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Let’s continue on the bottoms-up planning train. I’d like to focus on Performance Marketing today. Many in Revenue Operations will support one singular function such as marketing, sales, or CS. More recently however, RevOps teams are increasing overlapping capabilities within the organization to make the team more resilient. If one team member left who happened to have a sales operations background, the RevOps team can temporarily backfill the role with partial coverage from other team members.
So today I’d like to focus on working with the performance portion of the marketing team. If you have a sales ops background this may be brand new to you. If you’re from marketing operations then I hope this will be further validation of the great work you do.
How often have you come across this situation?
CEO: here’s your budget for the year, $200K per month totaling $2,400,000. Your goal is 400 sales accepted opportunities (SAOs).
Head of Marketing: great. I’d like to allocate 20% towards brand, 20% towards events, and 60% towards performance marketing.
Marketing Ops: why these specific allocations? what are your goals? what sources are we doubling down on? what industries and personas are we targeting?
Head of Marketing: I don’t have those details yet. I figured at $1.44M for performance marketing and a target of 400 SAOs our cost per SAO (CPSAO) is $3,600. At 20% MQL-to-SAO our CPMQL we need to have 2,000 MQLs at an average cost of $18,000 (CPMQL). I also assume 15% of all leads are MQLs so we would need 13,333 leads. So let’s find a path to 1,111 leads per month. Our overall $1.44M performance marketing budget should average out to $108.00 per lead (CPL).
Marketing Ops: blended averages are great to explain the situation concisely from a 10,000 foot view. But I suggest we also do a bottoms-up planning analysis to see how far we are apart from your tops down view.
Head of Marketing: okay I'm good with this approach but where do we start.
Marketing Ops: let's review our historical data and build up our performance plan layer by layer.
This fictitious conversation illustrates the virtuous feedback loop between a top down mandate and a bottoms up plan. The back and forth forces the business to ask what are the obstacles ahead and what would have to be true to make the plan reality.
Today’s article is going to feature a bottoms-up performance marketing planner template at the bottom of the article.
Here's an approach I recommend:
Prepare the data. Verify marketing attribution for all opportunities have high fidelity. This is essentially a cleanup exercise.
Review the data. Review opportunity sources from the previous year broken down by segment
Know your unit economics. Break down all of the cost components so you have a view of your unit economics. In particular: cost per impression, cost per click, cost per lead, cost per meeting, cost per sales accepted opportunity
Set goals. Break down the top down goal into segments
Set channels. Decide which performance channels you will utilize in 2023
Trial allocations. Start with your projected 2023 budget and develop allocations by source
Scenario planning. Now that you have your allocations, hypothesize what the upside and downside scenarios.
Prepare the data
Run a quick test. Check that you have the following fields on the following objects in Salesforce:
UTM Medium
UTM Source
UTM Content
UTM Term
UTM Campaign
Then check that you have them in the Lead and Contact object.
Then check that these are mapped fields between Lead>Contact and Lead>Opportunity.
If you’re in Hubspot you won’t need to worry. These fields are already in there. Just make sure you configure your ad connectors. Here’s more information on how to connect all of your ads to Hubspot.
I highly suggest using Fieldtrip or Sonar's Fieldspy application to identify field completion percentage.
As they say garbage in, garbage out.
Review the Data
Do you have sufficient insights where your pipeline came from in 2022? If not, then I doubt 2023 will either.
Get your house in order.
If your top line planning is broken down into the following:
Geography
Products
Segment
Industry
Then is it crazy to assume you should also have your SAOs, at minimum, to also reflect this breakdown?
Bonus points for having leads collect three of the four. Having product at the lead level is very difficult. This can be accomplished through rigorous form fill. All too common and more achievable is to enrich the lead via a third party data provider.
No matter how you set up your attribution rules ensure that you have a standard which you follow. Below is a sample attribution guide.
Know your unit economics
Know your costs. Each performance ad platform will have reporting capabilities. For example let’s say you have a breakdown of all costs from last year. In this view you breakdown the following columns:
UTM Source: the source where you ran your campaigns (see attribution taxonomy sample above)
Total Spend: all spend associated with the source
Leads: number of new leads entered into your CRM or leads that resurfaced (i.e. nurture leads)
Meetings: number of meetings your AEs or SDRs set
SAOs: number of meetings that meet your qualification criteria to enter your forecastable pipeline
Cost metrics: cost per lead, cost per MQL, cost per meeting, and cost per SAO
All of the numbers below are generated from a sample bottoms up marketing plan. All numbers are either inputs or outputs of a RANDBETWEEN function. This is for illustrative purposes only.
This breakdown serves as a starting point to discuss with your marketing leader what happened at the end of the year. What were the twists and turns that led to these numbers. Did you pivot during the year to shift from brand based campaigns to a heavier mix of demo requests? What was the narrative?
And what should the narrative be for 2023? Will you be doubling down on what works? Will you be cutting? The answers to those questions should be grounded in data. So here we are.
Set Goals
Not just the 400 SAOS the CEO mandated to the Head of Marketing. Instead, set granular goals. What audiences do you want to go after? What segments? What’s the expected win rate per segment and therefore working backwards you back into the necessary number of SAOs you need to generate in that segment. What does the data working backwards tell you?
Set Channels
Let’s say that in 2022 you started to dabble with paid review sites such as Capterra and Software Advice. You found some traction and would like to accelerate spending there in 2023.
In FY22 you may have found that 85% of paid review leads turned into MQLs. The 60% MQL to Meeting ratio also suggests these leads are further down the marketing funnel. You also find out that the cost per SAO is on the order of 4x to 5x lower than your traditional channels such as LinkedIn and Google Paid Search.
Trial Allocations
In the cost dummy data above Paid Search and Paid Social accounted for 90% of the budget in 2022. But let’s say for example our fictitious company has an expanded budget next year (outrageous for 2023!) and decides they want to reallocate some of that spend over to Paid Review. So instead of 90% towards Google and LinkedIn it dials down to 73%. Paid Review sites such as Capterra (etc.) would see a growing share of the wallet for FY23. This is because the marketing team believes there is more juice to squeeze there next year.
Also, the marketing team believes that a few strategies will help them to unlock a higher level of efficiency in Google and LinkedIn. These strategies may include something of the following below:
Strictly focus on Titles and Industries for LinkedIn. Avoid using the Skills section.
Narrow down demographic ad variations for Google Ads along the lines of geography, size of company, and industry (see here)
Scenario Planning
We all know about sensitivity analyses. In the bottoms up marketing template one could imagine creating several versions of the plan to account for different sized budgets. But this is where marketing and selling is a team sport. It’s not enough for just marketing to put improvements into a spreadsheet model and it will magically come to life. Instead, try putting sales and marketing into a room together to discuss common goals and how they could feasibly drive improvements. This is how those new outcomes could turn into reality. Below is a sample driver hypothesis table for the marketing and sales team to work together on.
In particular, the lead-to-meeting ratios and the meeting-to-SAO ratios will require sales input. Some ideas on how this could happen:
Speed-to-lead SLA shrinks down from one hour to five (5) minutes
All leads are pushed into a sequence
All leads must be worked unless filtered out by lead scoring
Bi-weekly lead disqualification review between sales and marketing. Feedback loop to performance marketing.
Thanks for reading this far!
Obviously this was just a fictitious scenario. But I have worked with plenty of clients who have planned their marketing goals in a vacuum. Numbers seem to come out of thin air. Much like my RANDBETWEEN function.
But if you put together a bottoms-up plan it helps to carve out the details of what could be. It stirs vigorous debate with your marketing team what is practical and what is in fantasyland. It also serves as an opportunity to bring the sales and marketing team together to jointly define goals to shepherd the marketing plan into reality. Selling is a team sport. But so is marketing.
My two cents 👋
P.S. as promised, the marketing template is below the "plug below”.
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Performance Marketing Budget Planning Template
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