F50 IT company zeros in on drivers of yield and cost per lead in outbound telemarketing channel

SITUATION: The management of the lead generation team at a large, multi-product line IT company was faced with a common set of business leader expectations – they were expected to better their previous year’s performance by generating more leads and pipeline opportunities without a proportionate increase in budget.

In alignment with the company’s channel structure, the team was focused on specific sets of targets that met selection criteria for the associated channel. Each set numbered in the mid tens of thousands. Throughout the previous year, the operations had ramped up considerably and had peaked at about twice its size at the beginning of the previous fiscal year. Through most of the previous fiscal year, lead yield had gone up as team size had increased.

However, at the start of the new fiscal year, the lead yield had begun to taper off and, in some specific segments, the telemarketing operation had fallen behind its goals.

This brought up several common operational questions:

  1. What are the drivers of performance of the large scale telemarketing operation?
  2. How do the current metrics for those drivers compare with best practices and the kind of results associated with best practices?
  3. How could those drivers be managed to increase lead yield and reduce cost per yield in this specific situation?


ASSIGNMENT: Massini Group was tasked to first identify the performance drivers of the operation and then to determine how to correct the issues that were causing yield to decrease and costs to increase.

Massini Group broke the problem into the following stages:

  1. Characterization of the basic operational parameters, including:
    1. total program FTEs;
    2. hours dialing per day per FTE;
    3. average dials per day;
    4. average dials per record;

       to determine total work capacity of the team;

  1. Comparison of current team operational parameters to benchmarks gathered from analysis of 100’s of similar campaigns;

  2. Quantification of the scope of the targets in the channel, including targets that may be eligible for inclusion in the channel, but were not yet included;

  3. Analysis of the processes by which the above resources were allocated to the available targets in order to isolate any practices that had resulted in waste of resources in terms of time, money or lost opportunities.


KEY STRATEGY: Massini Group drew on its 15 years of managing telephone based channel operations to characterize the operations of the telemarketing team in terms of two key diagnostic tools – the yield curve and the cost per yield curve. In this particular case, the yield sought was leads to the sales force, but the process works equally well for telesales or inside sales.

The yield curve (below) is essentially a plot of the proportion of targets that result in the intended outcome , i.e., lead or sale, as a function of the amount of effort put into obtaining the result. Below is the yield curve for this situation, with a comparison of net new (test) targets to the original (control) set of targets.

As a rule, the shape of the yield curve is always the same, though the precise proportions depend somewhat on the type of product, the brand value of the company and the complexity of the sale.

The cost per yield curve (below) is a plot of the cost of the intended outcome i.e., lead or sale, as a function of the amount of effort put into obtaining the result. Below is the cost per yield curve for this situation, with a comparison of test and control targets.

Again, as a rule, the shape of the cost per yield curve is always the same, though the precise figures depend on the type of product, the brand value of the company and the complexity of the sale.

Massini Group found that the client’s telemarketing operation had saturated the original set of targets, with the following results:

  1. All of the more attractive opportunities had been pulled from the list early in the process;
  2. The remaining targets were getting harder and harder to convert given the current set of messages and offers;
  3. Given the original set of targets, the operation had too many resources to continue the effort and was as such, was overcalling the targets and wasting money on the effort;
  4. All of which combined to reduce the campaign yield and increase its cost per yield.

Therefore, Massini Group sought to align the available targets with the available telemarketing resources by:

  1. Assuring that all of the available targets were considered (a significant number of net new in-channel targets was discovered and included in the process);
  2. Putting in place strict parameters to assure proper and uniform allocation of resources to targets, which assured that all targets received a minimum amount of coverage and none was overcalled;
  3. Instituting a specific recycling strategy to allow time to reset the needs of those targets that had been overcalled, thus bringing them back into play for the channel.


ENGINEERED PROCESSES: Massini Group utilized the data in the outsourced telemarketing vendor’s call management system to make a number of specific measurements related to alignment of the targets and resources.

This analysis found that:

  1. Based upon an operational parameters calculation, the number of targets and number of FTEs in the program were out of balance – in each calendar quarter, the current team could have called approximately 3X as many targets as it had – a shortage of available targets had effectively slowed down their work;
  2. The current lead yield had fallen to 27% of that average posted in the previous fiscal year – this was attributed to extensive and uncontrolled recycling of the same set of targets – this in turn was linked to the shortage of targets.

Massini Group calculated that if the telemarketing team had been sized to the available targets, the cost of the program could have been reduced by nearly $100,000 per quarter. Conversely, if enough targets were made available, the program could have produced $24 million in additional pipeline per quarter.

With the nature and cost of the inefficiencies in hand, Massini Group and the lead generation team set out to correct the issues by instituting two general types of measures:

  1. Identification of the full scope of the available market to assure that the program did not leave any part of the market universe unaddressed;
  2. Application of operational controls on the telemarketing program to assure that all of the targets received uniform treatment, and as a result the program became optimally placed on the yield and cost per yield curves.

The following steps were taken relative to the total available market:

  1. Identification of the total available market, based upon the criteria built into the client’s channel model;
  2. The total available market was compared to the targets in the program and it was determined that fully half of the targets had never been addressed;
  3. The newly identified unaddressed targets were broken into two subsets:
    1. 40% had a contact available in the client’s marketing database;
    2. 60% did not have a contact available in the client’s marketing database;
  4. An effort was undertaken to match externally available contacts to the 60% of the unaddressed targets for which the client had no available contacts;

The following steps were taken relative to the management of the telemarketing program:

  1. A new campaign was created to address the net new targets with a specific operating model that assured that all would be addressed and that each would receive uniform treatment – thereby mitigating any urge to overcall the targets;
  2. An operational parameter calculator was used to pair the correct number of telephone agents with the available targets and calculate the number of elapsed days necessary to complete the work – thereby driving cost controls.


RESULTS: Although this program is still running, early results show that the modifications made to the program increased lead yield by 4.1X and correspondingly reduced costs by 4.0X.

Part of the above result can certainly be attributed to replacing the overworked set of targets with a net new set, as described by the difference between the net new (test) and original (control) yield curves. However, examination of the difference between the two curves only accounts for approximately 2.5X change in results. The remaining change in the cost per yield is attributable to a change in the allocation of resources to the records based upon a maximum attempts threshold that seeks to keep the program operating on the left side of both the yield and cost per yield curves.

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