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7 Reasons Why CPG Marketers
Are Turning to Location
Analytics
Follow @CARTO on Twitter
Introductions
VP Marketing at CARTO CPG Specialist at CARTO
Has your office location
changed vs 1 year ago?
Are you or your family living
in a different location vs 1
year ago?
Are you shopping the same
way you shopped 1 year
ago?
Have you bought a puppy?
Has CPG evolved its
analytics to this new
normal?
Often not.
United States
China
United Kingdom
Spain
Australia
Japan
Canada
Germany
Italy
10 years ago
10 years ago
9 years ago
9 years ago
4 years ago
5 years ago
4 years ago
9 years ago
9 years ago
9.4
Year
Averageweighted by population
When was the last census?
7 reasons why CPGs are
turning to location
1. Spending behavior has changed
forever
● What we spend money on has changed
(rise of home fitness, struggle for
fashion industry)
● How we spend money (death of cash,
changes in contactless limits)
● Near real-time data is required to
respond to consumer behavior patterns
Eating places
Before lockdown After lockdown
Grocery & food stores
Before lockdown After lockdown
2. Mobility patterns change by the
week
● Local & regional lockdowns are top of
mind for brands to navigate (as a
long-term factor)
● Predicting mobility behavior is closely
tied to other demographic &
socio-economic variables
● Important to measure & monitor return
to work to mould campaigns
accordingly
Metro stations at risk of overcrowding
POLL 1
I’ve never used movement data ……………………………………..
Yes ………………………………………………………………………………….
No ……….....…………………...………………………………………………..
Has mobility/movement data proven useful for your organization?
It’s too expensive ..…………………...…………………………………...
3. Social sentiment is unpredictable
● Attitudes towards COVID-19 are closely
tied to location, with differing behaviors
and attitudes across regions.
● Social media data (with its limits) still
provide indicators on attitude for
brands to evolve content & campaign
channels accordingly.
Rapid changes in social dialogue:
Conservation attitudes:
Live & local music attitudes:
For Sonic, it varies massively by store:
● At some stores, there is an opportunity to cultivate
loyalist segments, while others should focus on
the emerging customer base.
● “Sleeper” audience in some suburban and rural
segments showing new interest & travelling
greater distances after their traditional options
have changed during stay at home orders.
● Sonic mattered to families before the pandemic,
and now has become increasingly important
during stay at home orders. Opportunity to focus
on family-related messaging across stores.
4. New workplace trends
● Shared workspace in apartment
buildings (increase productivity, no
commute)
● Shared workspaces in prime locations
(e.g. Shoreditch, Manhattan) suffering
with workers opting to meet a handful
of colleagues closer to homes
● Need to avoid mass transit for
considerable future
POLL 2
Intersecting admin. or political boundary (census tract, postal
code, etc ) ……………………………………………………………………..
Drive/walk area ……………………………………………………………..
A combination of both ..………………………………………………..
How do you determine a location’s catchment area (area of
influence)?
Where is it affordable to walk to work from?
5. Drastic behavioral changes
● Brands are targeting completely new
segments (or audiences) that they
haven’t targeted before
● This requires new data that brings
together online and offline behavior (i.e.
not just social media, but also first party
data such as:
○ Website
○ CRM
○ DMP
Influx of new home buyers:
Influx of online shoppers:
6. New transit preferences
● Certain demographics opting to use
ridesharing more or buy a vehicle
(opting to avoid mass transit)
● Changing demographics exposed to
roadside media
● Increased value for less urban outdoor
media (with many leaving cities for
second homes or selling up)
7. Physical brick & mortar data must
be real-time
● Retailers consolidating site networks &
opting for curbside collection formats
● QSRs & higher-end restaurants opting
to increase number of ghost kitchens
serving delivery business
● Changing behavior of typical POI visitors
(universities, hospitals, schools, parks) is
critical data for marketers evolving their
strategies
February POIs won’t do the trick:
CPGs need a 360 view of consumers to
tell the right stories in the right place:
Points of Interest
Road TrafficFinancial Data
Behavioral
Weather
Human Mobility Housing
POLL 3
None ……………………………………………………………..
1 - 3 ……………………………………………………………..
3 - 5 ……………………………………………………………..
5+ ……………………………………………………………..
How many 3rd party data providers does your organization
have?
Why?
Why do the vegans hang out there &
how will the vegans behavior change
over the next 6 months?
You need to use an LI Platform
Where?
Where do the vegans hang out?
You’re likely using a BI
platform
Build yourself or get some help:
Analyze Build Solution
I need a solution built for a
specific business problem, but
don’t have in-house resources
I want to a build a solution to
do something with my spatial
data
I want to analyze something
about my business with spatial
data
Any questions?
Explore specific stories at www.carto.com/blog
Jaime Sánchez
CPG Specialist // jsanchez@carto.com
Florence Broderick
VP Marketing // flo@carto.com

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7 Reasons Why CPG Marketers Are Turning To Location Analytics

  • 1. 7 Reasons Why CPG Marketers Are Turning to Location Analytics Follow @CARTO on Twitter
  • 2. Introductions VP Marketing at CARTO CPG Specialist at CARTO
  • 3. Has your office location changed vs 1 year ago?
  • 4. Are you or your family living in a different location vs 1 year ago?
  • 5. Are you shopping the same way you shopped 1 year ago?
  • 6. Have you bought a puppy?
  • 7.
  • 8. Has CPG evolved its analytics to this new normal?
  • 10. United States China United Kingdom Spain Australia Japan Canada Germany Italy 10 years ago 10 years ago 9 years ago 9 years ago 4 years ago 5 years ago 4 years ago 9 years ago 9 years ago 9.4 Year Averageweighted by population When was the last census?
  • 11. 7 reasons why CPGs are turning to location
  • 12. 1. Spending behavior has changed forever ● What we spend money on has changed (rise of home fitness, struggle for fashion industry) ● How we spend money (death of cash, changes in contactless limits) ● Near real-time data is required to respond to consumer behavior patterns
  • 14. Grocery & food stores Before lockdown After lockdown
  • 15. 2. Mobility patterns change by the week ● Local & regional lockdowns are top of mind for brands to navigate (as a long-term factor) ● Predicting mobility behavior is closely tied to other demographic & socio-economic variables ● Important to measure & monitor return to work to mould campaigns accordingly
  • 16. Metro stations at risk of overcrowding
  • 17. POLL 1 I’ve never used movement data …………………………………….. Yes …………………………………………………………………………………. No ……….....…………………...……………………………………………….. Has mobility/movement data proven useful for your organization? It’s too expensive ..…………………...…………………………………...
  • 18. 3. Social sentiment is unpredictable ● Attitudes towards COVID-19 are closely tied to location, with differing behaviors and attitudes across regions. ● Social media data (with its limits) still provide indicators on attitude for brands to evolve content & campaign channels accordingly.
  • 19. Rapid changes in social dialogue:
  • 21. Live & local music attitudes:
  • 22.
  • 23.
  • 24. For Sonic, it varies massively by store: ● At some stores, there is an opportunity to cultivate loyalist segments, while others should focus on the emerging customer base. ● “Sleeper” audience in some suburban and rural segments showing new interest & travelling greater distances after their traditional options have changed during stay at home orders. ● Sonic mattered to families before the pandemic, and now has become increasingly important during stay at home orders. Opportunity to focus on family-related messaging across stores.
  • 25. 4. New workplace trends ● Shared workspace in apartment buildings (increase productivity, no commute) ● Shared workspaces in prime locations (e.g. Shoreditch, Manhattan) suffering with workers opting to meet a handful of colleagues closer to homes ● Need to avoid mass transit for considerable future
  • 26. POLL 2 Intersecting admin. or political boundary (census tract, postal code, etc ) …………………………………………………………………….. Drive/walk area …………………………………………………………….. A combination of both ..……………………………………………….. How do you determine a location’s catchment area (area of influence)?
  • 27. Where is it affordable to walk to work from?
  • 28. 5. Drastic behavioral changes ● Brands are targeting completely new segments (or audiences) that they haven’t targeted before ● This requires new data that brings together online and offline behavior (i.e. not just social media, but also first party data such as: ○ Website ○ CRM ○ DMP
  • 29. Influx of new home buyers:
  • 30. Influx of online shoppers:
  • 31. 6. New transit preferences ● Certain demographics opting to use ridesharing more or buy a vehicle (opting to avoid mass transit) ● Changing demographics exposed to roadside media ● Increased value for less urban outdoor media (with many leaving cities for second homes or selling up)
  • 32. 7. Physical brick & mortar data must be real-time ● Retailers consolidating site networks & opting for curbside collection formats ● QSRs & higher-end restaurants opting to increase number of ghost kitchens serving delivery business ● Changing behavior of typical POI visitors (universities, hospitals, schools, parks) is critical data for marketers evolving their strategies
  • 33. February POIs won’t do the trick:
  • 34. CPGs need a 360 view of consumers to tell the right stories in the right place: Points of Interest Road TrafficFinancial Data Behavioral Weather Human Mobility Housing
  • 35. POLL 3 None …………………………………………………………….. 1 - 3 …………………………………………………………….. 3 - 5 …………………………………………………………….. 5+ …………………………………………………………….. How many 3rd party data providers does your organization have?
  • 36. Why? Why do the vegans hang out there & how will the vegans behavior change over the next 6 months? You need to use an LI Platform Where? Where do the vegans hang out? You’re likely using a BI platform
  • 37. Build yourself or get some help: Analyze Build Solution I need a solution built for a specific business problem, but don’t have in-house resources I want to a build a solution to do something with my spatial data I want to analyze something about my business with spatial data
  • 38. Any questions? Explore specific stories at www.carto.com/blog Jaime Sánchez CPG Specialist // jsanchez@carto.com Florence Broderick VP Marketing // flo@carto.com