What is Marketing Analytics?
Marketing analytics is the practice of understanding online marketing data in order to determine the ROI of marketing efforts, as well as the act of identifying opportunities for improvement. Measuring your traffic versus your conversions allows a business owner to learn how to show ROI in marketing.
How to Use Marketing Data to Forecast Sales:
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 marketing 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.