The existing systems were disjointed, lacking seamless integration between internal operations (e.g., managing brokers, listings, and leads) and external client interactions. Clients and prospective buyers had limited visibility into updated business listings and broker information. Manual efforts were required to synchronize data between internal systems and the company’s website, leading to inefficiencies. Additionally, website inquiries were not effectively captured or converted into actionable leads, and the current setup was not scalable for future business growth.
The CRM solution introduced a centralized system to manage broker profiles, business listings, and client inquiries. Brokers gained access to an intuitive interface to track leads and assist clients more efficiently. Real-time data synchronization ensured that updates to listings and broker information were instantly reflected on the website. The website was redesigned to provide a professional, user-friendly experience for prospective buyers, dynamically displaying listings via API integration. A lead capture mechanism was implemented to automatically push inquiries into the CRM, facilitating effective lead conversion.
The organization suffered from a poor employee experience due to outdated, legacy applications that required employees to navigate multiple systems manually. The existing system not only slowed down the selling process but also failed to offer features that were relevant to individual customer needs. Furthermore, there was no efficient mechanism in place to maintain the relationship between a single customer and the multiple accounts they held, leading to a high churn rate and missed opportunities to upsell or cross-sell products
Eclantiqx implemented a transformative solution that leveraged intelligent next-best–offer technology. In this approach, call center executives (CCEs) received automated suggestions generated from a sophisticated application that analyzed customer profiles, geographical data, and nature of expenses. The solution was built on Pega 8.6 and integrated with a Python-based data processing system and Tableau for business intelligence, enabling the backend marketing team and data scientists to continuously refine the offer engine. This multi-channel approach also supported call center, email, and web interactions so that every customer inquiry could be met with the most relevant and personalized offer.
