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Recall effect of short message service as a complementary marketing communications instrument.

A quasi-experimental study was designed to investigate the recall effect of Short Message Service (SMS) as a complementary marketing communications instrument. An experimental group (EG) was formed, consisting of people who had called an SMS number mentioned in a car brand campaign. A control group was formed using respondents who replied on a television quiz question through SMS. For both groups unaided and aided recall for two similar car brand campaigns was recorded. In campaign 1 no SMS support was used; campaign 2 was the original SMS-supported campaign. Using an omnibus [chi square] test, the data show a statistically significant effect supporting the hypothesis that SMS, as a relatively cheap complementary instrument, can boost the recall effect of an advertising campaign. Furthermore, two limitations of the study are discussed: limited control regarding respondents' exposure to the communication campaigns and the relatively long time elapsed between exposure to the campaigns and recall measurement, which necessitate further research.


In the last decade several new communication channels have emerged for marketers to choose from, such as Short Message Service (SMS), Multimedia Messaging Service (MMS), and I-mode. In particular SMS is one of the fastest risers. SMS provides the opportunity to deliver short messages (160 alpha numeric characters) to mobile phones. These messages can also contain data packages like ring tones and logos. In a short period of time, this form of communication has become widely accepted, especially among the youth (Holmes, 2001). The market growth for mobile phones is slowing down whereas the use of SMS is still growing spectacularly. More than 800 million users generated more than 30 billion messages in 2001. The popularity of SMS started in Scandinavia and Great Britain and subsequently affected the rest of Europe since 2000. For instance, in Great Britain the number of SMS messages reached an average of one billion messages per month in 2002 (James, 2002). For some mobile operators SMS is the only mobile application that is profitable (Biddlecombe, 2002; Holmes, 2001). Holmes (2001) estimates the European mobile advertising market to grow to 3.5 billion [euro]. Response rates to SMS messages in the target group (16 to 25 year olds) are reported to vary from 5 to 50 percent (James, 2002). Taking into consideration the decreasing cost of SMS and its availability to the masses, it is clear that this medium has quite some potential for marketers (Raffray, 2001).

SMS is on the marketing agenda for most brands right now (Kelleher, 2003). For example, SKY, McDonald's, and Armani have used SMS in their marketing campaigns. They use this medium because it has tremendous power to target people on the move. Kelleher (2003) also reports that in most cases SMS is not used as a marketing tool per se, but often is used as a direct response method or as a complementary channel alongside other marketing communication tools. The purpose of using SMS as a complementary channel is to create a positive brand experience. Probably the best illustration in which SMS was used as a complementary channel is the television show Idols. In this television show viewers could participate in the show via SMS. For one episode of the U.S. version of Idols, 2.5 million people took the time to vote for their favorite artist by sending an SMS (Ankeny, 2003).

In contrast to the traditional communication channels like radio, print, and television, empirical evidence about the effects of the new media is virtually nonexistent. Therefore, in this article we investigate the effect of SMS when used as a complementary channel in a marketing communication setting. In the next section we will first discuss the conceptual foundations of the study. Subsequently the research design and the methodological issues are presented. Finally conclusions are drawn and avenues for further research are presented.


First, the characteristics of SMS as a communication tool are discussed in terms of the information processing perspective. Second, the relevance of its interactive properties is examined and its usefulness as a marketing communication tool is elaborated. According to Daft and Lengel (1986), the reason why people exchange information is as a way to diminish uncertainty and ambiguity. Ambiguity is the existence of multiple and conflicting interpretations about situations (Daft and Macintosh, 1981; Weick, 1976). When ambiguity is high, confusion and lack of understanding are always present. In a situation in which ambiguity prevails, a "yes-no question" is not the right question to ask in order to get an adequate answer. Participants encountering ambiguous situations are not certain about what question to ask and a clear answer is not always possible (March and Olsen, 1979). Diminishing ambiguity is necessary to create a comparable level of knowledge about a subject for all participants. Based on early works in psychology (Garner, 1962; Miller and Frick, 1949), uncertainty can be defined as the absence of information. Galbraith (1977) defined uncertainty as the difference between the amount of information required to perform a task and the amount of information already possessed.

According to Kydd and Ferry (1991), every communication tool is characterized by its own particular balance between uncertainty and ambiguity. Communication tools can thus be positioned on a continuum (see Figure 1) ranging from high on ambiguity reduction and low on uncertainty reduction on the one end versus low on ambiguity reduction and high on uncertainty reduction on the other end of the continuum. Tools like electronic meeting systems (EMS) and face-to-face meetings are very personal and diminish ambiguity, whereas electronic messaging systems like email, voicemail, and audioconferencing reduce uncertainty. Face-to-face is the most effective communication tool to reduce ambiguity (Chidambaram, 1993). The equivalent for this tool in marketing communication is word-of-mouth communication. When detailed information is required, new mediums like email and the internet are more suitable communication mediums.


According to Stewart and Pavlou (2002), it can be said that although new media are undeniably unique mediums, they share many of the characteristics of the more traditional mediums. Appearance and usage of written and spoken text are even important when using new mediums. However, the new mediums change marketing communication from a one-way process, limiting the information flow to go only from marketer to customer, into a two-way process, where interaction between marketer and customer can occur. Goal-directed behavior, in the form of consumer involvement and interest, has long been recognized as an important determinant of consumer response to marketing communication. When a response can be provoked, the effectiveness of a campaign will be increased. However, empirical research shows that when direct marketing becomes unsolicited and control over the information is lost, a negative brand experience might be the result (Mitchell, 2003). This means that two-way marketing communication is better used when consumers show interest in the product or brand. Therefore, new mediums have to fulfill this need by not overwhelming the consumers, but by involving them in marketing campaigns.

SMS is a tool with which only specific questions can be asked and specific answers can be given. Communication through speech is not possible and written texts are limited to 160 characters. The main advantage of SMS is the speed of feedback. Answering and questioning on both sides can be done very quickly. These reasons show, according to the communication continuum given by Kydd and Ferry (1991), that SMS is not a rich medium and can only diminish uncertainty. Consequently, SMS should be used as a complementary communication tool in which a traditional one-way medium can be converted into a two-way medium.

To design effective communication campaigns, it is necessary to obtain knowledge of the market's response to communication campaigns and its associated costs. Vakratsas and Ambler (1999) argue that the effect of marketing communication is influenced by different factors such as how, where, and when a campaign is presented to the customer. The factor "how" relates to the media choice through which a campaign will be presented to the public. Often it is stated that every medium has the same effect (Allaway and D'Souza, 1995). However, several enquiries oppose this fact and indicate that measuring the effect of different mediums is getting more important because of the cost aspect (Mantrala, Sinha, and Zoltners, 1992; Tull et al., 1986).

According to Duke (1995), to measure the effect of using a medium in a campaign the following cause-effect reasoning is appropriate. When a marketing communication campaign creates a positive brand experience (attitude-toward-the-advertisement), the brand or product is better remembered (Donthu, Cherian, and Bhargava, 1993). Subsequently, better brand awareness will lead to increased sales. In measuring communication effectiveness dependent variables have been used that relate to the various positions in the cause-effect hierarchy proposed by Duke (1995), e.g., attitude-toward-the-advertisement, memory-based measures like recall or recognition, repeat purchase intention, and increased sales. Unfortunately, there are methodological issues pertaining to all the effectiveness measures mentioned. Positive brand disposition as a variable is liable for much subjectivity. Many studies use increased sales (or repetition of purchase) to prove the effect of a marketing communication tool (Stone and Duffy, 1993). In these cases a daring assumption is made by saying that increased sales are a result of marketing communication (Broadbent, 2001). However, the increase in sales might be due to a host of factors, such as season, price, and the economic situation (Zufryden, 2000). Recall and recognition are often considered to be poor indicators of advertising effectiveness (Lodish et al., 1995; Sternthal, 2001). This is because it is assumed that not so much the factual advertising information but rather the evoked associations within a person's thoughts determine choice decisions. In our study, due to practical reasons (further explained in the empirical section), effectiveness measures regarding disposition toward the brand and actual buying behavior cannot be used. Therefore the focus will be on memory-based effectiveness indicators.

Vakratsas and Ambler (1999) argue that the response to advertising implies that, consciously or unconsciously, advertising must have some mental effect. Conscious or unconscious mental effects can be measured on a memory basis. According to Lee (2002) there are two kinds of memory, implicit and explicit memory. Explicit memory is when a customer consciously thinks back to prior exposure and deliberately attempts to access previously presented information (Shapiro and Krishnan, 2001). Implicit memory is when retrieval of previous encoded information leads to a task performance without a deliberate attempt to recollect the information (Shapiro and Krishnan, 2001). According to Shapiro and Krishnan (2001) previous marketing studies researched only explicit memory. To get a good view of the complete recall in someone's memory, both types of memory have to be researched. Whereas both recall and recognition (explicit memory tests) fade in time, implicit memory is preserved (Lee, 2002; Singh, Rothschild, and Churchill, 1988). Implicit memory is considered to be revealed by facilitation in tasks that use memory whereas explicit memory is revealed by directly testing memory content (Jacoby, 1991). Lee (2002) and Shapiro and Krishnan (2001) suggest that implicit memory measures may be more useful indicators of advertising effectiveness compared to measures related to explicit memory. Krishnan and Chakravarti (1999) explain this with the fact that implicit memory matches the behavioral predispositions of consumers and is a form of memory used in everyday life. In Table 1 an overview is presented of which variables apply to which circumstances.

Despite the critical comments explicit memory has received over the past years, we choose to use "recall" as an indicator for effectiveness in our study. Several reasons lead us to adopting a measure for explicit memory as the most appropriate one. First, the buying process of the type of product featuring in our study (cars) as well as the use of humor in the advertising campaign suggests an enhanced information search and processing (MacInnis, Moorman, and Jaworski, 1991). It is this type of choice situation in which Shapiro and Krishnan (2001) consider explicit memory measures to be valid. Second, the marketing campaigns central in our study used a high degree of advertising repetition, thus further strengthening the memory encoding opportunities (MacInnis, Moorman, and Jaworski, 1991). Third, it is assumed that advertisements attended to only incidentally may be far less likely to be recalled than advertisements given deliberate attention through an extra act (in this case sending an additional SMS). Furthermore, Tavassoli (1998) states that receiving similar messages from various media will increase the strength and accessibility of the network in the brain. Little empirical research has been conducted on how cross-promotional tools influence each other. Jin (2003) found, however, that information about advertising campaigns increased subsequent advertising memory through active involvement in the advertising event. Stammerjohan, Wood, Chang, and Thorson (2005) found partial proof for interaction effects between publicity and advertising on brand attitudes and knowledge. Based on the above line of reasoning, we hypothesize that a marketing communication campaign that includes a complementary SMS element will show increased recall of that campaign when compared to a campaign without an SMS element.


We were given the opportunity to access respondents that had participated in a particular car brand campaign using SMS as a complementary medium. This campaign ran for six weeks in April and May 2002 and included extensive broadcasting of commercials on radio, television, and a website. In these commercials an SMS number was provided. By sending an SMS text message with their car registration number, respondents would enter a lottery in which a car of that particular brand could be won. A complicating factor in this research project was that access to the database containing the SMS-respondents' mobile phone numbers was given only several months after the campaign had run. This implied that no precampaign measurement was possible and that the considerable time lapse between campaign and measurement could have an effect on the level of recall. To deal with these problems a quasi-experimental design was chosen in which the SMS participants were designated as an experimental group (EG; Cook and Campbell, 1979). The EG consists of people who have participated once or twice in the SMS-supported car brand campaign and contains a population of 50,000. Furthermore, a control group (CG) was included, consisting of people that SMSed a reply on a television quiz question. Consequently, this control group consists of SMS-capable people. Furthermore, checks were made to ensure that members of the CG had not participated in the SMS-supported campaign. To complete the quasi-experimental design, a second car brand campaign with similar characteristics as the SMS-supported car brand campaign was selected. Both car brand campaigns were broadcasted for approximately six weeks in spring 2002 on both radio and television. Radio commercials lasted for about 30 seconds and television commercials for about 25 seconds. Both car brand campaigns had similar characteristics. In the first part (80 percent of the total time) a funny situation is presented; in the second and last part information is provided about benefits to be gained and how to participate. In the non-SMS advertising campaign (C1), respondents are invited to visit the dealer showrooms of that particular brand. Showroom visitors may win vouchers up to 25,000 [euro]. In the SMS-supported advertising campaign (C2) through SMSing, 1 out of total of 10 cars could be won. Thus, the design includes campaign C1 without SMS and, a manipulated condition, campaign C2 in which SMS was employed. For both the EG and the CG, the aided and unaided recall for the two car brand campaigns were recorded.

For our study this design results in four observations. Observation 1 ([O.sub.1]) represents the recorded recall for C1 (non-SMS condition) in the EG, and observation 2 ([O.sub.2]) represents the recorded recall for C2 (SMS condition) in the EG. For the CG, observation 3 ([O.sub.3]) represents the recorded recall for C1 (non-SMS condition), and observation 4 ([O.sub.4]) represents the recorded recall for C2 (non-SMS condition). Consequently, the design can be depicted as follows:


We expect no significant effects for the frequency distributions between [O.sub.1] and [O.sub.3] and [O.sub.3] and [O.sub.4]. We expect a significant effect for the frequency distributions between [O.sub.1] and [O.sub.2], and [O.sub.2] and [O.sub.4].

Previous to the final measurement, a test measurement was performed in which 700 respondents for both groups were contacted to participate in the measurement. Based on the quality of the data obtained and comments from respondents, the final measurement procedure was fine tuned. Response rates for this test were 7.0 percent (EG) and 7.7 percent (CG). Subsequently these response rates were used to establish the necessary sample size for the final measurement. For both groups a random sample of 5,500 respondents was drawn. Respondents were contacted through an SMS message on their mobile phones. The message contained a website address where respondents were directed through a questionnaire. For each of the two groups (EG and CG), different web addresses were used so respondents could easily be identified. After logging in on the web address, an introduction screen was presented welcoming the respondents and informing them that they were taking part in a survey regarding the effectiveness of advertising. Subsequently, respondents were asked for their (aided) recall of each of the two car brand campaigns. Control questions were used at several stages in the questionnaire to make sure it was genuine recall. To prevent order effects each of the two car brand campaigns was addressed 50 percent in first position and 50 percent in second position. It took respondents about 8 to 10 minutes to answer the questionnaire.

Explicit memory was chosen as the dependent variable because of the time passed by since the marketing campaigns were active. By giving subtle and not too revealing hints, explicit memory of the occasion can still be researched. Hereby the SMS-car-campaign link was not mentioned at first contact because then the SMS link would be the cause of recall and not the better notion of the brand campaign. The response for the SMS group was 7.2 percent (396 respondents) and for the control group 7.8 percent (429 respondents). After the age check (target group for the campaign was between 18 and 40 years old), 341 respondents remained in the SMS group and 343 in the control group. Nonresponse was checked through telephone contact with 50 nonrespondents in each group. The major reason for not responding was the time elapsed between receiving the request through an SMS text on the mobile phone and gaining actual access to a computer. Based on the nonresponse check and the similar response rates in the test measurement, we have no reason to assume that a nonresponse bias has occurred.

An important assumption is that all respondents have seen both campaigns. We only know for sure that respondents in the SMS group have seen campaign 2. A direct check through the questionnaire was not possible because this interferes with the main research question. Therefore an indirect indicator is used. Through the broadcasting schedules and gross rating points, it is estimated that the chances of respondents in the target groups having been confronted with both campaigns are above 98 percent.


The results of our study are given in Table 2. The results of the omnibus [chi square] test (Everitt, 1992) indicate a significant effect for unaided recall ([chi square](1) = 4.26, p = 0.039). We followed up the omnibus [chi square] test with four univariate [chi square] tests ([O.sub.1] versus [O.sub.3], [O.sub.3] versus [O.sub.4], [O.sub.1] versus [O.sub.2], and [O.sub.2] versus [O.sub.4]). We find no significant effects for the frequency distributions between [O.sub.1] and [O.sub.3] ([chi square](1) = 0.590, p = 0.442), and [O.sub.3] and [O.sub.4] ([chi square](1) = 0.352, p = 0.553). However, we find significant effects for the frequency distributions between [O.sub.1] and [O.sub.2] ([chi square](1) = 6.644, p = 0.010), and [O.sub.2] and [O.sub.4] ([chi square](1) = 15.091, p < 0.001).

The results support the hypothesis that using SMS as a complementary tool in a marketing communication campaign gives an additional positive effect to the recall of that campaign.


In our study we investigated the added value of using a relatively low cost communication channel such as SMS as a complementary tool in a marketing communication campaign. To deal with limitations in the data availability, a quasi-experimental design was used consisting of two respondent groups that were asked to recall two similar car brand campaigns. Through an SMS text message, respondents were directed to a web-based questionnaire. A net response of 341 for the SMS group and 343 for the control group was obtained.

The empirical part of this research gives marketers the evidence that SMS when used as a complementary marketing tool offers opportunities to enrich marketing campaigns. The literature review suggested that the addition of an interactive element to a campaign would have a positive effect. SMS as a complementary tool gives an additional positive effect to the recall of a campaign. The relatively low cost (0.05 [euro] per message) for the usage of SMS during a campaign is a relevant complementary marketing communication medium. The response to the SMS action was considerable; in total over 70,000 SMS messages were received. However, the main objective for the whole campaign, to generate more showroom traffic, was below expectations.

Two serious limitations are identified in the study. The first concerns the time elapsed between showing the campaign in the media and measuring its effect. Empirical research on recognition and recall by Martin, Le Nguyen, and Wi (2002) shows that when advertisements are asked to be recalled within a short period of time (adjacent to the viewing of a show containing the advertisements) the percentage of recall is approximately 51 percent and when a commercial was repeated several times during a show recall became approximately 59 percent. In another recall study (Franz, 1986), 53 percent of respondents were unable to remember any specific advertisement that was heard, seen, or read in the past 30 days. These percentages are still higher than the recall percentages found in this study where recall was asked several months after the showing. Low recall of both campaigns can be explained by the fact that explicit memory fades in time (Burke and Srull, 1988; Lee, 2002; Singh, Rothschild, and Churchill, 1988). The second limitation concerns the lack of control on the actual exposure of respondents to the campaigns. Although we have indications (no significant effects between [O.sub.1] versus [O.sub.3] and [O.sub.2] versus [O.sub.4]) that this condition is reasonably fulfilled, there is no explicit confirmation for this.

Several avenues for future research can be identified. First, repeat studies in a more controlled setting using a true experimental design are necessary. These studies can strengthen the findings in this article, and the measurement can be expanded to include implicit memory (which is less time sensitive). Second, comparing the added value of SMS with MMS or I-mode is relevant, particularly because several authors (Aaker and Brown, 1972; Meenaghan and Shipley, 1999) point out that "medium" and "message" are closely related. Services like MMS or I-mode can be considered much richer media than SMS and therefore can be expected to have a more profound effect. A third avenue could be directed at establishing the optimal format of SMS as a complementary marketing communication tool. This study focused only on the medium and not on the message. In an experimental study factors, such as reward, complexity, amount of repetition, and the host medium can be manipulated to determine their impact on the effect.

JOOST WOUTERS is an assistant professor of Marketing in the Department of Organization Science and Marketing at Eindhoven University of Technology, Eindhoven, The Netherlands. His research interests are business-to-business marketing, customer service, marketing of high-tech products, technology adoption, and new-product development. His work has been published in Industrial Marketing Management and the Journal on Network and Chain Science, among others. He contributes regularly to conference proceedings.

MARTIN WETZELS is a professor of Marketing and Supply Chain Research in the Department of Marketing at Maastricht University, Maastricht, The Netherlands. His main research interests are customer satisfaction and dissatisfaction, customer value, services marketing, business-to-business marketing, (online) marketing research, supply chain management, cross-functional cooperation, e-commerce, new-product development, technology infusion in services, and relationship marketing. His work has been published in Management Science, Marketing Letters, the International Journal of Research in Marketing, the Journal of Business Research, the Journal of Interactive Marketing, the Journal of Economic Psychology, Industrial Marketing Management, the European Journal of Marketing, the Journal of Management Studies, and Total Quality Management. He has contributed more than 60 papers to conference proceedings.


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Eindhoven Centre for Innovation Studies, Eindhoven University of Technology


Maastricht University
TABLE 1 Implicit and Explicit Memory Measurement Variables

                 Recall                   Recognition

Explicit memory  No notion of content of  Content of stimulus is
                 the stimulus is shown.   shown and must merely
                 Content must come from   be identified by the subject
                 subject's recollection   as having been seen or heard
                 (Lee, 2002; Singh,       (Lee, 2002; Singh, Rothchild,
                 Rothchild, and           and Churchill, 1988).
                 Churchill, 1988).
Implicit memory  --                       --

                 Conceptual Priming            Perceptual Priming

Explicit memory  --                            --
Implicit memory  After the stimulus is shown,  After the stimulus is
                 subject's task performance    shown, subject's task
                 improves as the result of     performance improves as
                 enhanced conceptual           the result of enhanced
                 influence (more accessible)   perceptual influence
                 (Lee, 2002).                  (more instinctively)
                                               (Lee, 2002).

TABLE 2 Frequency Counts per Cell of the Research Design

Recall   Manipulation  Experimental  Control

Unaided  No SMS         45  54%       38  46%
         SMS            73  69%       33  31%
Aided    No SMS        101  53%       88  47%
         SMS           105  56%       82  44%
No       No SMS         95  47%      217  53%
         SMS           163  42%      228  58%
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Date:Jun 1, 2006
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