Marketing Analytics and ROI
How much profit would a 10% increase in your marketing budget produce?
If you're not sure, don't worry—you're not alone. Forty-four percent of surveyed B2B marketers didn't know either. But unfortunately it's highly unlikely your CMO will give you a 10% increase in budget without knowing that answer.
For your executive team, the bottom line is where they are held accountable. Thus, it's understandable that they'll be reluctant to give you more budget without knowing the potential return. So how can you easily acquire this crucial information? The answer is marketing analytics. Marketing analytics allows you to speak the language of the C-suite by showing how your team is directly contributing to your company's overall revenue generation.
What Is Marketing Analytics?
Marketing analytics is the practice of managing and studying metrics data in order to determine the ROI of marketing efforts, as well as the act of identifying opportunities for improvement.
It's impossible, of course, to discuss analytics apart from metrics, but it's also crucial to define the difference. Marketing metrics are the data points themselves. Analytics is putting that data in the context of your brand and market, telling managers and investors a complete story about how your marketing efforts are driving revenue.
Why Do I Need Marketing Analytics?
Your "To Do" list is long enough. You're building awareness, launching campaigns, scheduling follow-ups, and driving and nurturing leads. As long as your campaigns are keeping the sales team is flush with qualified leads, you're golden, right?
Wrong. You might have a gut feeling about what works and what doesn't (and you might even be right), but measuring and monitoring your campaigns is the only way to prove it. With that being said, a thorough marketing analytics program will help you to:
- Understand big-picture marketing trends
- Determine which programs worked and why
- Monitor trends over time
- Thoroughly understand the ROI of each program
- Forecast future results
The executive team won't support or finance good feelings or trending marketing techniques without numbers behind them. Nor are they interested in bare metrics—spreadsheets full of numbers that don't tell a story and don't clearly relate to the revenue stream.
Tracking your marketing metrics is a necessary first step, but metrics don't speak to the corner office without analytics to interpret them. This is why you need marketing analytics.
5 Methods of Program Analysis
Strategically choosing which metrics to monitor will make analysis a much simpler process.Once you have the data, though, you still have to determine how to use it. Let's look at 5 different methods for analyzing your metrics to determine the success of your marketing programs.
Method 1: Single Attribution (First Touch/Last Touch)
Perhaps the most common marketing analytics strategy is single attribution. This allocates all of the value to either the very first or the very last interaction with the prospect prior to buying.
First touch attribution credits the lead generation strategy with the eventual sale, no matter how much later it happened. For instance, if an SEO-optimized landing page drew in a new lead from a web search—a lead that later consumed branded content, then connected on social media, and then attended a tradeshow all before becoming a customer—first touch attribution assigns the entire value of that sale to the SEO campaign.
Last touch attribution credits the final communication with the close of new business. In the example above, the tradeshow would be credited with the sale since it was the last interaction with the lead prior to the deal closing.
Both methods make sense. Without the first touch, a prospect may never have become a prospect. Without a strategic last touch, the prospect may have never made the decision to buy. Therefore, both first touch and last touch attribution have their merits. The use of either simply depends on the brand, industry, and market.
Method 2: Single Attribution with Revenue Cycle Projections
Single attribution strategies are simple, but that simplicity can create obvious disadvantages. Brands with longer buying cycles need to account for this lengthier period of time as well as all of the lead nurturing that happens therein in order to create an accurate picture of the quality of current marketing efforts.
Adding revenue cycle projections to a first touch/single attribution analytics strategy can overcome the difficulty. Revenue cycle projects use complete data from previous campaigns to project the eventual outcome of recent and similar marketing efforts.
Annual industry events are good examples. A year after an event, you can look at data on metrics like:
- How much was invested
- How many touches were made
- How many contacts eventually became leads
- How many contacts eventually led to sales
- How much revenue resulted from the event
At the end of this year's event, you will know how much was invested and how many touches were made. Using data from previous events, you can then project a confident expectation of leads, sales, and revenue.
Method 3: Attribution across Multiple Programs and People
Attribution across multiple programs and people attempts to give credit where credit is due. You recognize that no single marketing effort is responsible for a sale, and you try to determine the value of each touch by starting with the action that created a sale and working backwards.
Once every touch has been identified, determine how to weigh each one so that their values can be properly assessed. Here are three basic strategies for assigning those values:
- Timing: Some touches may weigh heavier based on when they happened in the buyer cycle. Usually, the touch that triggered key behavior from a buyer is assigned more value than a top-of-funnel touch that took place months or years prior.
- Role: Programs that targeted and influenced the key decision maker in an organization may be assigned more weight than those that spoke to other influencers. Just make sure that the scales tip in favor of the actual decision maker, not necessarily the people higher on the leadership flow chart.
- Program type: Programs that require greater engagement may be weighted higher than those that do not. A webinar or live demo, for example, requires more participation from prospects and would most likely influence them more than an infographic.
Some assumptions are necessary for this method, and that's OK. Just make sure you are prepared to defend them to the C-suite, or you may risk invalidating the whole process.
Method 4: Test and Control Groups
Test and control groups are a great way to measure the actual—not the projected or assumed—impact of a marketing campaign on your target audience. And in theory, it's as easy as your middle school science fair experiment!
Using test and control groups requires a little extra strategy from the start—you have to plan a program to be test-able. The goal is to apply the factor you want to measure to one part of your target market. So make sure you divide your audience into two groups that match up on other basic metrics.
Method 5: Full Market Mix Modeling (MMM)
Marketing Mix Modeling (MMM) demonstrates how each unique marketing touch, as well as non-marketing variables, impact sales volume. Statistical techniques create complex equations that can take into account an infinite number of factors, including:
- Economic conditions
To be effective, this model requires a lot of data. So much so that most marketers find that MMM consumes too much time and energy. This explains why only 3% of B2B marketers use it.
Forecasting Sales: A Marketing Task
The C-suite is never as interested in the next marketing campaign as it is in the sales forecast, which is why the CMO is too often left out of the conversation.
But that shouldn't be the case. In the digital era, marketing departments can (and should) take responsibility for at least the early stages of the buyer cycle. Marketing managers should have more insight into future revenue than the sales team based on its collection of data from past campaigns and its plans for the next ones.
There are four steps of forecasting:
- Modeling:Model the revenue cycle and map personas. Make sure you plan to gather the best metrics during the buyer journey.
- Collect inputs:Forecasts and educated guesses will only be as good as the data on which they are built. Do the due diligence necessary to get the most accurate data on how many new leads the marketing team will gather through each upcoming campaign.
- Pattern:Model how current and new leads will flow through the revenue cycle based on data you have gleaned from past campaigns.
- Forecast:Remember that these are estimates, so it's crucial to apply your judgment to the numbers. If your data and metrics are solid, though, you should be able to project a fairly accurate estimate of future revenue.
Projected sales are the numbers that executives want to see, which is why sales usually gets more credibility from the corner offices. But when marketing teams can gather data and map revenue cycles to accurately project sales forecasts, CEOs will start to better understand the marketing department's value.
Marketing Analytics: Grow Your Business and Your Brand
Enterprise marketers often initially see marketing analytics as a complicated endeavor, while SMB marketers tend to consider it unnecessary for their company's small size. But, neither perception is true.
An accurate map of the marketing analytics process reveals a very approachable practice—and one that is essential for growing a business of any size. Enterprise marketers will improve their campaigns and grab the CEO's attention in a way they never have before. SMB marketers will build their brands and drive sales…and grab the CEO's attention.
What to learn more about marketing metrics and analytics? Download The Definitive Guide to Marketing Metrics and Analytics for more in-depth information, or take a look at any of the Marketo resources below.