The relationship between emotional intelligence and sales performance in a business-to-business environment; with implications for cross-cultural adaptability

The relationship between emotional intelligence and sales performance in a business-to-business environment; with implications for cross-cultural adaptability

The existing empirical findings on the connection between emotional intelligence (EI) and sales performance are inconsistent. Possible reasons are examined: The non-linearity of the relationship between EI and sales performance as well as the interaction of EI with professional skills and demographic variables. The empirical research was conducted as a census of sales representatives within the Austrian branch of an international company in the construction sector. Data was collected using three different methods to reduce effects appearing from method variance. Hierarchical regression modeling including three-way-interaction analysis was applied. Results show a direct relationship between EI and sales performance in the form of an inverted ‘U’ as well as moderating effects of EI on the relationship between selling (but not technical) skills and sales performance. Higher order inter-action analyses reveal compensation effects of professional experience, age and education as well as EI. Younger sales representatives, such with less experience, and those with less formal training use EI more strongly to turn their selling skills into sales success. Implications for marketing and sales practices include: EI contributes to sales performance in B2B companies, also in the construction sector, often referred to as ‘unemotional’. The effect is non-linear, which means that the ‘the-more-the-better’ paradigm is to be critically questioned when selecting sales staff. For tasks requiring a high percentage of technical competence, the effect of EI is less (it can even be negative) than in tasks that primarily require sales skills. Sales and marketing managers should consider EI in recruiting and personnel development. Particular attention should be paid not only to sales staff with weak, but also to those with very strong EI levels. As the results of this study are subject to high cross-cultural variability, thoughts on potentially different results in other than the Austrian cultural zone are provided.

1 Introduction

Personal selling contributes to success in business-to-business industries (Singh and Koshy 2010). Effective job performance arises when the person’s capabilities are consistent with the job demands and the organizational environment (Boyatzis 2008). The „ideal” salesperson should exhibit both job-related skills (i.e. knowledge, technical, and professional abilities) as well as emotional intelligence (EI) related competencies and experience in order to perform their jobs efficiently. However, salespeople might vary to the extent in which they exhibit these competencies. Prior research has extensively investigated the direct effects of EI and performance, of EI and skills, and of skills and performance. However, compound effects and interactions of those variables have been rarely examined. Grounded in the work on trait emotional intelligence (TEI) (e.g. Petrides 2010b; Boyatzis 2008) model of performance, and on self-efficacy theory (Bandura 1977), this paper proposes a conceptual framework in the B2B sales context that examines direct and interaction effects of EI with skills, job experience and education, and their effect on sales performance.

2 Conceptual framework and hypothesis development

Our conceptual framework proposes direct non-linear effects, two-way interactions of sales/technical skills and TEI in explaining the variance of sales performance as well as three-way higher-order interactions including sales experience and formal education. Below, we elaborate on the major components of our conceptual framework followed by our hypotheses.

2.1 Trait emotional intelligence

EI plays a role in performing sustainable exchange processes (Lawler 2001). TEI theory is based on the concept of emotional self-efficacy, comprising self-perceived skills and behavioral dispositions on lower levels of personality hierarchies (Reichert 2013, p. 28). In contrast to ability measures which compare the measured levels of EI with an externally determined „maximum value”, TEI theory states that the relevance of different EI profiles can vary with contexts (Petrides 2010a). TEI theory is applicable for analyzing sales performance and its predictors because (i) it abandons the idea of measuring against a predefined „maximum” level of EI, and accepts the subjectivity of emotional perception and emotional self-efficacy, (ii) it is applicable throughout different contextual settings, and (iii) prior operationalization of TEI across disciplines provides evidence of solid psychometric properties.

2.2 Sales skills, technical skills and sales performance

In technical sales, sales people are required to present and explain technical products, solve customer problems, and sell complex products and services to create revenue and accomplish their planned targets, which necessitates the use of both sales presentation skills and technical skills. Selling skills are learned proficiencies at performing job activities. They are important determinants of job performance (Churchill Jr. et al. 1985). Such skills include both technical skills (i.e. technical knowledge, specialist knowledge and knowledge about the company’s products/services etc.) as well as sales presentation skills (i.e. knowledge about sales procedures, handling customers and their objections, abilities to convince the customer to buy etc.). Ultimately, sales performance is what is expected of sales people (Campbell et al. 1993). Our measure of salesperson performance is derived from the company’s database and ensures that salespeople are evaluated against factors which they can control (Cravens et al. 1993), while controlling somewhat for external artifacts (e.g. economic situation, competitive or customer-based volatility etc.).

2.3 Non-linear relationships

Influential ancient philosophers like Aristotle, Socrates, or Confucius have introduced concepts like „happy medium” or „doctrine of the mean” (cf. Phillips 2011 or Legge 1983). However, modern management literature and research only scarcely discusses this phenomenon. Most contributions refer to the „shortage”, only few address the „excess” of characteristics. This is why the assumption of „the-more-the-better” still serves as a paradigm in many models, hypotheses, and statistical procedures, meaning that maximising the input automatically leads to maximization of the output. With respect to emotional intelligence, Salovey und Mayer (1990, p. 198) warned of this ambivalence:
„On the positive side, they may enhance their own and others’ moods and even manage emotions so as to motivate others charismatically toward a worthwhile end. On the negative side, those whose skills are channeled antisocially may create manipulative scenes or lead others sociopathically to nefarious end.”
Also, the overstimulation hypothesis helps to understand, why too high levels of certain professional characteristics may lead to a hyperstimulation and hence are dysfunctional for performance (Singh 1998, p. 72):
„[…] there is an overstimulation effect, so that excessive levels of job characteristics, including feedback, participation, variety, and autonomy, hinder rather than help a person’s performance.”
Kopelman et al. (2006) emphasized the „strategic display of emotions”. Negotiators might consciously use emotions in difficult situations, e.g. to motivate a non-co-operative negotiating partner to cooperate. Thus, the targeted use of emotions is also a basis for negotiation strategies and tactics. On the one hand this is a crucial tool for negotiators who rely on their intuition, on the other hand negotiators can try to „fake” their own emotions and their feelings about themselves, and act „strategically”, or sometimes dishonest in order to influencing their counterpart’s behaviour. The effect of emotional intelligence on performance in this case depends on whether the manipulation is detected or whether there is at least a suspicion of manipulation and therefore uncertainty increases (Kopelman et al. 2006). Another phenomenon to be mentioned in the context of the present study concerns the expression of „played” emotions, which is discussed in the literature as „surface acting” (Mikeska et al. 2015). With „surface acting”, a person tries to change her behaviour in such a way that it corresponds to their expected emotional expression of the counterpart. It shows emotions that are not felt in this way. True emotions are suppressed and unimagined emotions are simulated. For example, a salesperson can be friendly in talking to an angry customer, even though he does not have that feeling in the moment (Grandey 2003).

3 Direct and indirect effects

Based on sales efficacy theory (Bandura 1977) and Petrides‘ (2010a) theory of emotional selfefficacy, a direct relationship of sales performance and emotional intelligence is assumed. Performance is related to self-efficacy, namely the trust that one’s own traits, skills and knowledge help to achieve goals. This is also supported by dual process theories (cf. e.g. Chaiken and Shelly 1980; Cacioppo and Gardner 1999; Evans 2003; Kahneman and Tversky 1979) and trait activation theory (Tett and Guterman 2000). However, the theoretical, conceptual and empirical contributions on non-linear relationships shape our argument in a way that there is an optimum level of TEI, which is located at the inflection point of a curved regression line. Below and beyond this level of TEI, performance declines: H1: The relationship of TEI and sales performance is inverted U-shaped, i.e. with increasing levels of TEI, performance increases, and, at a certain inclination point, performance decreases again with increasing TEI.

3.1 Interaction of EI, sales skills/technical skills and sales performance

Past research tested effects of either EI and sales performance, sales skills and sales performance, each bilaterally, independently, and with inconsistent findings. Whereas some work finds a positive relationship between EI and performance (e.g. Kidwell, Hardesty, Murtha, and Sheng 2011; Lassk and Shepherd 2013), other research has reported only a weak relationship between the two constructs. The relationship between skills and sales performance also exhibit a large amount of variation. Consequently Churchill et al. (1985) suspect „that one or more variables moderate the relationship between skill level and performance” (p. 109). We, thus, argue that the inclusion of additional interaction variables might shed more light on these inconsistent relationships. Self-efficacy theory provides the background for the proposed interaction effect of EI and skills. Emotional self-efficacy is the belief of a person that he or she possesses the emotional traits and abilities to accomplish the task given to him/her successfully (Petrides 2010b). A salesperson who is aware of his/her abilities and uses emotions to deal with the customer in an appropriate way, will exhibit better performance when using his/her acquired skills (Barling and Beattie 1983). It is argued that TEI interacts with skills in explaining performance. The following hypothesis is proposed: H2: Trait EI moderates the relationship of (a) sales skills, and (b) technical skills with sales performance. Higher levels of trait EI increase the effect of sales/technical skills on sales performance.

3.2 Higher-order effect of sales experience

Sales experience refers to a sales person‘s gaining of wisdom through sales encounters, discussion, and negotiations with different clients as well as the experience of success or failure of various sales strategies which accumulate over time (Ramendra Singh and Gopal Das 2013). Distinguishing between inexperienced and experienced sales people, Bartkus, Peterson and Bellenger (1989, p.15) state that „It is possible that inexperienced salespeople perform well by working harder while experienced salespeople perform well by working smarter.”
The interaction of experience and skills can be explained through learning curve effects (Leslie and Holloway 2006) wherein, salespeople, for example, share analogies and cases that they experienced with earlier customers to substantiate their current solution offerings (Wierenga and van Bruggen 1997). As such, it can be argued that, if experience and skills accumulate, the influence of additional components might naturally decrease. Hence, the more experienced a sales person is, the less he/she is dependent on additional traits or competences and TEI and experience reciprocally heighten each other’s influence on the skills and performance relationship. We state: H3: The interaction of trait EI with (a) sales skills and (b) technical skills and sales performance varies with the level of sales experience. With higher levels of sales experience, the moderating effect of trait EI decreases.

3.3 Higher-order effect of formal education

Education refers to the credentials or degrees an individual has obtained through educational facilities. Prior research has established a positive linkage between education and sales performance (Bolander, Bonney and Satornino 2014). Education is also related to selfefficacy, i.e. the belief of a person to be equipped with the abilities that are necessary to act in a way which is beneficial for achieving his/her goals (Bandura 1977). Self-efficacy should help sales people to be convinced of their potential and should allow sales people to better exploit their capabilities, and thus strengthen the relationship of skills and performance. Trait EI has been equated to emotional self-efficacy (Petrides, Pita and Kokkinaki 2007). If formal education is high, self-efficacy is established, and the positive effects of education and TEI may cancel each other out. As such, we can postulate: H4: The interaction of trait EI with (a) sales skills and (b) technical skills and sales performance varies with the level of formal education. With higher levels of formal education, the moderating effect of trait EI decreases.

4 Methodology

The study was conducted among sales people of the Austrian branch of an international company developing and marketing products and services for the construction industry. The company employs a personal selling approach, which puts the salesperson and his/her competencies, traits and skills in the center of the company’s revenue generation efforts. Three data sources were used in order to avoid common method variance issues. To assess trait EI, sales people were asked to complete a paper-and-pencil questionnaire (N=85). To make the questionnaires identifiably and to be able to connect the results with the supervisors’ evaluation and the company records, the respondents added their staff number.
The majority of the sample were male (92.8 percent), mean age was 35.5 years (min = 21.0, max = 61.0, SD=9.48). The average experience in sales was 10.94 years, the tenure with the current company was 8.24 years and the highest completed education was 67.0 percent primary/vocational education, 17.0 percent secondary education, and 16.0 percent tertiary education. Sales people’s sales and technical skills were measured through the assessment of the supervisors. Each supervisor manages 5-7 sales people, with whom he/she is in ongoing personal contact via group and individual meetings. Supervisors get feedback from customers about the behavior and performance of their sales people, and hence should be able to assess the skills of their sales representatives. As a third source of data, the company provided performance records.

4.1 Measures

Trait EI was assessed using the Trait EI Questionnaire (TEIQue), reported by Petrides and Furnham (2009). For the present study, the short version (SF) in German Language was used, which has been validated by Freudenthaler et al. (2008). Sales skills and technical skills were measured by scales developed by Rentz et al. (2002) and Johlke (2006). For objective performance, the company’s data warehouse provided a ratio of planned and actual contribution margins per sales person based on past performance (min=.67, max=1.33, mean=.9598, SD=.144).
Contribution margin was used instead of turnover, as it more directly contributes to company performance and as it is more robust against outliers and large single sales. Education was provided by the sales representatives and was coded categorically with two values, labelled „low” and „high”. Low education means completed basic education including vocational education. High education means completed high-schools with A-Levels (equiv. „Mature/Abitur”in the German speaking area) or a university degree, starting form an undergraduate („Bachelors”) degree. Sales experience in years/month and tenure with the company in years/month as sales representative was assessed through a self-report completed by sales representatives.

4.2 Results

Hierarchical regression analysis was performed to study the relationships. The first hypothesis intended to reveal a non-linear relationship between TEI and sales performance in the shape of an inverted U’. To analyze this relationship, a linear as well as a quadratic model was submitted to regression analysis. The results showed clearly that a quadratic model is better able to describe a significant relationship (β = -.602, T = -6.511, p = .000; R² = .299) than a linear expression (β = .056, T = .556, p = .579; R² = .034). Univariate ANOVA with three groups of EI – low, medium and high – F (2.,97) = 10.068, p = .000) and Tukey HSD-Post-hoc-test (lowmedium = -0.788, p = .002), (medium-high = .946, p = .000), (low-high = .1576, p = .763) support the assumption of a inverted U-shaped regression curve. As, such, H1 proposing a non-linear relationship in the form of an inverted U-shaped curve is confirmed.
In the second set of hypotheses, an interaction effect of TEI on the relationship of sales/technical performance and sales performance was proposed. As an independent variable, TEI had no significant effect on sales performance (β = 0.060; t = .623; p = .535). Sales skills had a significant effect on sales performance (β = 0.313; t = 2.361; p = .02). As an interaction variable on the relationship of sales skills and sales performance, the effect of TEI was significant (β = 0.430; t = 3.360; p = .001). The effect size was increased by 0.117 through the interaction. For technical skills, no significant direct and interaction effects were found. As expected at high levels of TEI, higher sales skills lead to higher performance. However, at low levels of TEI, an increase in sales skills leads to a decrease in performance.
The third set of hypotheses introduced a higher-order moderating effect of sales experience on the interaction of TEI with the skills-sales performance relationship. To analyze this effect, the dataset was split into two groups with (a) low, (b) high sales experience. Only for the group highly experienced in sales, significant effects were found. The interaction effect of TEI and sales skills on performance was significant at (β = 0.68; t = 3.69; p < .01). The direct effect of technical skills on sales performance was also significant (β = -0.36; t = -2.11; p < .01). However, this effect is negative, which means that, within this group, greater levels of technical skills lead to lower performance. This is a surprising result which needs more investigation.
Hypotheses 4a and 4b referred to the higher-order effect of formal education on the interaction of TEI with the skills-sales performance relationship. To reveal interaction effects, the dataset was split into two groups, primary education and secondary/tertiary education. Only within the primary education group, significant effects were found. In this group of sales people, sales skills have a direct effect on sales performance (β = 0.33; t = 2.14; p = .04). This effect is slightly higher compared with the whole sample (β = 0.31). Also there is a significant interaction effect of TEI and sales skills with respect to sales performance (β = 0.45; t = 2.70; p < .01). This effect is also slightly higher compared with the whole sample (β = 0.43). There were no significant relationships found with respect to the group comprising secondary and tertiary education.
High scorers in EI within the group with primary education only are able to transform sales skills to performance seemingly better than low scorers in TEI. The interaction effect of EI the selling skills – performance relationship is strong for the low education group (β = 0.45; t = 2.70; p < .01). Given the fact that within this group, a large majority has an education following the dual system of attending school and practical apprenticeship (which is very popular in the German speaking region, including Austria), this finding is interesting. It could be argued that with a lower level of formal education the effect of TEI becomes very important and perhaps compensates the lack of higher education, which provides confirmation to our hypothesis 4a.
Not hypothesized and because of curiosity, an additional analysis was performed. Two groups were defined within the dataset, one combining low education and high TEI, the other one with high education and low TEI. If TEI outperforms education, the sales skills – performance relationship should yield better coefficients with the low education/high TEI combination rather than with the high education/low TEI set. This analysis has to be interpreted with caution due to the small sample size within the groups (low Education/high EI: n = 35; high Education/low EI: n = 16). Analysis revealed a significant effect of sales skills on sales performance within the low education/high TEI group (β = 0.490; t = 3.23; p < .01). Within the high education/low TEI group, no significant effect was found.

5 Discussion

This research revealed some surprising and relevant relationships when analyzing direct as well as interaction and higher order effects. First, hierarchical regression showed that TEI does not have a linear positive effect on sales performance. Rather this relationship is curved and it has an inclination point that turns increasing TEI to the negative with respect to sales performance. As such, the relationship investigated follows the tradition of the „too-much-of-a-good-thing” effect.
Secondly, the effect of sales skills on performance increases with higher levels of the salesperson’s EI. Beyond that, at low levels of EI, higher sales skills can also negatively contribute to performance. As such, EI moderates the way in which a salesperson tries to convince the customer. Low levels of EI might lead to misinterpretation of situations, the sales person might (unknowingly) exert too much (or too little) pressure on the client, because the former is not able to read the latter’s emotional state and preparedness for closing a deal. Or, the sales skills exerted by the salesperson might not sound authentic to the buyer. The latter one might become mistrustful or hesitant.
Thirdly, sales experience leads to a stronger effect of sales skills on sales performance, and also the moderating effect of TEI on this relationship becomes larger with higher sales experience. Sales people with high levels of experience are better able to transform their sales skills into performance, and if they have higher levels of TEI, the effect is even larger. With respect to technical skills, the data shows a significant, but negative effect of technical skills on sales performance within the group of higher experienced sales people. Perhaps, high experience together with high technical skills leads to overestimation and arrogance in dealing with the customer, which the latter one does not appreciate.
Finally, the higher-order effect of formal education was confirmed only for the primary education group. A large majority of this group has enjoyed a dual education of attending school and practical apprenticeship (which is very popular in the German speaking region, including Austria). We argue that with a lower level of formal education the effect of EI becomes very important and perhaps compensates the lack of higher education.

6 The cultural variable

It might be considered as a limitation that this research has been conducted in own geographic and cultural area (Austria) and within one „company culture” only. When introducing cultural variability to this topic, two main aspects emerge. First, the relationship of culture and emotional intelligence: Which kinds of emotions are shown and how emotions are communicated differs across cultures. Emotional intelligence can be viewed as a crucial aspect for successful management. An interesting study provided by Gunkel et al. (2014) revealed a small but significant effect of cultural dimensions in explaining the variance for the four EI competencies. The second aspect comprises the relationship of sales performance and culture. In his seminal contribution, Salacuse (2005) describes the many „[…] ways that culture can affect your negotiation”, concluding that culture has an impact on how successful negotiations will be or not. Combing these two effects (culture on EI, culture on negotiation), it would be very interesting to analyze the effect of EI on negotiation under the interaction of culture. To do so, we suggest the following model for further consideration:

Figure 1: Conceptual model of EI and Sales Performance, cultural dimensions included.
Source: Author

7 Theoretical and managerial implications

The findings advance theory in marketing by providing a better understanding of the influence of trait EI on performance in a B2B selling context. Trait EI is a driver of sales performance, however, if available in excess, it might be detrimental for performance. Striving for ‘the-more-the-better’ with respect to TEI should be discussed with caution. Also, trait EI is a moderator of the skills-performance relationship, and low levels of EI not only weaken this relationship, but also turn it into the negative. Less formally educated sales people gain more from their EI than those with higher education. EI seems to be able to compensate for formal educational qualifications. For managers in the field of sales, marketing or HR, the study helps to better grasp the EI construct and its relevance for sales representatives. Considering the EI of sales representatives, measuring it, and perhaps, undertaking actions to increase the awareness for and the competences in EI, would be pertinent for recruiting and staff development practices in sales organizations. But on the other hand, an exaggeration in training of EI competencies might have negative effects as well. Avoiding extremes might be a good advice with respect to the key variable analyzed in this paper. Practitioners should take care of EI when recruiting staff members, and also when selecting them for training and promotion. They should take care of the fact that there is no „low” or „high” EI effectiveness, but just „right” or „wrong” jobs for people with specific EI traits.

8 Avenues for future research

As with most research, ours is not explaining „the world”. Some interesting prospects for future research are at hand. First, replicating the study with different businesses, company sizes and geographic areas would increase the variance explained and may also introduce additional interacting variables to be considered in future empirical work. Also increasing the sample size of sub groups should be considered in the future in order to improve the robustness of the findings. Additional independent variables such as cognitive abilities or customer orientation could enrich the model. Very important, the cultural variable needs empirical substantiation through additional studies. Finally, the perspective of the client should be integrated in future research. How do customers perceive their sales representatives’ EI, and how does this affect the buyer-seller-relationship beyond performance measured in this study? This is an important avenue for future research.

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Kľúčové slová/Key Words

emotional intelligence, sales performance, cross-cultural adaptability, sales skills
emocionálna inteligencia, predajný výkon, medzikultúrna adaptabilita, predajné zručnosti

JEL klasifikácia/JEL Classification



Vzťah medzi emocionálnou inteligenciou a predajným výkonom v prostredí B2B; s dopadmi na medzikultúrnu adaptabilitu

Existujúce empirické zistenia o súvislosti medzi emocionálnou inteligenciou (EI) a výkonnosťou predaja sú nekonzistentné. Vyhodnotené boli nasledujúce príčiny: nelinearita vzťahu medzi EI a predajným výkonom ako aj interakcia EI s odbornými zručnosťami a demografickými premennými. Empirický výskum bol realizovaný medzi obchodnými zástupcami v rakúskej pobočke medzinárodnej spoločnosti v odvetví stavebníctva. Údaje sa zbierali použitím troch rôznych metód za účelom zníženia vplyvov vyskytujúcich sa v metóde rozptylu. Využité bolo hierarchické regresné modelovanie vrátane trojcestnej interakčnej analýzy. Výsledky poukazujú na priamy vzťah medzi EI a predajným výkonom vo forme invertovaného „U“, ako aj zmierňujúcimi efektmi EI na vzťah medzi predajnými (ale nie technickými) zručnosťami a predajnými výkonmi. Interakčné analýzy vyššieho rádu odhaľujú kompenzačné účinky odbornej praxe, veku a vzdelania, ako aj EI. Mladší obchodní zástupcovia, ktorí majú menej skúseností a tí s menej formálnym vzdelávaním využívajú EI silnejšie na to, aby svoje predajné zručnosti premenili na predajný úspech. Dôsledky pre marketingové a predajné praktiky zahŕňajú tieto zistenia: EI prispieva k výkonnosti predaja v podnikoch B2B a to aj v odvetví stavebníctva, často označovanom ako „bez emócií“. Efekt je nelineárny, čo znamená, že paradigma „viac-lepšie“ sa pri výbere predajcov kriticky spochybňuje. V prípade úloh vyžadujúcich vysoké percento technickej spôsobilosti je účinok EI nižší (môže byť dokonca negatívny) v porovnaní s úlohami, ktoré si vyžadujú predovšetkým obchodné zručnosti. Manažéri predaja a marketingu by mali zvážiť EI pri nábore a personálnom rozvoji. Osobitná pozornosť by sa mala venovať nielen predajcom so slabými, ale aj veľmi silnými úrovňami EI. Keďže výsledky tejto štúdie sú vystavené vysokej medzikultúrnej variabilite, v príspevku sa uvádzajú postrehy na potenciálne odlišné výsledky v inej ako rakúskej kultúrnej zóne.

Kontakt na autorov/Address

FH-Prof. Mag. Andreas Zehetner, Degree program Global Sales and Marketing, Upper Austria University of Applied Sciences, School of Management, Wehrgrabengasse 1-3, 4400 Steyr, Austria, e-mail: [email protected]


8. March 2019 / 10. March 2019

Readiness, use and enablers of digital customer interaction tools in Austria

Readiness, use and enablers of digital customer interaction tools in Austria

This contribution presents a first holistic measurement of Austrian B2B companies’ readiness to improve customer interaction and sales performance through the application of digital communication services. To this end, the necessary steps to craft a sustainable and comprehensive corporate strategy for this subject matter are highlighted and the status-quo of implementation in Austrian Businesses is presented by means of a novel digital customer interaction metric on a scale of 1 to 100. The discussed digital communication services entail – but are not restricted to – well-known social media outlets as well as the interaction facilitated though digital communication such as LinkedIn, Twitter, Facebook, Blogs and YouTube, which belong to the most widely used tools globally. The conducted empirical analysis, which was carried out by means of a quantitative analysis among 74 representatives from different economic sectors, assessed the effects, which directly influence the degree to which Austrian businesses have implemented structured digital communication processes in sales and customer interaction service. The thereby gathered evidence supports the hypothesis of personal and industry-specific factors exhibiting the most significant effect on the introduction of digital customer interaction tools, as do the sales experiences based on digital lead and prospect generation. However, other often cited criteria, such as the size of the company, have not been found to directly influence the level of implementation likelihood.

1 Introduction

Following tremendous technological advances in the past decade, a variety of digital communication tools are available which enable suppliers and buyers to engage with one another in a more effective, tailored and customized manner. These involve a set of social media and other communication tools, which – in this paper – are summarized by the „structured digital customer interaction” terminus.
The technological advances have made vast amounts of information available to both sides,thereby improving the efficiency of communication and transactions (Mantrala and Albers 2015). They help suppliers to investigate how customers use products and to quickly react with providing adequate information (Curtis and Giamanco 2010; Agnihotri et al. 2012). The usage of digital communication platforms provides fertile ground to spread information on products, services, events, community and company related issues among customers and partners in a timely manner (Agnihotri et al. 2012; Agnihotri et al. 2014).
Orchestrating organizational resources is necessary to bundle knowledge from different parts of a company before sending it out to customers in a highly compressed manner through the digital channel of their choice (Mantrala and Albers 2013). Thus, digital communication tools provide an important opportunity to directly talk to customers and monitor any reviews, appraisal or criticism of products and services offered by the own firm or a competitor and take actions quickly to adapt and improve product as well as service attributes (Agnihotri 2012).
These tools do not only allow to react quickly but also to be more proactive in addressing the individual needs of customers. Proactively customizing solutions for customers substantially boosts customer perceived value (Andzulis, Panagopoulos and Rapp 2012; Agnihotri et al. 2012). Because digital communication tools hold potential to improve almost all interactions between buyers and sellers, they also transform the selling process of products and services. Social media as a widely applied means of digital communication is found to assist in the gathering of timely and up-to-date information about decision makers, communication styles, buying risks and overall needs of the purchasing organization (Andzulis, Panagopoulos and Rapp 2012; Sashi 2012). Furthermore – and in contrast to many traditional communication channels – gatekeepers can be avoided because decision makers can be directly addressed on platforms like LinkedIn by starting conversations regarding latest news and developments found on social media (Minsky and Quesenberry 2016; Cuevas 2017; Greenberg 2009).
In terms of communication efficacy, research has identified the effects of increasing use of digital interaction tools in terms of trust establishment between the parties involved in the transaction (Ferrell 2010; Schaub 2014). As regards the impact on sales’ processes, prospects have been found to publicly post their questions and concerns, which gives sellers the opportunity to listen, ask the right questions and analyze the prospects’ underlying needs. These novel forms of communication thus enables sales organizations to inform/educate customers more efficiently and enrich the presentation process by promoting collaboration and engagement in order to arrive at win-win solutions (Andzulis, Panagopoulos and Rapp 2012).

1.1 Introduction of digital customer interaction methods

The implementation of digital communication tools in the fields of sales and customer interaction consists of five steps: (i) a comprehensive strategy has to be crafted, (ii) the involved people have to be trained and (iii), a change in corporate culture that spans across all levels and departments has to be fostered. Step (iv) involves the required risk assessment throughout the whole process which includes the necessary steps to address found risks appropriately. Step (v) incorporates management’s oversight from taking the first step, acting as role models and providing all necessary resources. Crafting a comprehensive strategy and stating clear goals requires a deep understanding of the value that the customer is looking for (Andzulis, Panagopoulos and Rapp 2012).
Market knowledge and research are crucial, especially in the preparatory phase. Resources have to be dedicated to assess which digital communication tools are most important in the respective industry or customer segment. Metrics and communication plans need to be defined for each of the chosen tools (Ivens and Rauschnabel 2015). In terms of organization and human resource implication, a focus on developing employees with social media skills is generally seen as a prerequisite for successful implementation (Itani, Agnihotri and Dingus 2017). An influx of new staff is found to positively influence the identification of existing staff with digital communication’s development. Thus, the design and execution of trainings, the required assistance with setting up guidelines to avoid risks presented by the usage of digital communication tools and the creation of communication plans can either be dedicated to external specialists or social media savvy people in the firm (Bowen and Haas 2015).

1.2 Digital interaction metrics

The efficacy of using digital communication tools can be assessed with different indicators, which are grouped into soft and hard metrics (Culnan, McHugh and Zubillaga 2015).
Soft metrics measure the effect of digital interaction with regards to changes to a company’s follower base, the degree of customers’ engagement with the content shared, the time followers spend on a firm’s social media page and the intensity with which these contents affect associated forums and discussions. All these things can be measured with the help of features directly integrated in most digital communication tools (Culnan, McHugh and Zubillaga 2010). Hard metrics on the other hand help to measure financial indicators of success like revenue and cost reduction and personnel related metrics focus on employee satisfaction. These metrics serve as indicator for organizational effectiveness related to degree of customer satisfaction improvement or customer retention as well as service time and product or service quality. Hard metrics also allow measuring system performance (Culnan, McHugh and Zubillaga 2010). Furthermore companies have to measure the return on investment of their social media selling activities and have to set up key performance indicators as well as benchmarks (Hughes and Reynolds 2016).

2 Empirical analysis

2.1 Methodology

In order to determine the degree to which Austrian B2B sales organizations use digital communication tools to improve sales results and raise service levels, a survey was conducted, yielding 70 individual responses from 54 different companies. To determine the exact degree of implementation a scoring model was developed. The participants could reach between 0 – 100 points. The score then allowed to classify the respondents into 4 different categories based on how intensively digital communication tools are used for conducting sales activities and providing services.
In terms of effect detection, a three pronged approach was applied. This entailed the detection of structural differences between observed company types by means of independent sample T-tests. Identification was based on the widely used ÖNACE system, which asserts the sectoral differences of industries by means of a holistic, European, classification scheme (NACE). Secondly, the investigation of sub-layer differences of accumulated implementation score was assessed over the entire sample by means of a variance analytical approach in order to detect the differences across branches.
Finally, multiple regression analysis was carried out to detect the driving forces of digital customer interaction services’ implementation.

2.2 Results

The empirical investigation revealed the substantial differences of utilization of digital customer interaction tools as depicted in Figure 1.

Figure 1: Social media tools and their frequency of usage by respondents (relative values, N=74)
Source: Authors

The main motivation for the utilization in terms of the different stages of the sales process was detected within the area of customer network extension. The majority of reasons why respondents use social media on the job lies in the advanced options for prospecting and pre-approach as depicted in Figure 2.

Figure 2: Distribution of Social media usage in the different stages of the sales process (absolute values, N=74).
Source: Authors

Major differences were also detected between industries, as classified by the ÖNACE classification. Manufacturing is found to show 9.8% lower implementation rates (sign. at .95), when compared to other industries.
The same holds for businesses active in information and communication (ÖNACE 10) as well as in professional, scientific and technical activities (ÖNACE 13), which score higher on social media selling adoption than firms in other sectors (sign at .95). The size of the firm is found to be insignificant by common statistical standards, whereas the age of the responsible employee is found to highly significant, thus increasing the likelihood of digital customer interaction tools’ use by more than 12%.
In general, the degree of implementation among the majority of respondents is rather low. Few show a slightly advanced stage of implementing social media and even less reached a strong or full scale implementation. Austrian firms do not fully understand the role digital communication tools can play in order to overcome sales and service related problems. When looking at the degree to which social media is used in the sales process it becomes apparent that only a small fraction of respondents uses this technology throughout all stages. Respondents have profiles on professional social networks like LinkedIn but can be rather categorized as passive users. Top management does not strongly encourage using digital communication tools and little training is provided. Few companies are measuring social media success at all and only a small fraction of respondents have networks big enough to be visible in their target industries. Despite the low degree of adoption it has to be pointed out that firms are very interested in this topic because they believe that it will influence the way they sell in the future. As more and more social media savvy people from Generation Y are filling positions in sales organizations a quick change in the status quo is likely. However, it is the task of top managers to change corporate cultures and strategies in order to capitalize on the opportunities related to improving customer service through the usage of digital communication tools.

2.3 Discussion of empirical evidence

The investigated means of digital communication are found to assist overcoming a set of problems in traditional customer interaction and selling processes. Overcoming objections through social media can be facilitated through the creation of public forums where questions are discussed transparently and various parties are enabled to cooperate in order to reach a mutually satisfactory outcome. This is much in line with the findings of Andzulis, Panagopoulos and Rapp (2012) and affect different stages of the customer interaction and sales process.
For instance, after the completion of a transaction, customers can be provided with service instructions, news and answers to frequently asked questions by adding them to networking groups and forums. At this stage, the importance of inward facing social media grows because it helps to find solutions for service requests by faster communication between people from various departments. Again, this is much in accordance to the relevant literature (Sashi 2012). We found that a large part of changing the corporate culture involves in-depth investigation of customers’ needs and wants followed by a subsequent design process for according product and service offerings. These policy recommendations are also reflected by international research such as Culnan, McHugh and Zubillaga (2010) or Baird and Parasnis (2011).
The usage of digital customer interaction tools for sales and customer service related activities in Austrian B2B organizations is still in its infancy. The majority of companies are in an early or slightly advanced stage of adoption but with an increasing number of people that belong to Generation Y in sales positions this could quickly change in the next years. Few respondents show a high or full scale adoption of DCITs, social media in particular. Communication with customers via social media is happening rather infrequently. LinkedIn is the most popular social media platform among respondents.
When looking at the social media selling adoption scores by age group one cannot clearly state that younger people are more likely to use social media for their daily tasks than older respondents but it was found that the youngest respondents reached the highest scores more frequently. It was also found that people who are active in marketing, IT and telecommunications have a higher degree of social media selling adoption than those who work in manufacturing, wholesale or other industries.
Austrian salespeople are confronted with a large variety of challenges. Respondents do not seem to be aware of the potential that social media holds to cope with a lot of these current problems. Nevertheless they acknowledge its increasing influence on the sales process, where the usage dominates in the early stages. Traditional ways to find new leads still dominate in Austria. Social media is more popular when it comes to collecting information about customer needs and decision makers as well as new trends.
The CRM systems in place in most companies do not allow their users to get a 360 degree view of customers because they do not integrate information about customers obtained through social media. Austrian B2B sales employees do not provide deep know how through social media, the usage of blogs is hardly existing when it comes to individuals and low when it comes to corporate blogging. Engagement with the content posted by customers or experts is relatively low. Alignment and interaction between the sales and the marketing department is high. This fulfills an important criterion for the usage of digital customer interaction tools for selling.
The size of the LinkedIn networks of Austrian salespeople is in most cases insufficient. This also holds true for the frequency in which individuals post content on this platform. Twitter plays only a small role compared to other social networks in Austria. Only few sellers use it. The ones who do often have a follower base that is too small and do not send out tweets frequently enough to exert sufficient influence and reach a large audience. All these facts give the impression of a rather passive attitude of Austrian sales representatives when it comes to using social media, which in turn could be the reason why their customers do not interact more intensively with them.
Only a small fraction of sellers could ever relate a closed deal to their social media activities. This is supported by the fact that most people did not see strong performance improvement due to social media usage and most are scepticall about the future influence of social media on their selling activities. Nevertheless, the majority of Austrian salespeople believe that digital customer interaction tools are an adequate to provide additional value to existing and potential customers.

3 Summary and managerial recommendations

The process of implementing a social media selling strategy is not different from the implementation of a new pricing strategy. It requires the identification of the most pressing challenges, redefining and rethinking of existing processes, cooperation of several departments, strong support from top management, training by experts, putting one-self in the customer’s shoes, setting up metrics and step by step altering of the corporate culture to arrive at the desired status quo. It is also vital to understand that social media sales is not about selling a product or service on social media but that the integration of digital customer interaction tools in the sales process can lay the groundwork for future sales.
A deep integration of digital customer interaction tools in the sales and customer service activities is a continuous process that does not yield immediate results. All sales organizations have to keep a close eye on how the environment in which they operate changes. Even though it may feel strange for sellers to post whitepapers or case studies online without any reassurance that these efforts will lead to a directly relatable sale, they have to understand that this is part of a much bigger behavioral shift which is absolutely necessary to move from a transactional to a value-focused approach. Buying organizations are changing and the way in which selling organization interact and communicate with them has to adapt accordingly.
This contribution sheds light on the novel opportunities of customer interaction through social media, helps to better understand what drives the implementation of digital relationship tools and investigates the current level of incorporation with a focus on Austria for the first time. Future research ought to improve the empirical assessment of customer relationships’ innovations thereby improving the scientific basis of this relevant business topic even further.

Literatúra/List of References

[1] Agnihotri, R., Dingus, R., Hu, Y. M. and Krush, T. M., 2016. Social media: Influencing customer satisfaction in B2B sales. In: Industrial Marketing Management. 2016, 53, pp. 172-180. ISSN 0019-8501.
[2] Agnihotri, R., Kothandaraman, P., Kashyap, R. and Singh, R., 2012. Bringing „Social” into sales: The impact of salespeople’s social media use on service behaviors and value creation. In: Journal of Personal Selling & Sales Management. 2012, 32(3), pp. 333-348. ISSN 0885-3134.
[3] Agnihotri, R., Rapp, A. and Trainor, K., 2009. Understanding the role of information communication in the buyer seller exchange process: antecedents and outcomes. In: Journal of Business & Industrial Marketing. 2009, 24(7), pp. 474-486. ISSN 0885-8624.
[4] Andzulis, J. M., Panagopoulos, G. N. and Rapp, A., 2012. A review of social media and implications for the sales process. In: Journal of Personal Selling & Sales Management. 2012, 32 (3), pp. 305-316. ISSN 0885-3134.
[5] Baird, H. C. and Parasnis, G., 2011. From social media to social customer relationship management. In: Strategy & Leadership. 2011, 39(5), pp. 30-37. ISSN 1087-8572.
[6] Bowen, M. and Haas, A., 2015. Social-Media-Kompetenz: Der vergessene Erfolgsfaktor im modernen Vertrieb. In: Marketing Review St. Gallen. 2015, 32(6), pp. 54-61. ISSN 1865-6544.
[7] Cuevas, J. M., 2018. The transformation of professional selling: Implications for leading the modern sales organization. In: Industrial Marketing Management. 2018, 69(2), pp. 198-208. ISSN 0019-8501.
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[10] Ferrell, O. C., 2010. An assessment of the use of technology in the direct selling Industry. In: Journal of Personal Selling & Sales Management. 2010, 30(2), pp. 157-165. ISSN 0885-3134.
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[12] Itani, O. S., Agnihotri, R. and Dingus, R., 2017. Social media use in B2B sales and ist impact on competitive intelligence collection and adaptive selling: Examining the role of learning orientation as an enabler. In: Industrial Marketing Management. 2017, 66, pp. 64-79. ISSN 0019-8501.
[13] Ivens, B. S., Rauschnabel, A. P. and Leischnig, A., 2016. Social Media in B2B-Unternehmen: Einsatzpotenziale in Marketing und Vertrieb. In: Binckebanck, L. & Elste, R.: Digitalisierung im Vertrieb. Wiesbaden: Springer Fachmedien Wiesbaden pp. 414-435. ISBN 978-3-658-05054-2.
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[15] Mantrala, M. K. and Albers, S., 2013. The impact of the internet on B2B salesforce size and structure. In: Lilien, L. G. and Grewal, R. eds., 2013. ISBM Handbook on Business-to-Business Marketing. Cheltenham: Edward Elgar Publishing, 2013. 539-563. ISBN 978-1781005361.
[16] Minsky, L. and Quesenberry, A., K., 2016. How B2B sales can benefit from social selling. In: Harvard Business Review. 2016, 8(November). ISSN 0017-8012.
[17] Sashi, C. M., 2012. Customer engagement, buyer-selller relationships and social media. In: Management Decision. 2012, 50(2), pp. 253-272. ISSN 0025-1747.
[18] Schaub, K., 2014. Social buying meets social selling: How trusted networks improve the purchase experience. whitepaper, IDC (April 2014). [online]. [cit. 2019-02-03]. Available at: <>

Kľúčové slová/Key Words

digital customer interaction, sales performance, digital communication services, social media, digital communication
digitálna zákaznícka interakcia, výkonnosť predaja, digitálne komunikačné služby, sociálne médiá, digitálna komunikácia

JEL klasifikácia/JEL Classification



Pripravenosť, používanie a aktivácia digitálnych nástrojov interakcie so zákazníkmi v Rakúsku

Tento príspevok predstavuje prvé holistické meranie pripravenosti rakúskych B2B spoločností na zlepšenie interakcie so zákazníkmi a výkonnosti predaja prostredníctvom aplikácie digitálnych komunikačných služieb. Za týmto účelom sú predstavené potrebné kroky na vytvorenie trvalo udržateľnej a komplexnej podnikovej stratégie pre túto oblasť a následne je prezentovaný súčasný stav implementácie v rakúskych podnikoch prostredníctvom novej metriky interakcie s digitálnymi zákazníkmi na stupnici od 1 do 100. Analyzované digitálne komunikačné služby zahŕňajú – ale nie sú obmedzené len na – známe sociálne médiá, ako aj interakciu uľahčenú prostredníctvom digitálnej komunikácie, ako sú LinkedIn, Twitter, Facebook, Blogy a YouTube, ktoré patria celosvetovo k najpoužívanejším nástrojom. Vykonaná empirická analýza, ktorá bola uskutočnená prostredníctvom kvantitatívnej analýzy medzi 74 zástupcami z rôznych ekonomických sektorov, zhodnotila účinky, ktoré priamo ovplyvňujú mieru, do akej rakúske podniky implementovali štruktúrované procesy digitálnej komunikácie v predaji a v službách zákazníkom. Takto získané dôkazy podporujú hypotézu osobných a odvetvovo špecifických faktorov, ktoré majú najvýznamnejší vplyv na zavádzanie nástrojov digitálnej interakcie so zákazníkmi, ako aj skúsenosti z predaja založené na digitálnom vedení a získavaní potenciálnych zákazníkov. Iné často citované kritériá, ako napríklad veľkosť spoločnosti, však neboli identifikované, že by priamo ovplyvňovali úroveň pravdepodobnej implementácie.

Kontakt na autorov/Address

Michael Wenzler, MA, Degree program Global Sales and Marketing, Upper Austria University of Applied Sciences, School of Management, Wehrgrabengasse 1-3, 4400 Steyr, Austria, e-mail: [email protected]

Sakshi Bhambhani, BBA, Degree program Global Sales and Marketing, Upper Austria University of Applied Sciences, School of Management, Wehrgrabengasse 1-3, 4400 Steyr, Austria, e-mail: [email protected]

MMag. Dr. Michael Schmidthaler, Degree program Global Sales and Marketing, Upper Austria University of Applied Sciences, School of Management, Wehrgrabengasse 1-3, 4400 Steyr, Austria, e-mail: [email protected]


24. March 2019 / 3. April 2019