1. The State of Automotive
Internet Marketing
Jeff Tirey
Mongoose Metrics, CMO
May 16, 2012

2. What We Will Cover In The Next Hour
1. Review how the workshop’s data was created
and understand its strengths AND
pitfalls.
2. Discuss how benchmarking can be an important
tool in the formation of your marketing plans.
3. Dive deep into the data to uncover results, such
as the rates of use of important third-party web
technologies and services.
4. Identify how social media is used in the
automotive industry.

3. Workshop Goals
• Gain a high level vision of where you’re
industry is at.
• Identify best practices and top performers in
your industry
• Identify the rates of technology use within
your industry
• Justify your marketing decisions with data
• Discover the new world of big-data and big
data tools

4. Key Goal
More than anything…
I want you to understand at a high level what
your industry is doing and have confidence
when forming your own Internet marketing
strategic plan.
… because, you’ll have the data to backup your
decisions.

5. Best Of All
All the data we discuss in this workshop,
you will have full access to for your own further
study.

6. Part 1 – The Data
About The Data
• Approximately 17,669 U.S. automotive dealer
websites
• The data was built by first retrieving company
information, including web address, using the
Jigsaw.com API.
• With the website address, a website crawler
visited each website and download the
source-code of the homepage.

7. Part 1 – The Data
Data Collection Overview

8. Part 1 – The Data
To Be Clear
• The data-set only contains the homepage
source code.
• Not the entire website.
• If a technology is not present on the
homepage, it will not be found.

9. Part 1 – The Data
This Data Set is Not Perfect
• It’s only the homepage
• It contains rouge records introduced by Jigsaw
through the incorrect categorization of
companies

10. Part 1 – The Data
Bad Record Example - Trucks

11. Part 1 – The Data
Bad Record Example - Motorcycles

12. Part 1 – The Data
Bad Record Example - Tires

13. Part 1 – The Data
So How Can We Trust This Data?
• The API returned an initial dataset of 32,000
records.
• Approximately 15,000 records – about 46% of
records -where purged through cleaning to
bring the dataset to 17,669
• While stragglers remain in the record-set, they
are low enough to not skew the findings.
• This is the nature of big-data. It’s big, but
imperfect. (This is true for Hoovers and D&B.)

14. Part 1 – The Data
How do we know the study’s data-set
is a good representation of all U.S.
automotive dealer websites?

15. Part 1 – The Data
NADA Industry Research

16. Part 1 – The Data
NADA – New Car Dealerships

17. Part 1 – The Data
Study’s Data: 17,669
NADA’s Data: 17,700
The two record-sets are very close in count, but this
does not mean the two hold the same records. A
detailed examination of the study’s data-set indicates a
rate of error of about 3%-5%.
I can live with that.

18. Part 1 – The Data
Ok, so we have the data... What do we
do with it?

19. Part 2 – Benchmarking
Benchmarking
• Benchmarking provides a moment in time
snapshot of your business’s performance and
helps you see clearly your position in a
relation with a particular standard.

20. Part 2 – Benchmarking
Benchmarking Provides Context
• Context makes data relevant
• With context you can compare your
company’s efforts to other companies in direct
competition.
• Compare your company to best-performers in
your industry

21. Part 2 – Benchmarking
Benchmarking Beware!
• Benchmarking does not tell you what to do.
• You need KPIs for that

22. Part 2 – Benchmarking
Develop Your Own KPIs
• What is not measured is not managed.
• KPIs define and measure progress
• Base KPIs on your own overall business goals
• Measure KPIs over time
• Example: If overall company goal is to increase
customer service appointments, your KPI
could be to increase existing customer social
media engagement by 30%

23. “We have the facts and
we’re using them too”

24. Part 3 – Results
Distribution of Web Analytics Packages

25. Part 3 – Results
Unknown

26. Part 3 – Results
Trade-In Car Value
AutoTrader – 564
Pure Cars – 349
Black Book - 947

27. Part 3 – Results
Reviews/Customer Experience
Better Business – 564
Dealer Rater – 925
iPerceptions- 947

28. Part 3 – Results
Chat
Contact At Once – 2,619
Live Person – 65
Provide Support - 16

29. Part 3 – Results
Only 94 Dealer Websites Use Quantcast

30. Part 3 – Results
Be Sure To Hide Audience Reports

31. Part 3 – Results
Be Sure To Hide Audience Reports If You Do Not
Want Others To See Your Metrics

32. Part 3 – Results
Some Dealers Choose To Not Hide Audience
Metrics

33. Part 3 – Results
Quantcast is a great tool to discover and validate
your visitor demographics

34. Part 3 – Results
Great for metrics on local marketing

35. Part 3 – Results
And my favorite… where else does your
visitorship go on the Internet..
Are you strengthening your brand
With ad targeting
on bridal, jewelry, fashion,
Cosmetic, and parenting sites?
Use audience metrics to speak to their needs

36. Part 3 – Results
I trust Quantcast..

37. Part 3 – Results
Here’s Why…

38. Part 3 – Results
Speaking of Retargeting…
Google - 610
AdRoll - 100
Fetchback - 22
ReTargeter -2

39. Part 3 – Results
Marketing Automation
HubSpot - 29
Pardot - 0
Marketo - 0
Eloqua - 0

40. Part 4 – Social Media
Social Media Usage
Twitter 4,164 24%
Facebook 6,628 38%
LinkedIn 270 2%
Youtube 4,066 23%
Google+ 1,344 8%

41. Part 4 – Social Media
Combinations of Social Media Use
•Only Facebook 2,688 15%
•Only Twitter 224 1%
•Both Facebook & Twitter 3,940 22%

42. Part 4 – Social Media
Facebook Open Graph API Call

43. Part 4 – Social Media
Facebook’s ‘People Talking About’
Metric
This metric refreshes daily but goes back a
week. So it’s the current barometer of how
much conversation is being generated by
someone’s Page on Facebook. It’s a good
gauge of the content Pages are putting up and
how to generate more conversations around a
Page

44. Part 4 – Social Media
‘People Talking About’ Metrics
• liking a Page
• posting to a Page’s Wall
• liking, commenting on or sharing a Page post (or other
content on a page, like photos, videos or albums)
• answering a Question posted
• RSVPing to an event
• mentioning a Page in a post
• Photo-tagging a Page
• liking or sharing a check-in deal
• or checking in at a Place.

45. Part 3 – Results
Top 12 Brands By ‘Likes’ & Engagement

46. Part 4 – Social Media
But how do these rates of Facebook
Engagement Stack Up? ..
An example in another vertical for
context …

47. Part 4 – Social Media
It is possible to have satisfactory FB engagement
rates and high ‘like’ counts
How are engagement rates at the local auto dealership level?

48. Part 4 – Social Media
Top 12 Acura Dealers by ‘Likes’

49. Part 4 – Social Media
Most Facebook ‘Likes’

50. Part 4 – Social Media
Likes Graph
There’s even 1 like from my network of Facebook friends.

51. Part 4 – Social Media
Popular Likes

52. Part 4 – Social Media
Top ‘Likes’
Dave White Acura davewhiteacura 150655
Steve Castrucci Jeep Eagle Svc SuzukiAuto 85586
Smart Center of Walnut Creek smartusa 70366
Lake Country Chevrolet LakeCountryChevroletCadillac 50963
Furnace Brook Motors Inc autotrader 44156
Steve Rayman Chrysler Jeep steveraymanchevy 42831
Habberstad BMW habberstadbmw 41708
Town & Country Ford AlabamaFord 30350
Hunter Douglas HunterDouglas 29376
Dugan Chevrolet duganchevrolet 29169
Mercedes Benz of Austin mercedesbenzofaustin 20700
J.M. Lexus JMLexusFL 18418
Camelback Volkswagen camelbackdifference 17744

53. Part 4 – Social Media
How To Take Action?

54. Part 4 – Social Media
A Better Way To Visualize

55. Part 4 – Social Media
Geolocating Dealership Facebook
Accounts

56. Part 4 – Social Media
Facebook ‘Likes’ Map
Blue markers = 

57. Part 4 – Social Media
Auto Dealership Facebook Engagement %
Blue markers indicate < 0.58% engagement 

58. Part 4 – Social Media
BatchGeo.com Detail View
Follow me @tireytv
to get access to this
these maps

59. Part 4 – Social Media
Twitter By Follower Count

60. Part 4 – Social Media
Follower Count Over Time

61. Part 4 – Social Media
Friends Count Over Time

62. Part 4 – Social Media
www.followerwonk.com

63. Part 4 – Social Media
Geo Visualization of Twitter Followers

64. Part 4 – Social Media
Activity of Followers

65. Part 4 – Social Media
Followers Bio Cloud

66. Part 4 – Social Media
Geo Zoom-In of Followers

67. Part 4 – Social Media
View Followers

68. Part 4 – Social Media

69. Part 4 – Social Media
Shared Followers

70. Thank You!
Jeff Tirey
CMO, Founding Partner
@tireytv
jeff.tirey@mongoosemetrics.com