EFTA01378007.pdf

previously would have been likely to sign up for those products using the desktop. As a result. as the mobile migration has been rapidly underway. we have seen our overall conversion rates challenged in those businesses. However. we expect to see this trend reverse itself for two reasons. First, the migration to mobile will either slow rapidly or end as mobile devices obtain a more stable level of penetration within the population. Second. we expect to be able to make significant product improvements to our mobile products over the coming years. driving meaningful conversion increases. Our mobile products are relatively earty In their development stages, as we only began to devote meaningful resources to optimizing these products In the last two years; in contrast, we have focused on optimizing our desktop products for increased conversion for many years. For example, during the period between January 1. 2008 and December 31, 2013, we Increased conversion on our Match product In the United States by more than 50% (when comparing desktop users coming in through direct domain channels, which we believe is the purest way to isolate the relationship between product changes and conversion improvements): those improvements came after more than 10 years of that product's existence (as opposed to the relatively short history of our mobile products). Therefore, based on our prior experience with product improvement, and the finite nature of the mobile migration, we believe the conversion challenges we have been facing as a result of the rapid mobile migration in these businesses will level off and then reverse. 64 Table of Contents Lower cost users. All of our brands rely on word-of-mouth, or free, customer acquisition to varying degrees. Word-of-mouth acquisition is typically a function of scale (with larger communities driving greater numbers of referrals). youthfulness (with the viral effect being more pronounced in younger populations due, in part, to a significantly higher concentration of single people in any given social circle) and monetization rate (with people generally more likely to talk openly about using dating products that are less heavily monetized). Additionally, some, but not all, of our brands spend meaningfully on paid marketing. Accordingly, the average amount we spend to acquire a user differs significantly across brands based in large part on each brand's mil( of paid and free acquisition channels. As our mix has shifted toward younger users, our mbc of acquisition channels has shifted toward free channels. driving a decline of approximately 50% since 2011 in the average amount we spend to acquire a new user across our portfolio. Our costs of acquiring paid members has also declined meaningfully. For the nine months ended September 30. 2015, our advertising spend per first time subscriber declined 25% (excluding the effects of foreign exchange) from the nine months ended September 30, 2013. We expect the dynamics that have led to the growth in word-of-mouth customer acquisition to continue going forward and for our brands to continue to acquire significant numbers of users through low-cost means. Mix-driven decline In consolidated ARPPU. Tinder. OkCupid. Plenty0IFish and Twoo all have a lower average revenue per paid user, or ARPPU, than our other brands. ARPPU for these brands was approximately 50% of the aggregate ARPPU of our other brands for the nine months ended September 30, 2015. As the number of paid members from the lower ARPPU brands has become an increasingly large percentage of our aggregate number of paid members, our overall or consolidated ARPPU has declined. For example, pro forma for Plenty0fFish, our consolidated ARPPU for the quarter ended September 30. 2015 was 9% lower compared to the first quarter of 2013 (excluding the effects of foreign exchange). However, within many of our significant brands individually, ARPPU is increasing. For example. for the quarter ended September 30. 2015, as compared to the quarter ended March 31, 2013 (excluding the effects of foreign exchange), ARPPU was approximately 5% higher at Match North America, 4% higher at our affinity brands, 7% higher at Meetic, 5% higher at OkCupid and 10% higher (comparing the quarter ended June 30. 2015 to the quarter ended March 31. 2013) at PlentyOfFish. Additionally, the decline in ARPPU has coincided with the decline in the cost of acquiring new users discussed above. Although brand mix shift is reducing consolidated ARPPU, we see continued ability to increase price at many of our brands. In the third quarter of 2015, prices at Match North America, Meetic, affinity brands, (*Cupid. and Twoo were higher than they were in the comparable period a year earlier. For purposes of this paragraph, references to "Mettle include Meetic and all of our other brands and businesses in Europe. Younger users. Over the last few years, while user growth in all age cohorts has continued, we have seen a significant acceleration of our growth in younger users. This, in part, correlates to the increase in mobile adoption and the brand mix shift toward Tinder and OkCupid, each of which tend to attract younger users. As of December 31, 2011. 36% of our users were under age 35, and by September 30, 2015, that percentage had grown to 62%. We view this significant increase in younger users as a positive indicator of future growth, given the significantly greater duration we have to potentially engage these users within our portfolio and convert them to paying members. Changing paid acquisition dynamics. Even as our acquisition of lower cost users increases. paid acquisition of users remains an important driver of our business. The channels through which we market our brands are always evolving, but we are currently in a period of rapid change as W and video consumption pattems evolve and intemet consumption shifts from desktop to mobile devices. However, advertising opportunities have not kept up with audience migration, putting pressure on our paid marketing activities. Recently. we have been able to increase our marketing spend despite these trends, and to bring down the costs of acquiring new users to our products through our paid channels. However. 65 Table of Contents our increases in spend have generally been made in less effective channels, bringing in lower converting users. We believe that advertising opportunities will increasingly follow consumer usage patterns, and that as this occurs, and as we improve our expertise at exploiting these evolving marketing channels, we will be able to increase our marketing efficiency over time. Other factors affecting the comparability of our results Advertising spend. Our advertising spend. which is included in our selling and marketing expense, has consistently been our largest operating expense. In recent periods. we have focused our adverting spend on display, mobile, television and search channels. We seek to optimize for total return on advertising spend by frequently analyzing and adjusting this spend through numerous campaigns to focus on marketing channels and markets that generate a high return. Our data-driven approach provides us the flexibility to scale and optimize our advertising spend. We spend marketing dollars against an expected lifetime value of a customer that Is realized by us over a mufti-year period; and while this marketing is intended to be profitable on that basis, it is nearly always negative during the period in which the expense is incurred. Accordingly, our operating results, in particular our profit measures, for a particular period may be meaningfully impacted by the timing, size, number or effectiveness of our advertising campaigns In that period. Additionally, advertising spend is typically higher during the first quarter of our fiscal year, and lower during the fourth quarter. See --Seasonality' Seasonality. Historically, our Dating business has expenenced seasonal fluctuations In quarterly operating results, particularly with respect to our profit hap: wee, tec.gov An:laves eds.,' daW1575189,00010,47469150031B,112226453"-13.10001( 9,70139:27:17 AM] CONFIDENTIAL - PURSUANT TO FED. R. CRIM. P. 6(e) DB-SDNY-0075167 CONFIDENTIAL SONY GM_00221351 EFTA01378007