CREATING VALUE FROM MOBILE PHONE DATA – CASE STUDY IN THE OOH MARKET - NICK HENTHORN & MICK RIDLEY
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Nick is Commercial Director at Telefonica Dynamic Insights. He is responsible for the commercial and market development of Telefonica’s Big Data monetisation programme for the UK market. He led commercial engagement (with specific focus on the Retail and Media markets) and has helped establish Telefonica Dynamic Insights as the market leader in mobile data monetisation. Alongside the commercial development of the business, Nick is actively involved in shaping the product strategy of the business to ensure it remains at the forefront of insight services. Mick, as Head of Data & Technology for Exterion Media, Europe’s largest privately held out-of-home advertising business, is responsible for the strategic application of new and existing data sources to enhance Exterion Media’s proposition. Its core business is to engage and deliver valuable audiences for advertisers, and make ordinary journeys extraordinary for consumers.
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CREATING VALUE FROM MOBILE PHONE DATA – CASE STUDY IN THE OOH MARKET - NICK HENTHORN & MICK RIDLEY
- 1. Driving Relevance in the Outdoor Media Market Nick Henthorn Telefónica Dynamic Insights 25 November, 2015 Smart Steps_ | Mick Ridley Exterion Media
- 2. 2 Powering better decisions through insights based on real-time crowd behaviour mobile customers24million Anonymised Personal data eliminated and hashed with ID Aggregated IDs grouped to crowd data, no individual is identifiable Extrapolated Algorithms applied to represent entire population
- 3. OUR MULTIPLE REAL-TIME DATA SOURCES GIVE YOU POWERFUL INSIGHTS_ 3 Mobile Types of Data Active Passive Multiple Data Sources Behavioural Apps Websites 2 BILLION Network Events Every day 24/7 2 Years History Understanding customer behaviours consistently over time
- 4. iPhone 5S MOBILE 30 - 45 AGE 80th percentile AFFLUENCE SL6 HOME LOCATION WC1 WORK LOCATION Telegraph PRINTMEDIA Has Children LIFESTAGE Photography INTERESTS/HOBBIES Facebook, Flickr WEBSITES Paddington train REGULAR ROUTE Customer profiling whoWe can tell you who your customers are 13% 25% 29% 21% 9% 63% 80% 22% 75% 17%
- 5. 5 Customer location Insights whereWe can tell you where and how your customers move how TRAIN TO FROM WALK BIKE CAR BUS FIND OUT WHAT MODES OF TRANSPORT THEY USE, ACCURATE DWELL LOCATIONS AND JOURNEY PURPOSE
- 6. Smart Steps supports various industries 6 Transport Media Retail Viewing 100 million journeys per day to understand demand, journey type & mode of transport enables better transport planning. Understanding audience profiles enables more effective media targeting. Knowing who visits stores, how often, from where and why enables better decision making across a retail estate. Journeys Profiling Decision-Making
- 7. Understanding Behaviour_ Telefónica Dynamic Insights
- 8. From contract sign-up we know… Gender: Male Postcode sector: NG13 8 Age: 50 From operating business (O2) Device type: iPhone 5 Activity summary What we know? Name Address Phone number What we DO NOT know Mobile number represented as a persistent hashed ID #198JDgh79~mn436?kK*BZXf A typical day |
- 9. Phone pinged at 6:00am Multiple calls / texts made & received A typical day Home Mansfield Hucknall Nottingham Newark-on-Trent Crantham |
- 10. Drive 15 miles to Newark station Newark-on-Trent Station Crantham Home Phone pinged at 6:00am Multiple calls / texts made & received A typical day |
- 11. Multiple calls / texts made & received Multiple cell location updates Lose / regain connection (tunnels) Home Hucknall Nottingham Newark-on-Trent Loughboroug h Leicester Northampton Milton Keynes Luton Watford London Crantham Stamford Peterborough Huntingdon Bedford Stevenag e St Albans Kings Cross Station Newark Station Multiple cells + high speed + defined route A typical day |
- 12. Kings Cross Station (Disappears from network) London King’s Cross Office: 20 Air Street (Re-appear on network) SOHO A typical day |
- 13. Over time, we understand even more: • Commuting patterns • Affluence • Digitality (browsing and apps) • Etc. etc. So… how did the other 23,999,999 behave? |
- 14. 14 Outdoor Media Planning Decision Allocate right media for your customers Campaign success Measure
- 15. Smart Steps Success Cases 15 SMART STEPS SUPPORTING OUTDOOR MEDIA SALES. THE LONDON UNDERGROUND 1. Who flows through the network. 2. What is their traveller mission & mind-set. Understanding the London Underground customer. SOLUTION OUTCOMEPROBLEM Telefonica mobile data: Over time, we understand: ‣ Complimentary to exiting data. ‣ Enables evolution of Insights. ‣ Enables valuable story creation for marketing. ‣ Commuting patterns ‣ Affluence ‣ Digitality ‣ Etc…
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- 33. BIG DATA Big Data is an Enabler for market change in the Out of Home Media sector. TELEFONICA Telefonica will continue to innovate with mobile data to expand its application in new markets. EXTERION MEDIA Exterion Media will continue to explore the applications of mobile data insights in their business. | | Q&A SESSION |
Editor's Notes
- There are currently over 24 million O2 customers – a significant representation of the UK population. Smart Insights leverages the data created by these customers to understand the persistent behaviour of individuals over time and ultimately empower business decisions through crowd behaviour. Critically, Smart Insights protects customers’ information and data by aggregating and anonymising all information. Clients only ever see crowd and we never allow the identification of an individual . Our service is secure and protects customers’ privacy.
- The data we hoover up when creating the solution can be split into 3 core sources Mobility events arising from mobile devices and observed in our network. In-venue recognition as people enter a Smart Insights enabled site Behaviour events collected through app usage and web browsing behaviour Note that the passive mobility events are a key differentiator between us and our competition, assuring our accuracy and reliability. This creates a vast amount of rich data – we collect over 2Bn events per day from our mobile data alone, which is generated 24/7/365. In addition, we can ingest external datasets to enrich and contextualise our insights.
- Disruptive insight-led propositions Taken to market at scale Strongly supported across TEF UK
- Disruptive insight-led propositions Taken to market at scale Strongly supported across TEF UK
- Disruptive insight-led propositions Taken to market at scale Strongly supported across TEF UK
- Disruptive insight-led propositions Taken to market at scale Strongly supported across TEF UK
- Disruptive insight-led propositions Taken to market at scale Strongly supported across TEF UK
- Disruptive insight-led propositions Taken to market at scale Strongly supported across TEF UK