How Much Should You Pay for a Sales Lead?

When planning a B-to-B lead generation program, you need to deliver leads to your sales team at an affordable price. A neat way to determine in advance how much you can spend on a lead is to calculate the Allowable Cost per Lead.

LeadsWhen planning a B-to-B lead generation program, you need to deliver leads to your sales team at an affordable price. A neat way to determine in advance how much you can spend on a lead is to calculate the allowable cost per lead for your campaign. This number can then be used as a benchmark for evaluating campaign investments, and deciding which ones are likely to work. If a campaign is looking like it’s not affordable, then you’ll want to make some tweaks, like find a stronger offer, or narrow your targeting.

Begin by calculating your cost per inquiry. Assemble the total direct campaign costs, including all fixed and variable costs that can be directly attributed to the campaign. Include creative and pre-production work, cost of developing and producing content, and the normal variable costs of campaign development and execution. Divide this amount by the number of expected campaign responses, and voila! There’s your cost per inquiry.

Then, estimate the costs associated with qualifying a lead. Don’t try to determine this number on a per campaign basis — it’s too hard. Instead, calculate an average qualification cost for inquiries over a set period, such as a year. Gather up all your inquiry-handling costs, including the direct headcount involved in inquiry capture, fulfillment, qualification, and nurturing. If your back-end processes are outsourced, gathering the data is as simple as adding up the bills. After you have a number for the year, divide it by the number of inquiries handled in the year. This number will serve as your average cost to qualify an inquiry.

Finally, go talk to your counterparts in finance and sales to gather several data points. You need the average order size, namely, the total revenue divided by the total number of orders. (If this number swings wildly, do the calculation by product category.) You need the margin (or its opposite, the cost of goods sold) and the direct sales expense per order, calculated by the total sales expense divided by the total number of orders.

Let’s look at an example of how this works. The chart works through some hypothetical numbers to arrive at a cost of lead closed and an allowable cost per lead, and compares the two. Your goal is for the cost of a closed lead to come out lower than the allowable — obviously. If it’s higher, you lose money on the campaign.

To get to Allowable Cost per Lead, it’s not actually necessary to know how many inquiries will be generated, qualified, and converted. But you do need to know the cost per inquiry, the cost to qualify an inquiry, the qualification and conversion rates, the net margin per order, and the direct sales expense per order.

 

Comparing your cost per closed lead to your Allowable Cost per Lead: A hypothetical example
Cost per inquiry (campaign cost/# responses) $100
Average cost to qualify an inquiry (lead management costs/inquiries per year) $50
Total cost per inquiry qualified (cost per inquiry + cost to qualify) $150
Lead qualification rate 25%
Cost of qualified lead (cost per lead/qualification rate) $600
Lead conversion rate 30%
Cost of a closed lead (cost of qualified lead/conversion rate) $2,000
Average order size (annual revenue/# orders) $10,000
Net margin per order (revenue per order x margin, 60%) $6,000
Allowable cost per lead (net margin per order – direct sales expense, $3,500) $2,500

 

In this hypothetical example, say the campaign spent $15,000 and generated 150 inquiries. Whatever the cost and the responses, the important number is the cost per inquiry. Here, we have hypothesized it as $100. Separately, the average cost to qualify an inquiry for the year was calculated at $50. We divide the qualification rate (25 percent) into the total cost per inquiry qualified ($150) to calculate the cost of a qualified lead. Then, we divide that by the conversion rate (30 percent) to get the cost of a closed lead ($2,000).

This number is then compared with the allowable cost per closed lead ($2,500), which is a simple calculation of the net margin per order minus the cost of sales (hypothetically set here as $3,500). In this example, the campaign looks promising, because the expected cost per converted lead is $500 less than the Allowable Cost per Lead.

If you put this information in a spreadsheet and play with it, you can quickly see how much leverage there is on the back-end, meaning after the inquiry has come in and you are working it through qualification and nurturing. A few efficiencies on qualification rate and conversion rate work wonders on campaign ROI.

A version of this article appeared in Biznology, the digital marketing blog.

How to Maximize Your Lead Volume Within Your Allowable Cost per Lead

Many times marketers running lead generation programs shortchange their lead volume in order to maintain tight controls on their cost per lead. Their fear is that if they rollout media that tested at a cost per lead (CPL) that’s just equal to or slightly below their target CPL that a variation in response might put their overall CPL over the top. As a result, they roll out only those media properties that are performing below their target CPL.

Many times marketers running lead generation programs shortchange their lead volume in order to maintain tight controls on their cost per lead. Their fear is that if they roll out media that tested at a cost per lead (CPL) that’s just equal to or slightly below their target CPL that a variation in response might put their overall CPL over the top. As a result, they roll out only those media properties that are performing below their target CPL.

This conservative strategy ends up cheating you out of volume that could significantly increase your program’s total revenue and positively impact your ROI. The fact is that every well-constructed media test has its big winners as well as its big losers. The trick is to leverage the big winners in a way that allows you to include the “little losers” in the mix and still meet your overall target cost per lead.

With a few simple spreadsheet tricks, you can maximize your lead volume and still hit your target CPL by including media that actually generate higher lead costs than your target CPL! Think about it this way. If your target cost per lead is $15, for every $10 lead you get from a “big winner” media, you can accept a $20 lead from a “little loser.”

Let’s walk through the simple spreadsheet manipulations you need to manage this process.

Start out with your basic results spreadsheet like Table A that shows your media cost, responses, and cost per response for each media. For this example, we’ll look at a 500,000 impressions test (10 properties,
50,000 impressions each, with a roll-out potential of 15 million. The target CPL is $15.

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As you can see, the test yielded 700 responses at a cost of $11,425 or a total CPL of $16.32. But there are 7 out of 10 properties that are performing worse than the target CPL of $15.

The first thing you need to do is rank the results in ascending order of CPL using the Data Sort function, and you end up with Table B below. (Make sure you don’t include the total line in your sort).

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Here we see that properties H, B, and C are below the target of $15 per lead while all the others are higher. The combined roll-out quantity of these three properties is a disappointing 4,050,000 impressions out of the total potential roll-out quantity of 15 million. But let’s look at what the actual roll-out potential is when we leverage the “big winners” against the “little losers.”

To the spreadsheet that you sorted by ascending CPL, add columns for cumulative responses, cumulative cost and cumulative CPL. Table C, shows the formulas for calculating those.

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Looking at the results of this calculation in Table D, we get a better picture of the potential roll-out universe.

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If you look at the cumulative cost per lead column, you can see that taken together, 8 out of 10 media properties produce an aggregate cost per lead under $15. That leaves only properties E and F with their high CPLs out of the mix, creating a potential rollout of 12,250,000 impressions. (Note: If you decide to re-sort this spreadsheet do not include the cumulative results columns in the sort).

Now, some words of caution. Don’t roll all these marginal media out before retesting them in a larger quantity, say 250,000 impressions to make sure that you’re going to repeat your results. A test quantity of 50,000 impressions generating less than 100 responses does not create a high level of statistical confidence. So be especially careful with properties like A and I that have higher CPLs. You’ll also want to retest your “big winner” properties with a greater number of impressions to make sure the test results are not an aberration.