The Challenge –
Zinc Group are a Debt Collection Company specialising in Blue Chip Companies’ collections and were using Elsbeth, on premises, for their predictive dialler platform. Unfortunately, Zinc Group faced numerous challenges with Elsbeth as a provider. These included;
- Support below Zinc Group’s expected standards
- Stability issues
- Lack of efficiency from staff
- Compliance issues caused by call recordings being removed after a month
- Non-configurable real-time statistics
- Concerns over historic hardware
- Mediocre performance in terms of average ready times and live persons connects per day
Zinc Group knows the value of a predictive dialler; however, they felt the issues with Elsbeth were hindering the collections performance of the business too much. For this reason, they decided to look at alternative suppliers. The outbound collections department of Zinc Group is pivotal to the company’s success. Therefore, they were adamant that their next supplier not only have the right product, but also be the best company to work with
The Process –
Zinc Group were experienced users of predictive diallers, so they knew what they wanted, as well as what to watch out for. After the procurement process, Zinc Group were pleased and impressed with the total solution offered by the MaxContact Team.
The Result –
In addition to the increase in performance and stability, Zinc Group have utilised the additional features MaxContact had to offer. Before the switch to MaxContact, Zinc Group’s statistics were minimal, and reporting was poor, which hindered their ability to drive performance through change and different collection strategies. Since the switch, MaxContact’s reporting suite and real time configurable dashboards have helped Zinc Group to spot issues, improve training and target specific collection strategies, producing exceptional results and delighting their clients.
“The best day for Zinc, using the old system, was 260 payments/arrangements with 65 agents (4 each). Yesterday we managed 455 with the same number of agents; we can’t wait to see the results when we get more familiar with the system.”