What's a Lead Worth?

Most B2B marketers have been asked this question at some point in their career

It could be construed as a passive aggressive way of getting at the overall Marketing ROI is (or, the Return on Marketing Plan – ROMP – as we like to call it at Plannuh). It’s a difficult question to answer if you don’t understand your marketing system end-to-end, as covered by Peter, here

In this article, my goal is to outline some of the key criteria marketers should consider in answering this question objectively.

Identify the right levers in the marketing machine

If marketing is a system, it is measurable. It’s not a precision model (just like sales pipelines are valuable, but imprecise, models). The marketing system will yield a range of outcomes that have high and low bounds determined by quality of execution, likely external market changes, and so on. As we calibrate known steps in the system over time (e.g. repeated events, evergreen digital marketing campaigns) the sensitivity of the model (i.e. the range of possible outcomes based on the features in the system) will decrease. As we introduce brand new campaigns and channels, the sensitivity of the model will increase. You will want to reduce sensitivity (meaning repeating known campaigns), or increase sensitivity (meaning increasing new campaign types) depending on your overall marketing strategy.

The better we understand the key metrics in the marketing system, and their impact on the sensitivity of the outputs, the better equipped we are to answer the ROI question. The key levers in the system are:

  • Conversion percentage at each stage of the marketing system – how many prospects move to the next stage and how many fall out?
  • Duration of each stage of the marketing system – how long does it take to turn a responder into a prospect, into an MQL, into an SQL, into a deal, and so on.
  • The present value of an opportunity at each step in the system – the further out a deal is in time, the more speculative it typically is, and the lower its present value. Note, this is not a recommendation to prioritize short term outcomes; marketing is about building long term value. But we should be aware that spending $1000 to generate a $10K deal next month has a better ROI than spending $1000 to create a $10K deal a year from now, and plan accordingly. Another way of saying this is we should expect a greater return from campaigns whose value is realized further out into the future.
  • The resource surplus or deficit at each stage of the marketing system. We need to calibrate our marketing system so that we don’t create bottlenecks (e.g. we’re generating more SQL’s than our sales team can handle) or dead zones (e.g. there are insufficient prospects being generated to drive our mid-funnel MQL conversion campaigns cost effectively)

Below is a worked example showing a subset of the marketing system for an imaginary SaaS business, NerdCo. NerdCo’s expectation of the CMO is that the marketing team will generate at least 3x ROI, and the CMO uses this metric to assess the viability of marketing campaigns. Here are some baseline assumptions for NerdCo’s example:

  • Goal: Secure 100 new customers in production, with an average revenue per customer (ARPC) of $10K p.a.
  • Deliver a marketing ROI of 3x

The conversion funnel metrics and durations are outlined below, along with the churn rate

 

Funnel_Blog

If we run the funnel in reverse, it’s easy to work out that to achieve our target of 100 new customers in production, marketing will need to move 333 SQL, 1,333 MQL, and 4,444 prospects through the funnel for sales to close.

For clarity, we assume this is a brand-new campaign, and there are no carry over prospects, MQL or SQL in the funnel for this campaign. If you’re planning for the long term this should not be the case, but it allows us to isolate some of the key financial metrics for NerdCo that will let us demonstrate an objective ROI.

We know that NerdCo has a churn rate of 20%, so the average tenure of a new customer is 5 years, giving an LTV of $50,000. The funnel shows us that the full time for a prospect to convert to a deal, and for the deal to yield revenue (i.e. to be in production) is 190 days. Then we apply a discount rate of 12% to the future revenues, which tells us that present value of each new customer win is $33,983.

The CMO of NerdCo has been set an ROI target of 3x so we can calculate the upper bound of their campaign investment to meet our target of least 3x ROI per opportunity. It’s important for the CMO to understand the ROI in the context of the company’s gross margin (GM) targets as well. If the ROI is required to support NerdCo’s GM targets (vs just 3x marketing program spend), the CMO will need to take into account marketing spend and product delivery costs when calculating ROI metrics.

In the example below, we’re assuming a 90% GM business, which decreases the PV of each deal from $33,983 to $30,585

ROI = (PV of Investment – Cost of Investment) ÷ Cost of Investment

3

=

(30585 – x) ÷ x

3x

=

30585 - x

4x

=

30585

  x

=

7646

So, in principle, NerdCo’s CMO could spend up to $7,646 per customer win across the marketing funnel.

Now the resource capacity of the marketing system comes into play: at each stage of the marketing system, how many opportunities can we move from one stage to the next? If we invest all our money in converting MQL to SQL, and we only had one sales person, we would overwhelm the sales person with more SQL than they could handle or possibly. On the other hand, if we had a team of 50 sales people, we would struggle to keep them busy without a highly productive marketing funnel. These are both extreme examples to illustrate that we need to calibrate our investments throughout the marketing system to ensure we don’t create a surplus or a deficit at any stage of the funnel.

For our example, we’ll assume that the marketing team is perfectly calibrated with sales team capacity, so the marketing budget will be focused on winning each phase of the funnel evenly. Using our PV and ROI calculations from above, we see that we can afford to spend:

  • 80% getting new prospects into the funnel - $6,117 per new deal
  • 10% converting prospect to MQL - $765 per new deal
  • 10% converting MQL to SQL - $765 per new deal

Using the funnel conversion metrics, we can expand this to:

  • New prospects into funnel: $6,117 per deal, which means 444 prospects per deal at $13.775 per prospect
  • Converting prospect to MQL - $765 per deal, which means 133 MQL per deal at $5.75 per MQL
  • Converting MQL to SQL - $765 per new deal, which means 33 SQL at $$23.18 per SQL.

Double-checking our math:

(444 * $13.775) + (133 * $5.75) + (33 * $23.18) = $7,646

Which is the maximum we can spend to achieve the target 3x ROI for this campaign.

Know your marketing system

The more you can quantify your entire marketing system, understanding the dollar value of each conversion in the funnel, and calibrating your capacity to ensure there are no droughts or surpluses the better placed you are to deliver an objectively derived and financially defensibly ROI for your campaign investments.

This matters much more than channel optimization, because it will enable you to demonstrate the business value you are delivering with your campaign investments.

 

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