How B2B companies can set target CPLs when testing new channels

‘What is a good CPL’ is a question we routinely get from clients, but one for which there is no direct answer. Ultimately, a “good CPL” is one where the cost of acquisition is – on average – lower than the revenue received. However, with the kind of fast-growing B2B start-ups that Bizmut often works with, the fundamentals for setting specific targets are set may yet not be established.

Three typical issues when defining CPL targets for a new campaign, and how to solve them:

  • Conversion rate of a new channel is not established
  • Value of customer is unproven
  • ROI is not the priority

“Well you’re the experts, what do you suggest?”

While Bizmut has a wealth of experience and can offer good advice, ultimately the assumptions that go into CPL targets for a new campaign depend on the client’s understanding of how much lifetime revenue a new lead is likely to generate for them. Some clients already have established business models and are able to answer this easily but for many start-ups these numbers have not yet been established.

In these cases, acquiring new customers is usually the priority and so CAC (customer acquisition cost) is the focus metric. Once an acceptable CAC is agreed then we can build towards an initial target CPL like this:

  • Agree the required CAC, e.g. CAC Target = 800€
  • Understand historic Lead-to-Customer (L2C) conversion rates, e.g. on average 15% of leads generated are converted into customers by the sales team.
  • Use this basic formula to calculate required CPL: Target CAC x L2C = Target CPL. e.g. 800€ x 15% = 120€

This may seem like a simple enough formula, but to be accurate it needs some historic data which may not yet exist for new businesses. Here are some typical problems we’ve encountered when trying to set a target CPL and how we’ve solved them:

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1. Likely conversion rates for a new channel can be hard to estimate

Not all traffic sources are going to have an equal Lead 2 Customer rates. Certain channels bring in users with higher intent than others. For example, a user who searched for the service and signed up as a lead is much more likely to convert into a customer than one who was scrolling their Facebook feed and just clicked on an ad. To help understand this variable we break down lead sources into 3 main categories:

High Intent Direct, Brand searches (paid+organic)User has been convinced elsewhere of the value of the product/service and is actively seeking for it.
Medium Intent Non-brand search, Software comparison platformsUser is actively looking for solutions that the product/service can solve.
Low IntentPaid social, Display, content distribution networks (Outbrain, Taboola)  User was passively surfing the web and was interrupted with an ad about the product/service.

It is important to understand where historic performance data sits within this ranking before using it to predict how L2C will look in a different channel. So, if you have been focusing mostly on high or medium intent channels, you will need to make a downwards adjustment when calculating the target L2C rate for low intent channels.

Inevitably, this is not always going to be an easy or accurate process. At Bizmut we bring our experience to bear on such projections, looking at other clients we have with similar business models and/or industries. The ratios by which L2C rates deviate between the channel groups for similar services/products can be used to make more accurate projections and target setting for all our clients.

Looking back at our previous calculation for CPL we can see how this might be adjusted for a lower intent channel after we have reviewed performance across intent categories for similar clients. Let’s step through the process again, and imagine we are setting up some new campaigns in a lower intent channel:

  • Target CAC = €800
  • The historic L2C rate is 25% but this is based mostly on high intent channels. Reviewing past performance of 2 or 3 similar clients we establish that they have had 30% L2C rates for higher intent channels and 15% L2C rates for lower intent channels. We apply this ratio to our new campaign and arrive at a likely L2C rate of 12.5%.
  • 800 x 12.5% = 100€ target CPL

2. Value of customer is unknown

In cases where the value of customers is yet to be fully established, it is hard to predict what CAC can be afforded. With new businesses and/or businesses with long sales cycles, it is not always clear as we go-to-market to what extent they will be able to monetize their customer base and therefore they do not know their affordable CAC.

In such circumstances the robustness of business planning and projections is key. Without historic data, the lifetime value of a customer has to be based on assumptions. All parties need to accept this uncertainty and then commit to target that can then inform the CAC. Ultimately these assumptions are at the heart of good business planning.

3. ROI is not the priority

Sometimes a new business has little idea about their L2C rates or CAC and just wants to generate a large number of new leads, fast. Even so, it is always important to set a CPL target against which to monitor performance. There has to be a benchmark against which to measure success and value.

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In this case the calculation of a target CPL should be based on expected media costs and C2L (Click to Lead) conversion rates. Expected media costs can be generated by creating the target audiences in the ad networks and checking the recommended and expected CPCs (Cost per Click) for those target audiences. This can be done in both LinkedIn and Facebook. You can also see expected CPCs and traffic levels for a specific keywords in search using the Google Keyword Planner.

Once you have established expected CPCs for your selected audiences/keywords, you need to then make some assumptions regarding the C2L. This can be done following exactly the same process as above when making assumptions about what L2C rates you will have, taking into consideration that not all traffic sources are likely to have the same C2L.

For example: if we assess that the target group we have selected for a client in LinkedIn are likely to need a 5€ CPC to get traffic at scale and, looking into other channels, we assume LinkedIn will have a 5% conversion rate of C2L, we can then use the following formula to calculate our initial target CPL:

Recommended CPC x Assumed C2L = Target CPL

5€ / 5% = 100€

Monitoring and revising initial assumptions

It is important to move on from these initial assumptions when you can. Modelling is one thing, but there is nothing like hard data to make sure that you are optimising performance and, more importantly, not ‘burning money’. Make sure you regularly review how many lower funnel conversions (e.g. paying customers) are being generated from your leads and try to create a target CPL based on the actual CAC as soon as possible.