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Collecting information: routes planning
Collecting information: routes planning
Information gathering: maps preparation for inspection
Information gathering: maps preparation for inspection
Information gathering: maps preparation
Information gathering: maps preparation
OOH sites in Moscow
OOH sites in Moscow
OOH sites in Moscow
OOH sites in Moscow
OOH sites in Moscow
OOH sites in Moscow
OOH sites in Moscow
OOH sites in Moscow
OOH sites in Moscow
OOH sites in Moscow
Library of posters
Library of posters
ODA-Stat Program
ODA-Stat Program
ODA-Stat: selection of cities and period for analysis
ODA-Stat: selection of cities and period for analysis
ODA-Stat: statistical analysis (address programs)
ODA-Stat: statistical analysis (address programs)
ODA-Stat: creation of address program with given criteria and filters
ODA-Stat: creation of address program with given criteria and filters
ODA-Stat: selection of criteria and symbols for mapping
ODA-Stat: selection of criteria and symbols for mapping
Ex
Ex
Detailed map
Detailed map
Ex
Ex
Short-term into daily traffic flows recalculation system
Short-term into daily traffic flows recalculation system
Vehicular Traffic Volumes Estimation
Vehicular Traffic Volumes Estimation
Model of Pedestrian Flows: Moscow
Model of Pedestrian Flows: Moscow
Public Transit Routes
Public Transit Routes
Public Transit Routes
Public Transit Routes
GIS Capabilities: overlaying geocoded databases
GIS Capabilities: overlaying geocoded databases
GIS Capabilities: overlaying geocoded databases
GIS Capabilities: overlaying geocoded databases
Use of modeling for geometric visibility parameters
Use of modeling for geometric visibility parameters
Visibility factors and reduction coefficients (3 х 6m billboards)
Visibility factors and reduction coefficients (3 х 6m billboards)
ODA-View
ODA-View
Transportation network (graph) and residential areas Newtonian gravity
Transportation network (graph) and residential areas Newtonian gravity
ODA-Plan
ODA-Plan
25 faces: evenly distributed campaign throughout a city
25 faces: evenly distributed campaign throughout a city
Daily reach and frequency (even distribution, R(1+ ) = 20
Daily reach and frequency (even distribution, R(1+ ) = 20
Reach and frequency - 25 evenly distributed ad faces
Reach and frequency - 25 evenly distributed ad faces
Reach and frequency - 25 evenly distributed ad faces
Reach and frequency - 25 evenly distributed ad faces
Reach and frequency - 25 evenly distributed ad faces
Reach and frequency - 25 evenly distributed ad faces
Poster awareness studies (Poster Track)
Poster awareness studies (Poster Track)
Poster awareness research
Poster awareness research
Google Earth space images and outdoor sites in Moscow
Google Earth space images and outdoor sites in Moscow
OOH sites in Moscow
OOH sites in Moscow
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ESPAR - Analyst

содержание презентации «ESPAR - Analyst.ppt»
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1ESPAR - Analyst Evaluation of Sites 31Model of Pedestrian Flows: Moscow.
and Poster Audience Research Credential 32Public Transit Routes.
Presentation March 2007. 33Potential audience measurement.
2ESPAR-Analyst. Established in 1992 by Audience composition: people in cars,
a group of Moscow State University public transport passengers, pedestrians
geographers and cartographers (“Analyst”) People in cars = number of cars x 1.5
Since 1996 – “ESPAR-Analyst” - (average car occupancy) Public transport:
specializing in outdoor research. official data on intervals, mapping of
3Types of research provided. Outdoor routes, x coefficient 20 Pedestrians
advertising monthly monitoring Based on measurements (evaluations) for each site.
geographical-informational systems (GIS) 34GIS Capabilities: overlaying geocoded
OOH potential audience measurement databases.
(evaluation) for individual sites 35OTS estimation. Identification of
Estimation of key media indicators (reach “effective” traffic directions for every
/ frequency) of advertising campaigns OOH face of OOH site (up to 3 directions on a
posters awareness research. cross road) and traffic volumes Visibility
4ESPAR outdoor research concept. factors estimation for every face, for
5I. OOH monitoring on GIS basis. Dec every “effective” traffic direction Use of
1996 - Moscow Aug 1997 - St. Petersburg visibility factors for coefficients,
Jul 1999 - other 1mln+cities (12) Dec 2000 decreasing OTS (similar to OSCAR system in
- 32 cities Jul 2001 – 50 cities 180 000 UK).
ad faces are covered (sizes 1.2x1.8+) 36Use of modeling for geometric
Represent about 80% of all OOH sites in visibility parameters.
Russia. 37Visibility factors and reduction
6Key monitoring objective – make OOH coefficients (3 х 6m billboards). Clutter
advertising transparent. OOH ad volumes (other faces in visibility range).
(ad spend, brands, advertisers, product Visibility range. Angle. Visibility
categories) – together with TNS/Gallup obstacles. Accentricity. Distance to
AdFact OOH media environment – street lights. Height. Illumination.
classification of formats, locations, 38Calculation of Rating for ad face.
suppliers/sites owners Creation of single Gross audience x visibility factors =
database for media planning possibility effective potential daily audience (OTS)
(unification of all sites IDs) OOH media rating (GRP) = OTS / market population
clutter analysis. (18+) * 100 current ESPAR database has
7Methodology. 1. Development of evaluations for over 100,000 3х6 m faces
detailed electronic maps of cities (GIS) - in 40 cities of russia.
Exact link of a site to geo point within a 39Integration of maps, detailed plans,
city – basis for monitoring 2. Routes photos and evaluation data Preparation of
planning to cover city territory 3. Key sample from evaluated address programs
data gathering method – visual monthly Preparation of ad sites passports
inspections of all site locations 4. Preparation of presentational materials.
Development of unique coding (IDs) system Software for providing of evaluation data
and site classification 5. Development of – ODA-View.
system of catalogs of brands, product 40ODA-View. Daily audience (000).
categories, advertisers – joint database Monthly audience. GRP (18+). Site owner.
with TNS Gallup 6. Preparation of photo Format type. Number of faces. Size. Face.
libraries of posters (Moscow, SPb) 7. Transport position. Direct road segment.
Supply information in consumer required Cost per month.
format – possibility for both statistical 41III. Evaluation of campaign
analysis and mapping capabilities distribution (R&F modeling).
(ODA-Stat). 42GRP, Reach, Frequency. Basic formula
8Collecting information: routes GRP = Reach (1+) * Frequency Campaign GRP
planning. is a sum of ratings of all evaluated sites
9Information gathering: maps in address programs Average frequency is
preparation for inspection. calculated based on modeled daily movement
10Information gathering: maps of audience within a city Development of
preparation. transportation simulation models for major
11OOH sites in Moscow. cities to evaluate duplication of
12OOH sites in Moscow. contacts.
13OOH sites in Moscow. 43Computer City Maps (GIS).
14OOH sites in Moscow. ESPAR-Analyst Research in Outdoor Concept.
15Library of posters. Competitive Advertising Volumes Data.
16Methodology: key indicators Inventory Location Data. Monthly
registered. 1. Unique ID 2. Address 3. Monitoring (ODA-Stat). Math Models for OOH
Type of display 4. Size 5. Site owner 6. Campaigns (ODA-Plan). Site Evaluation
Average estimated market price 7. Brand (Ratings). City Traffic Flows Models.
advertised 8. Product category / service Population Census Data. Travel Surveys.
type 9. Advertiser. Poster Recognition Tracking. GRPs, Reach,
17ODA-Stat Program. Frequency etc. Traffic and Pedestrian
18ODA-Stat: selection of cities and Counts. Visibility Factors Model.
period for analysis. 44Transportation network (graph) and
19ODA-Stat: statistical analysis residential areas Newtonian gravity models
(address programs). for evaluating daily travel Simulation
20ODA-Stat: creation of address program modeling of Origin and Destination of
with given criteria and filters. daily trips.
21ODA-Stat: selection of criteria and 45Estimation of daily reach and
symbols for mapping. frequency: ODA-Plan. Program is based on
22Ex.: Moscow, march 2004, 3 х 6 traffic flows modeling Objective: planning
billboards. Advertisers, selected for and evaluation of OOH campaigns Daily
analysis (mobile operators). reach / frequency measurements for OOH
23Detailed map. campaigns Work with evaluated individual
24Ex.: Chelyabinsk, march 2004, 3 х 6 sites.
billboards. 46ODA-Plan. Address program creation.
25II. OOH potential audience measurement 4725 faces: evenly distributed campaign
(Site Evaluation). throughout a city.
26“Of all the major media, Outdoor is by 48Daily reach and frequency (even
far the most difficult to research.” Chris distribution, R(1+ ) = 20.3 F = 1.3).
Dickens, Former chairman, POSTAR. 49Duration of OOH campaign factor
27General approach to measurement: evaluation. Industrial standard in OOH in
Vehicular and Pedestrians flows x USA and Canada: Gallup Math Model –
Visibility factors of each ad face = evaluation of reach and average frequency
Potential audience (OTS – Opportunity to for campaign Frequency = (sum of daily
See). GRP’s x number of days)/100 + K (K = 2 to
28Traffic counts. Combination of 6) Reach = (sum of daily GRP’s x number of
long-term and short-term measurements days)/frequency.
Long-term (during a day) at key spots – 50Reach and frequency - 25 evenly
opportunity to identify typical daily distributed ad faces.
curves of traffic flows Short-term (10 min 51Additional functions of campaigns
in rush hours) – opportunity to estimate evaluaiton. Analysis of address program
flows for road segments Recalculation of split between municipality districts
short-term counts into daily volumes, Proximity Analysis – targeting
based on typical daily cycles (math opportunities (HORECAs, schools, etc)
coefficients recalculation system). User-friendly interface, allowing to
29Short-term into daily traffic flows prepare presentation materials for each
recalculation system (coefficients). address program.
30Vehicular Traffic Volumes Estimation. 52Poster awareness studies (Poster
Identify segments of roads with constant Track).
traffic volumes (from cross road to cross 53Poster awareness research.
road) Classification, IDs and coding of 54Moscow “norms” for 3x6 campaigns.
road segments 10 min measurements for 55Google Earth space images and outdoor
every flow direction Data processing, sites in Moscow.
recalculation into daily flows Traffic 56OOH sites in Moscow.
volumes mapping as a method of data 57Thank you for your time!
control.
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ESPAR - Analyst

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