This customer is active in the debt counselling market in South Africa. The cornerstone of any sales organization is lead generation - whether done by an internal marketing team or an external affiliate.
As a sales organization with affiliate marketers, reporting on lead performance and conversion is absolutely crucial. This was done entirely manually, with analysts exporting and manually correlating data from the dialer system and CRM database.
This meant that reports took a while to produce, were prone to human error, and were often challenged. In addition, the lead integration workload itself was manualized to a large extent: Users were uploading manually-sliced Excel sheets directly into the dialer platform - a workaround developed to cater for the limits of their systems, completely disregarding the optimal approaches for data management.
A single lead integration layer was developed for this customer. It "intercepts" the flow of leads from all sources (web, inbound, live chat, manual, cold lists) through a single interface, which then moderated the integration of those leads out to the dialer platform.
This approach yielded several benefits:
Elimination of most manual work. The new system allows multiple parties to submit information to a single API, with the categorization and prioritization of leads managed directly by the dialer team.
Consistent, automated reporting. By de-duplicating incoming leads in real-time and issuing global lead IDs, it became possible to track the life of a lead all the way through the sales process, then feed that back to a real-time dashboard.
Intraday prioritization. This enables the dialer team to react immediately to changing conditions throughout the day, by changing the prioritization of incoming leads based on call center performance.
Direct CDW integration. Having all the data available within the customer's own network made it much simpler to feed everything into their Customer Data Warehouse, which in turn made overall performance reports much easier to generate.
Designed for scale. The warehouse consisted of 16 sharded databases, and a simple algorithm for distributing incoming leads across them. This solution can scale both vertically (increase server capacity) and horizontally (spread databases out over more servers).