Outward-looking and future-oriented customer value potential management: The sales force value appropriation

: The management of customer relationships based on customers’ value to the selling firm has been a central topic in marketing research for decades. Yet, extant research has devoted only scant attention to the management of customer future value potential, focusing mostly on advanced statistical modeling based on firm-internal and historical data, which often lacks relevance in B-to-B settings. We employ a longitudinal intervention study, rooted in a constructive research approach, to assess the relevance of a novel customer value potential management model in business markets. The results, based on realized sales and customer portfolio dynamics, demonstrate that a firm can effectively manage customer value potential by adopting a non-statistical, sales force-driven analysis perspective. Further, the study presents evidence for the effectiveness of combinative outward-looking and future-oriented value potential criteria in value potential analysis. Finally, the findings demonstrate how a supplier can proactively manage customer portfolio dynamics in the long run by systematically enhancing its competitive position and capitalizing on customers’ organic growth at individual customer account level, through the interplay of organizational value management and sales force value appropriation efforts.


INTRODUCTION
Over the last three decades, a wealth of marketing research has focused on the topic of analyzing and managing customer relationships based on customers' value to the selling firm.A variety of theoretical perspectives have been employed including customer portfolio management (Homburg, Steiner, & Totzek, 2009;Terho, 2009), customer prioritization (Homburg, Droll, & Totzek, 2008), customer lifetime value (CLV), and customer equity management (Rust, Lemon, & Zeithaml, 2004;Kumar & George, 2007).Although the studies share a highly future-oriented perspective on managing customer value heterogeneity, they have paid surprisingly little explicit attention to the management of customer future value potential in business marketing settings, despite its obvious managerial importance.As such, several gaps exist in the extant academic research.
First, the majority of studies to date have examined customer value potential based on historical and firm-internal data rather than employing outward-looking and future-oriented metrics, such as share of customer wallet, total wallet size, or customer growth representing the critical determinants of customer value potential, particularly from an operative sales perspective (see Du, Wagner, Kamakura, & Mela, 2007;Eng, 2004).For example, many customer portfolio models address the question of the customer's value potential, but mostly in parenthesis (Eng, 2004;Fiocca, 1982; see also Ritter and Andersen, 2014).In turn, the majority of CLV models estimate the future expected value of customer relationships, but only by employing firm-internal data from realized transactions, leaving other aspects of value potential open (Mulhern, 1999;Ryals & Knox, 2007;Tarasi, Bolton, Hutt, & Walker, 2011).The backward-looking and inward focus in research is a major limitation, as it can provide a highly misleading picture of customers' market potential (Du et al., 2007).
Second, most studies on managing customer value potential have been conducted in consumer settings or in industries where firms have enormous customer bases, applying advanced statistical methodologies and complex data augmentation procedures (see Du et al., 2007;Reinartz, Thomas, & Kumar, 2005;Verhoef & Donkers, 2001).However, the proposed statistical tools are often problematic to apply in practice in business markets where industrial sellers frequently have a limited number of complex and unique customer relationships (Möller & Halinen, 1999;2000;Terho & Halinen, 2012).Most SME-sized B-to-B firms possess neither the required capabilities nor resources to conduct advanced statistical estimation.As a consequence, the academic customer value management models have not found their way into wider managerial application, and scholars have called for simpler customer value analysis and estimation techniques (cf.Selnes, 2011;Wübben & Wangenheim, 2008).
Third, customer value potential focused research has largely concentrated on strategic-level modeling and segment-level marketing campaigns to develop customer equity.Very little is known about salespersons' value appropriation role in firms' systematic efforts to manage customer value (see Blocker, Cannon, Panagopoulos & Sager 2012).Yet, as boundary spanners, salespersons are in a good position to develop customer-centric insights including outward-looking and future-oriented customer knowledge (Blocker et al., 2012;Carter, Henderson, Arroniz and Palmatier, 2014).In fact, the whole sales force forecasting role represents a critical but under-studied topic in sales discipline, where scholars have called urgently for new research (Geiger and Guenzi, 2009).Studies have also largely omitted the question of how to manage value potential concretely at the sales force level.This is in contrast to business firms' management practices, where a major focus of relationship management lies frequently at the individual relationship level and the role of sales is often emphasized (e.g.Möller & Halinen, 2000;Homburg, Jensen, & Krohmer, 2008).Only limited knowledge exists on how B-to-B firms can assess and proactively manage customer value potential and customer portfolio dynamics through their sales force (Homburg et al., 2009) This study provides novel insights on the identified research gaps by adopting an outwardlooking and future-oriented perspective on customer value management, as well as by examining closer of how firms' sales force can contribute to customer value potential management practices.
More specifically, the purpose of the study is to assess the relevance of applying sales force-driven customer value potential management in business markets.The empirical research is based on the constructive research approach (see Kasanen, Lukka, & Siitonen, 1993) and focuses through an intervention case, Alpha, on implementing a sales force-driven customer value potential estimation, analysis and management program.We assess the practical applicability and theoretical relevance of the suggested approach by analyzing Alpha's realized sales and rarely studied customer base dynamics (see Homburg et al., 2009;Johnson and Selnes 2004;Terho & Halinen, 2007).
The rest of the study is structured as follows.We start by reviewing the key aspects of customer value potential management from the analysis, management strategy and sales force perspectives.
Next, we discuss methods concerning the constructive research approach and unfold the details of the empirical intervention study.We reveal the empirical results, which demonstrate how the introduction of a value potential management program, grounded in sales force derived evaluations of sales potential, can enhance suppliers' resource allocation in the customer base.Finally, we discuss the theoretical and practical implications of the study as well as avenues for future research.

MANAGING CUSTOMER VALUE POTENTIAL IN BUSINESS MARKETS
Numerous studies have focused on the management of firms' customers, based on their value to the selling firm, from various theoretical perspectives such as customer portfolio management, customer lifetime value (CLV), and customer equity management (see Bolton, Lemon, & Verhoef, 2004;Homburg et al., 2009;Kumar & George, 2007;Terho, 2009).The common unifying factor in these studies is their aim to identify and manage customers based on their value to the selling firm.
Interestingly, the research on the topic has paid surprisingly little attention to estimation of customers' future value potential, and the few studies that have largely overlook the characteristics of the B-to-B context in value potential estimation, and mostly neglect the critical outward-looking and futureoriented aspects of customer value potential.
The wide range of portfolio models focus on "analyzing the current and future value of a firm's customers for developing a balanced customer structure through effective resource allocation to different customers or customer groups" (Terho & Halinen, 2007;p. 721).Most of the proposed tools are based on soft analysis methods, such as matrices for analysis and visualization purposes, and intended for employment as managerial heuristics rather than for strict statistical optimization (Terho & Halinen, 2007).The models are particularly appropriate to the B-to-B context, where firms have a more limited number of complex and unique customer relationships (see Möller & Halinen, 1999;2000;Terho & Halinen, 2012).While the portfolio models are future-oriented, they however mostly address the question of a customer's value potential in parenthesis, largely by employing firm-internal indicators that reflect historical trends, such as customer sales (Canning, 1982;Harltey, 1976;Yorke & Droussiotis, 1994), customer size (LaForge & Cravens, 1982), or customer growth rate (Dubinsky & Ingram, 1984;Fiocca, 1982).Further, while the portfolio models fit the characteristics of B-to-B markets, they pay only scant explicit attention to customer value potential or its management from an operative perspective (see Ritter and Andersen, 2014).
The predictive CLV and customer equity management models focus on estimating the value of customer relationships by employing statistical modeling typically based on extensive datasets from completed customer transactions (e.g., Kumar & George, 2007).The managerial focus lies on identification of valuable customers and estimating how various marketing campaigns affect CLV or the total customer equity, by utilizing a customer database or behavior-switching approaches to estimate CLV (see Johnson & Selnes, 2004;Homburg et al., 2009;Rust, Kumar, & Venkatasan, 2011).Interestingly, the importance of estimating the risk associated with customers emerges in all CLV approaches, and is usually approximated through the variability in a customer's cash flow (Tarasi et al., 2011).According to this logic, even if their revenue increases are predictable, customers that are growing are evaluated as more risky than those that are stable, making the modeling approach problematic from the operative sales-potential perspective (see Selnes, 2011).Similarly, the majority of these studies estimate CLV based on historical and firm-internal data, ignoring outward-looking aspects of customer value potential, which is emphasized as being of key importance to growth (see Du et al., 2007).The heavy emphasis on advanced methodologies is problematic for many firms operating in B-to-B contexts (see Möller & Halinen, 1999, 2000) In sum, the vast majority of studies on analyzing and managing customer relationships based on customers' value to the selling firm generally recognize the importance of understanding the customer's future potential, although they typically approach value potential from the perspective of historical and firm-internal data alone.To fully understand customer value potential, particularly from an operative perspective, firms should also assess external customer activities by employing data from outside the selling firm (Du et al., 2007).The next three sections summarize in more detail the key aspects and relevance of outward-looking and future-oriented management of customer future value potential.

Outward-looking and future-oriented sales segmentation model for managing customer value potential
From an operative sales-focused perspective, effective resource allocation means a firm successfully exploits the overall potential value of each customer relationship (Grant & Schlesinger, 1995).Hence, customer value potential can be defined as the size of future customer purchases from the selling firm, if a customer behaves ideally; that is, if the customer firm purchases all products or services it currently buys in the market from the focal company (ibid.;Verhoef & Donkers, 2001).Adopting this sales-focused perspective means that customer value potential is determined by three criteria relating to a customer's purchases: total size of the customer's wallet (TSW), share of the customer's wallet (SW), and growth of the total size of the customer's wallet (GTSW) (see Anderson & Narus, 2003;Du et al., 2007;Verhoef & Donkers, 2001;Selnes, 2011).While the prior customer value management research has addressed each of these key constituents, no studies have yet systematically approached customer future value potential using a combination of these critical key metrics.Figure 1 visualizes an operative sales segmentation model for customer future value potential management based on the three key constituents.
INSERT FIGURE 1 HERE TSW in the model represents customer's total requirements across all product categories offered by the supplier (Du et al., 2007).It is a measure of a customer's entire business relationships with the selling firm and competitors.SW focuses on the customer's scope of purchases with the selling firm, which is often employed as an approximate of behavioral loyalty (Eggert & Ulaga, 2010).SW has usually been operationalized as the ratio of a customer's total spending with the focal firm to the customer's size of wallet (Du et al., 2007;Reinartz et al., 2005).Therefore, the gap between SW and TSW is an approximation of a customer's potential value that the supplier should be able to develop through a customer-specific strategy (Grant & Schlesinger, 1995).For example, customers with large total category requirements characterized by small current shares have often been termed "platinum customers", as they represent the highest growth potential for selling firms (Zeithaml, Rust, & Lemon, 2001).The third central perspective that determines a customer's future potential from an operative perspective is the estimation of how the customer's TSW will progress in the future; that is, its organic growth (Selnes, 2011).GTSW can be defined as the forecasted growth of each customer's total size of wallet over a particular period of time.From an operative sales-focused perspective, a timeframe of one year bears high managerial relevance as firms typically set annual sales targets and craft annual account management plans (Campbell, 2003).
The two presented matrices in Figure 1 represent either positive (GTSW>0) or negative (GTSW<0) growth perspectives for customers in the customer base.Further, the horizontal axes of the matrices represent TSW and the vertical axes represent SW as suggested by Du et al. (2007).The value range for SW is from 0 to 100%, which approximates the scope of customer purchases from the focal firm in relation to its total purchases.The horizontal axes approximating TSW are based on absolute data of customer total wallet size within the customer portfolio.The use of absolute values enables the framework to detect each individual customer's sales potential in comparison with actual sales; that is, the product between SW and TSW, rather than employing relative segment level measures such as quintiles (cf.Du et al., 2007).
The upper matrix in Figure 1 represents positive growth segments.The highest future growth potential can be associated with customers in segments A+ and B+.The selling firm, by investing in these customers, can take exploit customer value potential through improving its market share or exploiting customer future organic growth, as indicated by the arrows in the figure.The focal firm's competitive position is stronger for customers in segments C+ and D+.For both of these customer groups, the generation of future value is strongly connected to the ability of the firm to preserve its customer share and follow customers' organic future growth prospects.In turn, the negative growth matrix, illustrated by the lower matrix in Figure 1, comprises four declining segments in terms of future buying trends.Here, the estimated sales potential is delimited by the improvement of market share, as indicated by the arrows in the figure.The contribution of low-share small customers in segment A-should be evaluated by taking into account their cost-to-serve incidence.For segment B-, the opportunity to generate future sales relates to the supplier's capability to enhance its competitive position for large customers with low shares.Customers in segments C-and D-represent loyal mature accounts with negative growth potential.Again, the future value is connected to the ability of the firm to preserve its customer share and, when possible, to safeguard these customers' value contributions by preventing future decline.The segment development strategies for the identified customer segments are discussed in more detail in the next section.

Segment development strategies for managing customer value potential
The systematic analysis on customer value potential enables a firm to assess each of its customer's future sales potential and to form effective management strategies for identified customer segments (Kumar & Petersen, 2005;Anderson & Narus, 2003).Basically all customer value management studies include strategies to develop the value of the identified segments, labeled the formation of long-term goals to build customer equity (Hanssens, Thorpe, & Finkbeiner, 2008), the development of a customer portfolio structure (Terho, 2009), or offensive versus defensive segment strategies (Homburg et al., 2009).The key focus of the strategies concerns the future-oriented development of a relationship portfolio structure: that is, which relationships should be developed and in which direction (Terho, 2009).Homburg et al. (2009) emphasize two highly related strategies: offensive and defensive management of customer segments.Offensive management focuses on developing customer relationships to become more valuable, either by developing existing relationships or acquiring new customers.Defensive management, in turn, focuses on preventing customer relationships from ending, or declining in value, by maintaining the customer segment's value at its current level.The strategies are discussed below in relation to the segmentation tool (see Figure 1).
Various simulation studies suggest the relative appropriateness of segment development strategies varies from segment to segment (Homburg et al., 2009).Offensive strategies tend to be more effective for bottom-tier customers as they represent the lowest value, and their maintenance is marginally better than losing them completely (cf.Johnston and Selnes, 2004;Zeithaml et al., 2001).
Accordingly, from the perspective of the developed segmentation model (see Figure1), offensive strategies are particularly suitable for customers characterized by a weak competitive position (segments A+, B+, and B-), for whom the focal supplier should attempt to enhance its share, and for positive growth segments also to exploit customers future organic growth.In turn, defensive strategies should be more appropriate for stronger customer relationships, due to the need to preserve the focal firm's competitive position and profitability (Reinartz, Krafft, & Hoyer, 2004); and because as customer relationships progress to draw closer, the costs of converting customers to even closer relationships also increase (Johnson & Selnes, 2004).Hence, the defensive strategies aiming to preserve a supplier's share of wallet should be suited to large and high-share customers, that is, segments C+, D+, C-, and D-in the model presented in Figure 1.Additionally, the supplier should try to capitalize on the customer's future organic growth prospects for C+ and D+.Finally, some scholars have also stressed that, on certain occasions, investments in particular customers simply do not generate sufficient return.If profitable development of an account's value is unlikely, firms should consider also passive or active divestment strategies (Mittal, Sarkees, & Murshed, 2008;Zolkiewski & Turnbull, 2002).This is the case for small, low-share customers with declining growth perspectives in the segmentation model (A-segment in Figure 1), for whom a supplier should decide to divest on the basis of these customers' cost-to-serve incidence.

The role of the sales force in customer value potential management in B-to-B settings
Customer value management research to date has focused heavily on abstract organizational analysis and management strategies, and largely overlooked the role of the sales force in these key organizational processes (Blocker et al., 2012).Only a handful of empirical studies have conducted a closer examination of how firms' value appropriation practices can be shaped through sales force efforts.This is striking, since salespersons have unique opportunities to contribute to the systematic management of customer value potential in B-to-B settings, based on their boundary spanning role, as indicated in Figure 2 (c.f.Blocker et al., 2012).More specifically, the sales force can play a twofold role in putting the suggested value potential management program into practice, as discussed below.

Sales force role in customer value potential analysis
Salespersons can contribute to firms' systematic customer value potential analysis by developing critical knowledge on customers' future value potential (Figure 2).The outward-looking and futureoriented management of customer value potential requires knowledge on how much business a customer transacts with the selling firm's competitors, as well as on the customer's organic growth prospects.This is often a highly problematic question for selling firms, as CRM databases typically include solely firm-internal data from realized transactions with customers (see Du et al., 2007).To address the problem of not knowing TSW and GTSW when relying on firm-internal databases, customer value management studies have typically proposed complex database augmentation methods that leverage correlation patterns between customer surveys and firm data to produce the required customer data (Crosby, Johnson, & Quinn 2002;Du et al., 2007;Kamakura, Wedel, de Rosa, & Mazzon, 2003;Verhoef & Donkers, 2001).However, most SME-sized business firms rarely possess the required resources to conduct sophisticated estimations (Wübben & Wangenheim, 2008).
An alternative to statistical estimation is to acquire outward-looking and future-oriented customer potential data based on sales force-derived estimates of customers' purchasing.
The sales force forecasting role remains an under-studied topic in sales research, despite its high managerial importance (Geiger and Guenzi, 2009).Yet, operating at the boundaries of their firms with customers, salespersons are in pole position to develop customer-centric insights (Blocker et al., 2012;Carter, Henderson, Arroniz and Palmatier, 2014;Darmon, 2002).This boundary spanning role means salespersons have particularly good opportunities to produce reliable estimates of the problematic firm external value potential data (see Anderson & Narus, 1998, 2003;Blocker et al., 2012).Hence, firms can train their sales force to systematically use a direct inquiry approach to estimate a customer's actual and future expected total requirements across different product categories; either by discussions with account managers, or when customers are unwilling to provide these kind of data, by crafting estimates based on observation at customer sites, for example focusing on warehouse stocks or a dedicated area in a customer's showroom (Figure 2) (Anderson & Narus, 1998, 2003).Effective data estimation requires further that the selling firm provides its sales force with clear-cut guidelines on how to report the estimates in a unified way.

Sales force role in implementing customer segment development strategies into practice
To put segment development focused strategies into practice, firms need to make concrete resource allocation efforts at sales force level, often labeled in the literature as customer treatment decisions (Terho, 2009), decisions to allocate marketing resources to build customer equity (Hanssens et al., 2008), or investment decisions on putting offensive versus defensive strategies into practice (Homburg et al., 2009).Interestingly, most academic modeling based value management studies have not paid close attention to this perspective, as they have delimited their focus purely to abstract segment level strategies, and studied the effectiveness of these strategies based on simulation (e.g.Johnson & Selnes 2004;Hanssens et al., 2008;Homburg et al., 2009).In turn, many customer portfolio management studies discuss concrete customer treatment decisions at sales force level, but typically do not examine empirically their deployment in practice (Fiocca 1982;Ritter & Adresen, 2014).Yet, in B-to-B settings, salespersons play a central role in implementing customer value potential management strategies in practice, and the organizational segment level strategies are keenly connected to sales force value appropriation efforts in several ways (see Figure 2).
First, organizational value potential management forms a systematic framework that helps salespersons recognize a financial yield perspective in dealing with their customers.Value potential segmentation related prioritization knowledge helps a firm's salespersons better recognize the value potential of each of their customers, and also to better understand their instrumental role in the overall health of the firm in the long-term (see Blocker et al., 2012).
Second, a firm's value potential management strategies can help salespersons' value appropriation efforts by giving them concrete guidelines on how to allocate their resources for individual relationships (see Blocker et al., 2012).Resource allocation at sales force level relates keenly to ways of interacting with the customer, based on customers' value to the selling firm, including decisions such as the allocation of salespersons' time, level of service, communication, and the adaptation of sales processes for customers (Reinartz & Kumar, 2000;Terho, 2009).Hence, organizational guidelines help salespersons make informed allocations of sales efforts to customers of different value (Jones, Brown, Zoltners, & Weitz, 2005).These efforts include, for example, prioritizing customers with the greatest growth potential (offensive strategies), allocating required attention to current high-value accounts to prevent their decline (defensive strategies), and assessing the feasibility of customer specific investment for low value customers based on the estimated costto-serve (potential divestment strategies).
Third, the organizational value management can further support salespersons' value appropriation efforts by providing them with concrete tools to implement segment strategies at individual customer account level.For example, organizational cross-selling and up-selling campaigns as well as KAM arrangements act as needed customer incentives to maintain or deepen the relationship, and also provide salespersons with the concrete means to signal their firm's commitment to customer value creation for the individual accounts (see Anderson & Narus, 2003;Eggert & Ulaga, 2010).The cross-selling tools are particularly important in implementing offensive segment strategies in practice, as customer value potential is often keenly related to cross-selling opportunities (Du et al., 2007;Reinartz et al., 2005).
In sum, the sales force value appropriation role is best understood in the context of strategic firm-level value management practices.If the value potential estimation and value appropriation efforts are driven by individual salespersons for single accounts, a firm's overall portfolio related decisions are likely to be undermined in the long run, and there will be no continuity of customer management (Johnson & Selnes, 2004;Terho 2009).Also, individual salespersons require firm-level support to truly be able to deepen and sustain customer relationships in the long run (Eggert & Ulaga, 16 2010).Finally, salespersons' information acquisition related to value potential estimation can be time consuming, and its sophistication as well as accuracy can vary significantly among salespersons depending on their skills and knowledge (Darmon 2002;Weitz, Sujan & Sujan, 1986).By providing unified training and effective tools, firms can systematically promote the effectiveness of their salespersons' value appropriation efforts.

METHODOLOGY: A CONSTRUCTIVE RESEARCH APPROACH
Explicit research on customer value potential analysis remains scarce.Further, the few extant studies on the topic have relied on statistical estimation, and most of the research has been conducted in consumer settings.This emphasis lacks managerial relevance in business markets and the various statistical customer value management approaches subsequently suggested by the academia have not migrated to wider managerial application (Wübben & Wangenheim, 2008).The business marketing field lacks alternative, low-cost, and simple customer value potential management tools.This study contributes to the gap by exploring the applicability of a non-statistical sales force-driven customer value potential management approach.In so doing, we rely on a constructive research approach that is particularly suited to examining the applicability and relevance of new management constructs (Kasanen et al., 1993;Labro & Tuomela, 2003).

INSERT FIGURE 3 HERE
The constructive research approach represents a research procedure to produce novel managerial constructs that solve emerging problems in running business organizations (Kasanen et al., 1993).It differs from the action research approach as its essential characteristic is to tie a managerial problem and suggested solution to theoretical knowledge and, in so doing, to apply scientific methods (Kaplan, 1998;Kasanen et al., 1993).The approach has been developed and primarily employed in the field of accounting and performance management (Kasanen et al., 1993), although it has also been utilized in other business disciplines (e.g.Koskinen, 2009;Hill, Nicholson, & Westbrook, 1999).The constructive research perspective as it is highly consistent with the aims of this study, which focuses on real-world evaluation of a novel customer value management construct.
Since constructive research is not as yet an established methodological approach in marketing, we discuss in detail the applied research process based on its three main phases: preparatory, fieldwork, and theorizing, as shown in Figure 3 (Labro & Tuomela, 2003).
At the core of the preparatory phase lies the identification of a practically relevant problem that bears high managerial relevance while possessing theoretically significant potential to be solved; that is, no readily available theoretical solutions to the problem exist (Kasanen et al., 1993).In the context of this study, the sales force-driven customer value potential management approach based on an outward-looking and future-oriented perspective contributes both to practical and theoretical gaps.
The second step in the preparatory phase is the selection of a case organization for longitudinal research cooperation (see Labro & Tuomela, 2003).Industrial firm Alpha was selected for this study as it wanted to improve its sales by more extensively exploiting its current customers' sales potential, and was willing to develop and implement a customer-potential management program built on the three sales-potential metrics, introduce systematic outward-looking data collection efforts to its sales force, and invest in systematic value potential management efforts.Alpha operates in the field of machinery manufacture, is one of Italy's leading agricultural equipment producers, and its competitive strategy focuses on offering technological solutions and services characterized by high standards of reliability at a competitive price.It maintains a strong international presence in many countries through a wide network of customers characterized by long-term collaborative relationships.
The fieldwork phase of constructive research should be based on extensive theoretical groundwork enabling informed interventions based on ex-ante theoretical knowledge (Kasanen et al., 1993;Labro & Tuomela, 2003).The study meets this criterion as the suggested managerial construct, that is, the sales force-driven customer value potential management approach, builds strongly on the extant academic research.The developed managerial construct simultaneously represents a novel practical solution, which we want to implement and test, to a real-world organizational problem (step 4).The implementation of value potential management (step 5) was performed over three years in close cooperation with Alpha's marketing division.We were granted rare access to customer-level data in one of Alpha's specific European markets before and after implementation of the framework, which enabled us to explore the sales and customer base dynamics.The details of the longitudinal intervention case are presented in greater detail in sections 4.1-4.3,describing the implementation process of value potential management in detail.
Finally, the theorizing phase focuses on analyzing the applicability and theoretical relevance of the discussed value potential management approach (Kasanen et al., 1993;Labro & Tuomela, 2003).
The practical applicability of the management program was initially supported, as Alpha adopted the management scheme in its sales practice, which represents a successful 'weak market test' (see Labro & Tuomela, 2003).The theoretical relevance of the approach is discussed based on the outcomes of the customer sales-potential program, grounded in Alpha's realized sales and customer portfolio dynamics.The theoretical contributions are elaborated in the discussion section, where the empirical results are related to extant research on customer value management.

RESULTS FROM THE LONGITUDINAL INTERVENTION CASE ALPHA
This section discusses the implementation of the value potential management program at Alpha, and the realized outcomes based on data from a period of three years.We first present the implementation process of the sales force-driven data estimation (4.1), followed by the applied segmentation framework (4.2), and the implementation of segment strategies (4.3).Finally, we describe the outcomes of the value potential management program, based on the realized sales and customer portfolio dynamics (4.4).

Sales force-driven customer sales-potential estimation at Alpha
Alpha commenced implementation of the customer sales-potential management scheme during 2006, starting systematic collection of outward-looking and future-oriented customer value potential data via its sales force.Alpha's marketing director launched systematic customer value potential estimation based on a direct inquiry approach (Anderson & Narus, 2003), initiating an internal sales force training program for effective collection of customer potential data.
Salespersons were trained to collect two main customer potential metrics by employing a straightforward direct inquiry approach.First, they were instructed to ask their customers to divulge their total number of purchased machinery units for which Alpha had a product category.These unit based responses enabled Alpha's management to calculate the sales volume based value potential for each customer for in depth analysis.Second, the salespersons were instructed to discuss the customers' planned purchase volumes in each product category over the next year, as defined by the customers' planned budget or by personal forecasts when budgetary information was not available.
Alpha's marketing unit developed a data collection form that each salesperson should complete and deliver within a fixed schedule, in order to build up homogenous customer value estimates.While sales volume based estimation did not enable the analysis of the customers' future potential from a profitability perspective, Alpha's management deemed that, for example, cross-selling campaigns were likely to have similar impacts across its key product categories and, with the salespersons' time taken into account, on customer profitability.This was because Alpha's average margins for its various product categories and products within categories were highly uniform.
Alpha's sales force received good access to the sales volume based data as part of the scheduled overall information exchange with their customers.More than 70% of customers were willing to impart information on their sales volumes.For those customers whose data were more difficult to obtain, salespersons estimated sales volumes focusing on the relative incidence of suppliers' products in warehouse inventory and/or at showrooms.With regard to planned purchases, salespersons were able to elicit budgets from 45% of customers, and another 35% of the accounts were willing to provide a rough forecast for the next year, expressed in terms of increasing, stable, or decreasing.The remaining 20% of the customer base was less accessible.In these latter cases, salespersons were trained in fine-tuning customer sales forecasts, focusing on local trends in real-estate and agriculture production, and competition in the local market.
Salespersons' motivation to put effort into data collection was determined by their future reward expectations, rather than by monetary incentives designed for this task.During the training process, Alpha's marketing managers highlighted how systematic data collection would enable the development of systematic tools to help salespersons better manage customer value potential, and enhance their sales performance.From the salespersons' perspective, the effort expended on the task was directly linked to their expectations of increased commissions through enhanced sales performance.The approach worked well as Alpha's sales force became committed to the estimation.

Operative customer value potential segmentation framework at Alpha
The sales force-driven data estimation procedure enabled Alpha to move to customer segmentation.
More specifically, the data on the intervention case Alpha were collected at two time points in Alpha's customer-potential management program: first, at the beginning of 2007 and, second, one year after implementing the management program in 2008.The study is delimited to Alpha's customer base in one European country, where it had 115 active customers.The value potential analysis was based on the three key customer value potential metrics presented in the theoretical framework of this study: 1) total size of wallet (TSW), 2) share of customer's wallet (SW), and 3) growth of the total size of customer's wallet (GTSW), based on the collected data.Utilizing these three metrics, Alpha identified 18 segments in its customer base that had varying degrees of potential, as illustrated in Figure 4.The figure is based on the number of machinery units sold, used to calculate the actual sales volume based value potential estimates at further stages of analysis.

INSERT FIGURE 4 HERE
More specifically, Alpha divided its customers, based on TSW, into three classes: small customers with total purchases of less than 100 units of machinery, medium-sized customers with purchases of 100-300 units, and large customers that bought more than 300 units per year.Similarly, each customer's SW was divided into three subsets: low penetration customers with a less than 50% share, devoted customers with a 50-75% share, and single-sourcing customers with a share greater than 75%.These metrics include two main product categories sold by Alpha that together represent more than 90% of its overall sales, both in terms of sales volume and profit.This choice is corroborated by the fact that Alpha's main product categories have a very homogenous price and margin range.
Finally, Alpha divided its customers into two further groups, based on TSWG, as measured by positive or negative growth prospects derived from customers' budgets.The magnitude of estimated growth per customer is further illustrated by circle size in the figure.
Figure 4 visualizes the 18 customer segments identified in Alpha's initial value potential estimation.As expected, more than half of Alpha's customer base is concentrated within two segments, A and D. Further, 80 of Alpha's 115 customers had a positive growth forecast.While the customer segments were rather unevenly distributed, Alpha's management perceived that this segmentation scheme was particularly useful and reflected the relative novelty of this market for the firm.The fact that most of the customers belonged to bottom-tier segments underlined the importance of investing in the management of customer sales potential, and also served as an effective basis to motivate the sales force on the relevance of the topic.

The implementation of Alpha's customer segment strategies
Alpha used the customer value potential segmentation scheme to develop strategies for managing its customer base.More specifically, Alpha crafted segment strategies to develop the value of the identified customer segments at an annual level.Alpha further developed concrete customer treatment guidelines and tools for its sales force to implement the segment strategies in practice, and to facilitate its salespersons value appropriation efforts at the individual account levelsee Table 1.
For top-tier customer segments, characterized by high SW and positive predicted organic growth (G+, H+, and I+), Alpha adopted a defensive segment development strategy aimed mainly at retaining customers and building relationships to capitalize on the customers' organic growth.The primary way in which to sustain and develop these accounts was a key account management (KAM) scheme through which Alpha's salespersons placed emphasis on service prioritization to build trust and commitment.The KAM arrangement included organizational investments for promotional support and high levels of post-sales assistance, aiming to help these customers grow their business and to signal Alpha's commitment to customer value creation.
For low-share customer segments with positive growth potential (A+, B+, and C+), Alpha adopted offensive strategies to improve its competitive position.Fundamentally, this strategic objective was implemented through cross-selling campaigns at sales force level.Alpha defined a specific cross-selling scheme to enable its salespersons to customize cross-selling campaigns on the basis of individual customer's cross-buying potential.The large accounts in segments B+ and C+ were prioritized for sales resource allocation, through special investments in salespersons' time and quality of sales interactions to fully capitalize the organic growth potential of these accounts.
For mid-tier segments with medium SW figures and positive growth prospects (D+, E+, and F+), Alpha aimed to strike a balance between defensive customer retention and offensive penetration by exploiting customers' organic growth opportunities.Alpha emphasized deepening the relationships by investing in special sales resources for these customers.For segments E and F, which include larger customers with growth potential, Alpha also emphasized KAM prioritization for deepening the development of relationships and sales.
Alpha's long-term goals for the low-share and declining customer segment A-focused on ensuring cost efficiency in its resource allocation to these customers.Alpha decided to adopt a passive divestment strategy based on salespersons' evaluation of cost-to-serve incidence in customers within segment A-, as these sales resources could be employed more effectively in other customer segments.
In turn, the low-share, and declining larger customer segments B-and C-, were deemed to involve growth opportunities by increasing Alpha's SW through an offensive approach involving crossselling campaigns adapted by the sales force to the individual accounts.
The top-tier declining customers (G-, H-, and I-) represent single sourcing-type devoted accounts that warranted defensive strategies to prevent a decline in sales.Alpha's strategy at sales force level focused on devoting special efforts to clarify the reasons for the estimated sales decline, and investing in the customer relationships through organizational KAM prioritization aimed at supporting customers' business.
For the mid-tier declining customer segments (D-, E-, and F-), Alpha's relational strategies focused on a balance between partial divestment and retention.For declining small customers (D-), Alpha decided to employ a passive divestment strategy by allocating its sales resources to customers with more lucrative sales opportunities, based on salespersons' evaluation of cost-to-serve incidence.
For the large and mid-sized segments (E-, and F-), Alpha adopted a defensive strategy similar to that employed for top-tier declining customers, realized through KAM prioritization, to maintain its position with these customers.Alpha invested further in efforts to clarify the reasons behind the projected decline in sales.

Realized sales for customer segments and the resulting segment dynamics at Alpha
The key outcomes resulting from Alpha's operative value potential management program after one year of initiation are summarized in Table 1.The results provide interesting insights concerning the management of future sales potential in business markets, based on the customer share of wallet (SW), total size of wallet (TSW), and growth of the size of wallet (GTSW).

INSERT TABLE 1 HERE
Overall, the results indicate that the suggested non-statistical and sales force-driven customer value management approach is effective in business markets, aligned with earlier related findings on soft value management methods (see Brinkmann & Voeth, 2007;Wübben & Wangenheim, 2008).
More specifically, case firm Alpha's overall sales volume increased 65% after the first year of its implementation of the customer value potential management program (see Table 1).This figure can be split into customers' organic growth, reflected in the growth of customers' TSW by 37% (Table 1, Δ TSW 08-07 column), and the strengthening of Alpha's competitive position within customer segments by increasing Alpha's customer SW by 7% (Table 1, Δ SW 08-07 column).Interestingly, the predicted direction of future size of wallet growth (TSWG) was accurate for 13 of the 15 customer segments, as ΔTSW was positive for all nine predicted growth segments, and negative for four of the six predicted declining segments.While the overall growth numbers reflect the positive economic environment and relative newness of the market for Alpha at the time of the study, it is important to note that the realized growth in segments closely follows Alpha's segment management strategies, and that the findings are partly aligned with earlier statistical modeling and simulation based studies (see Homburg et al., 2009;Johnson & Selnes, 2004;Verhoef & Donkers, 2001).
More specifically, positive sales growth was realized for all predicted growth segments from A+ to I+ (Table 1, Sales growth column).Especially, for low-share customers' segments A+, B+, and C+, Alpha could systematically increase its SW numbers due to better penetration achieved through cross-selling activities (Table 1, Δ SW).Further, as estimated, these segments also experienced notable organic growth that could effectively be exploited by Alpha's sales force.In turn, in the middle and top-tier segments, Alpha grew mainly through its customers' organic growth rather than by increasing its SW with these customers (from D+ to I+).In fact, realized SW delivered mixed results, indicating that Alpha could not fully maintain its competitive position in these segments, as SW metrics decreased in four out of six middle and top-tier segments (Table 1, Δ SW).These findings are consistent with Homburg et al. (2009), who demonstrated that bottom-tier customers are more likely to increase in value in future periods, due to the high probability that they switch to higher value segments.Extending earlier studies, our results emphasize the relevance of applying knowledge on a selling firm's competitive position, concerning each customer's purchases, to craft customerspecific strategies that systematically improve SW (see Du et al., 2007).The applied cross-selling schemes were particularly effective with low-share growing customers.In addition, the results demonstrate organic growth can be a major source of potential.This highlights the importance of considering the future oriented TSWG metric in value potential estimation, something that has been largely omitted by earlier studies focusing primarily on TSW (cf.Selnes, 2011).
As expected, customer wallet sizes reduced for four out of six segments with negative estimated sales growth (Table 1, Δ TSW).Also, realized sales followed Alpha's segment strategies as, for medium and large-sized low-share customer segments (B-and C-), Alpha could grow despite the negative segment growth as a result of a higher penetration rate (see Homburg et al., 2009).Further, the share and size of wallet figures reflect the partial divestment strategies for small declining segments A-and D-.In turn, for the middle and top-tier segments, the outcomes of Alpha's retention efforts were at best mixed, as its shares declined for segments G-and E-.These findings reflect the fact that maintaining the middle and top-tier segments with high shares can be challenging in the long term, particularly if customers' overall purchases are declining.
Longitudinal sales data can be further employed to analyze and track realized customer portfolio dynamics, as the SW and TSW data enable the detection of how specific Alpha customers moved from one segment to another, at the annual level (see Table 2).The diagonal bloc in Table 2 shows customers that have remained within their original segment over the examined time period, those which have moved to lower value segments (above the diagonal), and which have moved to higher value segments (below the diagonal).Table 2 confirms the earlier findings from studies applying advanced statistical modeling that negative segment dynamics are a concern, especially in the medium and top-tier segments (Johnson & Selnes, 2004).In turn, dynamics show that customers with a small share can be perceived as "platinum customers" since they demonstrated high growth potential also in B-to-B settings (see Zeithaml, Rust, & Lemon, 2001).declining TSW during the period of investigation.The negative segment dynamics are of particular concern in the medium and top-tier segments (Johnson & Selnes, 2004Homburg et al., 2009).Finally, the results confirm that the migration of even a single large customer in top-tier segments is likely to have a major impact on sales, and therefore on portfolio dynamics (Homburg et al., 2009).

INSERT TABLE 2 HERE
In sum, the longitudinal results from the intervention study at case firm Alpha suggest the implemented customer value potential management program has helped Alpha systematically grow its sales, thereby supporting the managerial relevance of the suggested value potential management approach.Further, the results partly align with earlier modeling based studies and reveal systematic patterns between segment strategies and realized growth, which supports the effectiveness of sales force-driven customer sales-potential estimation.Next, we discuss in greater detail the theoretical and managerial contribution, as well as future research implications of this study.

Theoretical Implications
This study contributes to the broad stream of research concerning the management of customer relationships based on customers' value to the selling firm (Homburg et al., 2008;Kumar & George, 2007;Rust et al., 2011;Zolkiewski & Turnbull, 2002).To date, only a few studies have specifically focused on the management of customer value potential in the business marketing context.While the management of customer relationships based on expected future value has been a growing trend in research, particularly in predictive CLV studies (Jain & Singh, 2002;Venkatesan & Kumar, 2004) and customer equity studies (Rust et al., 2004;Kumar & George 2007), extant research has delimited its perspective heavily to consumer business and relied on advanced statistical modeling, based on firm-internal and historical data (Reinartz et al., 2005;Verhoef & Donkers, 2001).The present study provides new insights on customer value management in business markets from an alternative perspective by exploring the relevance of employing non-statistical and sales force-driven customer value potential management from an outward-looking and future-oriented perspective.The study makes three specific contributions to the extant research.
First, the study introduces a novel customer value potential segmentation tool to manage customer value heterogeneity (Reinartz & Kumar 2005) on the basis of both outward-and forwardlooking metrics, rather than typical firm-internal and historical data which can give rise to a misleading picture of customers' market potential (Du et al., 2007).As such, the tool continues the long tradition of managerially oriented customer value management models in industrial marketing, from Fiocca (1982) to Ritter and Andersen (2014).The results provide rare empirical evidence on the combinative use of outward-and forward-looking metrics, and demonstrate how they can be effectively employed to manage value potential in B-to-B settings.More specifically, the segmentation framework builds on three critical determinants that together define customers' market potential: customer's total wallet size, share of customer's wallet, and customer's wallet growth.
While each of these criteria has been discussed in previous studies, they have not formerly been used in combination to systematically manage customer value potential (see Anderson & Narus, 2003;Du et al., 2007;Ritter and Andersen, 2014).With regard to the outward-looking perspective, the results demonstrate the importance of gathering information on a customer's relationship with competitors, as this knowledge enables the supplier to tailor customer-specific strategies to improve its customer share of wallet and, in turn, value growth.In relation to the forward-looking approach, the findings show that the largely ignored organic growth estimation, based on the estimation of total wallet size growth or decline, can play a substantial role in effective resource allocation among customers (see Selnes, 2011).As such, the proposed approach differs markedly from mainstream CLV studies that focus on estimating and minimizing risks associated with customers, usually based on variability in their cash flow (Tarasi et al., 2011).Based on this logic, growth customers are evaluated as more risky than stable customers, even if their revenue increases are predictable (Selnes, 2011).Contrary to CLV research, the proposed tool represents an active way for suppliers to capitalize on customer potential, and actively cope with risks relating to their customer base (see Eggert & Ulaga, 2010).
Second, the study extends the current knowledge by demonstrating that non-statistical, sales force-driven analysis can be effectively employed to manage customer value potential.This perspective fits well with the characteristics of business markets, where firms often have a limited number of complex customer relationships, making the dominant statistical models problematic to apply in practice (see Möller & Halinen, 1999;2000;Terho & Halinen, 2012).Interestingly, only a handful of empirical studies have thus far examined how firms' value appropriation practices can be shaped through the efforts of their sales force (see Blocker et al., 2012).This intervention study provides rare empirical evidence that business firms can effectively generate critical outward-looking and future-oriented customer value-potential data by training their salespersons to estimate customers' actual and future expected total requirements across different product categories in unified ways (see Anderson & Narus, 1998, 2003).The results indicate that salespersons' boundary spanning purely on firm-level segment strategies, the intervention case shows how portfolio dynamism is realized as interplay between organizational value management and sales force value appropriation efforts (Blocker et al., 2012).On the one hand, the sales force ultimately puts the segment-level strategies into practice by selectively allocating sales efforts to customers of different value.On the other hand, organizational customer value management enables effective sales force value appropriation efforts by providing salespersons not only with prioritization knowledge and account management guidelines, but also with the necessary tools to develop relationships and sales at the individual relationship level through cross-selling campaigns and KAM arrangements (Eggert & Ulaga, 2010).Importantly, the empirical findings concerning the realized sales and segment dynamics are aligned with earlier simulations which suggest that bottom-tier customers are more likely to increase in value in future periods through offensive management strategies, whereas defensive strategies are more appropriate to mid-level segments (Johnson and Selnes 2004;Homburg et al., 2009).

Managerial implications
Advanced academic statistical customer value management models have not migrated to wider managerial applications (Wübben & Wangenheim, 2008).Our study contributes to the field of customer value management by proposing a simple yet effective segmentation tool to manage customer value potential from an operative perspective, and by demonstrating the relevance of sales force-driven customer value potential management in B-to-B markets.Importantly, the proposed approach can be implemented by industrial SMEs lacking advanced modeling capabilities.As such, the study answers the call to increase managerial relevance in B-to-B marketing research (see Lilien, 2011), and responds to calls for simpler customer value analysis and estimation techniques (Selnes, 2011).
The proposed operative customer value potential segmentation tool is based on three outwardlooking and future-oriented relationship metrics: share of customer wallet, total wallet size, and customer growth, which represent particularly from an operative sales perspective, the critical determinants of customer value potential (see Du et al., 2007;Eng, 2004).We demonstrate that firms can gather these firm-external and customer's future buying related data in a straightforward manner by training their sales force to estimate necessary value potential information in their daily work (Anderson & Narus, 1998;2003).The suggested approach highlights further concrete strategies to develop the value of differing customer segments, and provides the means to follow the effectiveness of segment strategies based on realized sales and customer base dynamics in the long run.
From an implementation perspective, our methodology highlights the joint contribution of sales and marketing in cases where they are organized as separate functions (Guenzi & Troilo, 2006).In particular, a salesperson's commitment in collecting outward-looking and future-oriented data on customers becomes effective when the estimation approach is clearly defined and the rationale behind expected sales outcomes explicated.This enables marketing and sales to align their vision and decision processes, and to effectively analyze customer value potential, tailor customer strategies and put the strategies into practice both at customer base and individual customer levels (see Biemans, Brenčič, & Malshe, 2010).
Finally, it should be emphasized that the suggested value potential management approach is relevant for firms that have a "narrow" customer base comprising a limited set of long-term customer relationships.Alternatively, the suggested approach can be selectively implemented on a number of specific key customers and/or product categories, rather than on the whole customer base.For example, this methodology might initially be employed only on key accounts, with progressive implementation on the rest of the customer base (Ryals, 2005).For firms with extensive customer bases, the statistical methodologies are likely to bear more managerial relevance.

Limitations and directions for future research
This study is subject to some limitations that offer also potential for future research.First, the applicability of the studied approach to managing customer value potential rests on the assumption of a customer base's homogeneity in terms of customers' buying behavior.In cases where a selling firm's customers vary markedly with regard to their buying approaches or their relationship characteristics to the selling firm, the customer-specific strategies can be improved by focusing the value potential estimation to more homogeneous customer segments.
Second, the developed customer value potential management framework focuses on sales potential rather than profitability potential.As resources allocated to customers are largely proportionate to sales, in particular for cross-selling, we can only assume the overall profit growth as the average margins for the case firm's products were highly uniform.Because the suggested value potential management approach focuses on sales volumes, we recommend using it in conjunction with other management tools that address customer profitability, such as CRM systems.A worthwhile extension to our study would thus be to conduct a closer examination of the cost-to-serve estimates at sales force level for a closer assessment of the link between sales growth and profitability.Fourth, while our study makes a unique contribution to the marketing literature by providing exceptional evidence on the dynamic aspects of customer portfolio management based on longitudinal real-world data, only two periods of panel data were available in our empirical application due to data access reasons.We call for new studies with more extensive panel data for a better understanding of how customer value potential management can drive customer portfolio dynamics in the long run.
Finally, from a methodological perspective, our research demonstrates that the constructive research approach, focusing on developing novel managerial constructs and assessing their practical applicability, as well as theoretical relevance in business applications, is well suited to managerially oriented business marketing research.We encourage marketing scholars to consider this perspective when developing new managerial tools such as portfolio models in future marketing studies.
Third, the longitudinal intervention study supports the overall accuracy of sales force value potential estimates based on the predictive validity of the segmentation tool: the realized sales largely follow the applied segment strategies, and the portfolio dynamics are partly aligned with earlier simulation studies.Still, we cannot verify the exact accuracy of the individual account potential estimates as our study includes only sales force-driven estimation data.We invite future studies to compare the accuracy of salespersons' value potential estimates in relation to more objective statistical modeling based estimates.It would be particularly interesting to study closer how different contextual factors such as sales force experience and ability levels or number and heterogeneity of customers affect salespersons' estimation accuracy.

Figure 1 -Figure 2 .
Figure 1 -Illustration of customer potential based on TSW, SW, and TSWG* : Segments in the diagonal = static situation; above diagonal = negative change in SW or TSW; below diagonal = positive change in SW or TSW

Table 2
summarizes the main customer base level developments behind Alpha's sales growth, and depicts interesting trends in Alpha's segment dynamics.First, Alpha's offensive strategies, based on increasing customer SW, have been effective in bottom-tier segments (A, B, and C), as a total of 15 customers have moved to higher SW segments, representing a 21% increase.The strategies have also resulted in improvements in mid-tier segments (D, E, and F), with five customers moving to higher SW segments, representing a 13% increase.Second, the table indicates that customers' organic growth has been a highly significant source of growth for Alpha, especially in the middle (+15 customers, 38% increase) and bottom-tier segments (+13 customers, 18% increase).Third, the table shows that Alpha's negative segment dynamics, that is, customers moving to less valuable segments, were almost entirely caused by a decline in customer shares (9 customers) and not by customers'