300 Int. J. Internet Marketing and Advertising, Vol. 1, No. 3, 2004

Copyright © 2004 Inderscience Enterprises Ltd.

Developing interactive advertising strategies on the internet as a function of consumer knowledge, ability, and involvement

Richard G. McFarland*, Shane Van Dalsem and Chwen Sheu College of Business Administration, Kansas State University, 201 Calvin Hall, Manhattan, KS 66506-0506, USA E-mail: mcfarlan@ksu.edu E-mail: svandals@ksu.edu E-mail: csheu@ksu.edu *Corresponding author

Abstract: As the internet has developed and gained wider usage, investment in and the application of interactive advertising (IA) has grown. The effectiveness of IA has significant financial and marketing implications for many firms. This study reviews the different forms of IA and suggests that firms design their IA programmes based on a number of important factors. We make managerial recommendations for the appropriate selection of IA and the appropriate content of IA based on product, firm, and target consumer characteristics. Based on the consumer behaviour information search model, we suggest that the consumer-related characteristics of knowledge, ability, and involvement are critical factors to consider when implementing IA strategies.

Keywords: interactive advertising; information search; internet promotional strategies; e-commerce; interactive information search.

Reference to this paper should be made as follows: McFarland, R.G., Dalsem, S.V. and Sheu, C. (2004) ‘Developing interactive advertising strategies on the internet as a function of consumer knowledge, ability, and involvement’, Int. J. Internet Marketing and Advertising, Vol. 1, No. 3, pp.300–315.

Biographical notes: Richard G. McFarland is an Assistant Professor of Marketing at Kansas State University. He received his PhD from Georgia Institute of Technology, his MBA from the University of Arizona, and his BA from the University of California at Irvine. His research focuses on influence tactics and strategies in personal selling and marketing channels of distribution.

Shane Van Dalsem is currently a PhD student in Finance at the University of Arkansas. He received his MBA from Kansas State University.

Chwen Sheu is a Professor of Operations Management at Kansas State University. He is the current ‘Enterprise’ area Editor for the International Journal of Internet and Enterprise Management. He received his PhD from Ohio State University, his MS from Iowa State University, and his BS from the National Chung-Hsing University in Taiwan. His research, teaching, and consulting interests are in the areas of manufacturing strategy, international operations management, TQM, service operations management, Japanese manufacturing systems, and new technology acquisition.

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1 Introduction

Evolutions in information technologies have long caused revolutionary changes in advertising [1]. For example, advertising became increasingly more widespread and important with the advent of, first, the newspaper, then radio, and later television. However, these media represent a one-way transmission of information; they are non-interactive. In other words, whether a consumer chooses to pay attention to and process promotional information rests largely on the relevance of the information to the consumer and the consumer’s ability and motivation to process the information. In contrast, the internet provides opportunities for two-way transmission of information; it has interactive capabilities. Customers choose to view information that they feel is relevant; while with non-interactive advertising, it is a hit-or-miss proposition. Consequently, businesses now have an unprecedented opportunity to utilise interactive advertising (IA) to provide promotional information; information that customers choose themselves and use in making purchase decisions.

Leckenby and Li [2] defined IA as “the paid and unpaid presentation and promotion of products, services, and ideas by an identified sponsor through mediated means involving mutual action between consumers and advertisers.”

This term describes advertising with which consumers can interact, primarily via the internet, including recommendation agents, search engines, specialty websites, and hyperlinked e-mail messages. Scholars increasingly acknowledge the importance of IA. A new genre of advertising firm has emerged (the interactive agency) and traditional advertising firms are increasingly embracing IA as well [3]. It is estimated that $5.25 billion was spent on internet advertising in 2000, compared to $43 billion for network and cable advertising in the same year; and it is projected that spending on IA will reach $21 billion in 2004 and may exceed $45 billion in the year 2005 [4,5]. Thus, the growth rate for spending on IA is projected to be roughly 100% per year through 2005.

As the economic and marketing significance of IA increases, managers must be aware of the effectiveness of the IA strategies they choose to implement. Each of the IA strategies available is not equally effective in all situations; each having its own particular strengths and weaknesses. The premise of this study is that the effectiveness of alternative IA strategies is situational. Firm characteristics, product characteristics, and consumer characteristics all have an impact in determining the appropriateness and effectiveness of the different types of IA. This paper offers managers guidelines for designing IA strategies. In so doing, we make several important contributions to the theory and practices of IA strategy implementation.

In the following section, we introduce the five most common forms of IA used on the internet. We discuss each form’s strengths and weaknesses and provide examples of each type of IA. Following these discussions, we discuss three consumer characteristics (knowledge, ability, and involvement) that have a strong impact on the type of IA that firms should utilise. These consumer characteristics are then linked to suggested IA strategies, which are summarised in Table 2. Finally, our conclusions and potential research issues are presented.

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2 Interactive advertising

This section discusses the five most common forms of interactive advertising that are in current use. While other forms of IA may exist, and certainly new forms will be created in the near future, these five were selected based on the definition of IA stated above and a thorough review of the literature (e.g., [2,6–8]). Table 1 summarises each IA’s strengths and weaknesses.

Table 1 Summary of interactive advertising (IA) strategies

IA strategy Examples Positives Negatives Intelligent recommendation agents

Amazon.com BarnesandNoble.com

Proactive in matching customers’ wants and needs to existing products Accuracy improves over time

Requires a large amount of data for accuracy Depends on historical data – unable to recommend new or obscure products

Shop bots MySimon DealTime

Available as either a web page or desktop application Allows equal footing for smaller firms in a competitive market

Attracts price-sensitive customers Listings are not comprehensive Payment is often required for premium placement

Banner and pop-up ads

DoubleClick Inexpensive Ability to target customers through collaborative filtering

Low response rate Internet users see them as an annoyance

E-mail Landsend.com LLBean.com REI.com Cabblas.com

Inexpensive Ability to target customers Ability to advertise feature-rich products

Internet users see them as an annoyance

Corporate websites Ford.com Gateway.com

Total control over content Ability to gather firm-specific customer information

Can be costly Difficult to attract traffic for new companies

2.1 Intelligent recommendation agents

Intelligent recommendation agents, the most notable being the ones used by major online retailers such as Amazon.com and BarnesandNoble.com, utilise collaborative filtering in order to generate product recommendations. Collaborative filtering is defined as a system designed to make recommendations based on a large database of users’ known

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preferences for a basket of associated goods [9]. It bases recommendations upon buying patterns of people who are similar to the customer. This matching is not based on product features and attributes, rather it utilises a ‘people similar to you also liked X’ heuristic. Similarity between individuals is based on one’s preferences and not on individual characteristics. Thus, a recommendation might take the form of you liked books A, B, and C; people who liked books A, B, and C also liked books X, Y, and Z.

A great advantage of recommendation agents is that they ‘learn’ over time and increase their accuracy with respect to an individual’s characteristics and desired product choices. Because they rely on historical data, they cannot be used to recommend new products, and data requirements are high to ensure accuracy. Overall, intelligent recommendation agents can be useful for firms that sell a wide range of merchandise and have a large customer base, because cross-selling of diversified products can be improved [10]. However, they are not very useful for smaller firms that market a limited selection of products [11]. To date, intelligent recommendation agents have been used primarily for low risk purchases, such as books, and not for high-risk purchases such as honeymoons and mutual funds [12]. Non-collaborative filtering agents also exist that are rule based. These rule-based recommendation agents are more interactive and are based typically on product features preferred by the user. These systems, however, may tend to find a much more limited set of results than can a well-developed collaborative filtering intelligent agent.

2.2 Shop bots

Shop bots, such as MySimon and DealTime, are automated tools that allow consumers to seek out specific product information from online retailers through a keyword search for price and product characteristics [13]. Search results show a listing of products, online retailers, and prices for the range of products specified. Shop bots are available both as web pages and as desktop applications. One drawback to shop bots is that their users tend to be more price conscious than non-users. This limits the utility of shop bots for companies that do not compete well on price [14]. Shop bots usage can also result in increased switching behaviour for customers [15] due to the ease of comparison shopping across multiple online retailers. From a consumer’s perspective, one downside is that store listings are typically not comprehensive, with companies paying for listings [14]. Thus, consumers may not fully trust the results of the shop bot’s search.

2.3 Banner and pop-up ads

Banner ads include the traditional ad in a ‘banner’ that is typically found in the upper or lower portion of web pages. Pop-up ads are similar to banner ads in content; however, they show up as a separate, new web page. A more advanced fusion of the two has emerged as an animated pop-up advertising that is part of an existing web page and that can not be easily avoided. Banner and pop-up ads are inexpensive and they are particularly good for targeting the right audience [16]. The primary weakness with this type of advertising is a very low response rate. Overall, less than 1% of individuals who see a banner ad will click through and of those less than 1% will make a purchase [17]. Additionally, these types of ads are often small and receive too little attention to adequately express the specific attributes of the product.

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It should also be noted that the use of these ads (especially pop-up ads) can be a source of irritation to internet users. Companies, such as PanicWare, AOL, and Earthlink, have produced software to stop pop-up ads [18]. More recently, ‘pop-under web pages’ have been introduced to reduce customer irritation. Pop-under ads are a newer occurrence and designed to be less irritating as they do not directly interrupt the web browsing experience [18]. As the name applies, the ads ‘pop under’ the existing web page being browsed, waiting for consumers when they close the active page. The greatest users of this technology have been the almost notorious x10 Corporation and Half.com, a subsidiary of EBay [18].

2.4 E-mail

The use of unsolicited e-mail as a promotional tool, also known as spamming, is generally frowned upon as a violation of internet etiquette and generally creates far more ill will than positive promotional outcomes [19]. However, because e-mail is an inexpensive form of advertising, many firms continue to practice the usage of unsolicited e-mails (as any person with an e-mail account can attest to). Although this is typically a considerable irritant to recipients, many firms choose to irritate thousands in order to get to the one customer who may ultimately make a purchase. These are firms who generally are unconcerned about their reputations, and may in fact be firms that exist only for a short time period [20].

In order to reduce irritation to potential customers, online advertisers have begun using opt-in e-mails [21]. Opt-in e-mails come either directly from companies whose customers have given authorisation to receive e-mails, or from advertising partners of these companies. The click through rate for this type of interactive advertising is between 5% and 10% [21]. This response rate compares very favourably to the average click through rate of less than 1% for other types of online advertising. Because of the higher response rate, the ROI for this type of advertising is much higher than for other types of advertising [21]. However, it should be noted that consumers have an all-encompassing view of SPAM and may even consider e-mails from firms they have existing relationships with as SPAM if they perceive the e-mail as irrelevant [22].

2.5 Corporate websites

Firm-specific websites, such as www.ford.com, www.gateway.com, and www.benandjerrys.com, are a popular method of promotion. Given today’s technology, customers expect to be able to access a company’s website to find detailed information that often is unavailable elsewhere [23]. Additionally, because retailers often cannot carry a supplier’s full line of products, a corporate website allows consumers to examine the firm's entire product lines [24]. Moreover, the use of firm-specific websites allows companies the flexibility of selling their products directly online.

Manufacturers and suppliers should be careful when selling merchandise on their own internet websites, because existing sales channels and retailers may become quite upset that the company they work with is now directly competing with them [25]. To avoid this potential conflict, many firms have elected not to sell products on their corporate website but, rather, refer customers to their retailers [26]. Selling products directly to customers can be a great service when products are difficult to find or when selling impulse purchase types of items. For example, Mattel decided to establish an online

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website for its Barbie line of products [26]. One reason Mattel decided to sell products online was because no retailer can possibly carry the thousands of Barbie accessories, thus they help customers by making obscure products available. In order to reduce conflict with their retailers they set prices 15% higher than retail, gave referrals to brick and mortar retailers, and do not sell hot holiday items that are important for drawing customers into retail toy stores.

One drawback of corporate websites is that as they increase in complexity and in user flexibility, their associated design and support costs can become significant. An additional drawback is that attracting internet users to the site can be a challenge [27]. Moreover, beyond using the aforementioned banner ads, the use of search engines can be either costly or unreliable in bringing traffic to the site [27]. Non-paid placement on search engines is generally driven by the probability that the company will meet criteria set forth by the consumer. Creating a website that will increase the probability of a high ranking on search engines is time consuming and requires specialised knowledge [19]. Some firms turn either to paid placement on search engines, with placement going to the highest bidder, or to paid inclusion. With paid inclusion, firms pay to place their web pages directly on the search engine’s database, which dramatically increases the likelihood that, and speed at which, search engines find web pages; search engines can otherwise take weeks or even months to find particular information on websites and include these in search results [27].

In summary, there are multiple IA strategies from which firms can choose to promote their products and services on the internet. It should be noted that the level of control that firms have over each of these five forms of IA differs. For instance, firms have complete control over everything that a customer sees on their corporate website, while when using banner ads, pop-up windows, and shop bots they are dependent on third parties. This is analogous to the distinction between firms using direct marketing techniques vs. using traditional advertising. The next section discusses a theoretical consumer information search model, which will provide a basis for the selection of IA programmes.

3 Consumer characteristics linked to interactive advertising usage

We extend the literature on consumer purchase decision making and information search behaviour to the internet context. We later use information search theory to link consumer characteristics to suggested interactive advertising strategies. We focus on the consumer information search model because external information search is an active process of adding information to one’s environment; this active process is analogous to the interactive search activities of consumers on the internet. Thus, this section builds the theoretical support for the IA strategies we suggest in the next section. Based on a review of published literature, we have identified three consumer-related characteristics that affect the level and type of information search that consumers conduct: product class knowledge, the ability to search on the internet, and level of involvement.

3.1 Purchase decision making model

Figure 1 depicts a conventional decision making model that consumers use in their purchase decisions [28]. In the first stage, consumers recognise the need for a purchase. Next, consumers conduct an internal search for information pertaining to the purchase

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(i.e., they probe their memory for any pertinent information that is stored there). If the amount of information they possess is limited and/or if the purchase is important to them, consumers may conduct an external search for information. For example, they may ask others for their opinions (including salespeople), or they may obtain more information from magazines and books. In the third stage, the options within their consideration set are evaluated. Finally, a decision is made and, if a purchase was made, consumers will go through a post-purchase evaluation. The results of the evaluation will then be stored in their memory.

Figure 1 The consumer decision-making process

Source: Howard and Sheth [28].

3.2 Antecedents of information search

Based on a thorough review of the literature, three consumer characteristics (knowledge, ability, and purchase involvement) were found to be critical predictors for the level of interactive information search that consumers will undertake. Understanding these factors also allows us to make recommendations for which types of IA strategies should be used, as well as recommendations for specific IA content, which will be discussed later. Managers can thus make informed IA programme decisions based on their target market’s knowledge, ability, and level of purchase involvement.

3.2.1 Knowledge

As Figure 1 depicts, prior to a purchase, when a need arises, consumers first conduct an internal information search to access their memory to see what information (knowledge of products) is stored [29]. If consumers feel uncomfortable with what they know about the products under consideration, then an external information search may take place. Thus, a person’s knowledge determines whether an external information search will be undertaken and, if so, what type of search and to what extent this search will be undertaken. For example, with a relatively new product, such as a digital camera, a consumer would, most likely, desire a greater amount of product knowledge prior to purchase than with a standard 35 mm camera that the consumer may have been using for years. In this example, the consumer would seek information both on the product class for digital cameras (“What does dpi mean?”) as well as on the specific model and brand of the camera, while on a 35 mm the information search may be restricted to the latter.

It is thought that the overall level of search has a non-linear relationship to knowledge. Those with a great deal of knowledge will have little need to search for more information, while those with very little information will lack the capability to search. Within those extremes, however, the relationship should be positive and linear. Additionally, the ratio of interactive search to non-interactive search is likely to increase with an increase in knowledge. Coupey et al. [30] found that as product-class knowledge increases the amount of emphasis individuals placed on specific attributes or product features in making product judgements increases. An increased emphasis on specific

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features should lead to higher levels of interactive search vs. non-interactive search. In other words, those individuals who have the knowledge level to complete a keyword search will desire a higher level of attribute-specific information, which requires conducting an interactive search. Thus, we propose the following:

Proposition 1: Knowledge has a positive influence on the amount of interactive information search conducted by consumers.

3.2.2 Ability to search

Ability to search is referred to as knowing how and where to search, or the perceived cognitive capability to search and process information [31]. It is distinct from knowledge, which is the level of knowledge an individual has about the class of products under consideration. An individual’s ability to search for information is positively related to the individual’s level of knowledge. For instance, having a high level of general knowledge about cars should help an individual search for information on the internet because that individual will know more salient keywords to use as search terms and will be better able to filter out irrelevant information [32,33]. In a study measuring product knowledge and its effect on product decision making with regard to motorcycles, Mitchell and Dakin [34] concluded that individuals with higher levels of product knowledge were able to evaluate directly the appropriateness of each presented motorcycle for the particular usage situation while novices tended to directly compare attribute values of the presented motorcycles in making their choices. Web novices made more mistakes when conducting an online information search by utilising keyword queries, resulting in more query reformulations and increased search time.

However, while product class knowledge positively influences the ability to search, ability is distinct in that an individual may possess a very high ability to search for information (say a very experienced researcher), and a low level of knowledge. In discussing information search using the internet, the distinction between product knowledge and the ability to search can be easily clarified. Someone may have a considerable amount of experience with automobiles and through that experience have developed a high level of product knowledge; however, he/she may have little experience using the internet and may not be familiar with search engines, company-specific pages, etc.

As one’s ability to conduct an interactive search increases, the amount of interactive search should increase because the results of the search are better. Thus, the costs–benefits ratio will shift making the relative benefits greater for the interactive search than for individuals with less ability. Navarro-Prieto et al. [35] found that high experience web searchers tended to plan their searching behaviour ahead of time, while novice users tended to do little planning and were more driven by external representations. Hölscher and Strube [36] found that web experts were more likely to examine target documents than web novices. Both of these studies support the contention that ability to search increases the efficiency of an interactive search. Therefore, we propose the following:

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Proposition 2: Knowledge has a positive influence on the ability to interactively search for information on the internet.

Proposition 3: Ability to search has a positive influence on the amount of interactive information search conducted by consumers.

3.2.3 Involvement

Involvement is the pertinence and relevance of a purchasing decision to a consumer, which determines the extent of the effort he or she will put into deciding what to buy [37]. In general, consumers become highly involved when considering products or services that are expensive, complex, highly self-expressive, or risky in terms of the costs associated with making a poor decision. Once consumers are highly involved, they have a greater incentive to search for information in order to ensure that they will make good purchase decisions.

Because involvement is directly related to motivation, as the importance of the purchase decision increases, the individual’s level of involvement will increase. Thus, consumers are more motivated to search for information because the decision is too important to make without adequate information. At least two studies have supported this proposition. Cho et al. [38] discovered that individuals who had a higher level of involvement with certain types of products were more likely to notice banner ads promoting these products. Steenkamp and Baumgartner [39] also suggested that individuals with higher levels of involvement had a significantly higher level of cognitive responses to a television ad than those with lower levels of involvement. Furthermore, individuals with higher levels of involvement experienced higher levels of tedium faster when seeing repetitive non-interactive ads as compared to those with lower levels of involvement. The implications of these findings are that individuals with higher levels of involvement will seek out interactive information to a greater degree, they will be more acutely aware of salient information to which they are passively exposed, and they will more quickly become bored with repetitive non-interactive ads. Thus, we propose:

Proposition 4: There is a positive relationship between involvement and amount of interactive information search conducted by consumers.

4 Linking consumer attributes to IA strategies

This section provides recommendations for implementing IA strategies based on customer characteristics (Knowledge, Ability, and Involvement). Table 2 summarises these recommendations in terms of the types of interactive advertising to utilise and specific advice for tailoring the strategies with appropriate content and display features.

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Table 2 General recommendations for the choice of IA strategy

Consumer characteristics

Recommended interactive advertising Specific recommendations

High knowledge Corporate websites Shop bots Targeted e-mails

Focus on product features (attributes) rather than benefits Design the interactive features of websites around the knowledge of the user Limit the use of graphics and sounds If it is a new brand, show side-by-side comparisons with existing brands to utilise the consumers’ experiential knowledge

Low knowledge Banner ads Pop-up, pop-under ads Intelligent recommendation agents

Focus on product benefits rather than attributes Try to achieve an emotional connection between the product and the consumer by using graphics, sound, etc.

High ability Corporate websites Utilise strong interactive capabilities Customers tend to use rational decision making Add keyword search ability on the website For highly motivated individuals, provide customisation and large amounts of product information For less motivated individuals, provide games, design tools, and other means of enjoyment Because of the high level of website customisation, corporate websites would be the best choice for this type of consumer

Low ability Targeted e-mails Banner ads Pop-up, pop-under ads Search engines

Customers tend to use emotional decision making Websites that have clear and consistent links to product information Pay for placement on popular search engines, such as Google and Yahoo! May need hyperlinks to get to website Banner and pop-up ads, as well as e-mails, may play well to emotional decision-making as well as providing an accessible link to the website

High involvement

For complex purchases

Corporate websites

For self-expressive purchases

Banner ads Pop-up, Pop-under ads

Provide detailed information Provide comparative abilities Links to pages giving detailed product information and decision reinforcement High level of customisation Corporate websites are needed for the high level of customisation, while collaborative websites may increase customer trust of comparative data

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Table 2 General recommendations for the choice of IA strategy (continued)

Consumer characteristics

Recommended interactive advertising Specific recommendations

Low involvement

Not recommended Brand name important Do not need detailed, specific information Information more promotional/persuasive in nature Focus on encouraging emotional connections, brand repetition Play on hedonic needs with games, interesting graphics, etc. The use of banner and pop-up ads can be used to build brand recognition and making brief personal connection The use of corporate web pages can be designed to play on hedonic needs.

4.1 Knowledge and IA strategies

Individuals with higher levels of product knowledge will be more apt to conduct an interactive search focusing on attribute-specific information. They are also more likely to be frustrated with extraneous information and displays. These individuals derive more benefits from attribute level information and advertising focusing on product attributes (i.e., features over benefits) [40]. Conversely, promotions targeting novices should focus on product benefits rather than product attributes (i.e., benefits over features). Maheswaran and Sternthal [41] went further and suggested that promotions and advertising geared toward experts should not discuss benefits, since it is better to let experts arrive at their own conclusions. In short, websites designed for individuals with higher knowledge levels should focus on providing attribute information and avoid providing too much extraneous information.

One company that has mastered this idea is National Semiconductor. National Semiconductor’s website (www.power.national.com) is geared towards its customers – professional engineers – who have high levels of product knowledge. The website is devoid of flashy banners, explosive graphics, and proclamations of the benefits that their products provide. Rather, the website lists the attributes of all available products and gives the engineers the opportunity to design their own power supply boards [42].

The preferred interactive advertising strategies to be used with product class experts are collaborative websites, company websites, and targeted e-mails that give detailed product class information. Taking the example of cameras, an online marketer could advertise on a website that gives unbiased product class information and information on specific brands and models. The camera retailer could also use its own corporate website as well as targeted e-mails to provide product class information to develop a positive reputation and relationship with potential customers. Potential customers will, most likely, discount specific model and brand information coming from a perceived biased source, so it is important to present information in a non-biased manner.

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4.2 Ability and IA strategies

Online marketing efforts should focus on matching a consumer’s ability to search with the level of ability required to access information. For higher-ability consumers, firm-specific websites that offer good search capabilities would be the most effective online advertising tool. For consumers who have lower ability, online marketers should utilise clearly marked links, e-mail advertisements, and possibly banner and pop-up ads to drive consumers to the appropriate IA. Lower ability individuals may lack the ability to conduct an effective key-word search, thus links on web pages should be logically ordered (i.e. in alphabetical order, product categories based on popularity, etc.) and links should be consistent throughout the site in order to make it easier to find information [43,44].

4.3 Involvement and IA strategies

Taking advantage of increased involvement levels is a balancing act. Websites for high involvement items should be designed to create a positive search environment. This means providing the right amount of information. Too much irrelevant information takes away from customers’ ability to differentiate the product from other offerings; as a result, customers focus on price [45]. Highly involved individuals tend to also have a high need for cognition [46]. As such, providing too little information can cause the consumer’s desire for information to go unfulfilled in which case he or she will search elsewhere. To address the need for cognition for more highly involved consumers, websites should contain hyperlinks to detailed product specifications, pictures, testimonials, and e-mail addresses of satisfied users.

The choice of the appropriate type of interactive advertising is also determined by what drives consumers’ levels of involvement. If the product offering is complex, consumers will, most likely, focus on attribute level information when making a decision. Thus, corporate websites are a good choice. Online marketers should follow the lead of their brick and mortar counterparts by providing high levels of attribute information to the customer for their search. Websites for automobile manufacturers have done a good job by providing information similar to what would be found on car lots. If a highly self-expressive product drives the level of involvement, the use of banner and pop-up ads can be used to boost the emotional, self-concept enhancing appeal of the product through catchy, colourful ads that target the need for expressiveness of the individual.

Finally, for lower involvement products (e.g., groceries, detergents, etc.), a low cost non-interactive search, is generally preferred. In these cases there is little need to provide the level of information desired with a high involvement item. Rather, the manager’s resources and efforts should be focused on providing more exposure and building brand awareness through non-interactive promotion.

5 Conclusions

The development and wide usage of the internet has increased the importance and application of interactive advertising. It is estimated that online advertising expenditures will reach $21 billion by 2004 [1], with an estimated growth rate in spending approaching 100% per year from 2000 to 2005. Previous research has not provided a comprehensive

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evaluation of the situational effectiveness of various IA strategies. This paper contributes to our understanding of this important investment and provides managers with valuable insights into proper investment decisions for their IA programs. We proposed that three consumer-related characteristics (knowledge, ability, and purchase involvement) are critical to the level of interactive information search consumers are likely to undertake. Based on the support of the literature and industry examples, we recommended appropriate interactive advertising strategies, providing guidance for selecting the types and the content of IA under different circumstances.

5.1 Theoretical contributions

This paper contributes to theory in a number of ways. First, we have shown how consumer information search theory can be adapted to interactive information search, developing specific propositions in regard to the impact of knowledge, ability to search, and product involvement on the level of interactive search. Focusing on interactive search as opposed to a more passive search is an important distinction and an advance over existent literature, which treats all external searches as equivalent [47]. Clearly, an interactive search is distinct from a more passive search process in which new information is paid attention to, but no new information is actively sought out. Thus, this paper contributes to theory by distinguishing between passive and interactive external information search. Second, we have clearly linked the consumer information search process to appropriate interactive advertising strategies. This is critical given the pervasiveness of the internet as a source of advertising and as a source of information. Past studies have noted that often individuals purchased cars without conducting any information search (e.g. [48]), yet today it is estimated that over two-thirds of all new car buyers conduct research on the internet prior to purchase [49]. Finally, we provided an avenue for future research on the nature and effectiveness of IA strategies based on consumer behaviour theory.

5.2 Managerial implications and contributions

There has been little the literature could offer to managers regarding which internet advertising strategies they should spend their limited resources on. This paper describes the most common types of interactive advertising currently being used on the internet, including a discussion of their strengths and weaknesses. In addition to these contributions, this paper provides solid, theoretically grounded recommendations for which types of IA strategies are most effective based on the knowledge, ability, and involvement of the target customers. By assessing the level of these three characteristics in their target market, firms can better make IA implementation choices.

Additionally, we provide specific suggestions for managers regarding the content and design of the IA, which are summarised in Table 2. As an example, we suggest that firms use three types of IA when their target market is highly knowledgeable: corporate websites, shop bots, and targeted e-mails. We further suggest they limit usage of graphics and sounds with these media, since high knowledge consumers are typically extremely task-oriented and would not want to spend time on non-productive content. With these consumers, firms should focus on presenting product features rather than product benefits, and with new brands, utilise side-by-side comparisons with existing brands.

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Many small and medium-sized firms using IA may not have a good understanding of various IA strategies available to them and may have very limited resource to invest in their own IA programme. Very often managers adopt an IA strategy based on resource and technology availability without fully understand the effectiveness of the selected strategy. The information presented in Tables 1 and 2 will be very helpful to managers in aligning their resources, target market, and IA programme.

5.3 Limitations and directions for future research

It should be noted that, while this paper is thoroughly grounded in existent theory and based on the practices and experiences of many firms, our suggestions have not been empirically tested. Thus, we suggest that future research examine our suggestions empirically. In addition, there may be other consumer-related characteristics that predict interactive information search patterns that we have not considered. Other factors should be examined to determine their impact on the implementation and design of IA strategies. For instance, some consider motivation to be a factor that is distinct from involvement. Thus, the non-linear relationship between knowledge and information search level may be explained in that this relationship is mediated by motivation to search.

While we focused on the five most common forms of IA in current usage, other types of IA may exist and new types will certainly be developed in the future [7]. Additionally, our recommendations are based on the effects of knowledge, ability, and involvement independent of one another. There may be an interaction between these factors that would result in different recommendations. Future research should examine the interaction effects between these three factors. For example, there is some indication that level of involvement may have a greater impact on the level of interactive search undertaken than the level of knowledge or ability [50]. It is likely, that when involvement is very low, even if ability and knowledge are high, very little if any interactive search will take place. In which case spending money on IA may not be the most effective promotional tool.

Acknowledgement

We thank the reviewers for their helpful comments. This research was partially supported by a Kansas State University, College of Business Administration Summer Research Grant received by the first author.

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