mobile attribution modeling - open analytics nyc
Post on 12-May-2015
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The Channel-less Consumer
TALK ABOUT US USING
#FUTUREM
Identifying Attribution within Mobile
Michael KaushanskyAnalytics and Insights, Havas Media, michael.kaushansky@havasmedia.com@kaushansky
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New Approach to Consumer Centric Modeling
• Deterioration in key performance metrics (leads & sales)
• We looked for answers: why wasn’t our existing media mix working? Why wasn’t TV, search and display across screens generating the same volume of leads?
• Simulations of existing media mix models pointed to a shift to digital though unclear where. Current models were not reflective of emerging trends in media.
Our global Auto client had experienced a recent deteriorating trend
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• Click to edit Master text styles– Second level
• Third level– Fourth level
» Fifth level
Media Consumption
The Path to Purchase
The Role of the Consumer Consumer Expectations
What we experienced was a shift in marketing dynamics
Adding to the shift - the emergence of the multi-channel marketplace
2 explosive and complementary markets Local Advertising: $35B in 2015
Mobile Commerce: $39B in 2016
Location, Location, Location 70% of mobile revenue tied to location by
2015 40% of mobile search has local intent
1) BIA/Kelsey, U.S. Local Media Forecast, 03/20122) eMarketer, US Mobile Commerce Forecast: Capitalizing On Consumers’ Urgent Needs, 01/20123) Forrester Report, US Online Sales Forecast, 20094) BIA/Kelsey, U.S. Local Media Annual Forecast (2010-2015), 06/2011
Cross Channel Shopping will be 6X of Online Retail alone
Source: Paypal Media Network
Multi-channel brings a new complexity to the purchase funnel
Source: Paypal Media Network
Nearly 1/3 of retailers credited smartphones with driving traffic to physical stores in 2011, up from 1/5 in 2010-Retail Systems Research, ‘The 21st Century Store: The Search for Relevance”, 6/2011
15% of US online shoppers made a holiday purchase via their mobile, growing 3X over Holiday 2010- Baynote, ‘2nd Annual Baynote Holiday Shopping Survey’, 1/2012- IBM, ‘Benchmark December holiday report’, 1/2012
The purchase funnel becomes… the purchase pretzel
Source: Paypal Media Network
Existing model failed to identify the shift towards digital
Investment
Sales
BlackBox
Consumer journey is unique
Journey metrics are essential to understand the impact of media
Our objective was clear…update the model! Enhance our existing model to address the
unexpected digital shift
Approach – divided the journey into stages, defined success metrics across each stage & linked the metrics to show progression throughout the journey
Methodology – developed 4 models which explained key drivers at each stage, i.e. what drove search, site traffic, leads and sales
Of Course it will work
We modeled the consumer journey across the 5 stages
Stage Success Metric
Awareness Organic Branded Search
Engagement Page Views
Consideration Digital Leads
Shopping Showroom Traffic
Purchase Unit Sales
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Consumer Stages
Awareness
Engagement
Consideration
Shopping
Purchase
Hierarchical Modeling explained impact at each stage
4 Independent ECONOMETRIC Models
Known Strong Existing Correlation
Media Mix
TVPrintOOHDisplaySearchMobileOnline videoPaid socialSocial
We identified 12+ data sources across 52 weeks
Structured Equation
Source Data Begins Timing Data Descriptions Metrics Available
Digital Media (DFA) 2009 daily actual media spend by channel (OLA, SEM) impressions, clicks, hvtsKantar Evaliant 2010 weekly competitor web impressions and spend impressions, spendKantar Stradegy 2011 weekly offl ine GRP & spend GRP, spend
Sysomos 2009 weekly social media buzz data buzz volume, sentimentHitwise/Compete last year daily site visitation and duration visitation, duration
Google Insights 2004 daily total search trends (paid & organic) search trend indexAutodata/Wards 2008 monthly monthly sales data by brand/model/category sales figures
Google Analytics/ Omniture 2009 daily Website/model/configurator/RFQ pageviews visits, configs, RFQ, Model PVHarte-Hanks 2001 weekly owners, prospects, email/mail campaign, etc.
Urban Science 2009 weekly leads by channel by week leadsManufacturer 2009 weekly dealer visits dealer visits
Third Party Sites 2009 monthly Comp model PV, day/week/month model pageviewsBrand Tracker 2010 Semi attitudinal data by month consideration, intent
Census 2000 monthly economic data by Geo economic data
Yt= α + β1Mt + β2Et + β3St + β4Tt + εt, Y (represents the dependent variable, e.g.,sales)M (media), E (engagement), S (searches), T (store traffic), etc.
Results
As suspected… results pointed media consumption varying at each stage
We identified 5 key insights
1. Brand equity dominates & TV is king of paid (36% contribution from TV)Stage
Awareness
Engagement
Consideration
Shopping
Purchase
2. More channels at play in driving site traffic, digital media is the workhorse (33% contribution)
Stage
Awareness
Engagement
Consideration
Shopping
Purchase
3. Paid Search was essential in driving leads influenced by DRTV (paid/Mobile search + DRTV @ 46%)
Stage
Awareness
Engagement
Consideration
Shopping
Purchase
4. Leads were the most significant driver of showroom traffic (40% contribution)
Stage
Awareness
Engagement
Consideration
Shopping
Purchase
5. Showroom traffic was the best proxy of units sales
Stage
Awareness
Engagement
Consideration
Shopping
Purchase
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Show-rooming was responsible for 82% of sales
Sale
s U
nits
Unit Sales
Showroom Traffic
Moving the consumer further down journey increasingly relies on paid media
Awareness
Engagement
Consideration
Shopping
0%20%40%60%80%
100%
MediaBase
1 2 3 4 5 sales
The new models made our simulations more true-to-life… (what-if scenarios) identified dimensioning returns & ROI
What we’ve learned…
1. Consistently / frequently assess the journey of your consumers
2. Digital media is significant in the middle of the journey
3. Mobile’s role was stronger than previously thought
4. Promotional messaging is effective if consistent at each stage
5. Exogenous data (weather & holidays) have minimal impact
6. Going dark beyond 5-weeks would be detrimental
7. Optimizing media at each stage points to a 12% improvement
Ramifications and things you should consider
Do Your HomeworkDetermine consumer behavior by stage/funnelWeight social influence along journey
Set up for measurement successEstablish KPIs along purchase pathCRM listsPaid, owned and earned media
Unify 3 screensCreative + MediaMerge screen identifiers and interactions
Crunch dataWhat does it tell you?Weight activity against conversion contributionOptimize accordingly
Future ConsiderationWeight social influence along the journeyInvest in approach & tech to unify screens
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