What’s wrong with using “lead cost” as a B2B, lead-generation campaign measure? Oh let me count the ways: 1) activity after a “lead” is generated overwhelms “lead cost” in contributing to ROI; 2) “lead cost” doesn’t affect campaign ROI sufficiently to serve as a KPI (key performance indicator); 3) fixation with “lead cost” enables laissez faire attitudes towards what really matters; and 4) “leads,” as marketing and sales commonly use the term, are really inquiries, unqualified inquiries, and shouldn’t be called “leads” prior to successful qualification. But the whole world calls inquiries “leads,” so I’ll join in and stop using all the parentheses.
Why B2B Companies Use Lead Cost
Why can’t B2B companies get past judging campaign ROI by lead cost? Three basic reasons: 1) they don’t know any better; 2) they know better but lack the will and/or discipline to collect the data necessary to measure ROI; 3) they collect the data but can’t find a calculation for converting raw outcomes data into ROI information.
While I enjoy writing about issues 1 and 2, it takes onsite presence to address them, and I’d like to offer something practical. So it’s on to reason number 3.
Lead-Gen ROI Formula
Here’s our cherished formula at HYM.
Lead Gen ROI
Don’t panic! I can explain. Let’s take one operand (computational element) at a time.
Selling price minus variable cost (cost of goods sold): We arrive at this number by taking the average revenue created by all the leads converted to sales and then subtracting the average variable cost across all sales. “Variable cost” describes all expenses that change in consort with changes in the volume of products produced or services delivered. If you’re unfamiliar with the concept, please talk to your CFO.
One caveat–don’t treat selling costs as a variable cost. “The” formula factors in sales expense.
Marketing cost divided by number of contacts: Nothing more than the good old CPC (cost per contact). For web programs, you can use the number of click-throughs on your site as contacts.
Response rate multiplied by sales conversion rate: Just what it says.
Qualification cost: Average cost to qualify one inquiry. If you’re generating sales leads but not qualifying them before forwarding to sales, you should be shot.
Selling cost: Track the percentage of sales calls made on campaign leads over the sales follow-up period, then take that percentage of all relevant sales costs.
Fulfillment cost: Hopefully you’ve moved on to using PDFs instead of glossy product information brochures, almost zeroing this out.
That’s it for the terms. Now let’s discuss the whys and wherefores of the calculation.
Rationale Behind the Math
The formula says that average gross profit for a closed sale should be greater than or equal to the variable cost of the sale, with “equal to” representing break-even. To extrapolate from the value of a single transaction to total campaign profitability, you simply multiply this average gross profit (or loss) by the number of closed sales. Which begs the question why are we calculating the return on one transaction, rather than the whole campaign?
Two good reasons: 1) the math is so much simpler using a single, average transaction; but more importantly, 2) looking at a single transaction creates a formula ready-made for running “what-if” projections and pre-campaign modeling.
CPC (the numerator) divided by response rate multiplied by conversion rate (the divisor): All we’re doing here is allocating all marketing cost to only closed sales. The concept is simple, in words at least. Dividing the CPC by the response rate allocates all marketing costs to just inquirers. Then, dividing that number by the conversion rate shifts all marketing cost down further to only closed sales.
Qualification, selling and fulfillment costs divided by conversion rate: Because these costs apply only to inquirers, we just need to divide by the conversion rate to allocate them to closed sales only.
Q.E.D.
Is Calculating ROI Worth the Effort?
Yah sure, it is. Let me give you several examples.
Many clients are running ongoing lead-gen programs when we start engagements. They usually don’t know whether they’re making or losing money. Applying “the formula” tells the true story–and provides a critical tool for identifying what’s broken and what can be optimized.
On a more granular level, we’ve worked with numerous clients that think they’re saving money by skipping qualification. Invariably, their campaign ROI is in the toilet, with selling costs disproportionate to revenue. Using “the formula” (and lead-gen experience) to project the revenue increase and the sales cost reduction proper qualification would provide usually disabuses clients of that errant thought. Not only do the financial returns from qualification overwhelm qualification expense–but qualification often makes the difference between substantial sales returns and no sales whatsoever.
I was running a print, lead-gen program for a division of Pitney-Bowes, which wanted to kill the more expensive placements. Until, that is, “the formula” showed them the most expensive per-lead source was the most profitable. In fact, profitability of lead sources was almost inversely proportional to lead cost.
“The formula” got me fired by American Express by showing that AXP’s ill-fated Financial Services Direct initiative was going to do a face plant–which I duly reported, to the chagrin of AXP execs. But “the formula” didn’t lie. AXP lost its shirt, and a whole bunch of AXP execs had to “walk the plank” from the top floor for their foolish optimism. Boy, did I look good. After the fact.
On another AXP engagement, we applied “the formula” for up front modeling and learned that to generate positive numbers, we’d have to 1) change a planned two-step mail program to a one-step; and 2) keep our CPC brutally low. “The formula” was right–with one exception. We hadn’t dared plug in a response rate value 8X industry average. We forgave “the formula.”
And I could go on and on.
Yup, “the formula” really is worth the work. You betcha it is.
I believe you meant that the profitability of lead sources were proportional, not inversely proportional to lead cost. More expensive, more profitable.