Research

DOI: 10.2501/JAR-53-4-431-443 December 2013 JOURNAL OF ADVERTISING RESEARCH 431

INTRODUCTION

Cross-channel advertising has grown steadily and

significantly as a means to reach consumers. Tele-

vision, the Internet, and other channels are used

together to market products. Search engines have

changed the way people look for information.

Online advertising is growing rapidly and taking

budgets away from traditional channels.

The Internet does not exist in isolation, however,

and discussion around its expansion should not

neglect the roles other channels should play. Coin-

cidental with the growth in digital ecosystem, many

marketing paradigms are shifting from passive strat-

egies in communicating with consumers to more

proactive ones with engagement in multiple commu-

nication channels (Briggs, Krishnan, and Borin, 2005).

Although many marketers are giving more seri-

ous thought to online advertising as an option, it has

yet to reach its full potential within their marketing

mix. As a result, paid listings using search engines

often are not the first element of that media mix.

Industry reports have shown that main broad-

cast channels still garner the greatest share of

advertising revenue, but many companies have

started to allocate a larger portion to search-engine

marketing (ZenithOptimedia, 2013). In September

2013, ZenithOptimedia forecast paid search to grow

at an average of 15 percent per year to 2015, driven

by continued innovation from the search engines,

including the display of richer product information

and images within ads, better localisation of search

results, and mobile ad enhancements like click-to-

call and geo-targeting. Meanwhile, growth in the

use of search engines by consumers provides an

even greater incentive for companies to reconsider

their advertising budgets. In March 2009, there were

This study tracks the effects of advertising expenditures in different media outlets on subsequent consumer online search behavior for advertised products.

The data are from a large telecommunications company compiled over 78 weeks.Findings suggest that exposure to advertising on different media outlets increases the

likelihood of follow-up search by individuals. Radio is less effective than television and online

impressions in generating follow-up search.

For advertisers, the short-term effect in subsequent search stresses the need to synchronize online and offline advertising efforts to achieve the highest impact.

Effects of Multi-Channel Marketing on

Consumers Online Search BehaviorThe Power of Multiple Points of Connection

MICHEL LAROCHE

John Molson School of

Business, Concordia

University

laroche@

jmsb.concordia.ca

ISAR KIANI

John Molson School of

Business, Concordia

University

i_kiani@

jmsb.concordia.ca

NECTARIOS

ECONOMAKIS

Google Montreal

[email protected]

MARIE-ODILE RICHARD

Independent researcher

[email protected]

Amid the plethora of research on advertising effectiveness, the authors of the

current study believe consumers online search behavior, subsequent to exposure to

traditional advertising messages, has been understudied. Using data from a major

telecommunication company, this studys findings support the influence of employing

multiple channels, advertising expenditures, and television and online advertising on

consumers tendency to follow through with their own online investigations.

432 JOURNAL OF ADVERTISING RESEARCH December 2013

EFFECTS OF MULTI-CHANNEL MARKETING ON CONSUMERS ONLINE SEARCH BEHAVIOR

3.2 billion searches conducted across all

search engines, an average of 131 searches

per searcher per month.1 By 2012, Google

alone accounted for 5.1 billion searches per

day worldwide.2

Even as the effectiveness of cross-channel

advertising has been a primary focus for

many researchers and marketing practition-

ers, the authors of the current paper believe

that the manner in which traditional media

channels affect new-media use largely

has been overlooked. This study aims to

determine the effects of advertising and its

impact on consumer search.

One particular area of interest is the pro-

gression from exposure to brand search.

To elicit a behavioral change, exposure

to advertisingand its impactmust be

understood. Drawing on literature, the

authors of the current paper seek to shed

new light on overlooked aspects of the

theory and practice of advertising and to

provide answers to these issues.

To find support for their research, data

from a large telecommunications company

compiled over a period of 78 weeks were

used. The analysis examines how advertis-

ing exposure and expenditure impact con-

sumer search for the companys brand name.

LITERATURE REVIEW

The effectiveness of advertising has been a

major focus of interest (Bergkvist and Ros-

siter, 2008; Cho, 2003; Lodish et al., 1995;

Manchanda et al., 2006; Naik and Raman,

1 comScore Media Metrix, 20092 comScore Media Metrix, 2012

2003; Scholten, 1996; Telis, Chandy, and

Thaivanich, 2000; Yoo, Kim, and Stout,

2004). Advertising effectiveness has been

defined in terms of aspects of business

performance such as increase in sales

(Lodish et al., 1995; Tellis et al., 2000), cost

per impact (Briggs et al., 2005) and brand

awareness (Leone and Schultz, 1980; Mad-

dox, 2004; Vakratsas and Ambler, 1996).

And one study defined effectiveness as the

relationship between advertising expendi-

tures and brand sales, the affect of demand

by establishing a hierarchy of effects in its

audience (Scholten, 1996).

Media and Advertising Effectiveness

Advertising effectiveness may be

explained by factors such as brand and

category conditions, business strategies

objectives, media usage and copy related

measures (Lodish et al., 1995). Thus, dif-

ferences in media result in non-uniform

patterns of effectiveness.

This theory has led researchers to inves-

tigate responses of individuals to different

advertising media to measure their effec-

tiveness. Researchers focused on media

such as direct TV advertisements (tele-

vision commercials that include forms of

direct communication, such as 1-800 phone

numbers, that invite customer follow-up;

Tellis et al., 2000); online banners and Inter-

net advertising (Cho, 2003; Manchanda

et al., 2006); traditional and non-digital

methods (Naik and Raman, 2003); and

conventional television (Briggs et al., 2005).

These findings supported the effect of

advertising on firm performance indica-

tors. The support, however, was not uni-

form. For example, one study found higher

effectiveness (lower cost per impact) for

online compared to television advertis-

ing (Briggs et al., 2005). Furthermore,

the distinction between traditional and

new media was the focus of research-

ers who suggested novel media possess

stronger effectiveness through allowing

individuals to demonstrate higher degrees

of responsiveness to advertising (Fortin

and Dholakia , 2005).

Much attention has been directed

toward understanding key factors in

advertising effectiveness through tradi-

tional media (e.g., traditional and direct TV

advertisements, direct mail). The authors

of the current study, however, see the need

for further research on the effectiveness

of online advertising when accompanied

by other means of advertising communi-

cations, and to capture the mutual effects

of marketing communication channels in

broader time horizons.

Along those lines, the authors identified

past research showing that advertising

through one media outlet could influence

advertising effectiveness through another

media outlet (Assael, 2011). Exposure to

banner advertising significantly influ-

ences Internet purchasing (Manchanda

et al., 2006), and similarly, online adver-

tising has been found to have significant

effects on offline sales (Lewis and Reiley,

2013). In addition, the Internets appeal as

a low-cost advertising medium (Kim and

Balachander, 2010; Briggs et al., 2005) and

constraints on offline advertising (Gold-

farb and Tucker, 2011) have influenced the

use of online media as a desirable advertis-

ing communication channel.

Consumer responsiveness to advertising

and interactivity between individuals and

advertising media also have been influ-

ential in advertising effectiveness. High

program involvement, however, was a

potential blocker of mental processing of

advertising (Levy and Nebenzahl, 2006).

Research found lower involvement of

individuals to negatively affect subsequent

communication by advertisers (Cho, 2003).

Although user involvement may have a

significant effect on advertising effective-

ness, changes in interaction between media

and individuals could affect involvement,

which in turn could positively influence

Cross-channel advertising

has grown steadily and

significantly as a means

to reach consumers.

December 2013 JOURNAL OF ADVERTISING RESEARCH 433


advertising effectiveness. Besides varia-

tion of advertising effectiveness due to dif-

ferences in media, differences in product

categories (Lodish et al., 1995), the timing

of advertising, and vividness were pro-

posed to affect advertising effectiveness.

Furthermore, market and product charac-

teristics also influence advertising effec-

tiveness (Tellis et al., 2000). These instances

hint at the multi-dimensional nature of

advertising effectiveness.

Multichannel Advertising and Synergy

Over the last decade, advertisers increas-

ingly and successfully have used multi-

platform communications to achieve

synergistic results in getting messages

across to consumers within a single mar-

keting campaign. Recent reports released

by ESPN on viewers simultaneous usage

of TV and the Internet confirm the exist-

ence of such synergies (Enoch and John-

son, 2010). And NBCs sponsorship of the

2010 Winter Olympics has been used as a

platform to further measure mutual impact

of television (in-home and out-of-home),

mobile, and Internet advertisements to

better understand cross-platform market-

ing communications (Assael, 2011).

Novelty of a stimulus often has a pro-

found effect on its effectiveness. Research

has shown that a second exposure to a

novel stimulus with similar information

attracts more attention than exposure to the

same stimulus (Putrevu and Lord, 2003).

Another study found that employing both

digital and traditional advertising chan-

nels improved overall advertising effec-

tiveness (Naik and Raman, 2003) through

enhancement of processing and improve-

ment of memory performance than when

a single medium serves as the advertising

channel (Edell and Keller, 1999). Further-

more, subsequent research found a syner-

gistic effect of a second medium to result

from higher impact on cognitions and

increased processing, and that repetition

of an advertisement through the same

medium (television) is less effective than

when a second medium (Internet) is used

(Chang and Thorson, 2004).

Moreover, interactivity influences its

synergistic effects with other complimen-

tary media, as it defines a proactive role for

audiences, increasing their involvement in

the communication process (Allen, Kania,

and Yaeckel, 1998). Such characteristics

combined with televisions attention-

getting nature, which stems from its sound

and imagery effects (Blackwell, Miniard,

and Engel, 2001; Chang and Thorson, 2000;

Rossiter and Bellman, 1999)lead to high

levels of advertising effectiveness.

The characteristics of the Internet and

television as advertising media led some

researchers to focus on the synergistic

effects of their combined use in marketing

campaigns. Some pointed to similarities

between the Internet and traditional print

media (DeFleur, Davenport, Conin, and

DeFleur, 1992; Sunders and Nass, 1996;

Wakolbinger, Denk, and Oberecker, 2009);

others emphasized the differences (Eve-

land and Dunwoody, 2002; Karson and

Koraonkar, 2001) to explain and predict its

effects on audiences.

The visual and informative characteris-

tics of the Internet and television, in fact,

can result in different comprehensions

of the message, when the sequence of

being exposed to them could be differ-

ent (Chang and Thorson, 2000). Findings

of brand-memory extension when chan-

nels similar to the Web and television

are combined (Edell and Keller, 1999)

tend to support the elaboration likeli-

hood model (ELM), where motivations

to scrutinize arguments are linked to the

likelihood of message elaboration. Indi-

viduals exposed to campaigns form their

attitudes through central processing, in

contrast to those who move along the

peripheral route, when they are exposed

to campaigns with repeated messages

(Chang and Thorson, 2000; Petty and

Cacioppo, 1986, 1996a).

Applying the ELM to the Internet/tel-

evision advertising synergy resulted in

researchers speculating higher attention

(Allen et al., 1998; Blackwell et al., 2001;

Brock, Albett, and Becker, 1970; Grass and

Wallace, 1969; Putrevu and Lord, 2003;

Rossiter and Bellman, 1999) and more will-

ingness to scrutinize arguments, compared

to those subjected to repetition (Edell and

Keller, 1999; Harkins and Petty, 1981a,

1981b, 1987; McCullough and Ostrom,

1974) among consumers exposed to such

campaigns (Chang and Thorson, 2000).

These results are based on the effects that

multiple sources have on increasing mes-

sage credibility (Petty and Cacioppo, 1986,

1996b; Zimbardo and Leippe, 1991) because

of higher diversity in sources (Harkis and

Petty, 1987; McLuhan, 1964). Findings also

supported the synergy created by Internet

and television on advertising effectiveness.

For instance, although Chang and Thorson

(2004) did not find synergy to influence

credibility or attitude toward either brand

or advertisement, or purchase intention,

they obtained other findings.

These findings supported higher atten-

tion and positive thoughts and perceived

message credibility. And they further

reinforced the speculations on the impact of

Internet-television synergy on individuals

cognitions, rather than their affective state.

DEVELOPMENT OF HYPOTHESES

The authors believe that applying the

ELMto synergistic effects of multiple

media in communicating an advertising

messageresults in the expectation that

attitude change is a function of likelihood

to elaborate the message.

When elaboration likelihood is low,

the individual more likely changes atti-

tudes along the peripheral route, where

initial attitudes and biases are more likely

to play an important role. The synergy



among multiple channels is expected to be

more effective when individuals who are

exposed to the message are more attentive

to it, allowing for changes in their attitudes

to happen along the central route (Petty

and Cacioppo, 1986).

Consumers with high levels of elabo-

ration likelihood also are expected to be

more motivated in scrutinizing argu-

ments to understand the true merits of a

brand (Petty and Cacioppo, 1986; Chang

and Thorson, 2000). Thus, consumers at

high levels of elaboration likelihood are

expected to make attempts to scrutinize

arguments presented via one communica-

tion medium through other media.

The similarities between the Internet

and human-mind processing information

(Eveland and Dunwoody, 2002) make it a

prime candidate for this purpose. There-

fore, it is expected that a higher number

of individuals with high levels of elabora-

tion likelihood refer to the Internet when

exposed to advertisements communicated

through other media.

Hence, the following relationships are

hypothesized:

H1a: An increase in television adver-

tising leads to increased searches

for the companys brand online.

H1b: An increase in radio advertising

leads to increased searches for

the companys brand online.

H1c: An increase in online advertis-

ing leads to increased searches

for the companys brand online.

Although the ELM focuses on attitude

change and motivation to scrutinize argu-

ments in advertising media, there is research

on the influence that simultaneous exposure

to multiple channels to communicate a mes-

sage can have on the effectiveness of that

message. Multiple messages influence cred-

ibility of the message (Chang and Thorson,

2000) because of the diversity created for

audiences (Harkins and Petty, 1987).

Study of these influences, however,

barely has gone past conventional meas-

ures of advertising effectiveness. In par-

ticular, the likelihood of consumers

becoming motivated to scrutinize the

information communicated via multiple

channels has been under-studied. Based on

the ELM, multiple channels of communica-

tion are more effective if they direct con-

sumers to take the central route by raising

their elaboration likelihood.

Similarly to previous arguments, con-

sumers more likely employ accessible and

convenient media at their disposal for this

purpose. Thus, the authors expected con-

sumers to be more likely influenced by the

additional credibility presented by multi-

ple advertising channels to conduct their

own investigation in understanding the

true merits of a brand. Hence:

H2: The number of search-engine

queries for a companys branded

keywords is a function of the

exposure to advertising placed

in more than one medium (tele-

vision, radio, online).

The ability of companies to use multiple

advertising channels is related to their

expenditures. Expenditures are an accept-

able measure for the amount of advertis-

ing directed to consumers. Therefore, the

authors expected to find an increase in

advertising expenditures to result in expo-

sure to advertisements communicated

through multiple channels. Hence:

H3: An increase in total advertising

expenditure leads to increased

searches for the companys

brand online.

Also, similar to previous arguments,

the authors also expected exposure to

advertising to result in drawing more

attention to the brand online. Therefore:

H4: An increase in advertising

exposure will lead to increased

organic clicks.

METHODOLOGY

Sample and Data

To test the hypotheses in the current study,

data from a major telecommunications

company were gathered. The time frame

of the data collection was extended over

78 weeks, from January 1, 2007 to June 30,

2008. This company regularly used televi-

sion, radio, and the digital media to adver-

tise its products to consumers. To collect

the appropriate data, several variables

were taken into account, among them:

Costs

Costs from each of the campaigns of the

company during these 78 weeks were

collected. Data for weekly costs were

collected separately for radio, television,

and online advertising campaigns.

Impressions

As a part of its online advertising cam-

paign, the company measured perfor-

mance through a pay-per-click metric.

The costs were incurred on the basis

of only number of impressions, which

referred to the number of times the paid

listing appears alongside the users

queries. The total number of impres-

sions was extrapolated from the search

The ability of companies

to use multiple advertising

channels is related to

their expenditures.



engines. Thus, accurate data of the total

number of impressions were collected.

Clicks referred to the number of

times users clicked on the advertis-

ers sponsored results. Sales data were

obtained from each persons click as well.

Each time someone clicked on an image

or link, a cookie was installed on the

browser, and the sale can be tracked. The

data for impressions were collected from

three service providers: Google, Yahoo,

and MSN. In 2013, these three providers

account for close to 96% of the market.3

Clicks

The data for the number of clicks on the

advertising messagesand the num-

ber of times the products were visited

online through natural searches on

search engineswere collected. The

paid advertising clicks included those

from paid search, and from paid online-

display campaigns. The data for organic

searches were gathered using the com-

panys Web-analytics tool that gathered

visits made from non-paid searches. The

other data were collected from providers

of the paid online advertising services:

Online site sales: Total online sales

from the Web analytics tool were

collected. A sale referred to a com-

pletion and validation of a person

making a purchase of any of the prod-

ucts on the Web site.

Press-release data: Using Google

News, the number of online articles

that mentioned the companys name

was collected. This information was

useful because it indicated the pop-

ularity of the company during any

given week.

Control data: Several additional data

sources were collected to serve as

control variables. Wages, salaries, and

3 August 2013 U.S. Search Engine Rankings, comScore.com.

supplementary labor income as well

as personal disposable income and

personal expenditure on consumer

goods and services were collected.

FINDINGS

To test the studys hypotheses, the authors

implemented a three-step approach:

Unit root tests were conducted to deter-

mine whether the data were stationary

over time.

Data analysis using a vector time series

model in the form of an autoregressive

model with exogenous variables (VARX)

was conducted. Vector auto regressive

models allow for the evolution and

interdependencies between multiple

time series to be captured (Sims, 1980).

Corresponding impulse response

functions were generated to examine

the effect of a one-standard deviation

shock on one of the endogenous vari-

ables, in this case marketing spend-

ing or media impressions (Dekimpe

and Hanssens, 1999). T-statistics were

then conducted.

The first hypotheses focus on the influence

of advertising in each medium on subse-

quent searches of individuals who were

exposed to them. H1a, H1b, and H1c pre-

dicted that increased advertising through

television, radio, and Internet would

increase the number of online searches

conducted by individuals, following their

exposure to advertising.

Brand Impressions in Relation to

Television Impressions

To test H1a, total brand impressions result-

ing from customer searches subsequent to

the exposure to impressions from televi-

sion are analyzed using a VARX model.

Television impressions affected brand-

search behavior for 10 weeks, and the

authors witnessed an increased effect in

customer reactions on search engines as

well (See Figure 1). Interestingly, there was

a peak followed by a valley on customers

2018161412108642

80,000

40,000

0

40,000

80,000

120,000

Figure 1 Total Impressions on Branded Keywords in Response to Television Impressions



brand search behavior that lasted for four

weeks. The permanent effect was minimal,

a result that may have been attributable to

the fleeting nature of advertising messages.

Following the practices of an earlier

study, the adjustment period referred to

the period between the end of duration

of immediate response (fourth week) and

the time where the effect returns to normal

(tenth week; Pauwels, Hanssens, and Sid-

darth, 2002). This type of analysis origi-

nally was conducted for price promotions,

but it also can apply to customer search

behavior. In the case of television impres-

sions in the current study, the adjustment

period was six weeks.

The significance was calculated using

a t-statistic. A cut-off point of 1.0 was

selected. This cut-off point allowed for

relatively wide confidence intervals. Con-

sequently, instead of obtaining precise esti-

mates, the results of the current study were

indicative of cumulative effects (Dekimpe,

Hanssens, and Silva-Risso 1999). For H1a,

the t-test was 1.81; it was significant, sup-

porting H1a.

Elasticity also was calculated (See

Figure 2). The net effect during period

two was 0.0035, which illustrates the

amount of change in brand impressions

as the result of every impression made by

television advertising.

Television exposure resulted in high

levels of elaboration likelihood and, as a

result, the message delivered had more

impact than other types of advertising

messages. A 30-second spot enabled peo-

ple with interest in a brand to obtain their

product information through both sight

and sound. This enhanced elaboration

resulted in a longer-term effect on brand

online-searching behavior.

Brand Impressions in Relation to

Radio Impressions

Analysis of the VARX model for H1b

indicated that radio impressions had an

impact on brand online search behavior.

In fact, the effect of radio exposure on

brand keyword searches was noted dur-

ing the first four weeks followed by a

subsequent drop (See Figure 3). The adjust-

ment period, however, was found to be

less significant than for television

impressions.

The effects from radio impressions had

the same elasticity as the effects from tel-

evision during the first period, but it rap-

idly dropped afterward (See Figure 4).

0.00400

0.00350

0.00300

0.00250

0.00200

0.00150

0.00100

0.00050

0

0.00050

0.00100

1 3 5 7 9 11 13 15 17 19

Figure 2 Elasticity of Total Brand Impressions versus Total Television Impressions

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80,000

40,000

0

40,000

80,000

160,000

120,000

Figure 3 Total Impressions on Branded Keywords in Response to Radio Audience



However, the t-test was 0.51. As the over-

all impact of radio was not significant, H1b

was not supported.

Brand Impressions in Relation to Online

Advertising Impressions

To test for the effects of online advertis-

ing on subsequent online search, brand

impressions in relation to online advertis-

ing impressions were analyzed using the

VARX method.

Display of online advertising had a con-

siderable impact on search behavior. In

the impulse-response function (See Fig-

ure 5)as opposed to the finding for both

television and radio exposurethe effects

from online exposure had a steady (and

not sudden) decline. The t-test was 1.52a

significant resultsupporting H1c.

The finding implies that online adver-

tising engages people more than does tra-

ditional media. The fact that someone is

online surfing the Web is a plausible expla-

nation. A person exposed to display adver-

tising and engaged with the message can

search more easily for related brand infor-

mation. The immediacy of the message is

facilitated by the channels interactivity.

In addition, the long-term effect resem-

bles that of television, which implies that

online advertising can stimulate a change

in search behavior over a longer period of

time. Furthermore, the 0.012 elasticity (See

Figure 6) reflected a stronger response for

online advertising on brand search.

Brand Impressions in Relation to Total

Media Impressions

To test H2 and to see whether elaboration

developed through different advertis-

ing channels affected the search behavior

online, total brand impressions from cus-

tomer search behavior subsequent to all

of the impressions in different media (i.e.,

total media impressions) were analyzed

using the VARX model.

0.00450

0.00400

0.00350

0.00300

0.00250

0.00200

0.00150

0.00100

0.00050

0

0.00050

1 3 5 7 9 11 13 15 17 19

Figure 4 Elasticity of Total Brand Impressions vs. Radio Audience

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50,000

0

50,000

100,000

150,000

Figure 5 Total Impressions on Branded Keywords in Response to Online Display Impressions

The finding implies

that online advertising

engages people more than

does traditional media.



In an analysis of the impulse-response

function (See Figure 7), there was an imme-

diate effect of total marketing impressions

on branded keyword impressions that

lasted two weeks, and the adjustment

period lasted nine weeks. The t-test was

1.2well above the cut-off point of 1.0

and the result, therefore, was significant,

supporting H2.

In elasticity calculated for total brand

impressions, the net effect during week

two was 0.008 (See Figure 8). Thus, paid

media impressions from all different media

channels combined influenced brand que-

ries to a large extent.

Brand Impressions in Relation to Paid

Media Expenditures

To test the effect of advertising expen-

ditures on subsequent search, brand

impressions in relation to paid media

expenditures were analyzed using the

VARX model (See Figure 9). Total adver-

tising expenditures had a similar impact as

total media impressions on branded key-

word searches, though to a lesser extent.

The t-test result was 1.09, a significant find-

ing that supported H3.

Total Marketing Impressions in Relation

to Organic Searches

The effects of advertising exposure on

subsequent search through organic clicks

(H4) were tested using the VARX model.

The current study measured the effect of

total marketing impressions on organic

search traffic, which could be observed

in the impulse-response function (See

Figure 10) and the elasticity chart (See

Figure 11). Organic traffic was not sig-

nificantly affected by total marketing

0.0140

0.0120

0.0100

0.0080

0.0060

0.0040

0.0020

0

0.0020

0.0040

1 3 5 7 9 11 13 15 17 19

Figure 6 Elasticity of Total Brand Impressions vs. Online Display Impressions

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80,000

40,000

0

40,000

80,000

120,000

Figure 7 Total Impressions on Branded Keywords in Response to Total Media Impressions

Consumer responsiveness

to advertising and

interactivity between

individuals and

advertising media have

been influential in

advertising effectiveness.



impressions. The t-test was 0.59, a level

that failed to support H4. Moreover, the

elasticity was low and, in week two, it

was 0.0001.

Organic clicks measure total visits from

search engines regardless of keyword cat-

egory and are not the result of paid adver-

tising. A more in-depth analysis could be

conducted on organic traffic by examining

the keyword categories (i.e., branded ver-

sus generic). Such analysis would deter-

mine whether only frequency of search

for branded keywords saw an increase or

whether the same effect also was found for

online searches of general keywords (e.g.,

the words cell phone instead of a specific

brand of cell phone).

The authors findings support the effects

of total marketing expenditures, total mar-

keting impressions, television impres-

sions, and online display impressions

on consumers subsequent online search

behavior. However, the results of the

current study do not lend support to the

effect of radio impressions on subsequent

online search. They also fail to support the

hypothesized relationship for the effect of

media impressions on organic clicks (See

Table 1).

DISCUSSION

The effects of cross-channel online

advertising remain a relatively under-

0.01

0.00

0.00

0.00

0.00

0

0.00

0.00

1 3 5 7 9 11 13 15 17 19 21

Figure 8 Elasticity of Total Brand Impressions vs. Total Media Impressions

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40,000

0

40,000

80,000

120,000

Figure 9 Total Impressions on Branded Keywords in Response to Total Media Expenditures

The authors findings

support the effects

of total marketing

expenditures, total

marketing impressions,

television impressions,

and online display

impressions on

consumers subsequent

online search behavior.



studied field. This paper examined the long-

and short-term effects of offline and

online advertising on searchmore

specifically, searches for the advertisers

brand on search engines, using the

adjustment period and total effects of

advertising on brand search queries (See

Table 2).

The current study found that total mar-

keting impressions, total marketing expen-

ditures, and television and online display

exposure were found to have significant

impacts on brand searches. Radio exposure

did not have a significant effect on brand

searches. The impact of total marketing

impressions on organic clicks also was

found to be not significant.

The findings revealed a significant short-

term increase in queries for the target

brand. More important, they showed that

the increase in subsequent searches did not

sustain over time. The authors also found

that total marketing spending and total

advertising impressions had the greatest

short-term impact on brand queries. The

adjustment time period lasted only three

weeks and then leveled off, and the elas-

ticity was greatest during the first three

time periods.

The findings for television and online

advertising effects on brand searches were

similar (but to a lesser extent) to the effects

of marketing spending and total adver-

tising impressions. The total effects of all

the advertisers efforts sustained a lift in

brand queries. Albeit for a short time, the

0.00002

0

0.00002

0.00004

0.00006

0.00008

0.00010

0.00012

0.00014

1 3 5 7 9 11 13 15 17 19

Figure 11 Elasticity of Total Organic Clicks versus Media Impressions

2018161412108642

40,000

0

40,000

80,000

120,000

Figure 10 Total Organic Clicks in Response to Total Media Impressions

TABLE 1T-Test Results for Each HypothesisVariable T-Statistic Significant?

Total Marketing Spend

1.21 Yes

Total Marketing Impressions

1.09 Yes

Television Impressions

1.89 Yes

Radio Impressions

0.51 No

Online Display Impressions

1.52 Yes

Organic Clicks 0.59 No



effects of online display advertising were

more pronounced. The immediacy of the

medium allowed searches for the brand to

occur much more readily than through tra-

ditional channels.

The findings emphasize the importance

of consistency of messages across differ-

ent advertising media, particularly for

integrated marketing campaigns. The out-

come of our analysis suggests that large

advertising campaigns will drive more

traffic to their Web sites, and this addi-

tional traffic must be sustained through the

companys Web site. Marketers can seize

such opportunities to present additional

purchase incentives.

One key implication of the findings is

that firms can maximize brand-related

queries with their marketing endeavors.

As brand queries are known to occur dur-

ing the short term, firms may be able to

design their media plans to maximize cus-

tomer immediate searches through offer-

ing additional online information.

LIMITATIONS AND FUTURE RESEARCH

The study is not without limitations,

specifically:

User involvement with the advertising

message was not captured because the

relevance of the advertising message to

audiences is not captured by the data.

Using only secondary data does not

allow examining if the actual message

resonates with audiences.

Existing brand awareness might affect

how audiences perceive the brand and,

thus, their search behavior. A less-well-

known brand might not display the

same effects as those in this study; rep-

licating the study with a different brand

from a different industry would help

validate the results.

A third limitation concerns the lack of

precise measurement of existing con-

sumers looking for the companys

brand online. A number of brand

queries might have originated from

existing clientele, thus eliminating the

need to advertise directly to them. This

is a reality of any advertising campaign.

The current study suggests areas for

further research, in that it specifically

examines only the telecommunications

industry specifically. Further research

can replicate it by focusing on a differ-

ent industry. Customer search might

vary across different industries, and

it would be important to test whether

these findings hold across different

product categories.

Future studies may also involve focusing

on Web analytics data more in depth to

understand the quality of each visit on the

companys site. Looking at this Web data

may help researchers better understand

the behavior of visitors who did a Web

search as compared to the rest of the visit-

ors exposed to different channels. Finally,

an area of future research is to examine

the impact of offline advertising on

mobile search behavior (smartphones

and tablets).

MiChel laroChe is the Royal Bank Distinguished

Professor of Marketing, John Molson School of

Business, Concordia University, Montreal. His main

research interests are in marketing communications,

Internet and services marketing, and retailing, with

an additional interest in the role of culture and brand

decision processes in consumer behavior. He has

published more than 280 articles in proceedings and

journals, including the Journal of Consumer Research

and the Journal of Advertising Research. Laroche

is the managing editor of the Journal of Business

Research and a member of the Academy of Marketing

Science board of governors.

TABLE 2Summary of FindingsHypothesis Supported?

H1a: An increase in television advertising leads to increased searches for the companys brand online

Yes

H1b: An increase in radio advertising leads to increased searches for the companys brand online

No

H1c: An increase in online advertising leads to increased searches for the companys brand online

Yes

H2: The number of search engine queries for a companys branded keywords is a function of the exposure to advertising placed in more than one medium

Yes

H3: An increase in total advertising expenditures leads to increased searches for the companys brand online

Yes

H4: An increase in advertising exposure leads to increased organic clicks No

One key implication of

the findings is that firms

can maximize brand-

related queries with their

marketing endeavors.



iSar kiani is a PhD candidate in marketing at the John

Molson School of Business, Concordia University

(Montreal, Canada). Her research interests include

diffusion of market information, advertising, online

and digital marketing, cognitive and neurological

antecedents of consumer decision making, and

cultural influences in consumer perception and

decision making. Kiani holds an MBA degree

from Sharif University of Technology (Tehran) and

previously served as the marketing manager at Fara

Management Organization in Iran.

neCtarioS eConoMakiS, a Concordia University alumnus

(MS, marketing), is an account executive for Google,

Montral, where he leads the development of

quebec clients. Nectar uses his academic and years

of advertising agency experience to help promote

Googles products. He is also co-chair of the IAB

Canada Search Committee.

Marie-odile riChard (PhD, marketing, HEC-University

of Montreal) has research interests in marketing

communications (including Internet marketing),

neuromarketing, services marketing, and cultural

effects on individual responses. She has published

more than 30 articles in journals and proceedings,

including the Journal of the Academy of Marketing

Science, Journal of Advertising Research, Journal of

Business Research, and Journal of Social Psychology.

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