One of the research priorities proposed by the American Marketing Association in the 2014-2016 period was proving the value of marketing management in organisations (Marketing Science Institute, 2014). The global competitiveness index presented by the World Economic Forum (2018) showed that among private and governmental organisations managers in Colombia, there is a perception of a greater intensity of competition, a greater degree of consumer orientation and greater interest by differentiation; these issues encourage the implementation of marketing actions and therefore motivate the continuous improvement of marketing processes.

One of the most important marketing elements is investment in advertising, which is expected to increase to $630 billion worldwide by 2018. Therefore, optimal management of advertising resources is a key metric for organisations to use in evaluating marketing performance. Following this perspective, academic research on advertising has mainly focused on showing (1) the decisive factors of advertising effectiveness among the audience; and (2) ways to facilitate organisational decision-making related to resource allocation (Eisend and Tarrahi, 2016; Hutter and Hoffmann, 2014; Kim and Han, 2014; Ortiz-Rendón and Moreno, 2017).

Furthermore, in a less generalised form, another research line aims at explaining how advertising management processes are carried out and how theoretical advertising models influence decisions. For example, Gabriel, Kottasz and Bennett (2006) examine the degree to which account planners use theoretical models to assess how advertising works. Their results show that the differences between the models used by advertising agencies and the theoretical models stem from resource constraints, time pressure and lack of well- trained staff. In the Colombian case, it is argued that the creative identity required for advertising campaigns remains underdeveloped due to the commercial characteristics of the advertising industry, the economic difficulties experienced by the population and the country's social conflict (Roca, Wilson, Barrios, Muñoz-Sánchez, 2017).

It has also been shown that the advertising management carried out by advertising agencies and organisations focuses on attaining optimal levels of creativity in their campaigns (Behboudi, Hanzaee, Koshksaray, Tabar and Taheri, 2012; Hill, 2006) rather than on relating the impact evaluation of the designed advertisements; this reflects a tendency to base their decisions on basic advertising theories and results obtained during previous campaigns. The consequences of not taking advantage of lessons learned are evident in the academic literature (Brennan and Vos, 2013; Nyilasy and Reid, 2009).

Process management is an essential task for organisations because it improves internal efficiency and changes how they function (Shtub and Karni, 2010). In the particular case of advertising, improved management will lead to attainment of the expected results and allow decisions to be made based on more reliable information during the IMC process; this will integrate the brand's strategic management, audience definition, communication channels and result assessment (Kliatchko, 2005). In addition, by studying marketing communications' management along with its objectives, results, and the role of organisations (Christensen, Firat, Torp, 2008; Einwiller and Boenigk, 2012; Smith, 2012) can create new opportunities for IMC such that academics and professionals can increase the effectiveness of their promotional activities (Patti, Hartley, Dessel, Baack, 2017).

As the above discussion, illustrated, little evidence exists about how organisations manage their advertising activities. This is further demonstrated by the fact that the research units of analysis are mainly the audience and the advertising agencies (Kim, Hayes, Avant, Reid, 2014); such researches tend to overlook advertiser organisations' perceptions, which play a fundamental role in investment decisions.

Finally, t given that few studies have examined how companies manage their advertising campaigns, it is therefore necessary to analyse this process. Accordingly, this paper aims to analyse how the conduct of advertising planning marketing managers is influenced by factors such as types of consumer responses, measurement methods used and expected results among Colombian Companies.

This article is structured as follows, the first section overviews the theoretical framework on advertising management and presents the approach of five research hypothesis. The second section details the exploratory empirical methodology based on conducting a telephone questionnaire with 150 marketing managers at medium and large companies in Colombia. Third, the results are presented. The results are then discussed and the managerial implications of the research are presented.

Based on (1) the role that marketing managers assume when managing resources and (2) the importance of improving organisational processes, IMC's results are a key element organisation should consider when making decisions regarding advertising investments (Porcu et al., 2012; Reid, 2005). Outcomes are a pillar of IMC, which is focused on evaluating (1) the effects on consumers and their responses and (2) the financial results that influence the organisational results (Kliatchko, 2008; Patti et al., 2017; Tafesse and Kitchen, 2017). Assuming a financial orientation for measuring advertising, outcomes leads an organisation towards the design of metrics that provide greater certainty when deciding the future allocation of scarce resources and can even establish compensation elements for advertising agencies (Swain, 2004). In addition, measuring advertising effectiveness requires methods that ensure IMC programmes are able to focus on profitable customers and the media that will influence them. Therefore, the IMC results are assessed by considering the expected consumer responses, the expected results and the measurement methods used.

Consumer insight in planning advertising campaigns is important in order to attract consumers (Sánchez-Blanco, 2010) because it can guide designers in adapting advertising communication elements and linking the types of response expected. Marketing professionals must therefore research consumer behaviour by analysing their responses and improving the definition of communication objectives (Seric and Gil-Saura, 2012).

Measuring the results of marketing communication programmes against established targets has always been standard practice for business organisations. Given that IMCs are a process, its components can be considered as antecedents and consequences (Kliatchko, 2008; Tafesse and Kitchen, 2017). The antecedent elements are integrated into the planning and execution of new IMC programmes (because these programmes include a measurement, evaluation and analysis feedback mechanism that will impact future approaches). Accordingly, the improvements, changes and other adjustments made in response to the findings of the analysis, subsequently act as consequences.

Although IMC has a proven capability to provide positive returns, create value, foster relationships with stakeholders and generate competitive advantages (Jiménez, 2006), it is also clear that communication budget managers are under pressure. to quantify the impact of these activities (Rust et al., 2004). Therefore, based on the expected results, managers plan advertising campaigns and allocate the required resources and capabilities. Although from the theoretical point of view, the first step is planning, changes can occur in practice, which is also supported by the lack of generalised conceptual clarity regarding management of IMC (Porcu et al., 2017).

Therefore, IMC's results constitute the inputs for advertising campaigns planning exercises. In accordance with the above, the following hypothesis are proposed:

H1: The types of expected consumer responses influence the planning of advertising campaigns.

Academics and organisations sought to quantify the degree to which advertising influences consumer behaviour and what reactions it provokes at cognitive, emotional, attitudinal and behavioural levels (Eisend and Tarrahi, 2016). In order to assess these reactions, effective measuring methods must be applied according to the expected type of consumer response. An advertising campaign may have different objectives and consequently, different types of expected responses (Beerli and Martín-Santana, 1999). For example, researchers mostly assess campaigns based on memory or advertising recalling (cognitive response), attitude towards the brand and ad (affective response), and purchasing intention (conative response) (Kim and Han, 2014).

Gabriel et al. (2006) demonstrate how advertising agencies use methods to measure advertising effectiveness that are related to the hierarchy of effects, albeit with some variations. Even though some advertising agencies resist understanding their output in this way, it is useful to classify these measurement methods according to the advertising campaign's objectives. According to Ferrer (2006), advertising organisations and agencies assess advertising effectiveness based on the campaign's objectives and therefore, the types of response they expect from the target audience. These are usually evaluated based upon variations in sales levels and secondly, brand recall and awareness. In accordance with the above, the following hypothesis are proposed:

H4: The types of responses expected from the consumer influence the measurement methods used to assess advertising management.

According to the hypothesis proposed, Figure 1 shows the conceptual model that will be validated (See Figure 1)

Figure 1 Source: Own elaboration

To test these hypothesis, the cross-section survey methodology was used. The units of analysis of this study are medium and large companies located in Colombia because these types of companies are especially prominent in terms of their investment in advertising (Pérez, 2016) and levels of sales department (Superintendencia de sociedades, 2015). Marketing managers directly involved in investment decisions in marketing, specifically in the allocation of resources for advertising investment, were contacted. Surveyed organisations had implemented at least one advertising campaign in the last 6 months. In total, 162 surveys were completed, but I2 surveys were discarded because they presented inconsistencies in the answers (such as marking the same score for each question).

The fieldwork was carried out between August and October 2016. The sample was distributed as indicated in Table 2. According to the Departamento Administrativo de Estadísticas (2017), the large companies comprise 9% of the overall business market, and medium companies comprise 22%. This means that the sample in this study had a large company participation rate close to 30% (31.33%). Economic sectors and metropolitan areas were not determining variables in the study but they demonstrate its scope.

Table 2

Source: Own elaboration

A questionnaire was initially designed using the scales from previous studies (see Appendix 1) and evaluated by seven marketing and advertising experts; its goal was to assess each statement based on its relevance and wording, to determine if they adequately represent the construct. The evaluation of the experts used the following scale: I =eliminate the answer, 2 = modify it and 3 = maintain it. The validity coefficient was calculated to measure the degree of agreement among experts; the result of the evaluation was to eliminate 6, modify 21 and maintain I2 of the observable indicators. The final version of the questionnaire was implemented by telephone to marketing managers because they have a stronger role in the decision-making processes regarding advertising investment. However, some surveys were directed to administrative positions in charge of this type of decisions.

Regression analysis of the latent variables used in this study was carried out using the Smart-plus 3.0 PLS program, based on the partial least-squares optimisation technique (PLS), a multivariate analysis recommended for testing exploratory models (Escobar-Rodríguez and Carvajal-Trujillo, 2014; Kiwanuka, 2015; Matute Vallejo, Polo Redondo and Utrillas Acerete, 2015). The data analysis was conducted in two stages. In the first stage, the measurement model was assessed, and the second stage assessed whether the structural model predicts the proposed relationships.

First, the model was found to fulfil its predictive capacity because all R2 values are greater than 0.1 (Hair, Hult, et al., 2014). The validity of the dependent variables' effects over the independent variables was checked via resampling. Bootstrapping was performed with 5,000 subsamples taken at random to act as a contrast for the significance of the model's parameters (Hair, Hult, et al., 2014). However, the low value of R2 means that the model is not able to predict outcomes. Therefore, more explanatory variables should be added in future studies.

Table 7 presents statistics that the relations between constructs. The partial least-squares optimisation model's results reject Hypothesis H2 = β: 0.011 (p-value = 0.869). Therefore, effect of methods used to measure an advertising campaign's effectiveness do not have a significant impact on the planning of future campaigns. Hypothesis H4 = β: 0.110 (p-value = 0.214) is also rejected, indicating that the effect of the consumer's expected responses on the methods used to measure advertising effectiveness is not significant. However, Hypothesis HI = β: 0.278 (p-value = 0.00) is accepted, indicating that consumer's expected responses have a significant impact on the planning of advertising campaigns. Hypothesis H3 = β: 0.333 (p-value = 0.00) is also been accepted, thus upholding that the expected results do have a significant influence on the planning of advertising campaigns. In addition, Hypothesis H5 = β: 0.270 (p-value = 0.01) is also upheld, validating the relevance of the expected results' effect on methods used to measure advertising effectiveness. In addition, although relations are found to exist between non-relevant constructs, all relations are positive. Figure 2 summarises the conceptual model's results and hypothesis proposed.

Table 7

Source: Own elaboration

Figure 2 Source: Own elaboration

According to the proposed model's results (see figure 2), there is no empirical basis for claiming a significant relation between the methods used by organisations to measure advertising effectiveness and how those organisations plan future campaigns. Similarly, no relation was found to exist between a campaign's results and the methods used to measure those results. The inverse relationship of these variables was also analysed, but no significant relation was found (β: 0.028 p-value = 0.72). Therefore, it can be shown that organisations are not linking these variables because they place more priority on directly assessing the impact of campaigns in terms of achieving the expected results; they give little attention to assessing the intermediate components that could improve management of the advertising process.

On the other hand, organisations consider it important to plan advertising campaigns based on the responses they expect from consumers and the market. The previous analysed results fail to establish whether the methods used to measure advertising effectiveness are related to advertising management.

Previous studies support that organisations use the expected results and types of consumer responses to support campaign planning (Nyilasy and Reid, 2009). These are inputs to a feedback process derived from experience implementing past campaigns as aligned with organisational objectives. It has also been confirmed, in an exploratory manner, that organisations assume that the results expected from a campaign should determine (to a certain extent) the methods used to measure the effectiveness of brand communication (Ferrer, 2006)

These findings also indicate that methods used to measure advertising effectiveness are less influential within the management process analysed in this study. This has also been shown in previous studies, which suggest this issue acts as a barrier to measuring and evaluating advertising campaigns (Ebren, Kitchen, Aksoy and Kaynak, 2005). In general, advertising expects medium- and long-term results and additional investments are needed to collect the data that allow for these results to be calculated (Petersen et al., 2009). This is one reason why organisations are more focused on measuring advertising effectiveness in terms of sales, i.e., because this information already exists and can simply be subtracted from financial statements; it does not require another type of investment or measuring method. This result contradicts the advertising theory basis, which outlines in detail the measurement methods that organisations must conceive to reliably evaluate the effectiveness of advertising (Beerli and Martín-Santana, 1999).

According to the above findings, the persistence of the gap between theory and advertising practice fostered by the short-term focus on process management is evident because practitioners give little value to marketing management and to the results of academic research (AMA Task Force, 1988; November, 2004; Southgate, 2006).

For this reason, it is necessary to regard organisations as a unit of analysis and link them to academic research on advertising management because the responsibility for measuring advertising effectiveness cannot rest solely with advertising agencies (Porcu Del Barrio-García, Kitchen, 2017). It cannot be overlooked that organisations are responsible for marketing budgets and that they expect to use those budgets to make an impact in the market, which in turn will generate organisational value. In addition, they behave as an agent who integrates the creative team, the media, and the measurement of results. Comparing advertising management in organisations with the processes used in advertising agencies will help align efforts and determine each party's objectives in interpreting the scope advertising beyond the creative component of announcements (Behboudi et al., 2012).

Research on advertising management in organisations is scarce. For this reason, this study offers a relevant contribution in this field by exploring the relations among factors surrounding advertising management in Colombian organisations, with a focus on factors that are supported by IMC theory. This study is empirical and exploratory, and it expands existing knowledge, with academic and organisational implications. From an academic point of view, organisation's reluctance to apply measurement methods to the advertising processes, an action that would require investment of marketing research resources by the organisations, can be extended to the scope of IMC. This lack of evaluation detracts from the MIC's usefulness and serves as a reason why the lack of consensus regarding its theoretical delimitation has become widespread (Porcu et al,, 2017).

From an organisational point of view, there are weaknesses in implementing measurement methods that could properly calculate organisational results concerning advertising investment. Hence, it is important that organisations incorporate metrics into advertising management to measure the expected results in the target audience and market, according to the organisation's capacity and beyond only sales goals. As a consequence, organisations must take the risk of proposing measuring methods that, despite of involving additional investments, provide reliable information and thus, facilitate future decision-making. This approach will positively demonstrate the value of marketing because it provides rigorous marketing processes by including not only financial metrics but also attitudinal and behavioural metrics (Hanssens and Pauwels, 2016).

If organisations measure the level of compliance with the goals established in terms of IMC, they will make better decisions and allocate marketing budgets consistent with their objectives, resources, capabilities; the improvement of their advertising management systems will positively impact the reduction of uncertainty levels by better measuring the return on advertising investment. From an academic perspective, it is necessary to continue exploring organisational barriers to using measurement methods in their processes.

This is especially relevant in advertising management for the purpose of testing the impact that CIM has on the generation of organisational value. Future research may also establish control variables such as the life cycle of brands and organisations, the size of organisations or the type of marketing strategy implemented (among others) to assess whether these are determining aspects in managing advertising (Reid, 2005). Furthermore, including in the IMC the perspective of roles other than marketing managers that also influence the decision-making process can be useful to extend the theory.