Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Omnichannel Marketing with Google - Google Marketing Platform Sydney


Published on

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.

Published in: Marketing
  • Be the first to comment

  • Be the first to like this

Omnichannel Marketing with Google - Google Marketing Platform Sydney

  1. 1. Proprietary + Confidential Omnichannel & Footfall with Google Online to Offline
  2. 2. Proprietary + ConfidentialProprietary + Confidential ● How Google thinks about Omnichannel ● How Store Visits works ● Bridging the value gap ● Omnichannel bidding ● Local Area Marketing Agenda
  3. 3. Proprietary + ConfidentialProprietary + Confidential How do advertisers think about their Omnichannel customers? Buys online Buys online or in a store Buys in a store
  4. 4. Proprietary + ConfidentialProprietary + Confidential 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. 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. 6. These consumers are +40% more valuable +25% more likely to make in-store purchase +10% more spent on average Source: Google data, US
  7. 7. Proprietary + ConfidentialProprietary + Confidential 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. 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 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.
  9. 9. Proprietary + ConfidentialProprietary + Confidential Google Store Visit - this is how it works...
  10. 10. Proprietary + Confidential 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
  11. 11. Proprietary + ConfidentialProprietary + Confidential How does it work? Footfall tracking in detail
  12. 12. Proprietary + ConfidentialProprietary + Confidential Building your omnichannel insights
  13. 13. Proprietary + ConfidentialProprietary + Confidential 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)
  14. 14. Proprietary + Confidential 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.
  15. 15. Proprietary + Confidential 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.
  16. 16. Proprietary + Confidential 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.
  17. 17. Proprietary + Confidential 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.
  18. 18. Proprietary + Confidential 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. 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.
  20. 20. Proprietary + Confidential Omnichannel Optimisation
  21. 21. Proprietary + Confidential 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.
  22. 22. Proprietary + Confidential 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
  23. 23. Proprietary + ConfidentialProprietary + Confidential 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. 1 2 3
  24. 24. Proprietary + ConfidentialProprietary + Confidential 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...
  25. 25. Proprietary + ConfidentialProprietary + Confidential Local Area Marketing: Drive Store Visits
  26. 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.
  27. 27. Proprietary + ConfidentialProprietary + Confidential Local Campaigns Automated x-network Google campaign dedicated to optimizing for offline objectives Search Maps Business Profile YouTube Display
  28. 28. Proprietary + ConfidentialProprietary + Confidential 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
  29. 29. Proprietary + ConfidentialProprietary + Confidential 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
  30. 30. Proprietary + ConfidentialProprietary + Confidential Thanks!