Marketing Analytics 101
Marketing metrics and analytics provide a strategic road map to improve efficiency, predict returns, and prove marketing return on investment (ROI) across the entire organization.
Marketing analytics are your strategic road map to improve efficiency, predict returns, and prove marketing return on investment (ROI) across your entire business. But what actually are marketing analytics — and how do you get started with them? In this article, we’ll tell you everything you need to know.
In this marketing analytics guide, you’ll discover:
- What is marketing analytics?
- How marketing analytics helps your business
- Common problems that marketing analytics can solve
- How organizations use marketing analytics
- Components of marketing analytics
- 5 methods to analyze your marketing program
- ROI of a successful marketing analytics program
- Plan, implement, and optimize your marketing analytics program
- Frequently asked questions
What is marketing analytics?
Marketing analytics is the practice of managing and studying metrics data in order to determine the ROI of marketing efforts and identify opportunities for improvement.
You may use marketing analytics to determine the success of:
- Calls-to-action (CTAs)
- Blog posts
- Channel performance
- Thought leadership pieces
- Website user experience
The more technology develops, the more time and budget chief marketing officers (CMOs) allocate to understanding the performance and growth influence of their marketing.
In fact, a recent survey predicted spending in the area will increase by 200% in the next three years. Marketing teams can often struggle to demonstrate credibility, but if you adopt strategic marketing analytics, you can make it easier to show ROI.
How marketing analytics helps your business.
By tracking and reporting on business performance data, diagnostic metrics, and leading indicator metrics, marketers will be able to provide answers to the analytics questions that are most vital to their stakeholders.
Regardless of business size, marketing analytics can provide invaluable data that can help drive growth. At first, enterprise marketers may find the process too complicated. Similarly, small and mid-sized business (SMB) marketers might assume a company of their size won’t benefit from implementing metrics, but neither perception is true.
So long as marketing analytics is carefully curated and properly implemented, the data collected can help a business of any size grow.
With proper marketing metrics and analytics in place, marketers can better:
- Understand big-picture marketing trends
- Determine which programs worked and why
- Monitor trends over time
- Find the ROI of each program
- Forecast future results
Many businesses are getting in on the act, even if they may have once been hesitant. In fact, over 75% of marketers are reporting on how their campaigns are adding revenue to their business.
“Too often marketers talk about activities instead of outcomes — for example, how many campaigns they ran, how many trade shows they participated in, how many new names they added to the lead nurturing database. These are metrics that reinforce the perception that marketing is a cost center, not a revenue driver.”
- Glen Gow, Founder and CEO, Crimson Marketing
Common problems that marketing analytics can solve.
Determining the effectiveness of your marketing efforts can be more complicated than tracking simple engagement. What’s more, compiling that data doesn’t necessarily result in optimization of your future campaigns.
Here are a few problems that a marketing analytics solution can help solve.
As a default, marketers often put primary metrics such as lead source tracking and cost-per-lead in place. However, there is no holistic understanding of how marketing activities impact key bottom-line metrics.
Make sure to set up analytics to support the goals that your stakeholders most care about. This will ensure you aren’t compiling data without a plan in place.
Taking your data out of silos and spreadsheets can help with this. When you automatically connect and unify your data, you can spend more time acting on insights you’ve worked hard to collect and less time on tedious reporting tasks.
Keeping all your data in one place can also be beneficial, as it allows you to refer back to it quickly, if needed.
Many marketers think of marketing ROI as reporting on the outcome of their programs. This is often in the form of a set of reports they have to deliver monthly.
However, the most successful companies recognize that reporting for reporting’s sake is less important than using those reports to make decisions that boost sales.
Don’t just report on a single campaign. The incremental contribution of individual marketing programs and the ability to show how your marketing campaigns influence sales at every stage of the customer journey will help build credibility and show long-term program success.
Remember, it’s important to ensure metrics match what you want to achieve with your marketing efforts. This is something to bear in mind when planning projects.
When marketers take responsibility for the early stages of the revenue cycle and understand how to model these stages, they have better visibility into future revenue.
Marketing analytics allows the ability to forecast how many new leads, opportunities, and customers marketing will yield in future periods. That’s because it tracks where prospects are in each revenue cycle stage and how likely they are to move through each stage over time.
How organizations use marketing analytics.
When you retrieve offline or online marketing analytics, you can make important decisions on products, branding, campaigns and more.
Armed with your data, you can gain insights into:
- Trends and preferences. Analytics can help you meet your customers where they are. Use your data to see how well an advert has landed or fire out surveys on products and features.
- Media placement. Work out the success of your ad placements and branch into new media buying techniques. Analytics can help you see where customers click, engage and convert, and where they switch off.
- Competitors. Use marketing analytics to assess the market landscape and close the gap on the competition.
- User experience. Is your website placing unnecessary hurdles between customers and conversions? Analytics can help you spot snags in user experience and iron them out.
- Predictions. Armed with detailed data on your customers, products and market, you can make your future marketing campaigns far more successful.
Components of marketing analytics.
Marketing analytics is a multifaceted practice used to drive ROI and improve future efforts. It traditionally consists of:
Centralized marketing database.
Analytics require access to highly detailed marketing data, so you need to begin tracking this information now — preferably in one place. Required information will include:
- Historical data on when marketing programs ran
- What their attributes were
- Which customers they reached
- How much they cost
Without this information, analytics are essentially worthless.
Time series analytics.
Unless your operational system stores historical data, you cannot measure or understand marketing trends. Frustratingly, many marketing and sales solutions are operational and do not store historical information.
This means that if you want to analyze their metrics for prior time periods, you will need to manually take data snapshots from Excel spreadsheets. However, time series analytics can give you a full picture of performance trends over time, as the engine can analyze beyond point-in-time insight.
Advanced attribution capacity.
With marketing data in one place, you can understand what moves the needle and maximizes return on marketing investment. However, you will need technology that facilitates marketing attribution reporting.
Many solutions only offer basic attribution capacity: most commonly, first or last touch attribution or multi-touch attribution, which are both limited by the type of channel or time horizon. This can hamper your ability to grow into the most illuminating attribution models down the line.
Be sure to understand the attribution limitations of any technology you’re considering before you buy.
Powerful and easy insights.
Very few of the marketers who want and need to consume analytics data are business analysts. For such an audience, user-friendly dashboards are required, allowing you to explore data trends and gain insight into their programs, without wasting time learning the technology, build custom reports, etc.
Just make sure your marketing automation solution offers tools that are both and powerful and simple to use.
Ad-hoc reporting and dashboards.
On the other hand, marketing analytics experts will need the ability to delve deeply into the data and customize their ad-hoc reports. In this case, table-like reports and charts are most effective and allow analysts to follow the scent of particular insights as far as they need to go.
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5 methods to analyze your marketing program.
Having a strategic marketing analytics program means knowing which data points to monitor and which detract from your ultimate goal of demonstrating ROI. While this will take more work up front, in the long run, it will make analysis a much simpler process.
Method 1: Single attribution — first-touch and last-touch.
Single attribution is one of the most common marketing analytics strategies. This strategy allocates all the value to either the first or last interaction with the prospect before buying.
- First-touch attribution credits the lead generation strategy with the eventual sale, regardless of when it happens. For instance, if an SEO-optimized landing page gains a new lead from web search, who later consumes branded content, engages on social media and attends a trade show before buying, first-touch assigns the value of that sale to the SEO optimization.
- Last-touch attribution credits the final communication with the close of new business. In the example above, the trade show would be credited with the sale, since it was the last interaction the lead had before purchasing.
Method 2: Single attribution with revenue cycle projections.
Single-attribution strategies are simple, but this simplicity has its disadvantages. Brands with longer buying cycles need to account for that period of time. They also need to see all the lead nurturing that happens in between, 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 solve this problem. Revenue cycle projects use complete data from previous campaigns to project the eventual outcome of recent and similar marketing efforts.
Method 3: Attribution across multiple programs and people.
Attribution across multiple programs and people views credit more holistically. 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, you then determine how to weigh each one, so that their values can be properly assessed. 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, rather than the projected or assumed, impact of a marketing campaign on your target audience. 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, since you have to plan a program you can test. The goal is to apply the factor you want to measure to one part of your target market. Make sure you divide your audience into two groups that match up on other basic metrics.
Method 5: Full marketing mix odelling (MMM).
Marketing mix modeling demonstrates how each unique marketing touch, as well as non-marketing variables, impacts sales volume. Statistical techniques create complex equations that can consider an infinite number of factors, including:
- Economic conditions
To be effective, this model requires a lot of data. So much so that most find MMM consumes too much time and energy. Even larger companies can only afford to conduct MMM once every few years.
ROI of a successful marketing analytics program.
The ROI of a successful marketing analytics program is one of its greatest assets, and it can impact your company on a universal level.
- Builds credibility. Marketers can earn the respect of their organizations by taking a professional approach to marketing metrics and analytics. This is by using integrated technology to provide better insights for informing better business decisions. Marketers who invest in measuring and managing performance create more value, achieving 5% better returns on marketing investments and over 7% higher levels of growth performance (Forbes).
- Saves time and money, and improves efficiency. By providing a single platform for reporting across all channels, the entire process is simplified. Additionally, we found that across industries and regions, an integrated analytics approach can free up 15% to 20% of marketing spending (McKinsey).
- Results in faster revenue growth. Campaigns can be iterated to improve the bottom line when marketing metrics are readily available, resulting in more accurate forecasting and quicker revenue growth.
Learn more about how to speak the language of marketing metrics.
How to plan, implement, and optimize your marketing analytics program.
The first step to beginning your marketing analytics journey is setting goals and committing to the process. Get the ball rolling in just four steps.
Step 1: Plan.
Before you hit the ground running, you’ll need to set goals and targets, so you aren’t reporting for reporting’s sake. Estimate your expected ROI, then start to develop programs that are designed to be measurable, so you aren’t wrestling to pull data.
Ensure you focus on any and all decisions that will ultimately result in an improvement in your marketing efforts.
Step 2: Implement.
As with any business transformation, the success of your marketing measurement program depends on how well you implement it. Set yourself up for success by making sure you find the right team, use the right tactics, and have the right technology in place.
Step 3: Create a culture of analytics.
Hiring (or designating) the right people is only the first step. Even at companies that already have significant analytical activities under way, completing the analysis is only about a third of the battle.
The other two-thirds involve driving that data into all current business workflows, in a way that prompts your organization to use and act on your valuable conclusions to boost revenue.
Step 4: Optimize.
When you are able to spread the revenue over multiple activities, you know which marketing activities are effective for the top-of-the-funnel versus the bottom-of-the-funnel campaigns. You may determine that trade shows are great for getting leads, whereas webinars are more effective for moving leads further along the sales and marketing funnel.
Without multi-touch attribution, it’s hard to learn this information, and your campaigns may not be as successful.
Frequently asked questions about marketing analytics.
What is the definition of marketing analytics?
Marketing analytics seeks to find patterns in marketing data and create actions. In practice, the marketing analytics meaning can cover anything from statistics to modeling and machine learning. It helps businesses understand their customers, products, sales points and more.
What can we learn from marketing analytics?
Marketing analytics can demonstrate return on investment, plan more campaigns and measure performance. Using benchmarks, tracking and predictions, it looks to the past, present and future to help marketers make data-driven decisions.
What are examples of marketing analytics?
Marketing analysis can be used on a wide range of areas to maximize ROI, plan campaigns and keep up with competition. Some examples of marketing analytics might include:
- Customer segmentation
- Campaign planning and scheduling
- Competitor analysis
- UX performance
- Workflow efficiency
- Customer lifetime value