Budgeting season is here again, and demand marketers are not immune. How big does your demand gen budget need to be in order to support your organization’s revenue goals in the new year? Alternatively, is the budget you’ve been handed enough to do the job?
Based on the work we do with our agency’s B2B clients, here’s a basic, funnel-based approach to determining a realistic demand gen budget based on specific revenue targets:
1. Start with your revenue goal for the year (or deals x ASP/ARR).
2. Define the percentage of that revenue (or pipeline) for which marketing is responsible. Industry standards for this figure vary widely, from 25% to 80%. The trend is towards the higher end of that range, as marketing assumes responsibility for more and more of the funnel. Your number will depend on your business model and sales cycle, amongst other factors.
3. Use this online lead calculator to arrive at a total number of MQLs or raw leads (inquiries) required to hit your revenue number. Enter “target revenue” based on total revenue x the % figure from #2 above, plus your average deal size. The calculator uses industry standard figures for conversion rates (Lead to MQL, Close Rate, etc.), but if you have your own funnel metrics based on historical data, those real-life numbers should take precedence and you can adjust the calculations accordingly.
4. We prefer to base budgets on MQLs vs. raw inquiries. Raw leads (form-fills) can convert to MQLs at widely disparate rates based on channel and CTA (e.g. SEM, Webinars, content syndication) so using MQLs allows for a more even playing field. In round numbers, a common cost standard is $250 per MQL. Here again, use your own figure based on the historical data if you know it.
Voila: there’s your demand gen budget (number of MQLs required x $250).
Here’s a sample calculation:
Total target revenue is $5 Million.
Marketing needs to drive 80% of that number ($4 Million)
$4 Million is 40 deals at an ASP of $100K.
At a close rate of 20%, 40 deals requires 200 opportunities
200 opportunities requires 400 SALs (50%)
400 SALs requires 606 MQLs (66%)
At $250, 606 MQLs requires a budget of $151,500.
What do these budget numbers not include?
* People (in-house or outsourced, salaries or agency fees)
* Content (Webinars, ebooks, video)
* Technology & infrastructure
A traditional metric for marketing planning is 50% programs/50% people. (A $150,000 programs budget would translate to a $300,000 total budget including people costs.) In this tech-driven era, consultant Dave Kellogg suggests a more modern 45/45/10 people/programs/infrastructure split or even 40/40/20.
How to Calculate Demand Gen Budget: A Rough Guide
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It goes without saying that these formulas and the underlying assumptions are subject to your specific sales model, tech stack, staffing model, product category, target audience, and marketing preferences. If you have little if any content that’s suitable for demand gen, for example, you’ll spend more on content development than the formula otherwise allows for. If you outsource 100% of your programs to an agency, your people costs may be higher but (says the agency owner with no bias whatsoever) your metrics should be higher. If your organization is ABM-centric, many of these lead-based formulas simply won’t apply, for obvious reasons.
If you’re handed a budget that won’t support target revenue goals based on this model, you can ask for more money, certainly, or alternatively you can look to improve the underlying metrics:
* improve ASP by integrating ABM or target-account programs to secure bigger deals
* improve close rate by leveraging intent data or AI technology to target “better-fit” prospects
* improve lead conversion rates by optimizing lead nurture strategy
Greater effectiveness at the top of the funnel can have an out-sized impact. Increasing Lead to MQL conversion rates even by a few points, for example, can have an exponential effect on pipeline downstream. It’s worth also taking a hard look at MQL definition. In many cases, the weak point in these funnel-based models is when companies have a too-generous MQL threshold, resulting in a scenario where marketing hits their MQL goals, but pipeline and closed-won numbers don’t keep pace.