This week for our Google Marketing Platform Sydney meetup we talked about Omnichannel Marketing with Google. In this post we'll cover What You Need to Know about OmniChannel Marketing presented by Richard Johnson, Omni-channel & Measurement Products Lead at Google. You'll learn: *What 'Omni' is and how trends are changing especially in bricks/mortar environments *Measurement aspects from the Google side, and how they work (especially store visits) *Omnibidding and store visits in Search Ads 360 *New reporting capabilities based on this data *How to leverage and take advantage of the data through changing strategies, new products, omnibidding, etc.

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Omnichannel & Footfall with Google
Online to Offline

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● How Google thinks about Omnichannel
● How Store Visits works
● Bridging the value gap
● Omnichannel bidding
● Local Area Marketing
Agenda

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How do advertisers think about their Omnichannel
customers?
Buys online
Buys online or
in a store
Buys in a store

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How is the market shifting
Footfall is down, but conversion rates tend to be up. Online research & offline sales are crucial
↑
AU retailers also reporting a
rise in conversion rate
↓
AU retailers reporting a
decline in footfall
Source: McKinsey/NADA, 2016

5. of all retail sales still
take place in-store
of non-grocery retail sales
are expected to be digitally
influenced this year
>90% 58%
Source: 2016 Internet Retailer Top 1000 & Forrester (US)

6. These consumers are
+40%
more valuable
+25%
more likely to make in-store purchase
+10%
more spent on average
Source: Google data, US

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Our approach to omnichannel
Traffic-based
measurement. Click
traffic the primary
measurement. More
= better. Limited
qualifiers (good vs
bad)
Actions not traffic.
Enabled Cost Per
Action (CPA / CPL /
CPQ etc). Aligned to a
clear outcome but
limited value definition
within each action
category (are all ‘leads’
equal?)
Aligned to actual
business revenues
(distinct values per
event). Enables ROAS,
COS, ROI strategies -
more aligned with
business success than
Conversions or Clicks.
FOUNDATION : Effective Measurement
Everything starts with Measurement
Click Tracking
Conversion Tracking
Revenue Tracking
Offline tracking
Online Tracking Solutions
Bridging Online & Offline
Store visit tracking (based on
device GPS / Wifi triangulation)
for media impact on physical
store footfall. Biddable online.
Store Sales Direct - connecting
offline events via user
email/phone number to online
user to record revenue impact
of online on offline
OFFLINE CAPABILITIES:
Improvements in store mapping,
validation & machine learning
extrapolate & translate to action
online

8. Store Visits Reporting - The How
Location History Hundreds of millions of users have opted to share their location with Google as part of signed-in
Location History. This option enables users to get the best out of Google Maps, Google Photos, and
Google Now.
Web History
Data
GMB Linking
Hundreds of millions of users have also opted into Web History. This option stores signed-in Search ad
clicks and provides a superior, personalised search experience.
These two data sources together can be used to generate anonymous, aggregated statistics of how
many people visited a store within 30 days (you can select 1, 2, 3 or 4 weeks) after clicking on a
Google.com Search ad. Due to our high privacy thresholds, we typically only have data available for
large, multi-location retailers who generate a large number of ad clicks.
Store location data comes from account-level location extensions that are linked from Google My
Business (GMB). This is final step that requires advertiser approval in order to enable the Store Visits
Reporting functionality.

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Google Store Visit - this is how it works...

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Store Visits methodology
Visits
store
Store
2
Ongoing data validation
(surveys) with 5M+ user panel
Store
Visits
Extrapolated to the population
aggregated and anonymized
3
Geometry, Wifi
scanning
(200M+ locations)
GPS, Wifi
triangulation,
Location history
Backend
data
Clicks
on an ad
Signed-in and opted into
location history
User behavior
1

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How does it work?
Footfall tracking in detail

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Building your omnichannel insights

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Per Store Reporting
Per Store reporting:
Use-cases : validation & opportunities
Checking visit volumes & comparative assessments in performance (SVR) for what are considered the ‘best’ outlets.
Multiple success indicators - calls, visits and driving directions. Some potential for overlap in results.
SVR (Store visits/local reach) can be used to isolate competitor impact / strength in geographic area (low SVR vs average could be due to
higher local competitors and loss of visit traffic)

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Thinking ‘Omni’ - Conversion Delay effect
E.g If my activity runs on the 1st, it takes 8+ days to have recorded 50% of the total store visits driven by the activity on the 1st.
Reviewing, optimising and building out strategies for Offline requires broader timeframes than e-commerce activity.
Any tests also need a ‘cool-down’ period to review / analyse full impact.

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eCommerce & Store Visits
Generics, Competitors & product campaigns tend to over index on store visits compared to online actions.
Time-sensitive promotions deliver the greatest ‘omni’ impact in delivering on and offline impact.

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New vs Returning Customers
New vs Returning segmentation - available at a campaign level. Can be used to establish which campaigns are
driving the most loyal or the best new acquisitions.
Classification currently set at 180 days. Can be reduced to a minimum of 30 days.
Is also based on a chain, not an individual store.

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DEMOGRAPHIC Reporting
Demographic overlay on the data allows advertisers to understand how their audiences are
interacting, and to potentially validate ATL media targeting. It’s also possible to compare ecommerce
vs offline footfall to show how certain segments differ.

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Build out a store support / store accelerator strategy
Low performers
Top performers
● Identify poor performers (competitive geo, weak performers, new stores etc?)
● Leverage existing activity to replicate key activities and target to these geos with
increased bids (get more with the same)
● Build out activity to include broader terms to capture wider demand (get more
with more)
● Focus on efficiency and volume.
● Broaden keyword coverage - where can you drive greater footfall?

19. Understanding what drives footfall & what drives ecomm
Break campaigns down into three segments:
Ecommerce Primary
Focus is on continuing to drive efficiencies
and volumes.
What % of conversions do these campaigns
drive and what budget do they use.
This becomes your ‘MAINTAIN’ ecom activity
with the majority of the existing budget
assigned to continue to drive ecommerce
outcomes.
Omni (online & offline)
For campaigns which drive both online &
offline, measure success and investment on
the basis of driving both outcomes (using an
existing ecom budget to drive store visits will
damage the capacity to drive ecom).
Using remaining ecom budgets, run a test
upweight for a selection of campaigns to drive
omnichannel results.
Offline (footfall) Primary
Find campaigns which are driving a
disproportionate volume of store visits with
few/no ecom sales.
Identify increased coverage potential (to drive
higher footfall), including expansion into
additional categories/keywords.
Deploy TEST budget to drive footfall output and
generate offline results.

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Omnichannel Optimisation

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Managing GA & AW store visits together
Both platforms have differing but complementary capabilities
Able to show SVs for all channels that drive to website. **must include a website visit
in order to be an eligible action for a store visit record **
Deduplicates across channels based on standard GA ‘last paid channel’ preferred.
Enables channel budget management based on omnichannel performance.
Less rich reporting currently. In pipeline to improve.
Shows a store visit for all enabled media engagements (search ad click, TrV
engagement, display view etc). **does not need to include a website visit in order to
be an eligible action for a store visit record **
Currently de-duplicates across Google media if within MCC. Q2 rolling out DDA for
Store Visits for better attribution. Search in AW will show a higher store visit # than
AW PPC in GA.
Ability to operationalise and bid to store visit actions.

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Example
74,197 GA store visits
(Google PPC)
93,718 AdWords store
visits (Search)
0.791
Example store visit value: $30
Store Visit value applied to AdWords =
{$30* 0.791} = $23.73
AW
$2,223,928
GA
$2,225,910
74,197 * $3093,718 * $23.73

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Attributing the right value
How valuable is each store visitor? Efficiency-based approach or Volume-based
Ensure the right
optimisation targets
and levers are being
deployed to drive
footfall
Ensure the business is
focused and aligned
on driving the metric
across your media
activities
Attribute offline sales to online media
events (clicks/engagements etc)
Use this validated AOV data
to establish value / revenue
per store visit
Operationalise / optimise to the
confirmed/validated value per store
visit.
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2
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Get more total conversion value or revenue
at the specified omnichannel ROAS (return
on ad spend) you set with Target ROAS
Optimizes your bids to deliver higher total conversion
value at the specified omnichannel ROAS goal
Set unique values for online and offline conversions
Available for Search and Shopping campaigns
Ad Creative
Search Partner
OS
Device
Remarketing List
Browser
Location
Time of day
Store Visit
(BETA)
Actual query
Omnichannel Bidding - Google Ads & SA360
Drive online purchases & footfall with the same bidding strategy...

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Local Area Marketing:
Drive Store Visits

26. LOCAL: Three powerful solutions to drive footfall
Local Campaigns
Machine-learning powered campaign running
across Search, Display, YT & Maps optimised
and built to deliver Store Visits to selected
stores.
Local Inventory Ads
Locally relevant ads for shopping - drive higher
engagement (20% higher CTRs) and increase
foot traffic to store.
Local Catalogue Ads
Local campaigns
include the ability to
serve logo pins. High
cut through &
engagement to
stores.
Drive store visits
through flagging
local availability of
searched for
products.
Rich execution for extending reach of offline
catalogues, driving people in-store based on
local availability of key inventory. This can be
100% or partly supplier funded.

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Local Campaigns
Automated x-network Google campaign dedicated to optimizing for offline objectives
Search Maps Business Profile YouTube Display

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Learning
During the first few days
an equal start-up budget
is allocated to each
channel to monitor the
store visits
performance.
Store Visits KPI
We set Store Visits
conversion as the
primary metric to
optimize the
campaign.
Optimizing
Machine Learning is
used to identify channel
performance and
patterns to optimize
budget and serving to
maximise Store Visits.
Fine Tuning
Serving and performance
is continually monitored
using advanced learning
to make optimization
tweaks.
How Local Campaigns Works

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Considerations for Local Campaigns
Getting the most out of Local Campaigns
Which Stores? Why?
What are the stores you want to drive footfall to? Your best stores, your worst stores?
Geographically competitive stores? All stores?
Group similarities
Bring together similar stores to align ‘success’ metrics appropriately: struggling stores
(willingness to increase CPSV). Low AOV stores (manage to a lower budget)
Extend activity (BAU gives the best efficiency)
ML-based activity. Longevity = improved efficiency and learnings. Stop & Start approach
requires relearning process for each kick off.
● Single Campaign
● Multiple Campaigns
● Manage via labelling

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Thanks!