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By Ashok N

When an organization is executing agent-specific campaigns, LCM enables one-on-one, personalized service by mapping one agent exclusively to one customer. This keeps agent productivity at peak levels when specific callback records are depleted or the strategy has changed.

Here are a couple of use cases for us to discuss:


As agents dial the initial contact outbound campaign, when they reach a prospect that is interested in completing the insurance documents, that agent will then take control of the record in the CRM and follow the customer through the application process to completion (accept/deny). Typically, this process is the main method for agent lead distribution.

The main drawback here is that the agents are only on the dialer during a prescribed time during the day, maybe only for an hour to two, and the remainder of the day is spent handling inbound calls and following up on their “named” customers. This means that specific agents are dialing at good contact times where others may be dialing at bad contact times, affecting the lead distribution AND probably reducing the overall RPC rate because more calls aren’t made during better contact times.

Also, with the agent being off-system doing manual work, they have less time accountability or, at a minimum, there is a multiple application reporting issue. Agents have one set of metrics on the dialer which is very detailed and another set off the ACD which is very general.

With agent based campaigns, an agent can be connected to the dialer for an extended period of time, taking both group calls in a predictive or progressive environment AND their personal calls in a preview mode (which makes sure they have time to review the record before doing the follow-up). Ideally, we would see an agent on the dialer the entire day taking inbound calls, making outbound predictive calls, and doing personal call-backs which provides a single-source reporting environment and maximizes the agent performance.

3rd party collections

Agents are calling on the dialer roughly 50% of their day, hitting a particular campaign with very limited success (typical hit rates on agency calls are around 1-2%). When they do finally get in touch with a debtor and commit a payment arrangement, it is that agent’s responsibility to monitor the debtor to ensure payment. Usually a significant part of their compensation is based on the actual payment, so the completion of the payment arrangement is critical.

Much like the insurance example, the drawback here is the agent is not calling across the day but only during certain times of the day, which will affect their ability to get RPCs and subsequent payment arrangements. The bigger issue here is efficiency – more critical than in any other dialer oriented industry, Collection Agencies are driven by cents. Any second spent not dialing is lost productivity and lost revenue.

Applying agent based campaigns here would mean a larger population of agents (say 50 all day instead of 10 x 5 different shifts) which dramatically increases dialer efficiency and drives down idle time. This can mean 5-10 more agents worth of work across the entire 16 hour work day which, even at a 1-2% hit rate, is still more RPCs and more payment arrangements. The agents would still manage their “follow-ups” but would do so in between typical predictive dialer calls and/or inbound calls improving their month-over-month results.

Both of these examples are pretty basic but the overall theme of agent based campaigns is keeping the agents ON THE DIALER. The customer bought the dialer knowing that it would improve agent efficiency, but then their business owners enacted policies that immediately reduce the effectiveness because agent campaign functionality doesn’t exist in a way that would allow them to leverage it DURING predictive dialing.

With the agent based campaigns, they can have the best of both worlds: efficient dialer driven agent performance with the individualized attention of agent owned calling.

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