Does Location Intelligence Really Matter, Today?
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Does Location Intelligence Really Matter, Today?
- 1. Does Location Intelligence Really Matter… Today?
- 2. “In the mobile, always-on, highly internet-connected world… Geography will be history: Place will cease to be a constraint for messaging …place will cease to define a consumer” Does 2021 Main Street Matter? 2
- 3. 3
- 4. 4
- 5. 5
- 6. 71% will drive 15 minutes or less to try a new provider after moving 6
- 7. 81% are willing to consider switching providers 7
- 8. Top Categories pharmaceutical gasoline grocery internet phone 8
- 9. 10% off - 45% will not travel; 55% will go 15 min. 25% off - 45% will go 30 min. 50% off - 82% will go 30 min; 40% will go 60 min. 9
- 10. Unaddressed admail: 10 vs 30 minute distance to store increases action intent by 50% Addressed Admail: 10 minute distance to store increases action intent by 20% 10
- 11. How far is your consumer willing to travel? 11
- 12. 84% of consumers will drive 20 minutes or less 12
- 13. 80% of consumers will drive 20 minutes or less 13
- 14. 40% of consumers will drive more than 30 minutes 14
- 15. Consumers prefer ads that are locally relevant Most take action to a location specific message 15
- 16. Consumer behaviour continues to be influenced by Location 16
- 17. 17
- 18. 70% unprepared to manage the explosion of data 50% struggling to create a single view of the customer 18
- 19. 80% of business data has an address element incorporated Addressing is a key element for consumer authentication 19
- 20. Census demographics at address/DA Lifestyle segmentations at address /postal code Credit scoring requires address 20
- 21. Trade areas a critical marketing decision criteria Prospects based on homes in trade area Many products stay at the address; or are purchased by address 21
- 22. We find Geospatial analysis is often underutilized Limited insight on market dimensions Choose limited attributes for targeting Consider market by structured radius 22
- 23. Structured Analysis can be limiting distance radius geographic boundaries 23
- 24. Unstructured areas - distanceleverages Unstructured analysis they will travel customer behaviour C lient D is ta nc e A nalys is 10 0 90 80 70 60 50 40 30 20 10 0 1 2 3 4 5 6 7 8 9 1 11 D is ta nc e fro m S to re ( km) 60% of customers drive 10 minutes 24
- 25. Optimizing your marketing program Wasted message Lost opportunity 25
- 26. Optimizing trade areas, a GIS puzzle 26
- 27. Support franchisees’ customer acquisition targets Focus on neighbourhoods with the greatest opportunity to acquire new customers 27
- 28. Traditional radius approach offers a high degree of overlap 28
- 29. Each store’s trade area defined by the distribution of their customers The Yonge Street effect 29
- 30. Customer profiling identified distinguishing demographic characteristics Hhld $ 0-19K Hhld $ 20-79K Hhld $ 80K+ Age 25-34 Age 35-49 Age 50-64 Dwelling Rented Dwelling Mixed Dwelling Owned A B C 30
- 31. Acquisition model assigns unique score to each postal code 31
- 32. 32
- 33. Original Trade New Customized Areas Trade Areas 33
- 34. Leverage GIS to Optimize customer acquisition in 3 steps 34
- 35. Is there a role for trade-area location analysis and e-commerce providers? 35
- 36. High Penetration Low Penetration Sales Sales 36
- 37. Is there a role for trade area location intelligence and mobile marketing? 37
- 38. The customer sees a custom map to the nearest retail location The direct marketing voice, March 18 2011 38
- 39. Respondent’s information is sent automatically by e-mail to agent The direct marketing voice, March 18 2011 39
- 40. Location intelligence: ShopAlerts by AT&T Location-based opt-in platform: designed to use mobile marketing and geofences to drive consumers into retail locations For consumers: receive offers, and coupons based on their specific geographic location 40
- 41. Is there a role for trade area location intelligence and social media? 41
- 42. Social ?? Unstructured Demo & Psychographics Structured Physical and Behavioural Structured 42
- 43. Mapping search and social activity to geography….a start esri case study Search events, unfiltered for single day Highlights clusters, hotspots and spatial errors 43
- 44. Density and sentiment mapping to create hot-spots by geography esri case study 44
- 45. Location Intelligence as an essential tool to drive ROI 45
Notas del editor
- Source: JWire Mobile Insights Audience Report Q4 2011
- The first step: Where is your target audience located or what is your trade area? Is it within a specific city, CMA, or maybe a radius around your store.
- Each locations trade area is different and a standard 10 km radius applied to all locations does not represent each locations true customer base Some store location trade areas overlap due to the close proximity of store locations; potential customers in the overlapping areas may belong to one postal route but are likely to frequent different locations. Thus printing one location on a flyer is insufficient and results in imbalanced Unaddressed Admail allocation Targeting is based on only 3 demographic variables weighted equally with little understanding of key demographic drivers or their multivariate interactions in identifying potential customers
- Define a trade area for each store by associating all customer postal codes to the postal route and calculating distance from the routes to each store; graphically represent customer percentiles ranked by distance to determine boundary limits Construct individual store trade areas by geocoding all store locations and creating a buffer around each store with the respective store’s 85 th percentile distance ranking applied to historical customer data (boundary limit identified in previous step)
- Integrate CPC proprietary geographic data with Statistics Canada demographic data to create an aggregated data set at the postal code level Weight each route on household density and customer penetration combined to ensure true representation of demographic characteristics Compare demographic characteristics of the Customer Base to the Trade Area to create an Index, and identify over and under indexed demographic variables among the many demographic variables in the data set
- Deciling the model scores show postal codes in the lowest model decile have very low penetration of customers, while postal codes in the top decile have more than 2 times the penetration of customers than average A thematic map is produced to provide a visual representation of the neighborhoods with the greatest opportunity to identify potential customers.
- The data utilized to accomplish this process integrates customer base information associated with individual stores, CPC proprietary data, as well as the complete Statistics Canada 2006 Census data (the most recent available). Leveraging this comprehensive modeling data set enables CPC to differentiate between areas of greatest and lowest opportunity.
- Many Social Media apps are built with the social geography in mind. Commscore says that “Local” is at the forefront of the intersection of social and mobile trends. By definition, local equals place. Local is geographic and is the means to connect anything, anywhere. SoLoMo features are readily embraced by consumers but are marketers keeping up with the innovation? How quickly are they adopting geo-aware and SoLoMo features? Local – or location - exposes preferences, relationships and connections. Trends that can be used to understand loyalty and affinity. We can mine and quantify these interactions and connections to understand more about consumers. What are they looking for when they search, how much demand exists, where do we have supply and demand imbalance and hence opportunity and gaps? What else do people want? What are they longing for in an area, a market or community? The very things we need to do as marketers.