Expect Data Partnership between Google and Visa

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SEE LAST PAGE OF THIS REPORT Howard Mason

FOR IMPORTANT DISCLOSURES 203.901.1635

hmason@ssrllc.com

October 6, 2014

Expect Data Partnership between Google and Visa

  • As consumers shift viewing time to mobile screens, which grew 60% in 2013 to an average of 2.2 hours daily for US adults and now accounts for ~20% of total media consumption time, Google faces a challenge in its core advertising business: it is less able than in the case of online (i.e. internet activity on a desktop or laptop) to follow a consumer from search, through declaration of intent, to checkout. This is because conversion rates are lower (at 20-25% versus 60-65% for customers who start checking out online through a typical e-commerce site) and the vast majority of conversions are offline; as Jim McCarthy, head of Visa partnerships comments, Google is then largely blind: “you have got a great big physical world that they don’t see”.
  • Gibu Thomas, SVP for digital and mobile at WMT, sizes the challenge and opportunity at double e-commerce volumes: “Mobile-influenced in-store sales are double those of the entire e-commerce opportunity. By 2016, e-commerce sales are projected to get about $345bn in the US; ‘m-commerce’ sales – online sales through a mobile device – are projected to get about 10% of that number. But if you look at mobile-influenced offline sales in that same time frame, they are projected to reach more than $700bn”.
  • With lower and less track-able conversion than online ads, Google finds that “mobile does not monetize as well other forms”; this contributes to declining costs-per-click (down 6-11% from the prior year in each of the last five quarters) and the disproportionately low share, of below-4%, that mobile commands in the US advertising pie (see Chart below) despite providing context, including location, that is not available to online advertisers. Apple Pay (for iOS) and Host Card Emulation (for Android KitKat and above) can lift mobile conversion (consumers do not need to enter card credentials onto a small screen) and track-ability (consumers transact from mobile ads without leaving the screen) but the data flow to the card networks and issuing banks, not Google or Apple[1].

Chart: US Major Media Share of Viewing-Time and Ad-Spend (Source: @KPCP)

  • Google Wallet can address the issue, but lacks reach and draws Google into the relatively unattractive merchant-aggregation business (leading Visa to comment that “Google hates payments but wants the data to support the underlying business of search and advertising”). A data partnership Google and Visa can provide a more scale-able link between online search activity and offline purchases. Visa understands the value of its data assets (“we have both real-time and historic data on every off-line transaction and that off-line data is extremely valuable”) and their sensitivity (“because of the trust model, because of the brand, because of our relationships with issuers”).
  • Indeed, with large merchants concerned[2] that the payments data harvested from mobile wallets can be used against retailers who accept them, Visa has avowed “we would never expose a merchant’s volumes or data even at an aggregate level to another merchant; but we can help merchants understand how they play in a sector or geography”.
  • Integrated into search data from Google and financial information from issuers, and incorporated into analytics that drive track-able mobile advertising, Visa’s offline purchase data has the potential to help merchants address the strategic priority of competing more effectively with online merchants such as AMZN by using mobile to drive the value of loyalty programs and allowing consumers to move seamlessly between mobile, online, and store-channels. As Visa comments “that is the big differentiator and we can provide that service for issuers and merchants that don’t have the scale [to do it bilaterally]; and, for those that do [such as ChaseNet], they can still use our network to deliver the ultimate service.”

Overview

There is a meaningful and well-documented shift in media consumption towards mobile devices relative to online activity (i.e. internet activity using a desktop or laptop) and relative to traditional media such as TV. Specifically, at over 5 hours/day, US adults on average spend more time with digital media than watching TV according to e-marketer.com (see Exhibit 1 – left hand panel). Viewing-time on (non-voice) mobile activities now matches that online (i.e. internet activities on a desktop or laptop) and increased 60% in 2013 while online and TV viewing were flat-to-down. Within mobile viewing, time on smartphones and tablet is approximately equal and growing at approximately the same rate (see Exhibit 1 – right hand panel).

Exhibit 1: Average Time Spent with Major Media by US Adults

However, while mobile represents near 20% of total media consumption time, KPCB notes that it accounted in 2013 for less than 4% of the nearly $200bn in US ad-spending on media (i.e. excluding ~$90bn on direct channels such as tele-services and direct mail); the firm adds that if digital channels (i.e. online and mobile) had an ad-spend share equal to share of viewing time, it would add $30bn to the associated advertising revenue pool (see Exhibit 2). In practice, this understates the opportunity since mobile viewing time is increasing rapidly (with You-Tube reporting that that 40% of global video watch-time is on mobile) contributing to a 150% expected increase in mobile ad-spend for the US to near $18bn in 2014; the retail[3] and finance verticals are expected to account for more than one-third of the total (see Exhibit 3).

Exhibit 2: US Major Media Share of Viewing-Time and Ad-Spend

Source: @KPCB
http://s3.amazonaws.com/kpcbweb/files/85/Internet_Trends_2014_vFINAL_-_05_28_14-_PDF.pdf?1401286773

Exhibit 3: 2014 Projected US Mobile Ad Spend in $mm

Source: Mobile Advertising Trends Report 2014 by FunMobility

The Opportunity and Challenge for Google

The shift to mobile represents both opportunity and challenge for Google. The opportunity is that mobile provides location and other context that is not available on a desktop leading Nikesh Arora, Chief Business Officer, to comment that “in the medium to long term, mobile pricing has to be better than desktop pricing”. In the meantime, however, Google acknowledges that “mobile does not monetize as well as other forms” so that a mix-shift to mobile is likely contributing (along with a mix-shift overseas and particularly to emerging markets) to declines in cost-per-click (see Exhibit 4).

Exhibit 4: Google – Year-on-Year Change in Ad Revenue and Cost-Per-Click (CPC)

Part of the pricing challenge in mobile arises from relatively weak track-ability. Jim McCarthy, SVP of Innovation and Strategic Partnerships at Visa, expresses the issue as follows: “They [Google] have built a really nice business, $50 billion-ish in ad words, by effectively watching consumer behaviors from search to purchase and clickstream. So they are able to traverse the internet from the time I start a search to the time I get to a merchant and the time I check out. But they don’t really know you checked out.” In the case of e-commerce, Google can mitigate this because they “can see webpages and figure out, if you moved through a checkout and got to the end of it, you probably made a purchase”; indeed, the “enhanced campaign” program introduced by Google in February 2013 helps advertising clients measure cross-device conversions where, for example, a consumer begins a shopping journey on a mobile device but transacts online.

However, when a transaction is consummated offline, Google is largely blind: “you have got a great big physical world that they don’t see”. And purchases where some portion of a consumer’s shopping journey are on a mobile device but the payment is offline could be double e-commerce volumes as early as 2016. Gibu Thomas[4], SVP of digital and mobile at WMT, has commented: “by 2016, e-commerce sales are projected to get about $345bn in the US; ‘m-commerce’ sales – online sales through a mobile device – are projected to get about 10% of that number. But if you look at mobile-influenced offline sales in that same time frame, they are projected to reach more than $700bn”.

The Role of Visa

Google Wallet can address the issue, but lacks reach and draws Google into the relatively unattractive merchant-aggregation business (leading Visa to comment that “Google hates payments but wants the data to support the underlying business of search and advertising”). On the other hand, a data partnership Google and Visa can provide a scale-able link between online search activity and offline purchases. Visa understands the value of its data assets (“we have both real-time and historic data on every off-line transaction and that off-line data is extremely valuable”) and their sensitivity (“because of the trust model, because of the brand, because of our relationships with issuers”).

While retailers may be leery of a data partnership between Visa and Google, and have been explicit about concerns[5] that the payments data harvested from mobile wallets can be used against retailers who accept them, Visa has avowed “we would never expose a merchant’s volumes or data even at an aggregate level to another merchant; but we can help merchants understand how they play in a sector or geography”. Furthermore, integrated into search data from Google and financial information from issuers, and incorporated into analytics that drive track-able mobile advertising, Visa’s offline purchase data has the potential to help merchants address a strategic imperative: competing more effectively with online merchants such as AMZN by using mobile to drive the value of loyalty programs and allow consumers to move seamlessly between mobile, online, and store-channels.

A data partnership with Google could give Visa increased protection against disintermediation from bilateral connects between large issuers and retailers, and the merchant-driven consortium, MCX. Of course, large issuers and retailers can form their own data partnerships with Google, but this can become unwieldy for more merchants in general. As Visa has commented “we can provide that [data analytics] service for issuers and merchants that don’t have the scale to do it [bilaterally] which are most in this country; and, for those that do [such as ChaseNet], they can still use our network to deliver the ultimate service”. Finally, with merchant consent, Visa’s network “has the capability to capture SKU-level data and add that to the series of data and analytic services we can provide, and while management acknowledges “there are going to be examples of private label programs that succeed because they have a unique value proposition and can link it to offers” they are positioning to work with existing issuers and the “broad base of merchants” to offer the best value proposition.

“Big Data is Pretty Easy”

In the above remark, Charles Horn, CFO of ADS, may be underplaying the analytic challenge of translating payments data into targeted and relevant loyalty offers, but direct access to payments data is likely preferable to the inferential techniques Google will need to estimate mobile conversion rates if it does not partner with the payments industry. Indeed, payments players probably have the stronger hand having demonstrated success in enabling merchant-loyalty programs without access to search data.

In short, access to payments data may be a more important success factor than sophisticated analytics (see Exhibit 5). As Ed Heffernan, CEO of ADS, comments: “That type of information is the gold standard that’s out there is the ability to link SKU [i.e. first-party transactional data at the stock-keeping unit or SKU level] with who the customer is [i.e. personally-identifying information or PII]”.

Exhibit 5: Payments Personalization

  1. For offline payments, Apple Pay and HCE can no more capture the transaction data than can the manufacturer of physical plastic; this is a key reason the card networks supported these solutions and qualified them as EMV-compliant.
  2. http://www.paymentssource.com/news/walmart-other-retailers-on-why-mcx-can-beat-rival-mobile-wallets-3012969-1.html
  3. Within retail, three verticals account for 80% of retail mobile ad spend: big box stores at 33%; clothing and apparel at 29%; and home & garden at 20%.
  4. http://www.theatlantic.com/magazine/archive/2014/03/get-ready-to-roboshop/357569/?single_page=true
  5. http://www.paymentssource.com/news/walmart-other-retailers-on-why-mcx-can-beat-rival-mobile-wallets-3012969-1.html
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