When we’re brought in by a private equity firm to help a particular investment, the portfolio company’s immediate expectation is that we will ramp up Marketing priorities like demand gen and content right away.
Our response is always to slam on the brakes.
Scaling is always the goal, but doing so without the right data framework in place is equivalent to setting your marketing budget on fire. Scaling Marketing isn’t like flipping a switch: It’s about building an engine that is predictable so that we can invest more dollars with confidence as time goes on.
This requires data organization. Without data, you’re pursuing complex initiatives in the dark. You don’t know where to invest or how to track success on those investments. You’re playing Pin the Tail on the Donkey, and maybe you guess right and invest in the right space, but maybe you don’t.
To avoid costly misjudgments, you need to build a marketing data framework that gives you hard evidence of which campaigns are working and which ones are not. You can then allocate budget to the winners, and keep tabs on whether that increased investment continues to pay off or whether you’ve maxed out that channel.
This data framework should be a series of metrics that connects Marketing’s actions to revenue and provides clarity on where your marketing dollars are going. These metrics include:
Below are the three steps to building a data framework that shows where investing your marketing budget can really move the needle on revenue.
In most organizations, Marketing’s accountability stops at the MQL number. Contribution to pipeline or pipeline dollars is the only concrete measurement Marketing tracks to judge their performance. This is why Sales and Marketing are often at odds.
Marketing generates leads and considers their job done. Then, Sales calls those people, only to discover those leads don’t meet BANT criteria. Sales complains about lead quality; Marketing fires back, saying they should work the leads more. Each side thinks they’re right because of the metrics and responsibilities you’ve given them.
Part of Marketing’s job is to make Sales better at their job, so if Sales is failing, so is Marketing. In other words, this is an accountability problem. If Marketing thinks it can wash its hands of a lead once an MQL is generated, the problem will continue to exist—no matter what Sales does.
To get a real picture of which marketing activities are actually delivering what Sales needs, you need to bridge the gap in data across each stage of the buyer journey by tracking the performance of each individual lead that Marketing brings into the funnel. This will realign Marketing’s metrics to focus on revenue.
To understand Marketing’s true impact on revenue, we need to be tracking Marketing-Generated Pipeline and Closed Won Deals. By tracking beyond the MQL stage, you remove Marketing’s argument against Sales. If Sales has a qualification call with a prospect, and they deem the lead to be a bad fit for any reason, then that lead is removed from the pipeline generated by Marketing.
This metric allows everyone to focus on who is actually ready to buy and enter the next stage of the funnel. It also removes channel bias. Some channels will generate leads who are more ready to buy than others. At the MQL level, that nuance is hard to distinguish, but when you look at Pipeline and Closed Won Deals, the value of leads from each channel becomes clear. Once a sales rep has called the lead and verified that this is a good candidate to buy your product, we remove the channel bias entirely.
Most importantly, this metric removes excuses on both sides. Once marketers are accountable for revenue instead of MQLs, they are tied to revenue impact, and Sales is accountable for closing leads because they themselves validated the quality of those leads.
Reorienting the company around the pipeline gives Marketing a revenue target and clearly establishes its core accountability to revenue. This begins a transition to data and reporting becoming a top priority for marketing leaders.
Very quickly, Marketing will realize they need to have the right reporting mechanisms in place to measure all stages of the funnel. They need to know:
Once this becomes a priority, it’s time to start organizing, interpreting, and acting on that data in the next two steps.
Before Marketing can begin to restructure its investments, we need to answer a very important question: How much can we spend to acquire an MQL?
Too often, businesses don’t have an answer for this. They simply hand Marketing $200,000 and expect that budget to somehow return enough leads for Sales to close. If the company remains profitable, they assume Marketing has done its job.
To have a baseline to compare your campaign and channel data against, you need to know how much you can spend for each MQL: This is your acceptable cost per lead.
Your acceptable cost per lead is the amount you can spend on each lead and remain profitable based on how likely that lead is to close. This is your benchmark to evaluate the success of any marketing activities and avoid burning cash on dead ends.
To find this number, you need to track your leads all the way down the funnel. Your funnel likely looks something like this:
To break down the performance through the funnel, you need to know:
You need concrete numbers so you can work backward and discover what your acceptable cost per lead is.
Let’s say you generate 10,000 leads for a spend of $200,000. That sounds quite promising. But that math is based on some significant assumptions. You need more data to see if those assumptions are true.
For simplicity’s sake, we’ll say the answer to all three questions above is 50 percent. This means for every eight MQLs, you get one closed-won deal:
Multiplying those conversion rates gets us an overall MQL to Closed rate of 12.5%. If you’re paying $200,000 for 10,000 leads, then you’re only closing 1,250 of them. That means you’re generating $125,000 in revenue for a $200,000 investment. In other words, that seemingly productive campaign is a failure.
So how much can you afford to spend on an MQL? To determine that, you need to know your Annual Contract Value (ACV). You can then do the following calculation:
Acceptable cost per lead = ACV x MQL to Closed rate
Let’s say that in this example, the ACV is $1,000 in revenue over a year. If you’re converting your MQLs at 12.5 percent, some simple math tells you that your acceptable cost per lead is $125 ($1,000 x 12.5 percent). You now have a yardstick by which to measure each campaign.
For some channels, you may be able to spend more than $125 because they’re better at finding the right kind of leads. For others, you’ll have to spend much less due to the inefficiency of the channel. This is why we need to go deeper with our marketing reporting.
It’s not enough to say that your current channels exceed your company’s acceptable cost per lead. You also have to ask: Is there somewhere else more profitable that those dollars could be spent?
Let’s say your company has a marketing budget of $3.5 million, allocated like this:
Perhaps you’re losing $1 million on poorly performing LinkedIn ads, but is there a campaign or channel out of the remaining $2.5 million in marketing spend that is generating superior returns for the company?
Imagine if there was a channel delivering MQLs for 10 percent of the cost of LinkedIn Ads and converting to Closed Won deals at higher rates. Wouldn’t you immediately shift more budget to that channel or campaign instead?
This is why you need reporting at the level of channels and campaigns. Luckily, your current marketing investments have valuable clues about where to scale next.
Using the same philosophy that gave you your acceptable cost per lead—tracking investment all the way through to Closed-Won—Marketing can drill down into the cost per opportunity on a channel-by-channel basis, and even for specific campaigns.
You can use our free data framework template to save time building out yours—click here to download the template. Filling out these figures for each channel should give you something like this:
For this particular company, investing $600,000 in trade shows brings in a whole lot of MQLs and opportunities. But the Cost per Opportunity is high. At $1,500 Cost per Opportunity, if their average deal size is $7,500, this company would need to close one in five opportunities to break even within a year on this spend.
If their Opp to Close rate for trade shows is pretty high, continuing to heavily invest here makes total sense. That being said, the Cost per Opportunity on paid media is phenomenal (less than 5 percent of the cost of trade shows), yet that channel only receives 10 percent of the budget that trade shows do.
Even though both channels may be profitable, paid media represents a huge opportunity for the company to capitalize upon. Even if there’s only room to invest $20,000 more into Google Ads before you max out that channel, that would represent an additional 325 opportunities you would be leaving on the table if you didn’t invest here.
That is the true power of tidying up your marketing data. When you’re playing with millions of dollars in marketing budget, knowing the efficiency of each dollar can make the difference between huge wins and unforgivable losses.
Investing in marketing data has a huge benefit—the more data we have, the clearer the growth levers inside marketing become.
Without data to anchor marketing decisions, we will inevitably see repeated mistakes that waste budget. By tying Marketing’s accountability to revenue and gathering the data needed, we can build the foundation to scale Marketing faster. As Marketing becomes a rainmaker and revenue-accountable, it’s responsibilities shift down-funnel, and the focus on sales increases.
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