Introduction
Aside from some sales lead generation methods provided by the Logistics Company, it is reasonable for Jennifer to resort to networking and the company sources tactic. Making use of these approaches can increase Jennifer’s chances of success during the attention stage of the AIDAS model (Tadajewski, 2020). To start with, networking strategies, including social media communication and referrals, analyzing the centers of influence, and networking with non-competing business players’ sales representatives, would be helpful (Cornwell & Kwon, 2020; Ingram et al., 2020). As per the model utilized by Business Networking International, non-competing salespeople’s collaboration facilitates the exchange of contacts, thus promoting sales lead generation opportunities (Ingram et al., 2020). Another option for Jennifer revolves around identifying lead generation options in the Logistics Company’s internal/external resources, including record examination, advertising inquiries, and attending trade shows (Ingram et al., 2020). Despite being effort-intensive, these methods can add more diversity to Jennifer’s overly heterogeneous and unsystematic lead generation strategy.
Qualifying the Leads and an Ideal Prospect’s Profile
The qualification of leads should emphasize gradual transitions between initial identification and suspect screening, and Jennifer’s perfect prospect should incorporate specific shipping preferences. For both pre-existing and independently generated leads, Jennifer should follow the process that consists of data collection and assessments using the three-level model. The levels include the confirmation of suspects as marketing qualified (MQL), sales-accepted (SAL), and sales-qualified (SQL) leads (Chen & Zhou, 2021; Sánchez-Teba et al., 2020). Next, in terms of the ideal prospect’s profile, the basic theoretical assumptions about suitable prospects suggest the combination of three distinct factors. These include the need for the product, financial capacity, and decision-making authority to proceed with purchasing decisions (Ingram et al., 2020). Thus, in Jennifer’s case, an ideal prospect is a steadily developing manufacturing company wishing to expand its operations, which is impossible without trucking services. To be reflective of the authority part, a perfect prospect is to be located in areas in which no legislative barriers to collaboration with the Logistics Company exist.
Prioritization of Qualified Prospects
Since prioritization ensures time use efficiency in working with prospects, Jennifer should prioritize the existing prospects in the right way and accordance with a clear scoring methodology. The key strategy for Jennifer to implement is comparing each prospect against the detailed ideal prospect profile and determining the approach to point allocation and score calculation (Ingram et al., 2020). Depending on the Logistics Company’s current priorities, Jennifer should allocate the degrees of importance to the profile’s different areas. For instance, she can prioritize the prospective customer’s paying capacity if her employer is oriented toward reliability/trust and rank the qualified prospects accordingly (Mier et al., 2020). To avoid excessively complex multi-component ranking systems, Jennifer can resort to the ABC approach. In it, the prospects are divided into the best (A), average (B), and not the best (C) categories (Ingram et al., 2020). Working time can then be distributed between the prospects to pay more attention to the most promising options, which is in line with the Pareto principle.
Data Collection to Prepare for Sales Dialogues
Information for Jennifer to collect to prepare for one-on-one sales dialogues includes basic and situational prospect-specific details, as well as data from open sources. Along with the AIDAS selling theory, leading prospects through the interest and desire stages might require staying informed of the dynamics of their needs (Tadajewski, 2022). It implies staying updated on each crucial prospect’s strategic position in the market and development-related goals. To comprehend a prospect’s needs, Jennifer should gather basic buyer-related data, such as the industry of operations, services, and expectations (Ingram et al., 2020). To take this understanding further, collecting situation-specific information, including the buyer’s financial health, funds available, relationships with previous service suppliers, and desirable purchase order types, is essential (Ingram et al., 2020). Finally, any information from prospects’ social media could promote success during the interest stage.
Implementation of Social Selling to Improve Strategic Prospecting
Jennifer’s strategic prospecting processes can be improved by implementing a social media content-sharing and prospect interaction strategy. Based on the technology-task fit theory, integrating social media and customer relationship management can create more effective salesperson behaviors (Barney-McNamara et al., 2020). Jennifer’s personal social media profiles, especially LinkedIn, can become a platform for sharing company-related data (Ingram et al., 2020). Particularly, LinkedIn has the Social Selling Index tool that will support Jennifer in improving her prospect interaction practices in response to the changing success scores (Barney-McNamara et al., 2020). The three-component social selling framework that emphasizes antecedents, outcomes, and social selling activities suggests that company factors should be reflected in information exchange (Barney-McNamara et al., 2020). Thus, demonstrating the Logistics Company’s strategic advantages in the content to share with potential suspects will benefit Jennifer’s approach to strategic prospecting by increasing the number of communication channels. In contrast, the cold calling technique that she relies on does not allow the sales agent to share the same amount of information per encounter.
References
Barney-McNamara, B., Peltier, J., Chennamaneni, P. R., & Niedermeier, K. E. (2020). A conceptual framework for understanding the antecedents and consequences of social selling: A theoretical perspective and research agenda. Journal of Research in Interactive Marketing, 15(1), 147-178.
Chen, J., & Zhou, W. (2021). Drivers of salespeople’s AI acceptance: What do managers think? Journal of Personal Selling & Sales Management, 1-14.
Cornwell, T. B., & Kwon, Y. (2020). Sponsorship-linked marketing: Research surpluses and shortages. Journal of the Academy of Marketing Science, 48(4), 607-629.
Ingram, T. N., LaForge, R. W., Avila, R. A., Schwepker, C. H., & Williams, M. R. (2020). Sell: Trust-based professional selling (6th ed.). Cengage.
Mier, J., Carlson, J., Bellenger, D. N., & Johnston, W. J. (2020). Business buyers are people too: Exploring how geodemographics affects business-to-business selling effectiveness. Journal of Business & Industrial Marketing, 35(10), 1539-1552.
Sánchez-Teba, E. M., García-Mestanza, J., & Rodríguez-Fernández, M. (2020). The application of the inbound marketing strategy on Costa del Sol Planning & Tourism Board. Lessons for post-COVID-19 revival. Sustainability, 12(23), 1-15.
Tadajewski, M. (2022). Rethinking ‘marketing as applied economics’. Marketing Theory, 1-23.