Mastering the Art of Marketing Analytics in 5 Simple Steps

A good marketing analytics strategy is essential to your marketing department’s ability to make a measurable contribution to the overall performance and growth of your company. Of course, the key word in the previous sentence is “measurable.” The primary purpose of analytics is to measure, monitor and make decisions based on what your data is telling you. As you monitor various metrics, you should be able to “see” patterns, anomalies and results that lead to insights that inform your actions.

Three Benefits of Marketing Analytics

A few of the big benefits a solid marketing analytics strategy provides include being able to understand customer behavior, optimize marketing efforts, and make better plans for the future. Examples of the types of insights and advantages gained per benefit are featured below: 

1. Understand Customer Behavior

• Know how customers are searching for your products/services
• Map customer journeys and plan accordingly
• Reduce your cost per lead

2. Optimize Marketing Efforts

• Adjust ad campaigns to produce greater results
• Know which channels and devices are bringing in the most leads
• Enhance the content of blogs, landing and product pages, etc.

3. Plan for the Future

• Understand the ROI of various marketing efforts
• Enable sales to close more business
• Invest your budget where the ROI is greatest

Pre-Analytics Prep

Before you invest time developing and pursuing a marketing analytics strategy, you need to prepare both your data and the various tools, apps, systems and platforms within your marketing technology stack. After all, you can’t make data-driven decisions based on disparate data and disconnected tools. To ensure your decisions are based on the best-possible data we recommend taking three critical steps:

Step One: Locate and Integrate All Data Sources Throughout Your Company

It’s vitally important to your ability to make informed decisions to integrate both major and minor data sources, from marketing automation platforms (MAPs) and customer relationship management systems (CRMs), to content management systems (CMSs), analytics tools and more. If you’ve got data that’s buried inside any of the tools in your martech stack, consider adding a data dashboard tool that centralizes your view and access to all of the data contained within your stack.

Step Two: Get Your Data Results-Driving Ready

According to Experian, companies worldwide report that 26 percent of their data is dirty. This leads to the average business losing 15 to 25 percent of revenue thanks to inaccurate, incomplete or inconsistent data (aka dirty data). These days, there’s no excuse for having dirty data when you can keep your data perpetually clean, complete, standardized and enriched by adding AI-driven automated processes and data management solutions that monitor and maintain data quality. Beyond producing better results, using clean data will also save your budget and enhance your customers’ experience, loyalty and lifetime value.

Step Three: Connect Your Content Sources and Channels to Data Sources

The best way to track the performance of your marketing efforts is to measure campaign performance across all channels. When you connect your data and content to the various channels you use, it empowers you to scale personalized campaigns. which perform much better than non-personalized campaigns. In fact, 86 percent of customers are more likely to make a purchase when companies provide personalized experiences.

Step Four: Choose a Marketing Analytics Strategy or Apply a Combo Approach

Most marketers use a combination of marketing analytics strategies or approaches, and we will discuss the differences and advantages of the two most common below—Marketing-Mix Modeling (MMM) and Digital Attribution.

1. Marketing-Mix Modeling or Media Mix Modeling: MMM measures the performance of your campaigns and other marketing efforts by determining how different metrics or variables contribute to a specific goal, like signing up for a blog or making a purchase. Campaigns are then adjusted according to how various metrics impact performance. Because MMM uses aggregate data and multiple variables are involved in determining a campaign’s success, this approach is the most popular analytical approach.
   How MMM Works: MMM uses multi-linear regression (MLR) to determine how a dependent variable (i.e. a purchase) is affected by multiple independent variables (i.e. media channel, ad spend, etc.). According to Investopedia, MLR is “a statistical technique that considers the effect of more than one explanatory variable on some outcome of interest. It evaluates the relative effect of these explanatory, or independent variables on the dependent variable when holding all other variables in the model constant.”
   MMM Pros and Cons: Although MMM is a quick and easy way to uncover high-level insights on trends that occur over a span of time, it cannot be used to gain in-depth understanding of your customer experience or the relationship between the various channels you are using.
   
2. Digital Attribution Modeling (DAM): This approach leverages data from multiple touch-points or channels to determine how customers make a purchase. Within DAM, there are several model variations including:

• First-Touch Attribution – This model assigns credit for a lead to the first channel that engaged them. It’s easy to track, but it doesn’t account for the impact other touchpoints have on a customer’s decision to purchase.
• Last-Touch Attribution – This model assigns credit for a lead to the last channel they engaged with prior to purchase. Like its predecessor, it’s easy to track, but it doesn’t account for the impact of other touchpoints.
• Multi-Source Attribution – This model gives credit to every channel that contributes to a customer’s decision to purchase; however, it does not account for the specific level of contribution each channel makes.

Step Five: Use the Right Marketing Metrics

Three Types of Marketing Metrics

Whether you are measuring the performance of a text campaign, the technical SEO of your website, or your social media pages, most marketing metrics fall into one of three basic types—volume, conversion and big picture. Each category of metrics has dozens of variables that can be tracked, and each provides varying degrees of insights and information that can be used to inform your decisions. The most simple type of metric, and the easiest to track, is volume. Conversion metrics are a bit more complex than volume, but also equip users with more actionable information. Lastly, big picture metrics are the most time-consuming to track and calculate, but they also provide the greatest opportunity to glean actionable insights. Below we’ll define each of the three types and share a few examples.

1. Volume Metrics – These are quantitative measurements of the sum total of something, such as how many times something happened (i.e. page views, clicks, unsubscribes, etc.). This type of metric is typically used to measure things like audience reach, growth and churn. Volume metrics are great for providing basic or low-level insights. Some examples of volume metrics include:

• Email/SMS Opens – Number of people on your list that opened your email/SMS, etc.
• Email/SMS Unsubscribes – Number of people requesting removal from your list
• Impressions – How many times your content was displayed to users
• Reach – The number of people who actually viewed your content
• Engagement Rates – The number of people who reacted to your content (likes/shares/etc.)

2. Conversion Metrics — This type of metric reveals how effective marketing is at turning prospects into customers. Google defines conversion metrics as those numbers associated with motivating a person to action. An example of a conversion metric is when someone visits your site and clicks a button to schedule a demo. Other common conversion metrics include:

• Lead Inquiries – Prospect requests more information, a demonstration, etc.
• Click-Through Rates – The number of times people clicked-through to engage with your content
• Marketing Qualified Lead (MQL) – Person who has demonstrated an interest in your products or services
• Sales Qualified Lead (SQL) – Person who has demonstrated an intent to buy your products or services
• Conversion Rate – The percent of prospective buyers who become viable leads or make an actual purchase

3. Big Picture Metrics – These metrics are essential for demonstrating marketing’s value and typically require input from several different KPIs, which are plugged into a formula in order to calculate actual values. Big picture metrics are often what C-suite executives expect to see in marketing performance reports. Examples of these metrics include:

• Cost to Acquire a Customer (CAC) – This metric reveals the sales and marketing costs involved in obtaining a new customer.
  CAC Formula: Add Marketing’s costs in acquiring a new customer to Sale’s costs in acquiring a new customer and divide it by the total number of new customers.
• Cost to Serve a Customer (CTS) – CTS measures the costs involved in serving a customer over a measure of time.
  CTS Formula: According to Easy Metrics, a business labor intelligence company, “The traditional method for calculating CTS is to use an Excel model to estimate the average cost for each process, then multiply that cost by the transaction volume. The average is usually determined using an estimated labor standard.”
• Return on Ad Spend (ROAS) – This metric calculates the amount of revenue gained for every dollar spent on advertising.
  ROAS Formula: To measure ROAS, you take the revenue that is attributable to an ad campaign and divide it by the cost of the ad campaign.
• Customer Lifetime Value (CLV) – The CLV measures the total revenue a company can expect from a customer and compares it to the typical span of time a customer remains with a company.
  CLV Formula: To determine your CLV, subtract the cost to acquire a customer (CAC) and the Cost to Serve (CTS) customers from the revenue you earn from them.

Developing Your Marketing Analytics Strategy

Now that we’ve covered the three different types of marketing metrics, you are ready to identify the ones that will be most valuable to you. To set up your strategy for maximum effectiveness, make sure you define the goals you want your strategy to achieve. For example, if your goals are to improve marketing campaign performance and increase sales, then you must carefully consider all the variables contributing to the problem you want to solve or goal you want to reach. Begin by asking questions, such as:

• What Key Performance Indicators (KPIs) are most relevant to the problem/goal?
• How can each KPI be changed, improved or manipulated?
• What outcome will mark the endeavor a success?

Sureshot has a long history of helping organizations get better results from their marketing strategies by automating data processes and message personalization, and empowering customers to create coordinated customer journeys that delight at every touchpoint. If you are ready to unlock the full potential of your marketing endeavors, start by taking our FREE Martech Assessment.