Geico Company Product Concept
The product concept assumes that customers require superior products with improved performance. Therefore, customers often value products with innovative features. To improve its performance, Geico Company should leverage its online presence with technological advancements, such as the complex event processing (CEP) software.
This software will increase the company’s focus on providing customers with the best quality and performance features that reflect market needs (Predictive Customer Interaction Management for Insurance Companies 2011). The CEP software will heighten the company’s interaction with its customers and further improve its marketing strategy, which many critics view as unprofessional.
For Geico to reach its critical business objectives, the CEP software will assist the company shift towards more customer-centric strategies. Additionally, the CEP software can help the company understand their customers through efficient customer service, given the systems and process that the software offers. Thus, the CEP software presents Geico Company with the best opportunity for leveraging cross selling to prospects of contact.
The product concept proposed in the CEP software, entails various features of customer interaction management. This model uses real time events to maintain relationships with its family market segment, drive up-and-cross-sell prospects, and incorporate a feedback model for calculating effective model dimensions (Predictive Customer Interaction Management for Insurance Companies 2011).
At Geico Company, an effective customer service interaction management will allow real time cross selling, thereby, increasing customer relationship value. Using an effective business optimization technology will improve customer service management by spotting up-sell opportunities to improve customer service. The software also creates a more personal feel to its customers’ interactions with the company.
The CEP software is capable of matching customer profiles with the company’s products. The CEP software will include product recommendations depending on laid down rules. The case below shows the numerous ways that the CEP software can improve the service offerings of Geico Company. If a couple gives birth to a new baby boy named Dan, the father, Fabian, adds this information in real time to Geico’s online self-service portal.
After updating his personal profile upon receiving the bundle of joy, Geico Company will send Fabian and his wife a present the following day to congratulate them on the delivery. Geico Company then offers Fabian’s family a college savings account specifically designed for the child. Fabian’s local agent also receives this update, and congratulates him when he visits.
The agent offers to consult Fabian on the progress of his insurance. This consultation gives Fabian a deeper insight into whether his life insurance and annuities can adequately cover his present family. This example shows how the CEP software can help Geico Company access real time information across channels using programmed sales and servicing process.
The CEP software will relay immediate data to Geico Company as events unfold. Moreover, the CEP software gives Geico Company the opportunity to streamline significant events with correlated information. Considering a family’s historical information will allow the company to review gaps in their offerings.
This feature makes the software valuable, since it allows the company to assess the marketing campaign that best suits specific customers. Geico Company will gain a competitive advantage given that the CEP software allows the company to recommend products to its customers in real time.
Of additional value is that, the CEP software allows the company to execute its marketing strategies appropriately. This product concept leverages the company strengths and opportunities to create a competitive advantage that gives the company a real-time competitive advantage over its peers.
Bibliography
Predictive Customer Interaction Management for Insurance Companies 2011. Web.