Bulletin, December/January 2006
Repeat Search Behavior: Implications for Advertisers
by Nico Brooks
Nico
Brooks is director of research & development, Search at Atlas. He can be
reached by email at nico.brooks at atlassolutions.com.
Research
by comScore Networks in December 2004 found that people who search online before
making a purchase tend to search many times before purchasing (www.comscore.com/press/release.asp?press=526).
For purchasers of keyword ads, this finding raises the question: What
impact does repeat search behavior have on how search marketing performance is
evaluated? To gain insight into this issue, we used advertiser campaign
tracking data and some of the metrics commonly used in managing online
advertising campaigns. The data analyzed included all tracked search clicks
leading to conversion for 10 different advertisers. One month of click-to-order
conversion data was analyzed. Unique users were identified by means of a
tracking cookie. Orders were tracked by a tracking pixel placed on an order
confirmation page. The advertisers included in the analysis were all
consumer-focused, but they encompassed a broad range of products and services.
The first question we
investigated: Of purchasers driven by
search, what percentage clicked on more than one keyword ad for a given
advertiser before purchasing?
The findings are
summarized in Table 1, which indicates nearly a third of visitors who completed
an order clicked on more than one keyword ad. This percentage certainly has a
material impact on how search advertising campaign performance is evaluated.
The next question we
investigated: What impact does repeat
search behavior have on conversion attribution?
In this context,
conversion attribution refers to the attribution of an online purchase to a
keyword ad click - the user who clicks on a search ad converts from a visitor
to purchaser. Typically, a click-to-order conversion is attributed to the last
click before purchase. However, if a searcher clicks on more than one keyword ad
before purchasing, then presumably each keyword ad that is clicked influences
the sale and should be considered when calculating performance metrics. We
looked at the impact of attributing conversions to the first click before
purchase versus the last click before purchase on the two metrics often used in
the management of online advertising campaigns: time-to-convert and
cost-per-order (CPO).
Time-to-convert is
calculated as the period from when a visitor clicks on an ad to when the visitor
completes a purchase. For example, if a visitor clicks on a keyword ad at 1:00
p.m. and returns the next day and completes a purchase at 11:00 a.m., the
time-to-convert is 22 hours. Time-to-convert is a useful gauge in understanding
the consideration cycle for products and is relevant to performance analysis by
time-of-day or day-of-week as a recent study by the Atlas Institute documents (www.atlassolutions.com/pdf/DaypartAnalysisDMI.pdf).
In Table
2, average
time-to-convert metrics are compared for the advertisers in our sample. The
"First" column shows the average time-to-convert from the first search ad
click and the "Last" column shows the average time-to-convert from the last
search ad click. For most of the advertisers, there is a dramatic difference
between the two figures. On average, the time from first click to conversion is
2.7 times as long as the time from last click to conversion.
The observed increase
in time-to-convert has an important implication for advertisers: if an
advertiser is only looking at the last click before purchase, part of the
consideration cycle may be missed. For example, the last click before purchase
may largely represent shoppers who have already made a decision regarding which
product to buy and are now deciding on where
to buy.
The second metric we
looked at was CPO, which is calculated as advertising cost divided by the total
number of tracked orders. If considered at the campaign level, CPO does not
change when we account for repeat searches, since the total cost and orders do
not change. When calculated at the keyword ad level, however, how we look at ad
performance may change dramatically. For example, consider the following with
keywords X, Y and Z:
Scenario 1:
100 clicks on keyword ad X resulting in 5 orders at a cost per click of
$1.
Scenario 2:
100 clicks on keyword ad X preceded by 25 clicks each on keyword ads Y
and Z resulting in 5 orders. Keyword ads X, Y and Z are priced at a cost per
click of $1.
In Scenario 1, the CPO for keyword X is
calculated as (100 x $1)/5, or $20. In Scenario 2, we don’t have enough
information to calculate CPO. We need to know which keywords specifically were
clicked before purchase. For the purposes of the example, we will presume that
keyword ad X was the only ad clicked before 3 of the 5 orders and was preceded
by ad Y for one order and by ad Z for one order. The ads clicked before each
conversion have been summarized in Table 3.
With this information,
we still have to make a decision regarding how we will attribute click-to-order
conversions to each ad clicked. Should the first or last keyword ad clicked
receive all credit for the conversion? Should credit for the conversion be
shared among all ads clicked? This topic most certainly merits further study,
but for the purposes of this analysis we will choose the latter approach and
share credit equally. While this choice may be arbitrary, it is no more
arbitrary than the last click attribution method proscribed by most ad tracking
technology available today.
Sharing credit equally,
we apply the data in Table 3 to Scenario 2 as follows to calculate the CPO for
keyword ad X:
1. 100% of orders 1, 2 and 3 are attributed to X, totaling 3 orders
2.
50% of order 4 is attributed to X,
totaling 0.5 orders
3.
50% of order 5 is attributed to X,
totaling 0.5 orders
4.
The sum of orders attributed to X is
therefore 4
5.
The total cost for keyword ad X is $100
(100 x $1)
6.
The CPO for keyword ad X is $25 ($100/4)
Comparing Scenarios 1 and 2, the CPO has
increased by 25% when we account for previous keyword ads clicked.
To better understand
the impact of shared click conversion attribution versus last click conversion
attribution when calculating CPO, we compared CPO using the two methods of
conversion attribution for the top-performing keyword ad for each advertiser in
the sample shown in Table 1. The top-performing ad in this case was determined
by which ad drove the highest number of conversions. The results are summarized
in Table 4.
We were very surprised
by these results, which generally showed very little difference between the two
calculations. Given the fact that 32% of purchasers overall clicked on more than
one keyword ad before purchasing, we had expected that there would be a more
significant shift in CPO valuation if we included clicks preceding the last
click in our calculations of CPO.
This unexpected result
prompted us to dig further into the distribution of keyword ads in the sequence
of ads clicked before purchase. What we found was that high volume keyword ads
tend to appear frequently among all ad clicks leading to conversion, whether
first, middle or last. In fact, we found that searchers would often click on the
same ad multiple times before converting. Analyzing repeat search behavior for
the advertisers sampled, we found that 82% of visitors who clicked on more than
one keyword ad before completing an order clicked on the same ad multiple times.
The visitor may have also clicked on more than one unique ad, but his/her clicks
included clicks on the same keyword ad at least twice.
Summing up: People
who click on search ads often click more than once before purchasing. There is
usually a long delay between the first and last click before purchase, and they
are very likely to conduct the same search over and over.
While there are
quantitative implications in these results for search ad performance, perhaps
the greatest implication is in the nature of search behavior itself. The fact
that visitors are conducting the same search multiple times to get to the same
place implies that their behavior shifts from being inquisitive in nature to
being navigational in nature as the search sequence progresses. While this
knowledge appears to have minor implications for how keyword ads are valued, it
has major implications for the state of mind of the searcher and therefore has
major implications for how the advertiser can best serve the visitor when he or
she arrives.
Table 1:
Percentage of visitors who clicked on more than one keyword ad before completing
a purchase.
|
Advertiser |
Percentage |
|
a |
13% |
|
b |
42% |
|
c |
33% |
|
d |
30% |
|
e |
41% |
|
f |
18% |
|
g |
48% |
|
h |
36% |
|
i |
47% |
|
j |
11% |
|
Average |
32% |
Table 2: Difference in time-to-convert when comparing
first-click-to-conversion with last-click-to-conversion.
|
Advertiser |
First |
Last |
|
a |
4:04:57 |
1:48:22 |
|
b |
33:56:40 |
23:25:52 |
|
c |
24:26:26 |
11:45:17 |
|
d |
45:28:34 |
4:30:20 |
|
e |
27:13:13 |
9:58:34 |
|
f |
23:49:35 |
20:17:05 |
|
g |
214:11:43 |
111:26:17 |
|
h |
16:37:34 |
16:22:18 |
|
I |
69:02:53 |
29:56:00 |
|
j |
0:52:17 |
0:26:06 |
Table 3:
Illustration of click-to-order conversion attribution.
|
|
Keyword Ads Clicked |
||
|
|
X |
Y |
Z |
|
Order 1 |
yes |
no |
no |
|
Order 2 |
yes |
no |
no |
|
Order 3 |
yes |
no |
no |
|
Order 4 |
yes |
yes |
no |
|
Order 5 |
yes |
no |
yes |
Table 4: Difference in CPO for the top performing keyword ads when
comparing last-click-to-conversion attribution with shared-click-to-conversion
attribution. A difference with a negative value means that CPO decreased when
calculated using shared click attribution.
|
Advertiser |
Difference |
|
a |
0.17% |
|
b |
1.67% |
|
c |
-0.21% |
|
d |
-0.11% |
|
e |
0.35% |
|
f |
-0.59% |
|
g |
0.68% |
|
h |
1.67% |
|
i |
-0.94% |
|
j |
1.01% |
Articles in this Issue
Paid Search as an Information Seeking Paradigm
Clicking Instead of Walking: Consumers Searching for Information in the Electronic Marketplace
Sponsored Search: A Brief History
The Power of Understanding: Switching Paradigms with Your Target Customer in Search Marketing
Repeat Search Behavior: Implications for Advertisers
The Flip Side of Fear: Marketing to the Empowered Consumer
The Value Implications of the Practice of Paid Search