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Using CRM data : Modeling and measuring the effect of sales force knowledge on customer decision making. Othman BOUJENA– Wesley JOHNSTON & Dwight MERUNKA. Research context. Increasing investments in CRM (Forester research report 2011 on CRM trends)
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Using CRM data : Modeling and measuring the effect of sales force knowledge on customer decision making Othman BOUJENA– Wesley JOHNSTON & Dwight MERUNKA
Research context • Increasing investments in CRM (Forester research report 2011 on CRM trends) • Objective : value creation and customer equity valorization through a 360° view of the customer • Each customer interaction/touch point : an opportunity for improving satisfactionand maximizing relationship profitability • The crucial role of sales force in conveying market information • One main challenge : an effective usage of CRM generated knowledge
Previous main studies CRM adoption by organizations Adoption of CRM/SFA by salespeople The impact of SFA/CRM usage on individual performance Engle and Barnes 2000; Ahearne et al. 2008; Widmier et al. 2002; Keillor, Bashaw and Pettijohn 1997; Speier and Venkatesh 2002; Zablah, Bellenger and Johnston 2004…
Research issue If and how CRM usage by sales force improves their knowledge and then customer decision making ?
Literature review Exploratory qualitative study Conceptual model Research development process 1 2 3
Literature review: CRM and sales force performance • Sales force : one of the main users of CRM • CRM is first ‘’a company philosophy and strategy that aims at aligning all processes to improve customer satisfaction and loyalty’’ (Zablah, Bellenger and Johnston 2004) • CRM definition: ‘’ CRM unites the potential of relationship marketing strategies and IT to create profitable, long-term relationships with customers and other key stakeholders. CRM provides enhanced opportunities to use data and information to both understand customers and cocreate value with them’’ - Payne and Frow (2005)
Literature review: CRM and sales force performance… Leveraging opportunity and leads intelligence (Grant and Schlesinger 1995; Jayachandran et al. 2005) Prospecting, development & customer profiling (Pullig et al. 2002) CRM/SFA Usage Formulating alternatives, effective decisions & relationships (Hill and Swenson 1994) Customer communication (Hunter and Perreault 2007; Rice & Blair 1984; Sproull and Kiesler 1986; Ahearne et al. 2008, Khandpur and Wevers 1998)
Thematic content analysis Lexical analysis Cognitive mapping Exploratory qualitative study • Semi-structured in depth interviews • Matched sample : CRM editors, sales managers, salespeople, customers • Double coding process with meta-categorization (Miles & Huberman 1994) – manual and with NVIVO • Agreement based coding : Cohen’s Kappa = 80 %
Conceptual model :The impact of CRM usage on customer decision making
Salesperson competence • ‘’Customer perception that a salesperson is knowledgeable in important areas such as specific needs, product knowledge, industry trends, and competitive products’’ (Behrman & Perreault 1982; Narver & Slater 1990; Day 1994; Sinkula 1994) • Knowledge contributes in sales effectiveness (Behrman et Perreault 1982 ; Leigh et McGraw 1989 ; Sujan et al. 1986 ; Weitz 1978 ; Weitz et al. 1986) • Technology and CRM capacities for information gathering, storage aznd diffusion (Glazer 1991 ; Fletcher 1990 ; Huber 1991; Marshall, Moncrief and Lassk 1999) • The impact of IT/SFA on market and technical knowledge (Ahearne et al. 2008)
Customer decision making • ‘’Process based on information requirements, decision making time, people involving in buying decisions, and buying criteria’’ (Sharma and Pillai 1996) • The role of sales force in optimizing the decision process : providing critical information and showing the capacity of meeting expectations and integrating customer’s constraints (Atkinson and Koprowski 2006) • Two critical components : decision making assistance and empathy (Marks 1988)
Empirical study • Online survey questionnaire • Customers’ sample : 249 valid respondents • 68% know their referent salesperson for at least two years • Measures : established/adapted scales (Likert) – exploratory and confirmatory tests (SEM)
Hypotheses test : Main results • A positive effect of CRM applications usage on salesperson competence • CRM usage is significantly related to market knowledge (H1; =0.408, R²=0.163, p<0.05). • CRM usage influences positively product knowledge (H2; =0.322, R²=0.1, p<0.05) • CRM usage influences positively customer knowledge (H3; =0.388, R²=0.147, p<0.05). • The effect of salesperson’s competence on customer’s decision making • Only product knowledge (H5; =0.460, p<0.05) and customer knowledge (H6; =0.137, p<0.05) have significant effect on customer decision assistance • The hypothesis related to market knowledge was not supported (H4; =-0.162, p<0.05) • Only product knowledge and customer knowledge have significant effect on empathy
Results analysis • Knowledge capacities show through interactions, sales calls and critical moments for specific needs or information • The role of sales presentation • Differences in explained variance of knowledge levels : information sourcing balance • Behavioral conditioning due to established performance criteria • The importance of the quality, updating and exhaustiveness of the database as perceived by sales force
Results analysis… • No (significative) impact of market knowledge on customer decision making : • Customers tend to focus more on the ability of the salesperson to master the offer and capacity to adapt to specific needs and constraints • Market knowledge is generally a domain that the customer knows and that can also be mentioned during other different sales presentations • This result can be related to the maturity level of database content or usage that sometimes doesn’t integrate yet market aspects • Empathy drivers
Research contributions • Contributing to better evaluate CRM effectiveness and customer centricity • Adoption of the customer’s perspective (customer based metrics !) • Methodological triangulation and sampling • Revealing value creation ‘’intangible’’ mechanisms • Providing insights on : • data usage issue (balancing data collection, analytics and relationship monitoring) • the capacity of capturing effective information • perspectives about channeling CRM data • Facilitating CRM adoption by showing the importance of the impact on customer
Future research directions • Testing an integrated model linking the improvement of customer decision making with key relationship variables : satisfaction, loyalty, commitment or predisposition to recommend the supplier • Adopting a dyadic approach that combines different perspectives • Consider moderating variables like : customer attitude toward IT or salesperson familiarity