SurveyMonkey Audience launched a research project to discover what regular users think about SEO(search engine optimization) basics. The survey asked common questions like Google vs Bing but also asked deeper questions meant to understand the value of guest posts from a user standpoint. Some of the topics addressed by the SEO research are: social media (specifically Facebook, Twitter and Google Plus, ccTLD, links with or without anchor text, and the reasons user might bounce from a page. All the raw survey data is freely available and linked in presentation, so feel free to come up with your own insights! More info here: http://bit.ly/12kS2DfSlide

1. Survey: SEO Assumptions
Conducted by:
Eli Schwartz
Online Marketing Manager
SurveyMonkey

2. Background
• We created a survey to test 16 common SEO assumptions
• The survey was conducted via the SurveyMonkey Audience tool
• Respondents were randomly assigned into 1 of 2 surveys with 16
questions
• Survey sent to 3,000 people
• Survey was open for 5 days
• 615 people participated
• The following slides show a comparison of means between the 2
surveys when the data was shown to be statistically significant
• 2 surveys: https://www.surveymonkey.com/s/seo-assumption-1 &
https://www.surveymonkey.com/s/seo-assumption-2
• Actual survey response data: http://bit.ly/12kS2DfSlide

3. Who answered the surveys? Survey 1

4. Who answered the surveys? Survey 2

5. Summary of conclusions
• Search users are biased towards Google, but they consider Bing’s
results to be of equal quality to Google when branding is swapped
• A branded site impacts a user’s level of trust on content
• An increase in Facebook likes influence a users likelihood of sharing
content
• An increase in Tweets influences a users likelihood of sharing content
• An increase in Google Pluses influences a users likelihood of sharing
content
• Linking to high quality sites makes a site/content more trustworthy
• US users do not seem biased towards .COM vs .CA
• Users trust a guest post less when told that it is a guest post
• An exact match domain makes a user more likely to do an action like
fill out a lead

6. Summary of conclusions cont’d
• The publish date of content does not seem to affect user trust
• Poor grammar and spelling impacts user trust of content
• The greatest reasons users would block a site from appearing in
search is because of “too many ads” and “poor content”
• If a user does not find what they expect on a webpage after clicking
from search they will most likely go back to Google and click another
result
• 33% of users start web surfing on Google
• 76% of users rely on Google to search for information
• Users appear to be able to guess the context of a link whether there
is optimized anchor text or not

7. Question 1: Do users prefer Google or Bing
• Users in survey 1 were shown a Google search result page and a
Bing Search Result page for the query “File taxes”. The headers on
the SERP page showed whether it was a Bing or Google result
• Users in survey 2 were shown a Google search result page and a
Bing Search Result page for the query “File taxes”. The headers on
the SERP page were swapped, and users choosing Bing’s results
actually thought they were picking Google.

8. Question 1: Do users prefer Google or Bing
Google results
labeled as Bing
Bing results labeled
as Google
Bing results
Google results
Conclusion:
Users are
biased
towards
Google as a
result of the
brand

9. Q2: How much does brand matter for trust?
• Users in survey 1 were asked about their level of trust for an article
published on CNN.com
• Users in survey 2 were asked about their level of trust for an article
published on Internetnews.com

10. Q2: How much does brand matter for trust?
Conclusion:
Users have a
greater degree of
trust for content on
a recognized brand

11. Q3: Impact of Facebook Likes
• In survey 1 users were told that there were a large number of Likes
on an article, and asked if they were likely to read the content.
• In survey 2 users were told that there were a small number of Likes
on an article, and asked if they were likely to read the content.

12. Q3: Impact of Facebook Likes
Conclusion:
Facebook likes do
impact the
likelihood of
reading content

13. Q4: Impact of Tweets
• In survey 1 users were told that there were a large number of Tweets
on an article, and asked if they were likely to read the content.
• In survey 2 users were told that there were a small number of Tweets
on an article, and asked if they were likely to read the content.

14. Q4: Impact of Tweets
Conclusion:
Tweets do impact
the likelihood of
reading content

15. Q5: Impact of G Plus
• In survey 1 users were told that there were a large number of Google
pluses on a photo, and asked if they were likely to share the photo.
• In survey 1 users were told that there were a small number of
Google pluses on a photo, and asked if they were likely to share the
photo.

16. Q5: Impact of G Plus
Conclusion:
Pluses do impact
the likelihood of
sharing content

17. Q6: External links conveying trust
• In survey 1 users were told that a site they read links out to well
known sites.
• In survey 2 users were told that a site they read links out to unknown
sites.

18. Q6: External links conveying trust
Conclusion:
Outbound links do
impact the trust of
a site by users

19. Q7: US user trust of ccTLD
• In survey 1 users were told that they read an article on unknown
.COM site
• In survey 2 users were told that they read an article on unknown .CA
site

20. Q7: US user trust of ccTLD
Conclusion:
ccTLD does not
significantly impact
trust

21. Q8: Trust of guest posts
• In survey 1 users were informed that a writer was a staff writer and
asked to rate their trust of the article
• In survey 2 users were told that a writer was a volunteer writerand
asked to rate their trust of the article

22. Q8: Trust of guest posts
Conclusion:
Users trust a guest
poster less than a
staff writer

23. Q9: Exact match domain as a level of trust
• In survey 1 users were told that the site they are looking at is an
exact match for the business they sought.
• In survey 2 users were told that the site they are looking at is a
random domain name for the service they sought

24. Q9: Exact match domain as a level of trust
Conclusion:
Domain name
match to query
does motivate trust

25. Q10: Freshness
• In survey 1 users were told that the article was 10 days old
• In survey 2 users were told that the article was 2 years old

26. Q10: Freshness
Conclusion:
Publish date on
evergreen content
had no significant
difference

27. Q11: Spelling and Grammar
• In survey 1 users were shown an article about oil changes as it was
published on Discovery.com. Users were asked to assess their trust
of the article.
• In survey 2 users were shown the same article about oil changes but
typos were inserted and obvious grammar issues were inserted..
Users were asked to assess their trust of the article.

28. Q11: A

29. Q11: B

30. Q11: Spelling and Grammar
Conclusion:
Spelling and
grammar
impact trust

31. Q12: Users block sites in search
• This question was the same in both surveys

32. Q12: Users block sites in search

33. Q13: When users bounce
• This question was the same in both surveys

34. Q13: When users bounce

35. Q14: First website users go to
This question was the same in both surveys

36. Q14: First website users go to

37. Q15: Where users search for information
• This question was the same in both surveys

38. Q15: Where users search for information

39. Q16: Linking and context
• In survey 1 users were shown an article that used exact anchor text
to link to another site
• In survey 2 users were shown an article that used a domain name as
the anchor text to link to another site

40. 16A: Linking and context (exact match)

41. 16A: Linking and context (domain name)

42. Q16: Linking and context
Link contained anchor
text
Link did not contain
anchor text

43. Thank you!
Questions? Email: elis@surveymonkey.com or get in touch on
LinkedIn: http://www.linkedin.com/in/schwartze