5 Trends Driving Location Targeted Mobile Advertising. Mike Boland Chief Analyst & VP, Content BIA/Kelsey

Transcription

1 5 Trends Driving Location Targeted Mobile Advertising Mike Boland Chief Analyst & VP, Content BIA/Kelsey Mobile Research Summit June 19, 2014

2 5 Trends Driving Location Targeted Mobile Advertising 1. Mobile: By The Numbers 2. Will Local Save the Day? 3. It s an Offline World 4. Search, Discovery & Big Data 5. Payments: The Ultimate Attribution

3 5 Trends Driving Location Targeted Mobile Advertising 1. Mobile: By The Numbers 2. Will Local Save the Day? 3. It s an Offline World 4. Search, Discovery & Big Data 5. Payments: The Ultimate Attribution

4 Let s Start with Mobile Usage: Where are we now?

5 Mobile Usage: Where are we now? U.S. Smartphone penetration = 72% 25% of search query volume is mobile 50% of mobile search is local Compares to 20% on Desktop 300, , , , , ,450 63% Smartphone Count 213,840 72% 239,200 80% Share of Mobile Phones 261,000 87% 276,000 92% 50, Source: BIA/Kelsey

6 (BUT: Ad dollars haven t kept pace.)

7 Media Share of Usage vs. Share of Ad Dollars Source: KPCB Internet Trends Report

8 Oversupply of Inventory = Undervalued Ads

9 Sure Enough Source: KPCB 9.

10 5 Trends Driving Location Targeted Mobile Advertising 1. Mobile: By The Numbers 2. Will Local Save the Day? 3. It s an Offline World 4. Search, Discovery & Big Data 5. Payments: The Ultimate Attribution

11 US$ Billions Location Based Mobile Ads Take Over $35 Non-location Targeted Location Targeted $30 $25.47 $30.30 $25 $20 $15 $11.43 $16.08 $7.03 $20.26 $9.22 $12.52 $ % $10 $5 $0 $7.22 $4.54 $12.95 $14.56 $ % $11.05 $9.05 $6.88 $ Source: BIA/Kelsey (See more of the forecast) 11.

12 Mobile Engagement = Local Intent

13 Daily Device Use for Offline Shopping Share of smartphone and tablet users who use their devices daily to qualify local offline purchase decisions Source: BIA/Kelsey s Consumer Commerce Monitor 13.

14 Mobile Search Is Highly Local Source: Google 14.

15 And Quickly Source: Google 15.

16 The Lesson: Capture that local intent. (But How?)

17 The Many Flavors of Location Targeting

18 And It s Actually Working Source: Verve Mobile 18.

19 Case Study: xad and Columbia Source: xad 19.

20 Case Study: Scion 40% lift in CTR with SmartFence 120% lift in SAR with SmartFence 0.50% 0.45% 0.40% 0.35% 0.30% 0.25% 0.20% 0.15% 0.10% 0.05% 0.00% 0.45% SmartFence 0.32% GeoFence 3.00% 2.50% 2.00% 1.50% 1.00% 0.50% 0.00% Source: xad 2.78% SmartFence 1.27% GeoFence 20 SAR = Secondary Action Rate which includes calls, map, directions and details

21 PSA: The Dark Side of Location Thinknear Location Score Index The mobile industry scored 49 out of 100 for location accuracy 67 percent of industry ad requests included latitude and longitude data 34 percent of those were accurate within 100 meters of users true location Culprit: Ad networks that claim lat-long accuracy but really infer it from blunt tactics When advertisers use accurate location data, store visits increase (51 percent). Takeaway: Make sure location targeting promised by networks or exchanges is accurate. Ask about their source and methodology. (See our recent podcast) 21.

22 5 Trends Driving Location Targeted Mobile Advertising 1. Mobile: By The Numbers 2. Will Local Save the Day? 3. It s an Offline World 4. Search, Discovery & Big Data 5. Payments: The Ultimate Attribution

23 6.2% (Retail Spending that is e-commerce)

24 e-commerce Share of Retail Sales Source: U.S. Census Bureau 24.

25 But It s Increasingly Influenced Online and in Mobile $4,000 $3,500 U.S. $ Billions $3,000 $2,500 $2,000 $1,672 $1,723 $1,741 $1,771 $1,780 $1,812 $1,500 $1,000 $500 $0 $1,103 $1,206 $1,320 $1,429 $1,552 $1,660 $202 $226 $252 $278 $304 $ Pure Online Online to Offline Pure Offline Source: Forrester

26 The Lesson: Stop Looking at the World in Clicks & Online Conversions.

27 The Tyranny of the Click Measuring clicks in some cases provides a faulty picture of a campaigns effectiveness at driving actual sales. Source: Placed 27.

28 Case Study Launch Movie 28.

29 Offline Attribution is the Name of the Game Measuring Conversion data post-ad exposure (several methodologies) Extrapolating performance via adexposed control groups (PlaceIQ) Linking sales and ad exposure through census household data (Neustar) Direct conversion data via credit card linked systems (Datalogix, Facebook) Tracking opt-in panel groups (Placed) (See our recent white paper) 29.

30 Case Study 30.

31 Traditional Geo-Fencing JCP Store Locations in NYC 31.

32 Geo-Fencing on Steroids JCP Store Locations in NYC Placed Targeting Reach Based on Behavioral Data 32.

33 5 Trends Driving Location Targeted Mobile Advertising 1. Mobile: By The Numbers 2. Will Local Save the Day? 3. It s an Offline World 4. Search, Discovery & Big Data 5. Payments: The Ultimate Attribution

34 The Age of Big Data Brings Predictive Modeling To Mobile.

35 Case Study: Google Now

36 Enter Push Alerts 1 million apps has led to app fatigue High abandonment rates (See our recent webinar) Highest valuations in today s app environment go to those that incite active daily usage (i.e. Snapchat, WhatsApp). Compels strategy to meet users half way (push) 36.

37 UI and Content Delivery are Transforming Search replaced by discovery; Serps replaced by cards. Card swiping: natural to humans opposable thumbs Invites easy interaction and therefore more inputs by which to model behavior and personalization

38 5 Trends Driving Location Targeted Mobile Advertising 1. Mobile: By The Numbers 2. Will Local Save the Day? 3. It s an Offline World 4. Search, Discovery & Big Data 5. Payments: The Ultimate Attribution

39 Mobile Payments Will Tie it All Together Closing the loop on conversions is advertising s holy grail (cue overplayed John Wanamaker quote ) BUT Mobile payments are nascent, experimental & fragmented Winners will be those that can build network effect from installed base of billing relationships (Amazon, Apple) (See our recent white paper) 39.

40 The Biggest Fail Factor in Tech: Solutions in Search of Problems

41 If it Ain t Broke We keep forgetting that paying with cash or card ain t broke Winners in mobile payments will solve true pain points Pain points: Don t Include: My wallet is heavy by the atomic weight of a credit card. Include: waiting in line, forgetting what I bought last time, saving receipts Examples of a Solved Pain Points: 41.

42 The Future of Offline Payments: Apple itunes to purchase physical goods Scan UPC, pay with itunes, go on your way (already in Apple Stores). Next step: take it to third party retailers. Imagine at IKEA: Scan items via iphone, pay via itunes, skip the line (ibeacon navigates the IKEA maze). Could transform store layouts, avoid bottlenecks (checkout aisle), increase basket size, and optimize operations. (More analysis here) 42.

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