurable It is more effective to measure engagement rather than financial ROI Financial and non-financial arguments SM can be now measured due to traditional media tactics Internet marketing has developed web metrics for measuring and evaluating online performance It’s impossible to precisely measure ROI
Sheehan (2010) Crosti (2013) Robson (2013) Turner (2010) Orsburn (2012) Kaske et al. (2012) Author Heggestuen (2013) Seiter (2012) Filisko (2011), Westlund (2013) Cleverwood (2011)
Author Powell et al. (2011) Gay et al. (2007) Crosti (2013)
financial, and technical, although those three categories can be inter-connected (Ryals 2008, cited in Rautio 2012). Different performance indicators are used for engagement, traffic measurement, customer service, financial return, reputation management and so on (Powell et al. 2011; Fisher 2009; Orsburn 2012). Barefoot and Szabo (2010) suggest that the following metrics can deliver ROI measurements: visitors, incoming links, social network activity, conversations and contributions, references in the blogosphere, views on SM sites, RSS subscribers, and social bookmarking (cited in Perdue 2010). Different authors use different approaches to SM ROI and present various metrics. This paper identified and categorized those metrics as financial and non-financial, depending on the result that is delivered during the measurement. For instance, The Rocky mountain Hotel increased revenues by their online marketing campaign, grounded on Twitter, for the year 2011–2012 (Herrmann 2012). Based on the formula: Revenues ¼ Reach impact Yield and knowing that Influenced conversations ¼ Reach Impact the company revealed revenues increased by $21,900 due to SM initiatives. The Twitter strategy procedure extracted the following data: 365 tweets, 876 re-tweets, 1,777 followers on Twitter and 1.630.394 reach in all their tweets, 3,606 clicks, 0.22 % click-through rate, 0.3 % Lead conversion rate, 11 conversions and $1,059.29 average revenue per room. The expenses measured in that period of time were: $5,667 for personnel and $7,500 for the social analytics solution. The outsourced company (BCF) that delivered these data used the common ROI formula: ROI ¼ ðGains CostsÞ=Costs 100 The result shows that the ROI through the company’s SM marketing strategy that year was 66 %. Accordingly, BCF trusts that SM ROI is obviously possible to be
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measured though proper measurement practises as well as clear objectives and strategy (Herrmann 2012). Despite the fact that ROI metrics have been consolidated to hard financial metrics non-financial metrics of investments are sometimes better predictors of the future than the standard accounting systems (DTTI 1994; Kaplan and Norton 1996; cited in Ittner and Larcker 1998). Hard-financial metrics need to be complemented by non-financial ones due to the SM marketing complexity. Engagement is the most important element of the non-financial ROI. Few marketers actually try to translate the benefits of engagement into hard financial return. Engagement is immediate, accessible, and appears where the audience already exists. Engagement can be effectively accomplished through several marketing actions, namely: (A) Word-of-mouth (WOM) the most productive influences in online conversations between consumers (Fogel 2010), as research showed that 90 % of consumers trust more other consumers rather than advertisements (cited in Fogel 2010), 76 % of people think that marketers lie (Athanasiou 2013), and 20–50 % of all purchasing decisions are affected by WOM; (B) reach, which is the metric that is easiest to quantify across all platforms (Kaske et al. 2012); (C) traffic, to find out where the customer came from, which SM applications customers used and finally what led the customer into the actual purchase of the product or the service; (D) customer service as the key for customer engagement strategy; and (E) brand advocates, who apart from positive recommendations about a brand through the e-WOM, they can deliver ten times (10) financial ROI.
2.2
Cost of SM Activity
The cost of a SM campaign is calculated depending on the strategy a company follows. Whether a company outsource its online marketing activities or keep them in house is of significance. In the effort to establish the rates for the creation, design, and maintenance of SM channels, the websites of the top 10 SM agencies in the UK, and in rest of the world were examined. It appeared that there are no standard rates amongst the services those agencies provide. The costs cannot be accurately defined, however they can be broken down into four basic categories: (a) staff costs; (b) external costs; (c) advertising; (d) other costs. Perdue (2010) highlights that despite costs, paying for these reputation-tracking tools can be highly beneficial as these tools can help the engagement and response in real time.
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3 Methodology Comprehensive case studies are a very productive way to expose the interaction between a phenomenon and its context (Dubois and Gadde 2002). The purposive selection of the Princess Andriana hotel was because it offers a very active presence in the online marketing area, with the use of three social media channels, as well as two social travel networks. Princess Andriana belongs to the small local hotel chain HHotels managed by the Hatzilazarou family. Furthermore, the hotel’s management were really interested in the evaluation of their efforts regards to the return on several investments they made on the promotion sector. Therefore, they granted access to confidential data and offered assistance. Through a netnographic observation, the research gained consumer insights through both qualitative and quantitative data (Kozinets 2010). The research design was split into two pathways. The first pathway reflected to quantitative web analytics research using hard financial metrics, frameworks, formulas, and figures that contributed to the evaluation the performance of the SM marketing strategy. The second pathway comprised the qualitative user engagement and reputation, by observing soft metrics that aimed to show the non-financial forms of ROI. Taking as an advantage the unlimited boundaries of data that can be collected by the netnographer (Kozinets 2010), the research proceeded with the recovery and analysis of insights data from a web analytics platform (Google Analytics), a reservation and analytics platform (WebHotelier), and a social network insights platform (Facebook). Apart from the two social travel networks, TripAdvisor and HolidayCheck, the only SM channel that was thoroughly examined was Facebook, as YouTube and Google + did not show any activity at all. The analysis process was benefited by the Facebook insights, which were compared with Google Analytics statistics. After determining the purpose of this study, the data were selected, pulled, examined, and categorized, with the help of those online analytics platforms (Table 2).
4 Findings and Analysis To understand the audience of Princess Andriana Hotel, the Google analytics account of the hotel was observed. For the year 1/12/2012–1/12/2013, the official website received 75,882 visits in total. Out of those visits, 64.5 % were new users, while the rest 35.5 % were returning users. Google analytics provides the traffic sources that show where the users came from and the type of search used (Table 3). Among those types of research, the observation focused on the social referral traffic, which presents the visits from a website that has embedded link for the hotel’s website. Facebook holds the overwhelming 93.4 % of the social referral visits to the website, and this is the reason why it is more thoroughly examined than the other SM channels.
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Table 2 The sources of the data Platform Google analytics WebHotelier
Facebook
Type of platform Web analytics Reservation and analytics
Social network
Table 3 Social referral traffic sources to Princess’s Andriana website
4.1
Type of data (metrics) Number of visits, traffic sources, referral traffic sources, visitor’s flow, conversion rates Number of referral visits, number of bookings, conversion rates, revenues from referral sources, revenues for extended examination period, number of views through social travel networks Post analysis, post reach, page likes, engagement rates (likes, shares, comments), inbox messages
1 2 3 4 5 6 7 8 9 10
Source
Number of visitors
Percentage (%)
Facebook Vkontakte Odnoklassniki Twitter TripAdvisor Google + Draugiem.lv Jappy Facebook apps goo.gr Total
2,873 91 44 21 17 13 8 5 4 2 3,080
93.30 3.00 1.40 0.70 0.60 0.40 0.30 0.20 0.10 0.10
Costs
Lewis’s (2012) proposed framework of expenditures presents the types of expenses that constitute the summary of the cost: social marketing budget, staff and technology investment (Table 4). The SM channel management for all five properties of the HHotels chain was the exclusive responsibility of one employee in the marketing department. It was impossible to estimate the exact amount of time that the employee spent on the SM channels of each hotel since it varies according to the traffic. Therefore, the calculation of the expense for each hotel was calculated by dividing the salary in five parts assuming that the employee devotes equal amount of time to each hotel’s SM activities. In addition, paid advertising on the Facebook channel was also used in the hotels’ marketing strategy. Offering a free, seven-night stay for two people as a prize, the advertisement was posted as a quiz challenge requiring the uses to like, share, and then take the quiz. This CPC approach aimed to spread the content as the post would appear on the users’ timeline and their friends’ news feed update. Finally, a booking application, powered by WebHotelier was added into the hotels’ Facebook page expecting to facilitate customers to make reservation directly through the Facebook platform, instead of transferring to the hotels’ official website.
Social Media Return on Investment and Performance Evaluation in the Hotel. . . Table 4 Hotel’s online marketing costs for 2012– 2013
4.2
247
2012–2013
Annual costs (€)
Employee (pro rata employment cost) Facebook CPC advert (April 2013) Facebook instant booking Total
3,360 74.18 200 3,634.18
Financial Return
The calculation attempt of the financial ROI started with the WebHotelier insights, which provide the reservations and sales landscape in details. Table 5 reveals that the referral traffic from the Facebook channel yielded 37 visits in total, however without any conversions. Consequently it is evident that there were no revenues coming directly from Facebook, or from the embedded in Facebook page booking platform. As a result, the formula: ROI ¼ ðGain of investment Cost of investmentÞ=Cost of investment was acknowledged unnecessary, as the data revealed that there was no direct conversions from any referral sources. Despite the fact that no revenues were found through the SM channels, Kaske et al. (2012) provides a rational explanation, “More troublesome are indirect influences, for example when a customer uses a crowdsourcing platform to obtain advice and then proceeds to buy in a physical store”. Booking arrive through an email, phone call, or simply by walk-in customers.
4.3
Non-financial Return
The non-financial return findings present the levels of engagement as a result of reach, customer service, and positive sentiment, as well as high levels of brand reputation, that emerged from the users’ interaction with the hotel’s social media platforms. According to Facebook (2014), post engagement is the number of actions related to a post as the outcome of an advertisement. Metrics such as likes, comments, shares and post clicks, are used in an algorithmic filtering for the calculation of engagement (Facebook 2014). Unfortunately, Facebook insights do not provide the total engagement rate for the period of time that the hotel is examined. Due to a range of complexities and inconsistency of the Facebook insights, it was found impossible to calculate the engagement rate by adding the engagement rate for each individual post. Thus, the research procedure moved on with the manual observation of the posts on the timeline. Those posts consist of promotional photos, customers’ photos, holidays and welcome cards, promotional videos, and charity promotions (Table 6). During the observation it was revealed
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Table 5 Bookings and conversions through Facebook
www.facebook.com www.startsiden.no www.google.es www.google.by search.sky.com hotels.sletat.ru m.facebook.com
21 21 19 19 19 19 16
0 0 0 0 0 0 0
0.00 % 0.00 % 0.00 % 0.00 % 0.00 % 0.00 % 0.00 %
Table 6 Facebook posts along with their views, likes, and shares Type of post Promotional photo Customer’s photos Holiday & welcome cards Promotional video Charity promotion Quiz Other Total
Number of posts
Average views per post
44 11 4
1,620 1,593.3 1,255.5
1 2 4 3 69
1,209 1,039.5 13,434 1,089.6 146,047
Average likes per post
Average shares per post
91.6 58 49
6.74 2.87 0.25
37 13 144 26.6 5,493
0 1 52.5 1 308
that, the posts with the higher organic average of views, likes, and shares were promotional photos posts. However, the unique action that boosted the hotels’ reach to its likers and followers of the page was the quiz post which delivered 9,941 paid reach, three times more than the organic reach (2,934). A further part of the examination of the user engagement and reputation was the user’s correspondence activity on Facebook timeline posts. Out of the 543 comments on those posts, the overpowering 75 % showed that the users commented very positive to the posts, while the staff liked every very positive, positive, and neutral comment. As a part of customer service, every query was answered in real time and in detail. Users occasionally used posts as a chat room to exchange opinions and experiences about the hotel between themselves. Negative and very negative responses were only 0.75 %. Yet, the staff managed to reverse any negative sentiment or complain that was spotted through the posts, by providing solutions or detailed and rational clarifications. Those actions minimized the negative responses from the customers by adding value to the positive ones, as the customers tented to like staff’s responses after a helpful reply. Taking into consideration all the activity for the period that the hotel was examined, and considering that the number of the fans at the end of this period was 1,810, the total engagement rate can be calculated based on Smitha’s (2013) formula:
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Engagement rate ¼ Total engagement ðlikes þ comments þ sharesÞ=total fans ¼ ð5, 493 þ 308 þ 543Þ=1, 810 ¼ 3:5 After an extended research of 500,000 Facebook pages, Leander (2013) supports that the average engagement rate of a page below 10,000 fans is 0.96 %. Furthermore Leander trusts that a satisfying engagement rate for a business should be above 1 %. In a smaller scale, Lee (2013), after a research of 5,000 Facebook pages among 168 industries, supports that the average engagement rate of a page below 10,000 fans is 6.1 %, with the minimum engagement rate being around 1.7 %. Therefore, according to the above statistics, the engagement rate of Princess Andriana hotel seems to be between medium and good levels. Customer service refers as any form of social interaction that assists meeting customers needs. The aim of customer service examination is to reveal the effectiveness of the hotel customer care. Facebook appeared to be the only SM channel that customers used to reach the hotel to place their complaints and make queries. As seen on Table 7, those private (inbox) messages were categorized depending on the content. The overall positive sentiment between the customers and the hotel through Facebook was retrieved both from the customer service support and engagement metrics. Ghali’s (2011) following formula from was chosen for the calculation: Positive sentiment ¼ ðtotal likes þ total shares þ positive comments þ positive messagesÞ=total number of posts þ total number of comments þ total number of messages ¼ 84 % As a result of the positive sentiment, the e-WOM delivered growth of the total page likes; as on December 1st of 2012 the total page likes were only 240 and after a year of online promotional operations, the hotel likes were boosted up to 1810, which is a growth of almost 655 %. Taking into further consideration the critical use of social media in relation to the brand advocacy, the netnographic research continued to the observation of the two social travel networking channels that the hotel uses as promotion tools. The findings presented a very good presence of the hotel in the Table 7 Visitors’ messages through Facebook ‘Inbox’ messages (125) Type of message
Number of messages
Percentage (%)
Positive feedback Complaints Quiz competition Price and availability Transportation and guidance Price list for spa & other services Candidates hiring Other Error Total
10 4 56 10 2 2 4 43 1 132
7.6 3.0 42.4 7.6 1.5 1.5 3.0 32.6 0.8
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social travel networks, TripAdvisor and HolidayCheck. The 390 customer reviews on TripAdvisor with overall percentage of 89 % customer satisfaction, place the hotel in the third ranking position in Kiotari, Rhodes, Greece. On HolidayCheck, Princess Andriana stands for 5.1/6 in overall rating out of 168 reviews. Furthermore it is 83 % recommended from the official website of. Princess Andriana seems to have grown a very good reputation among the online travel communities.
4.4
Further Findings
The same time that this examination was taking place the hotel’s management was investing into further marketing and sales actions for the tourist season 2014. A short observation revealed some investments as well as returns, involving the two main social travel-networking platforms that the hotel uses as promotional tools (Table 8). Due to the fact that the main period of examination 2012–2013 revealed no hard financial return, a slight extension of the examination period of nearly 2 months was considered as an immense opportunity for this research. According to Holmboe (2011), if the actual sales of a specific period are higher than the forecasted sales, then that difference can be used as the value of the SM return. During that period, there was an increase in revenues by 134.61 % (Table 10), that has to be partially attributed to the contribution of TripAdvisor and HolidayCheck. According to Table 9, paid advertising boosted the views through these two referral websites. As a result, the connection between increased views and revenues delivers possible ROI through the formula: ROI ¼ ðGain of investment Cost of investmentÞ=Cost of investment Essentially, the financial return of Princess Andriana for its online marketing campaign between 1/12/2013–27/1/2014 is estimated to be: ROI ¼ fð63, 336:28€ 8, 376:5€Þ=8, 376:5€g 100 ¼ 656:11 % Marketers can use a more simple equation to calculate the Return on Marketing Investment (ROMI). ROMI refers more specifically to marketing activities as ‘the revenue generated by a marketing program divided by the cost of that program at a given risk level’ (Powell et al. 2011). In our case, ROMI is estimated as: ROMI ¼ incremental value=marketing cost ¼ ð63, 336:28€ 26, 669:83€Þ= 8, 376:5€ ¼ 4:33 With the completion of the findings, Table 11 was generated to present the overall outcome of Princess Andriana hotel SM ROI. The table consists of the forms of ROI that were revealed, as well as the SM platforms that were used in the SM campaign for the examination periods, along with the required metrics for the measurement.
Social Media Return on Investment and Performance Evaluation in the Hotel. . . Table 8 Hotels online marketing costs for the period 2013–2014
Table 9 Increase in hotel’s website views through referral websites
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2013–2014
Annual costs (€)
TripAdvisor HolidayCheck Employee Total
3,937.50 1,079 3,360 8,376.50
1/12/2012–27/01/2013 1/12/2013–27/01/2014
TripAdvisor
HolidayCheck
0 301
0 185
Table 10 Increase in revenues after the investment in TripAdvisor & HolidayCheck Period of time
Return
1/12/2012–27/01/2013 1/12/2013–27/01/2014
26,996.83 € 63,336.28 €
Increase: 134.61 %
Table 11 The overview of princess Andriana SM ROI 2012– 2013
Platforms
Metrics
ROI
Financial
Facebook
Direct sales, Instant booking cost, Advert cost, Pro rata employment cost Visitor’s flow, Conversions through referrals Bookings through referrals, Mobile Facebook app reservations, Facebook platform reservations Overall sales, Incremental value, Social travel networks investments, Pro rata employment cost Engagement Posts, Likes, Comments, Shares, Views Reach Posts, Organic reach, Paid reach, Post reach, Total page likes Customer Messages, Post comments, service Positive sentiment Reputation Reviews, Ratings, Overall satisfaction, Ranking
ROI ¼ 0 %
Google Analytics WebHotelier
Extended period
WebHotelier
Nonfinancial
Facebook
TripAdvisor
HolidayCheck
Reputation
Reviews, Ratings, Overall satisfaction, Recommendations
ROI ¼ 656.11 % ROMI ¼ 4.33 Engagement rate ¼ 3.5 Daily engagement rate ¼ 11.05 % Positive sentiment ¼ 84 % 1,810 page fans 89 % in overall satisfaction Ranked #3 out of 13 in the region 5.1/6 in overall satisfaction 83 % recommendation from HolidayCheck
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5 Conclusions and Recommendations The main purpose of this paper was the evaluation of the ROI of SM activities using the Princess Andriana hotel in Rhodes as a case. The paper illustrates that SM ROI can be measured into two forms, financial, and non-financial. Financial ROI, the conversion rates revealed no direct revenues from Facebook. However, during the extended examination period presented financial ROI of 656.11 %, and ROMI of 4.33. The incremental value that was generated during that period is partially attributed to the positive reputation of Princess Andriana from the two social travel networks. It is clearly verified that social media can indeed generate hard revenues for a business. All promotion platforms can be utilized either as selling points, or as promotional tools. The innovative functions of the Facebook instant booking as well as the direct booking through messages, provide extra purchase potentials to the user by avoiding unnecessary transitions to other websites. In regards to non-financial ROI, the findings demonstrated very satisfying levels of engagement and brand reputation. An overall increase in popularity, especially on the Facebook page contributed to the hotels’ reputation, as Facebook stands as the most popular and multidimensional platform. Return and investment proved to have a similar positive relationship. Rationale management and correct tools can convert a high investment to high returns. Marketers should not hesitate to invest on SM channels for their online campaign. Successful marketing campaigns must not underestimate the power of SM and especially the e-WOM. Real time B2C engagement and customer service are fundamental for a dynamic presence in the online communities.
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