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Rediscovering the Essentiality of Marketing pp 779–780 Cite as

Sales and Marketing, and Customer Relationships: A Structured Abstract

  • Kenneth Le Meunier-FitzHugh 4 &
  • Leslie Caroline Le Meunier-FitzHugh 4  
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Part of the Developments in Marketing Science: Proceedings of the Academy of Marketing Science book series (DMSPAMS)

This research investigates the impact of sales and marketing collaboration on the customer’s propensity to purchase and customer value, thereby extending the current research into the sales and marketing interface. Prior research has established that sales departments may fail to support marketing initiatives and that marketing been known to fail to communicate marketing objectives effectively and to exclude sales from decision-making. This lack of coordination may become visible to the customer and consequently influence their relationship with the supplier. We suggest that internal sales and marketing relationships can impact on relationship quality and consequently the customers’ propensity to purchase.

Customers demand greater value from their suppliers and consequently a relationship-building approach to marketing has been more widely adopted by many organizations (Harker and Egan 2006; Biggemann and Buttle 2012). Further, sustainable long-term relationships benefit the supplier by reducing costs and increasing sales (e.g., Hennig-Thurau et al. 2002). It has been suggested that relationship quality encompasses the concepts of satisfaction, trust and commitment related to the selling organization (Crosby et al. 1990; Palmatier et al. 2006).

The study was conducted through a series of semi-structured, hour-long interviews within the sales and marketing personnel from four B2B organizations in the UK, and with a selection of their customers. This approach produces rich qualitative data on the participants’ attitudes and experiences of the interface between buyer and seller. The customer respondents were selected randomly from the organizations’ databases.

The study highlights that conflict or collaboration between sales and marketing is visible to the customer and affects the different dimensions of relationship quality. Collaboration creates customer satisfaction and operating through the dimensions of trust to improve customer commitment, and creates customer value in the relationship and leads to an increased propensity to purchase.

  • Qualitative Data
  • Customer Satisfaction
  • Relationship Quality
  • Customer Relationship Management
  • Customer Commitment

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Kenneth Le Meunier-FitzHugh & Leslie Caroline Le Meunier-FitzHugh

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Department of Business and Law Studies, University of Bari Aldo Moro, Bari, Italy

Luca Petruzzellis

Stern School of Business, New York University, New York, New York, USA

Russell S. Winer

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Le Meunier-FitzHugh, K., Le Meunier-FitzHugh, L.C. (2016). Sales and Marketing, and Customer Relationships: A Structured Abstract. In: Petruzzellis, L., Winer, R. (eds) Rediscovering the Essentiality of Marketing. Developments in Marketing Science: Proceedings of the Academy of Marketing Science. Springer, Cham. https://doi.org/10.1007/978-3-319-29877-1_148

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Salesperson communication effectiveness in a digital sales interaction 1 ☆

Neeraj bharadwaj.

a Department of Marketing, Haslam College of Business, 916 Volunteer Boulevard, 333 Stokely Management Center, University of Tennessee, Knoxville, TN 37996, United States of America

Garrett M. Shipley

b Department of Marketing, Haslam College of Business, 916 Volunteer Boulevard, 305 Stokely Management Center, University of Tennessee, Knoxville, TN 37996, United States of America

B2B buyers are exhibiting an increased preference to transact digitally with vendors. A topic which has yet to receive sufficient academic attention in this modern selling environment is salesperson communication effectiveness. Accordingly, this article: 1) defines digital sales interactions (DSIs) as technology-enabled, face-to-face buyer-seller exchanges; 2) proposes a typology of DSIs to set the stage to examine salesperson communication effectiveness; 3) introduces a framework that reifies the sender's auditory and visual cues that can influence receivers' thoughts (i.e., cognition, affect, intention) and activity (i.e., purchase behavior, advocacy); 4) suggests theoretical lenses that can illuminate various aspects of the salesperson's communication barrage; 5) advances how machine learning can be applied to understand what constitutes effective communication in a digital interaction by asking: to what extent does what a salesperson says (auditory cues) and how s/he says it (visual cues) impact her/his effectiveness in a DSI?; and 6) concludes by noting promising future research directions for B2B marketing researchers.

  • • Examines salesperson effectiveness in a digital sales interaction (DSI)
  • • Proposes a typology of DSIs based the nature of the sales communication in conjunction with its temporal aspect
  • • Introduces a holistic framework summarizing the salesperson's communication barrage
  • • Advocates applying machine learning to undertake holistic assessment of sender's cues
  • • Identifies promising research directions for B2B marketing researchers

1. Introduction

Technological advancements are ushering in the fourth industrial revolution ( Schwab, 2016 ). Whereas the steam engine, mass production, and the internet were responsible for providing the foundation for innovation in past eras, the case is being made that economies and industries will be disrupted by technologies which permit the blending together of the digital, physical, and biological worlds (e.g., artificial intelligence, quantum computing, 3D printing, and the internet of things). 2 In brief, the new technologies are predicted to change the way that we live, work, and interact ( Syam & Sharma, 2018 ).

A notable shift that is transpiring is that business exchanges (among suppliers, intermediaries, customers, and other constituencies) are increasingly being carried out in digital environments ( Hoffman & Novak, 1996 ; Turkle, 2017 ; Yadav & Pavlou, 2014 ). In a world marked by greater connectivity and interactivity, digital interactions have emerged as a dominant mode for buyer-seller exchanges ( Steinhoff, Arli, Weaven, & Kozlenkova, 2019 ). This assertion is supported in studies reporting that:

  • • 68% of B2B buyers prefer doing business online versus with a salesperson ( Hoar, 2017 ) because the digital channel offers greater convenience, price transparency, and access to product information and customer reviews ( Caitlin, Harrison, Plotkin, & Stanley, 2016 ).
  • • B2B buyers considering a purchase spend 17% of their time meeting with potential suppliers and 27% of their time researching sources independently online ( Gartner, 2019 ).
  • • Owned media (a company's website) and digital inbound marketing (e.g., webinars, white papers, and blogs) play a pivotal role for B2B sellers in acquiring new business customers ( Vieira et al., 2019 ).

To better align themselves with the demands of digital commerce so as to achieve competitive advantage, selling firms are modernizing their sales strategy and pursuing digital sales interactions (DSIs), which we define as technology-enabled, face-to-face buyer-seller exchanges. Although the digital sales channel holds potential to drive topline revenues and/or conduct sales interactions more efficiently ( Sheth & Sharma, 2008 ; Thaichon, Surachartkumtonkun, Quach, Weaven, & Palmatier, 2018 ), some open questions remain before those business gains are to be realized (see, e.g., Singh et al., 2019 ; Organizational Frontline Research (OFR), 2019 ). Central to this article is salesperson communication effectiveness in a DSI.

It has long been understood that effective communication is a fundamental determinant of salesperson performance outcomes (e.g., Singh, Brady, Arnold, & Brown, 2017 ; Spiro & Weitz, 1990 ; Webster, 1968 ; Weitz, 1981 ). Furthermore, it is well established that a sender's verbal (e.g., Peterson, Cannito, & Brown, 1995 ) and nonverbal (e.g., Bonoma & Felder, 1977 ; Lim, Lee, & Foo, 2017 ) cues matter in face-to-face encounters. However, the extent to which the earlier findings on salesperson communication effectiveness hold in a less rich, digitally-enabled medium is not yet fully known.

Two promising developments facilitate studying the next frontier in sales communication effectiveness. First, digital commerce generates a continuous stream of video footage (OFR 2019). Instead of narrowly studying a single aspect of a salesperson's communication in isolation as was historically done (e.g., does “service with a smile” matter in shaping customer-related outcomes?), researchers are now in a position to couple the salesperson's auditory and visual cues with moment-by-moment customers' mindset and/or behavioral data for more holistic predictive and prescriptive purposes ( Marinova, Singh, & Singh, 2018 ). Second, advances in artificial intelligence (AI) permit capturing and analyzing the massive amount of unstructured and structured data from the video footage not previously possible ( Syam & Sharma, 2018 ). Whereas, for instance, the current literature that examines the “service with a smile” maxim relies on human raters to manually code the facial expressions of frontline employees ( Du, Fan, & Feng, 2011 ; Pugh, 2001 ; Wang et al., 2017 ), recent efforts deploy convolutional neural networks to automate the facial coding process, extract the sender's facial expressions, and subsequently associate visual and/or verbal signals with business outcomes ( Choudhury, Wang, Carlson, & Khanna, 2019 ; Liu, Shi, Teixeira, & Wedel, 2018 ).

These developments (i.e., the availability of video footage of seller-buyer interactions and state-of-the-art AI techniques) coupled with the increased interest in the digital sales channel among business buyers and sellers yields interesting opportunities for scholarship. Our discourse can offer researchers a path to address Marketing Science Institute's (MSI 2018–20) paramount research priority to deploy technological advances to capture and analyze audio and video data to improve marketing communications. The approach described is also pragmatically useful as it can provide guidance to firms on ways to improve salesperson communication effectiveness in DSIs, and in turn, drive key performance metrics.

In this article, we first propose a typology of buyer-seller interactions that can transpire in a digital medium to provide a starting point to assess salesperson communication effectiveness in this modern selling channel. 3 We then introduce a comprehensive framework that reifies the totality of the salesperson's auditory and visual cues directed towards a customer that can influence buyer outcomes. Subsequently, we advance how machine learning can be applied to better understand what constitutes effective communication in a digital interaction: to what extent does what a salesperson says (auditory cues) and how s/he says it (visual cues) impact her/his effectiveness in a DSI? We conclude by noting future research possibilities.

2. Digital sales interactions (DSIs)

Exchange is a foundational concept in marketing —it has been described as “the crux of marketing” ( Kotler & Levy, 1969 , p. 57) and as “a fundamental framework for viewing marketing” ( Bagozzi, 1974 , p. 77). The exchange system refers to “sets (of parties) in which interactions occur which serve to define the boundaries of the set” ( Alderson & Martin, 1965 , p. 125), and recognizes that the macro-environment in which the dyad is embedded is an important consideration ( Hunt, 1983 ).

The increasing prevalence of buyer-seller communications and transactions being conducted remotely via a screen-to-screen interface marks an evolution from the traditional in-person, face-to-face exchange ( Kopalle, Kumar, & Subramaniam, 2019 ; Salesforce, 2019 ; Verhoef & Bijmolt, 2019 ; Yadav & Pavlou, 2014 ). The fact that digital technologies can fundamentally alter marketing processes ( Kannan & Li, 2017 ; Kumar, Sharma, Vatavwalla, & Kumar, 2020 ) provides the impetus to study the efficacy of a salesperson in a technology-enabled, face-to-face buyer-seller exchange, or what we deem a digital sales interaction (DSI). Akin to an in-person face-to-face interaction, a DSI can occur at any point along the B2B buying journey, spanning from pre-sales communications to actual sales transactions to post-sales activity. 4

Scholars opine that digital technologies can alter the customer experience ( Kannan & Li, 2017 ; Kumar et al., 2020 ). This means that even though leading firms are innovating their sales channel in an attempt to deliver a superior customer experience across the entire customer journey (see, for example, Moorman & Lemon, 2020 ), and in turn, drive topline revenues and/or conduct sales interactions more efficiently ( Sheth & Sharma, 2008 ; Thaichon et al., 2018 ), salesperson communication effectiveness in a DSI is not yet fully understood.

One way to begin thinking about salesperson communication effectiveness in a DSI is to consider the nature of the sales communication in conjunction with its temporal aspect. 5 A seller's interaction with an institutional buyer can be scripted or tailored, and it can transpire in real-time or without temporal synchronization. Whether the communication is adaptive (i.e., the seller tailors the message) versus standard (i.e., the seller conveys a scripted message) or synchronous versus asynchronous can be used to formulate Table 1 , which contains an exemplar digital exchange in each cell. For illustration, we juxtapose a one-to-one interaction and a one-to-many interaction to highlight how these require differing theories to illuminate the DSI.

DSI exemplars.

A key implication arising from Table 1 is that a researcher interested in comparing a pair of cells will require different theoretical lenses to explicate the determinants of salesperson effectiveness. Take, for instance, a researcher interested in understanding the emotions displayed during an adaptive, synchronous DSI in relation to a standard, synchronous one. Assuming that the former is a one-to-one interaction, the DSI provides the researcher access the facial expressions of both sides of the dyad. This permits employing emotional contagion theory to examine the extent to which a facial expression by a seller (e.g., a smile) results in the buyer mimicking the viewed facial expression and experiencing a positive affect towards the seller ( Chartrand & Lakin, 1993 ; Hatfield, Cacioppo, & Rapson, 1994 ). In contrast, a standard, synchronous DSI may involve a one-to-many interaction. This means that the researcher has access only to the seller's facial display. In this instance, one possibility is to construe the facial expression as a signal that the seller manipulates in order to achieve a desired response from a buyer (e.g., whether to smile, and if so, how broadly and for how long?). The emotions as social interaction (EASI) model ( van Kleef, 2009 , van Kleef, 2016 ) can provide the theoretical scaffolding to construe the seller's facial behavior as a signal. The seller can consciously determine which facial expression to display and the intensity of the emotion (e.g., slight versus broad smile) in order to elicit the desired response from the buyer.

In the next section, we expand on the cues that are available from a DSI. In addition to facial expressions, the researcher can access other nonverbal and verbal cues. As there are multiple cues, we provide a framework to conceptualize the sender's barrage of communications. For ease of exposition, we focus on a standard, synchronous communication in a one-to-many setting.

3. Conceptualizing salesperson effectiveness in DSIs.

A communication in an exchange system involves a sender conveying a plethora of signals to the receiver. Akin to a face-to-face meeting, the sender transmits auditory and visual signals in a DSI. However, other cues – such as touch and smell – are not as salient because the sender and receiver do not occupy the same physical space. Thus, we construe a receiver's appraisal of a sender in digital interaction to be shaped by the sender's auditory and visual signals, and the screen-to-screen interface makes it a less rich medium than an in-person, face-to-face interaction, yet richer than a telephone encounter in which only the sender's words and the delivery (i.e., auditory cues) play a pivotal role in shaping customers' appraisals ( Bharadwaj & Roggeveen, 2008 ).

Ekman and Friesen, 1978 , Ekman and Friesen, 2003 describe the abundance of auditory and visual signals from a sender as a “communication barrage.” Those authors suggest that the receiver can gather information from the sender's statements in terms of the content (i.e., words used) and delivery (i.e., rate of speech, loudness, tone, number of pauses, and disruptive words such as “umms” and “aahs” used). In addition, the receiver is subjected to a host of information from the visual channel. These cues can hail from the sender's facial expressions as well as their head and body movements. The audio and the visual channels, respectively, give rise to the verbal and nonverbal cues in a communication, and theories exist to conceptualize the receiver's affective appraisals and/or behavioral outcomes (see e.g., contagion theory ( Hatfield et al., 1994 ; Hennig-Thurau et al., 2006 ; Pugh, 2001 ) and emotions as social information ( van Kleef, 2009 , van Kleef, 2016 )). Fig. 1 depicts our conceptualization of the communication barrage in a DSI and possible customer outcomes.

Fig. 1

The salesperson's communication barrage and buyer outcomes.

It is well-established that how effectively a salesperson from a selling organization communicates with a buyer influences her/his success (e.g., Singh et al., 2017 ; Spiro & Weitz, 1990 ; Webster, 1968 ; Weitz, 1981 ), and the extant research on salesperson effectiveness has examined the sender's auditory and visual communication cues noted in Fig. 1 . Below, we briefly mention some exemplar studies.

To investigate the impact of what is said (i.e., the words used), Singh, Marinova, Singh, and Evans (2018) develop dictionaries of words to operationalize salesperson competence (e.g., in resolving customer queries such as need specification and transaction clarification) and warmth (e.g., relating/emoting in attending to customer queries). The authors' analysis of words demonstrates the primacy of salesperson competence in retaining a customer's interest, which in turn, drives customer purchase intent. In their paper evaluating the salesperson delivery-effectiveness relationship, Peterson et al. (1995) begin with the premise that how a sales message is communicated may be as important is what is communicated. They examine specific voice characteristics as determinants of customers' purchases, and find rate of speech (i.e., arguing that a rapid speaker is perceived as more knowledgeable and trustworthy) fundamental frequency contour (i.e., mean, variability, and contour), and loudness variability to be associated with higher sales. To assess visual cues, Pugh (2001) manually evaluates observational data from 106 actual bank teller-customer service encounters, and finds that the seller's positive facial expressions (i.e., happiness as conveyed by a smile) can influence the perceived quality of the service received. In their study of head and body activity, Pauser, Wagner, and Ebster (2018) rely on two trained observers to utilize the body action posture (BAP) coding system – which classifies 141 behavioral variables into 12 categories (e.g., head action, arm action) – to manually assess sales presentations, and find that symmetric movements (asymmetric movements) have a greater impact on attitude towards the salesperson in a low-gesture culture (high-gesture culture).

While the aforementioned sample of studies (as well as a large body existing research) can provide meaningful insight into the auditory and verbal cues summarized in Fig. 1 , the individual aspects are studied in isolation. What is needed is a broader examination of the relationship between sales success and effective communication in a DSI. Such a study could shed insight into an important, open question: to what extent does what a salesperson says (auditory cues) and how s/he says it (visual cues) impact her/his effectiveness in a digital sales interaction?

4. Holistically assessing salesperson effectiveness in DSIs

The volume and variety of data created at an increased velocity by the sender's barrage of digital communications that are digitized pose unique challenges. The structured and unstructured data are massive, which taxes human abilities to collect, store and process ( Bharadwaj & Noble, 2017 ; Marinova et al., 2018 ; McAfee & Brynjolfsson, 2012 ). They are also high dimensional, and situations in which p  >  n require new methodologies and computational capabilities.

Wedel and Kannan (2016) equate such big data to the “oil” of the digital economy. We see this as a fitting comparison because, just like crude oil, it is necessary to refine unstructured (i.e., audio, video, images, or text) data and structured (i.e., organized by variables or numeric values) data to extract meaning. Given that roughly 80% of data available to firms are unstructured ( Rizkallah, 2017 ), this suggests a rich, untapped reservoir of insights. For instance, deep learning can be used to detect the presence of a face in a given frame of the video footage and neural nets can then be used to transform the information from the face into a field of weighted pixels in order to extract the salesperson's facial expressions.

The aforementioned implies potential insights on both customers and sellers (MSI 2018), which raises two questions: how can firms harness and refine this data, and what potential insights can emerge? Recent developments in artificial intelligence (AI) can aid in this regard. 6

4.1. A primer on machine learning

Unstructured data, specifically audio and video, have successfully been structured and analyzed using methods from the field of artificial intelligence ( Arandjelovic & Zisserman, 2017 ; Balducci & Marinova, 2018 ; Li, Shi, & Wang, 2019 ). AI is an umbrella term for any technology or program that attempts to make decisions without explicitly being programmed to do so. AI mimics human cognition using algorithms, which allows a computer to structure unstructured data, analyze multiple features of the data simultaneously, and estimate an equation that will best fit the available data.

Machine learning, a subfield of artificial intelligence, focuses on the mathematical and statistical modeling of a particular task allowing a computer program to make inferences or decisions. Machine learning can be divided into two general types of learning: supervised and unsupervised. Supervised learning is described as observing input-output pairs and then creating a function that maps input to output ( Russell & Norvig, 2014 ). It is important to note that a supervised learning program will require “correct” input-output pairs—this is covered thoroughly by Syam and Sharma (2018) . Alternatively, an unsupervised machine learning program will learn the patterns of the data set based on the inputs with no output feedback ( Russell & Norvig, 2014 ).

The utility of machine learning comes from its ability to adjust the weighting of variables as more data becomes present. Because of this, machine learning provides an opportunity to derive a holistic prediction. Consider salesperson-customer interaction wherein the salesperson says something polite but uses a sarcastic tone. If the seller's tone of voice is not considered in tandem with the content of his message, it could register as a positive communication (and predict a successful sale outcome). However, including tone of voice along with additional cues (e.g., eye contact, arm movements) should make the prediction more accurate. In this way, the algorithm can learn what variables are important in predicting the outcome of an interaction (rather than having a researcher set parameters a priori).

4.2. Applying machine learning to assess a salesperson's communication barrage

Prior to describing strategies to assess distinct components of the auditory and visual cues noted in Fig. 1 , we begin providing the basic intuition as to how those individual aspects can influence customers' outcomes. To this end, we suggest theoretical lenses that prior researchers have used to illuminate the individual components of the salesperson's communication barrage. We then mention studies from the nascent stream of research that apply state-of-the-art machine learning techniques to analyze the auditory and/or visual cues from the video footage.

Psycholinguistic theory ( Pennebaker, 2011 ) offers a novel approach to evaluate what a sender says. In brief, quantifying the proportion of certain words used in relation to the total words used in the discourse can capture important aspects of the sender's communication, including the underlying sentiment of the message sent (i.e., positive emotion and negative emotion) and the thinking style that underlies those words: narrative thinking (i.e., the sender's message is characterized in a free-flowing, stream-of-consciousness manner with minimal structure), formal thinking (i.e. the sender's message consists of big words in an attempt to put on a performance to be consumed by the receiver), and analytic thinking (i.e., the sender's message is marked by a detailed analysis of the situation in an attempt to convey cause and effect). Bharadwaj, Noble, Tower, Smith, and Dong (2017) , for instance, use Linguistic Inquiry and Word Count (LIWC) to extract the aforementioned 24 variables from words conveyed by movie critics in their evaluations of movies (i.e., one variable for positive emotion, one variable for negative emotion; eight variables for narrative thinking; eight variables for formal thinking; and six variables for analytic thinking). Peterson et al. (1995) draw on linguistic theory to extract how a sender conveys his message, and the characteristics of the sender's delivery yield another set of variables (e.g., rate of speech, fundamental frequency contour, and loudness variability). To assess facial activity, researchers (e.g., Liu et al., 2018 ) rely on Ekman and Friesen's (1978) Facial Action Coding System (FACS) to categorize a set of emotional displays (e.g., happiness, sadness, anger). The presence of the face in a video and the six basic emotions generated in FACS yields distinct 7 variables. Lastly, the body action posture (BAP) coding system mentioned earlier captures the sender's head and body activity, and yields 141 behavioral variables.

Digital commerce generates a continuous stream of video footage, and allows researchers to move beyond narrowly study a single aspect of a salesperson's communication. The auditory and visual cues mentioned in the preceding paragraph, for instance, generate 175 predictor variables in each video frame. Assuming that there is on average 30 min of video footage for each sales interaction and the unit of analysis is a frame that is captured every second, the pixels from 315,000 frames for each salesperson must be analyzed. Given the large-scale nature of the analysis, the task must be automated, and a set of parallel computers (instead of human coders) trained to execute it. 7 Johnson, Ogihara, Ren, and Lee (2019) , for instance, process the raw content data by the CNN parts, then the CNN features (outputs from the CNN layers) are fed into the LSTM (long-term short-term) layers, and the fully connected CNN layers fuse together the data and generate the prediction.

5. Future research directions

Although digital sales interactions (DSIs) have emerged as a dominant mode for buyer-seller exchanges, some open questions remain regarding salesperson communication effectiveness in this modern selling environment. To begin to understand the knowledge gaps, this article defines digital sales interactions (DSIs); proposes a typology of some exemplar DSIs to set the stage to examine salesperson communication effectiveness (in Table 1 ); presents a framework (in Fig. 1 ) that reifies the sender's auditory and visual cues that can influence receivers' thoughts (i.e., cognition, affect, intention) and activity (i.e., purchase behavior, advocacy); and advances how machine learning can be applied to further understand what constitutes effective communication in a digital interaction.

The preceding discourse regarding sales effectiveness in commercial exchanges raises a host of issues in need of inquiry. In Table 2 , we identify a sample of possible research questions organized around five main promising avenues for B2B researchers: (1) the cues that can shape a customer's perceptions of a salesperson's digital communication effectiveness; (2) training and recruiting the digital salesperson; (3) organizational strategy and structure to support their digital selling transformation; 4) the suitability of digital selling; and (5) the potential negative effects of digital sales interactions.

Future research directions.

The cues available in digital sales interactions (see Fig. 1 ) can allow buyers and sellers to digitally simulate face-to-face interactions; however, these interactions are not as information rich as traditional face-to-face sales interactions. In an environment where the visual cues of body language and verbal cues of intonation can be out of sync, buyers and sellers can be deprived of information that could otherwise inform back-tracking or rapport building behaviors. Without the more subtle communication cues of traditional face-to-face interactions, a key starting point is to test the synchronous communications noted in Table 1 with their in-person, face-to-face counterparts. For instance, are the cues from the sender's communication barrage valued differently in digital sales interaction? What is the level of success that a salesperson is likely to achieve delivering the same standard script and call-to-action in a face-to-face sales interaction versus in a synchronous DSI (and versus asynchronous DSIs), and might those results generalize across a one-to-one and one-to-many situation? How might testing the counterfactual be influenced by the seller and/or buyer interfacing with multiple screens simultaneously? (see, e.g., cross-media consumption discussed in Bharadwaj, Ballings, & Naik, 2020 ).

Digital selling will likely require salespeople to possess an updated skill set in order to deliver a successful sales pitch ( Angevine, Plotkin, & Stanley, 2018 ; Davenport & Westerman, 2018 ), and require large expenditures on sales training ( Loechner, 2018 ). In this regard, machine learning and AI have the potential to completely change the way that firm's train their sales employees ( Singh et al., 2019 ). In their pursuit of more effective salesperson training, how might machine learning and AI help firms: reduce the amount of time needed for sales professionals to hone their digital selling skills in synchronous and asynchronous exchanges?; aid digital immigrants (i.e., older salespeople not as well-versed with digital interaction) to be more at ease with screen-mediated interactions (akin to digital natives)?; and ascertain the optimal script for a standard, synchronous sales pitch versus a standard, asynchronous sales pitch? Firms can also harness AI and machine learning for hiring decisions as well. For instance, can the repertoire of verbal and nonverbal behaviors of the most successful salespeople be cataloged and aid in the selection of prospective candidates? How should firms train employees to address cultural differences? In other words, might differences between individualistic and collectivistic cultures change the way that sellers navigate DSIs?

Firms undergoing a digital selling transformation will also need to attend to a host of issues pertaining to organizational strategy and structure. One of the most important strategic questions that firms need to address is: which set of customers is/will be most valuable? Even though new digital customers may absorb more time and require higher initial acquisition costs, it will be prudent to develop an updated decision rule in order to prioritize the firm's customer portfolio based on customer profitability (see, e.g., Zeithaml, Rust, & Lemon, 2001 ). Firms can then rely on the algorithm to determine which customers require an in-person, face-to-face meeting and which can be relegated to some type of digital interaction. From a structural standpoint, firms are often organized around functional areas, which leads to coordination issues. In this regard, a key challenge that chief marketing officers (CMO) face is how to develop “the necessary capabilities…to design, deliver, and monitor the customer experience” ( Moorman & Lemon, 2020 ). Stemming from this is: how can CMOs work with those leading other functional capabilities to develop an integrated value proposition and thereby drive favorable firm performance (see, e.g., Nath & Bharadwaj, 2020 )? Relatedly, a firm's technological platform may be built to support a traditional salesforce calling on customers in person, and set up to suit the needs of separate functional areas. An important question that arises is: what might “legacy” firms be able to learn from their “born digital” counterparts in order to expedite their on ramping of online interactions? (see, e.g., Kopalle et al., 2019 ).

Another fertile area for future research is the suitability of digital interaction. It is estimated that DSIs have the potential to significantly reduce face-to-face interaction expenses ( Laplana, 2017 ), but should the DSI be viewed as a substitute to the face-to-face sales force or a complement (see Angevine, Plotkin, & Stanley, 2017 )? As acknowledged in Footnote 3, a fully digital salesforce may not be advantageous in all instances. The factors limiting a firm from fully converting to a digital salesforce could depend on many different factors (i.e., the customer's lifetime value to the firm, stage of customer relationship, strategic importance of product, nature of purchase (e.g., straight rebuy) etc.). With a variety of limiting factors, the question becomes: under what circumstances should firms opt for an in-person, face-to-face interaction? What factors may moderate this business strategy decision (e.g., technological readiness of seller; technological readiness of buyer)? With consideration to researchers and firms unable to access machine learning or AI technologies, Tóth, Henneberg, and Naudé (2017) discuss innovative techniques, such as fuzzy set qualitative comparison analysis (fsQCA), that facilitate analyzing complex data sets holistically.

Lastly, what are the potentially negative effects of a digital sales interactions? In order to utilize the data produced from digital sales interactions, firms will need to collect data on each sales interaction. In doing so, firms will be collecting video, text, and/or audio data of not only their customers but also their employees, which could pose considerable security and privacy concerns. How might some employees or customers react to firms collecting information on each interaction? How might consumers react when they find out that firms are providing salespeople with real-time customer information and coaching to improve communication effectiveness, and in turn, business outcomes? Could their reactions augment the cost-saving potential of a digital salesforce? Alternatively, could these privacy concerns reduce the potential benefits of a digital salesforce? How might these effects be moderated by other firm specific factors? Could AI and machine learning mitigate or propagate biases?

Firms are still grappling with a variety of challenges in this new communication forum, which opens up a host of questions in need of academic attention. We are hopeful that this article spawns greater empirical research that harnesses structured and unstructured data and machine learning to better understand marketing communication effectiveness in DSIs. Additionally, we hope that future research considers the varying effects of synchronous and asynchronous digital sales (both adaptive and standard) interactions as firms need more guidance on their digital salesforce transformation investments and initiatives.

☆ The authors benefitted from helpful comments from: our anonymous reviewers, session participants at the 3rd Annual Industrial Marketing Management Summit at the Fox School of Business at Temple University, and suggestions on our earlier thinking provided by Jagdish N. Sheth.

1 The authors benefitted from helpful comments from: our anonymous reviewers, session participants at the 3rd Annual Industrial Marketing Management Summit at the Fox School of Business at Temple University, and suggestions on our earlier thinking provided by Jagdish N. Sheth.

2 We thank Audhesh Paswan for suggesting that we address broader societal changes to contextualize the prevalence of digital exchanges. We believe that the COVID-19 pandemic is yet another force that is likely to further accelerate the adoption of digital commerce.

3 We thank Raj Agnihotri for this suggestion.

4 We acknowledge that a DSI is not suitable for all instances. In a straight rebuy situation, for instance, it is more efficient for both the buyer and seller to have the repurchase of a known, required input transpire via the click of a button on a sales platform. Additionally, an in-person, face-to-face interaction may be required to lay the foundation for a relationship with a promising prospect in a complex new buy situation or a follow-up visit may be required at a strategic account for a modified rebuy . We thank an anonymous reviewer for this suggestion.

5 We thank an anonymous reviewer for this suggestion.

6 AI is technology that mimics human intelligence and cognitive functions such as perception and reasoning ( Russell & Norvig, 2014 ). For a more in-depth treatment, we direct the interested reader to Paschen, Kietzmann, and Kietzmann (2019) .

7 The aforementioned audio and visual cues can be extracted using crowdsourced lexicons developed in the R environment. The sentiment underlying the sender's spoken words can, for instance, be calculated the using the Syuzhet package and can reveal the valence of the communication over the passage of time, and Soundgen can quantify the qualities of the sender's delivery.

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The use of social media in the B2B sales process: a meta synthesis

RAUSP Management Journal

ISSN : 2531-0488

Article publication date: 29 April 2020

Issue publication date: 22 April 2021

The purpose of this study is to understand how business-to-business organizations use social media during the sales process.

Design/methodology/approach

The meta-synthesis steps methodology (Hoon, 2013) was applied.

This study presents a theoretical framework and contributes to improved understanding of how business can use social media in the sales process stages. The results allow identifying stages, discussing the integration between marketing and sales and generating benefits for the organization.

Originality/value

The proposed framework helps in understanding the previously performed fragmented studies. This study shows that social media use not only influences the sales process stages and increases the benefits to the business but also works as a mediator in the relation between sales process stages and identified benefits.

  • Meta-synthesis
  • Social media
  • Sales process
  • Business-to-business

Rodrigues, G.P. , Takahashi, A.R.W. and Prado, P.H.M.H. (2021), "The use of social media in the B2B sales process: a meta synthesis", RAUSP Management Journal , Vol. 56 No. 1, pp. 9-23. https://doi.org/10.1108/RAUSP-02-2019-0024

Emerald Publishing Limited

Copyright © 2020, Graziela Perretto Rodrigues, Adriana Roseli Wünsch Takahashi and Paulo Henrique Muller Henrique Prado.

Published in RAUSP Management Journal . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at http://creativecommons.org/licences/by/4.0/legalcode

Introduction

Social media is a technology that has been acquiring importance in our daily personal and business lives. It has changed the business scenario because it has offered organizations a chance to communicate with clients in a more effective manner ( Rapp, Beitelspacher, Grewal, & Hughes, 2013 ). Social media usage has been a discussion theme for academics and for professionals because it benefits business growth ( Lashgari, Sutton-Brady, Solberg Søilen, & Ulfvengren, 2018 ). More research is required, however, to investigate its use by the sales force ( Itani, Agnihotri, & Dingus, 2017 ).

Gradually, business is becoming aware of the importance of social media usage for client relations and communication ( Rodriguez, Peterson, & Krishnan, 2012 ), in addition to its use as a platform for realizing online campaigns in which marketing actions are performed ( Khang, Ki, & Ye, 2012 ). Despite its relevance, there is no understanding of its impact on organizational activities and how activities performed in the media influence the sales process, thereby generating benefits for the organization.

Businesses sell products and services in a market that has become more competitive. Moreover, a consumer is more careful in his purchase decision-making process because of the considerable amount of available information. Based on these facts, businesses should use new technology to enhance the sales process ( Rodriguez, Ajjan, & Peterson, 2016 ) and allow information exchange with clients ( Marshall, Moncrief, Rudd, & Lee, 2012 ).

Recently, as can be seen in the literature review, studies have investigated the impact of social media on the sales process ( Andzulis, Panagopoulos, & Rapp, 2012 ) in studies that are related to social media use, sales capability and performance ( Rodriguez et al., 2012 ; Rodriguez et al., 2016 ), as well as in studies that focus on social media use as a tool for customer relationship management (CRM) ( Trainor, Andzulis, Rapp, & Agnihotri, 2014 ). In these studies, there is a consensus that social media helps in the sales process and generates performance. They show some converging aspects by the existence of a relation between the use of social media and sales ( Rodriguez et al., 2016 ).

Other studies have been about social media use and product sales for consumers (B2C). Companies that operate business to business (B2B) have started to explore social media, although there is no understanding of whether its adoption favors sales ( Brink, 2017 ; Siamagka, Christodoulides, Michaelidou, & Valvi, 2015 ) or its organizational implications ( Ngai, Moon, Lam, Chin, & Tao, 2015 ). B2B companies have a sales process with a larger number of stages that demands considerable effort to build and maintain customer relationships using communication-related tools such as social media ( Chang, 2014 ; Rodriguez et al., 2012 ).

How has social media been used by B2B organizations in the sales process?

To achieve this objective, the meta-synthesis methodology proposed by Hoon (2013) has been applied. It allows the understanding of how companies use social media in the sales process in an exploratory and inductive way since it seeks the information synthesis already addressed in case study qualitative research. Thus, it is possible to gather information to build the theory and subsequently present a theoretical pattern with concepts and new perspectives, thereby contributing to the already existent theory. This study presents the concepts of social media use, sales in B2B organizations, methodology, the results and final considerations.

Social media use

New technologies arise and consolidate themselves in the market as social media, thus influencing the way business is performed. There is a requirement to identify emerging technologies and know-how to operationalize them to be able to add value to organizational activities ( Marshall et al., 2012 ). Social media comprises applications that use the Internet as support and allow creation, sharing and content exchanges by users e.g. YouTube and Facebook ( Kaplan & Haenlein, 2010 ).

Social media helps professionals from marketing and sales areas. Both areas use this media to help communicate not only with prospects and clients but also with other stakeholders ( Rodriguez et al., 2012 ). Social media allows sharing of content online, facilitating social interaction and developing online networks ( Agnihotri, Kothandaraman, Kashyap, & Singh, 2012 ).

There is a tendency to use social media to help communicate with clients and to facilitate sales ( Itani et al., 2017 ). Social media use is not sufficient; it is necessary to understand its application in the sales process, which comprises distinct activities. The efforts of those who manage the sales force and support the salespeople are included in these activities ( Guenzi, Sajtos, & Troilo, 2016 ). This management aims to guide team efforts to the correct usage of tools. Managers need to define how much to invest in social media. They ought to understand how social media can be used in practice to support sales activities and engender a relationship with clients ( Trainor et al., 2014 ).

Some studies show that social media use is valuable to improve sales ( Marshall et al., 2012 ), and its use contributes to organizational results ( Rodriguez et al., 2012 ). Moreover, to establish the relationship between the business and consumers and in B2B negotiations, social media use and sales activities are important ( Rapp et al., 2013 ). Social media use is a strategy that can be applied in B2B ( Siamagka et al., 2015 ) contexts to understand and develop customer relationships ( Chang, 2014 ).

Sales in business to business organizations

B2B organizations usually have fewer customers and need to manage the relationship using information technology systems ( Chang, 2014 ). However, the adoption and implementation of new technologies is a challenge because of the complexity of the B2B sales process, which has a greater number of stages ( Agnihotri, Dingus, Hu, & Krush, 2016 ; Rodriguez et al., 2012 ; Siamagka et al., 2015 ).

A sale starts with the acquisition of clients in the market and comprises activities arranged into different stages. D’Haen and Van den Poel (2013) proposed a framework that divided the sales process into different stages related to the purchase funnel. The first stage is the prospection of new potential clients (suspects). Second, the qualification of these suspects according to the criteria defined by the business (prospects). Third, contact is made with the prospects who are prepared to become an opportunity (qualified leads). Lastly, qualified leads are prepared to become real business opportunities. In this framework, the authors did not mention the post-sale stage, which involves tasks that aim to enhance client satisfaction and loyalty ( Dombrowski & Malorny, 2016 ) because the model focuses on client acquisition.

Andzulis et al. (2012) cited the sales process stages and included follow-up activities after sales closing. The stages are client acquisition, approach, understanding client requirements, business opportunities, solution presentation, closing sales and the final client follow-up.

Methodology

The eight-step meta-synthesis methodology by Hoon (2013) was applied in this study ( Table 1 ).

For case selection, the following keywords were searched: “social media” AND “sales*”. The parameter - * - was used because of the need to search for words related to sales, such as sales process and salesperson, because it is the salesperson who performs the sales activities that uses social media. The databases used were Web of Knowledge and ProQuest. For a more assertive selection, filters were selected: “title, abstract and keywords”, “article”, in the area of “applied social science and business” in the last five years of publication. 173 study papers were then identified in the search on Web of Knowledge and 127 in ProQuest. A total of 261 study papers were found because some of them were in both databases. These studies were published in 133 journals. The main journals were Industrial Marketing Management , Journal of Advertising Research , Journal of Business & Industrial Marketing , Journal of Marketing , Journal of Marketing Research and Journal of Research in Interactive Marketing , all of which had eight studies. Both the Journal of Personal Selling & Sales Management and the Journal of Retailing and Consumer Service had six studies. The others had five or fewer publications.

In the third step, 25 studies were selected for the meta-synthesis with the case study. A complete reading of the 25 studies was performed to verify if they were in the investigation scope. This eliminated another 18 studies ( Table 2 ).

The selected studies for the meta-synthesis are listed in Table 3 . It can be observed that six of them were published in journals A1 (H Index > 24) and one classified as A2 (24 <= H Index < 9) according to the QUALIS from CAPES criteria, which indicates high-impact journals.

Table 4 shows the coding and extraction of data. The final guide had 42 items.

Data analysis

After data coding, seven selected articles were analyzed, and a transversal level synthesis was realized. It was possible to suggest a theoretical framework and present research propositions with this data.

Case-specific level analysis

To be able to develop this meta-synthesis from each selected case study, the causal relations between the variables (social media use and sales process) were confirmed. A theoretical framework was elaborated from the synthesis information of each case ( Figure 1 ).

This framework gathers the main results of each analyzed study. Social media use encompasses the development of content to be published in social media ( Lashgari et al., 2018 ). Other already consolidated tools in marketing and sales, such as CRM, continue to be used by companies. Because of the influence of social media, it is suggested that CRM be used along with social media ( Cron, 2017 ) and thus it is presented as a social CRM concept ( Lipiäinen, 2015 ). It is suggested that a company use social media in conjunction with the content marketing technique (material and text creation) published in different online media and with the support of other available tools. These technologies influence the sales process ( Bocconcelli, Cioppi, & Pagano, 2017 ; Järvinen & Taiminen, 2016 ; Karjaluoto, Mustonen & Ulkuniemi, 2015 ); however, they are modified when used because social media use and sales process stages suffer each other’s influence. Finally, social media use in the sales process stages generates benefits for the organization ( Andersson & Wikström, 2017 ; Bocconcelli et al., 2017 ; Karjaluoto et al., 2015 ; Lipiäinen, 2015 ).

The proposed framework shows that the functional marketing and sales areas should be integrated ( Andersson & Wikström, 2017 ; Bocconcelli et al., 2017 ) because the stages that form the process have activities in both areas. However, closing sales is a task with commercial intent and is directly realized with clients. In the B2B context, clients perform repetitive purchases, and the focus in this market is to create loyal relationships ( Chang, 2014 ); therefore, clients that have gone through the post-sales stage can become potential clients again, i.e. prospects or leads. Because of the small number of clients, they end up purchasing again from the supplier, which strengthens the necessity to include a post-sales step.

The detail on how these presented relationships were identified is displayed in the following topics.

Transversal level study synthesis

The transversal analysis aimed to show the relation between the variables (meta-causal). A mapping was done, which was displayed in summary in Table 5 .

Table 5 shows the main insights and highlights the essential information for the development of the proposed framework.

Theory development from meta synthesis and results discussion

The studies of social media use and its relation to B2B negotiations offer a partial view about the theme. This meta-synthesis proposes a wide framework that embraces the main results in the research area using the case study method ( Hoon, 2013 ).

From the articles that were analyzed, it is proposed that social media use is a tool that comprises as much the creation as the exchange of content by users ( Kaplan & Haenlein, 2010 ). The studies mentioned some of these tools, such as Facebook, Instagram and Youtube, as well as suggesting explanations about their use ( Andersson & Wikström, 2017 ; Bocconcelli et al., 2017 ; Järvinen & Taiminen, 2016 ). Lipiäinen (2015) and Cron (2017) highlighted the CRM tool. Lipiäinen (2015) discussed the CRM social concept and showed the strong social media influence in the tools already used in the marketing area.

Järvinen & Taiminen (2016) presented the requirement for greater integration between sales and marketing areas. The objective was the use of fewer resources for the leads qualification stage, leaving more options to apply in all sales processes. This integration resulted in a greater volume of qualified leads and resource optimization. Another benefit was the sales support; however, with resource optimization, there was a possibility of increased focus on the relationship between consumers and salespeople, which generated better results in the long-term ( Andersson & Wikström, 2017 ).

This integration between consumers and salespeople is benefited by better communication, which is only possible with greater agility in the process, knowledge about message monitoring and use of media and online tools ( Bocconcelli et al., 2017 ; Karjaluoto et al., 2015 ). This justifies the requirement to propose a framework that shows the visualization of social media use and its impact on the sales process.

Social media use should be performed by sales and marketing areas that enjoy the benefits of this integration.

In addition to social media and CRM, marketing automation, content marketing, e-mail use, and blogging, are tools found in studies ( Andersson & Wikström, 2017 ; Bocconcelli et al., 2017 ), but this does not prevent social media from being a post-sales tool or a prospection; however, more studies in the area are necessary. For these reasons, it was decided to study the use of social media as a whole and not specify each media. These media frequently change ( Kaplan & Haenlein, 2010 ) and it is as difficult to understand them as it is to identify qualified professionals to use them adequately ( Andersson & Wikström, 2017 ).

The use of social media (content marketing, online media and other tools) in the sales process stages creates benefits to organizations such as better relationship with clients, sales support, improvement of the corporate image and brand, help with talent recruitment, enhanced prospection of clients and suppliers and services and products presentation.

Social media use influences sales processes, composed of the stages of identification of potential clients, prospection, contact with clients, service and products presentation, closing sales and post-sales.

Social media use is a mediator between the sales process stages and the benefits generated for the organization.

The interaction occurs all the time. The organization interacts with clients in social media and they provide information. Much more optimized content is published because of this constant exchange. The value is then co-created between the parties because both manifest themselves in the sales process ( Lipiäinen, 2015 ). Cron (2017) emphasized that this interaction brings a value proposal. This joint work (social media in the B2B sales process) offers benefits to the companies such as improved customer assistance and content offerings adequate to the client’s expectations.

There are three benefits consolidated in the literature and recurrently appearing in the analyzed articles (greater client relationships, sales support and corporate image/branding). This study has identified three other benefits and has added them to the proposed framework ( Karjaluoto et al., 2015 ; Andersson & Wikström, 2017 ; Bocconcelli et al., 2017 ).

Finally, the discussion about CRM social concept in a B2B context ( Lipiäinen, 2015 ) reinforces social media relevance. Its use has been changing the way companies operate already consolidated tools such as CRM, thus modifying the business model, including B2B negotiations.

Final considerations

social media use demands activities in the marketing and sales areas;

social media use influences the sales process stages and brings a series of benefits to companies; and

social media influences the sales process stages while acting as a mediator in the relation between these stages and the identified benefits.

Research about social media use and B2B sales processes are fragmented; the present study permitted a wide framework view. The qualitative case studies offered relevant information for developing this model and to verify repetitive information among studies. The relevance of these concepts to the problem proposed in the research has been demonstrated. The selected cases were published between 2015 and 2018, which shows the current importance of this theme. Conceptual study models were found, reinforcing the existence of opportunities for research and theory development. Comparisons among different studies are necessary to discuss and consolidate the concepts in the area while new studies can complement this study. Future research can test the proposed framework and increase the understanding of the consequences of social media use using large-, medium- and small-sized companies.

It is a consensus in the literature that social media use helps the relationship with clients, branding and sales support. However, its use extrapolates these points. According to Lipiäinen (2015) and Cron (2017) , social media use is much more than a sales and support technology; it is an essential element in value co-creation. Future studies could advance the understanding of this interaction between business and clients in the creation of a value proposal ( Cron, 2017 ), thus investigating and measuring client engagement during the sales process.

A limitation of this study is the number of studies using the case study method about the theme, only seven articles being analyzed. Despite the existence of but a few studies, they were published in high-impact journals, which shows the relevance of the analysis and its potential contribution to future studies.

research paper on marketing and sales

Meta causal net

Meta synthesis protocol

1 – Andersson and Wikström (2017) ; 2 – Bocconcelli et al. (2017) ; 3 – Cron (2017) ; 4 – Järvinen and Taiminen (2016) ; 5 – Karjaluoto et al. (2015) ; 6 – Lashgari et al. (2018) ; 7 – Lipiäinen (2015)

Source: The authors (2019)

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Acknowledgements

The authors contributed in the following ways to the paper: Perretto Rodrigues, Graziela Perretto, Corresponding Author, Conceptualization (Lead), Formal analysis (Lead), Investigation (Lead), Methodology (Lead), Project administration (Lead), Resources (Lead), Supervision (Lead), Validation (Lead), Visualization (Lead), Writing-original draft (Lead), Writing-review & editing (Lead), Takahashi, Adriana Roseli Wünsch, Conceptualization (Lead), Formal analysis (Supporting), Investigation (Supporting), Methodology (Lead), Project administration (Supporting), Resources (Lead), Supervision (Supporting), Validation (Supporting), Visualization (Supporting), Writing-original draft (Supporting), Writing-review & editing (Supporting), Prado, Paulo Henrique Muller Henrique, Conceptualization (Lead), Formal analysis (Supporting), Investigation (Supporting), Methodology (Supporting), Project administration (Supporting), Resources (Supporting), Supervision (Supporting), Validation (Supporting), Visualization (Supporting), Writing-original draft (Supporting), Writing-review & editing (Supporting).

Corresponding author

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  10. Improving the relationship between sales and marketing

    Findings - The paper indicates that there are two types of factor that affect collaboration between sales and marketing. Those that are out of the control of sales and marketing staff - management attitudes to coordination, interdepartmental culture and structure and orientation, and four that are internal to the interface - inter‐functional conflict, communications, market ...

  11. The state of selling & sales management research: a review and future

    With countless papers on the various sales-centric topics that have been authored, there are still massive gaps in the literature that require deeper examination. Therefore, the purpose of this paper is to review several areas of professional selling and sales management research and provide avenues ripe for future investigation.

  12. Journal of Marketing: Sage Journals

    The Journal of Marketing (JM) develops and disseminates knowledge about real-world marketing questions relevant to scholars, educators, managers, consumers, policy makers and other societal stakeholders. It is the premier outlet for substantive research in marketing. Since its founding in 1936, JM has played a significant role in shaping the content and boundaries of the marketing discipline.

  13. Research in marketing strategy

    In line with this, the marketing literature broadly indicates that a firm's marketing efforts impact its marketplace and economic performance through the formulation and implementation of specific patterns of resource deployments designed to achieve marketing objectives in a target market (e.g., Katsikeas et al. 2016; Morgan 2012).This formulation-implementation dichotomy perspective ...

  14. Sales and Marketing, and Customer Relationships: A ...

    This research investigates the impact of sales and marketing collaboration on the customer's propensity to purchase and customer value, thereby extending the current research into the sales and marketing interface. Prior research has established that sales departments may fail to support marketing initiatives and that marketing been known to ...

  15. Social media in marketing research: Theoretical bases, methodological

    1 INTRODUCTION. The exponential growth of social media during the last decade has drastically changed the dynamics of firm-customer interactions and transformed the marketing environment in many profound ways.1 For example, marketing communications are shifting from one to many to one to one, as customers are changing from being passive observers to being proactive collaborators, enabled by ...

  16. Introduction: Organizing Marketing and Sales

    Introduction: Organizing Marketing and Sales. Organizing Marketing and Sales. ISBN : 978-1-78754-969-2 , eISBN : 978-1-78754-968-5. Publication date: 29 May 2018.

  17. Sales: Articles, Research, & Case Studies on Sales

    by Doug J. Chung and Das Narayandas. This study of different sales quotas and their effect on sales performance at a major retail chain in Sweden finds that changing from a monthly to a daily quota plan increases performance mainly for low-performing salespeople. 06 Dec 2016. Working Paper Summaries.

  18. Journal of Marketing Research: Sage Journals

    Journal of Marketing Research (JMR) is a bimonthly, peer-reviewed journal that strives to publish the best manuscripts available that address research in marketing and marketing research practice.JMR is a scholarly and professional journal. It does not attempt to serve the generalist in marketing management, but it does strive to appeal to the professional in marketing research.

  19. Salesperson communication effectiveness in a digital sales interaction

    2. Digital sales interactions (DSIs) Exchange is a foundational concept in marketing —it has been described as "the crux of marketing" (Kotler & Levy, 1969, p.57) and as "a fundamental framework for viewing marketing" (Bagozzi, 1974, p. 77).The exchange system refers to "sets (of parties) in which interactions occur which serve to define the boundaries of the set" (Alderson ...

  20. PDF Reimagining marketing

    Reimagining marketing is a comprehensive report by McKinsey that explores how the COVID-19 pandemic has transformed the marketing landscape and what strategies can help businesses thrive in the new normal. The report covers topics such as customer insights, digital channels, agile marketing, and performance measurement. Learn how to adapt and innovate your marketing practices according to ...

  21. Sales and Marketing: Integration

    between sales and marketing improves business performance rather than evaluating its consequences. Hence, this research focuses on drivers of sales and marketing integration for creating superior customer value. Various models of this paper aim at providing guidelines for sales and marketing managers for building competitive advantages by

  22. The use of social media in the B2B sales process: a meta synthesis

    In addition to social media and CRM, marketing automation, content marketing, e-mail use, and blogging, are tools found in studies (Andersson & Wikström, 2017; Bocconcelli et al., 2017), but this does not prevent social media from being a post-sales tool or a prospection; however, more studies in the area are necessary.For these reasons, it was decided to study the use of social media as a ...

  23. Artificial intelligence in marketing: A systematic literature review

    According to previous research "When technology works on a personal level, it creates an endearing bond with the users, when marketers tap into such a bond, the potential for customer value creation is enormous" (Kumar et al., 2019, p. 137).Advanced and innovative AI-powered marketing solutions can rapidly adapt to the changing needs of businesses and come up with communications and ...

  24. Using a naive bayes classifier on goods sales data to optimize

    Selling is a business or concrete step made to move a product, whether products or services, from the manufacturer to the target consumer. The primary goal of sales is to generate profit or profit from the items or goods produced by good management producers. In practice, sales cannot be carried out without the participation of actors such as agents, dealers, and marketing employees.