Analytics have always been important to marketers. Before the internet, marketers used analytics to measure the return on investment from different promotional activities, such as newspaper advertising or telemarketing team performance.
Now that marketing has moved mainly online, the analytics of today are more granular. That’s because software tracks what customers are doing at every point of the sales process. It’s now possible to identify the point at which customers drop off the most and then make changes to improve performance.
In the digital era, a unique set of business terms to describe marketing tools and concepts has emerged to determine campaign performance. Below, find 30 of the most important marketing data analytics terms.
Here are 30 marketing data analytics terms you should understand:
An action is any customer interaction with your website, application or product. This could be an email sign-up, page view, download, video play, purchase or any other activity you would like to track.
As artificial intelligence and machine learning continue to grow in use and popularity, marketers need to understand how these technologies work. On many customer relationship management (CRM) and marketing software platforms, it’s possible to create your own algorithms to more precisely measure whether you have achieved your marketing goals.
An automation is a triggered response to a user’s activity or behavior. For example, if a visitor to your site downloads an e-book, that activity could trigger an automation to add that visitor to an email campaign or to create a lead in your CRM software.
Attribution ties results to specific actions. For example, if you write blogs to generate sales, you can set up attribution reports to track how many visits to that blog turn to leads and sales. Marketers use attribution models and reporting to understand how well their marketing actions succeeded.
Behavioral targeting is an advertising technique that monitors the behavior of a user to deliver more personalized, relevant messaging. If a marketer is collecting the right data, they can use behavioral targeting to engage customers and prospects based on a variety of information. For example, you could send someone a personalized email featuring the products they looked at the last time they visited your website or used your app.
A bounce rate is the percentage of people who come to your landing page and leave without browsing further or clicking elsewhere on your website. Marketers aim to reduce bounce rates to keep visitors engaged longer, in hopes of boosting conversions.
Churn is the percentage of customers who don’t buy from you anymore. There are multiple ways to calculate churn, depending on your business model. At a software-as-a-service (SaaS) company, for example, if a customer comes on board with a one-year subscription and leaves later, they will have “churned.” By keeping churn rates low, you keep revenue higher.
A conversion rate is the percentage of users who took the action you wanted them to take. For example, if 1 in 20 people visiting your site makes a purchase, that’s a 5 percent conversion rate. You can measure the conversation rates of almost anything, including free-trial sign-ups, whitepaper downloads and ad clicks. Conversion rates are useful because they help you benchmark the success of each marketing action you take.
Cookies are small files that are stored on a user’s browser or computer when they visit a website. Cookies (often called tracking cookies) allow marketers to track the behavior of visitors while on their site, retarget visitors while on other sites and map the path visitors take once landing on their site.
Anyone who has come to your site by typing your domain name into their browser or by using a saved bookmark to access your site will be attributed to direct traffic.
Engagement rate is a term used to measure how engaged a visitor is with your brand. Your engagement rate can be calculated in multiple ways. For example, a visitor who came to your website and clicked multiple pages for an extended period is more engaged than someone who landed on your site and left after a few seconds. The term engagement rate is also used to describe how people interact with social media posts — specifically, how many people like a post, share it with others and leave a comment. The term is frequently used in email marketing and text message marketing, too.
Custom events are the specific actions you want to track. For example, a mobile gaming company might want to monitor how many of their users make it past the first level. To measure this, they would create a custom event that tracks level completion.
Impressions are the number of times a piece of content has been viewed. Impressions can apply to websites, but the term is now more commonly used in respect to Facebook and Twitter advertising. For example, a post on Twitter could receive 200 impressions if it has been viewed by 200 Twitter users.
Remember that social media platforms limit the number of organic (nonpaid) impressions a post gets because they’d like to charge you for the exposure instead.
A sales funnel is a way of describing the stages a customer goes through, from first realizing they need your product or service all the way to the end purchase. In marketing, a funnel can also refer to the steps users take from the moment they interact with your brand to the time they become a customer.
By monitoring funnel analytics, marketers can identify weaknesses in the conversion process. For example, an online retailer could see that most customers are dropping off during the checkout process in their funnel and could optimize this process based on the data.
Labels allow marketers to classify customers based on their behavior and other data. For example, by examining the features used, the support tickets issued and the number of times an account has been accessed, a SaaS provider could identify a customer as being “at risk of leaving.” They could then use this information to create campaigns — in this case, campaigns designed to persuade a customer to stay.
HubSpot or Marketo users will probably be familiar with the term “lead score.” Lead scoring assigns a number (score) to a lead based on the perceived fit for your company and the lead’s behavior. For example, a visitor who downloads a whitepaper, reads a blog post, attends an event and requests a demo may have a much higher lead score than someone who just downloaded the whitepaper.
Omnichannel refers to customers’ increasing expectation that they can deal with you across multiple channels. For example, if a customer is shopping for your product, their experience across multiple channels — their tablet, smartphone, desktop and in-store experience — should be consistent.
Personally identifiable information (PII) refers to any user data that could be used to distinguish one person from another. Standard PII identifiers include phone numbers, email addresses, Social Security numbers and mailing addresses.
A property is something measurable or identifiable that you track. For example, properties relating to consumers might include their age, gender, location, company, email address and revenue. For business-to-business clients, the properties you’d like to track might include industry sector, website address, number of followers on LinkedIn, and average revenue.
A referrer is an online location that sends a new visitor to your website. This could include social media posts, Quora questions, images embedded with links, posts on other blogs, backlinks and more.
Retargeting tracks users who visit your site by placing a cookie on their device or browser. You can then advertise to that same user if they visit sites that allow retargeting. This method of advertising brings back those who might have been interested at one time but need a little reminder to convert them into a paying customer.
A revenue report is a scorecard that measures the turnover generated by a particular action or event. For example, you might want to pull a revenue report if you’re interested in understanding exactly how much revenue a particular marketing campaign has generated.
Segments are groups of customers who share certain characteristics you specify as important. For example, you could create a segment of users who belong to an enterprise organization, visited your site at least three times and downloaded your e-book. Segmenting helps marketing teams create separate strategies for each cohort. Customer analytics solutions such as Woopra allow for in-depth and targeted segmentation to help marketers quickly identify issues and opportunities.
A session (sometimes called a visit) is how long someone stays on your app or website at a given time. The actual amount of time that is attributed to a session varies depending on your analytics solution. For example, a two-hour session could include the projects, purchases and reports that a user engaged with while on your application. After a period of inactivity, the session ends, and a new session will begin as soon as the user comes back to your site or application.
A source can be any offline or online channel that drives traffic to your site or generates leads. Like referrers, sources can include search engines, social media, blog posts and more. Unlike referrers, sources also may include specific campaigns, like an offline direct-mail campaign.
Taxonomy is a way of organizing your data into categories and subcategories to allow for greater segmentation and filtering. For example, if you’re tracking blog post engagement within WordPress, the taxonomies you could employ for additional filtering might include comments, searches, article views and blog subscriptions.
Touchpoints are the interactions a user has with your business before they become a customer. Touchpoints could include anything from their first email response to a live chat conversation they have with a support representative.
By tracking the different touchpoints, marketers gain a better understanding of which touchpoints are most valuable and how many it takes to convert an interested visitor into a paying customer.
Touchpoints form part of the customer journey for your clients. Analyzing positive and negative feedback at each stage of the journey can lead to better outcomes by allowing you to tweak the stages where you see the greatest drop-offs.
A tracking URL is a regular URL with a token or UTM parameter (learn about UTM parameters below) assigned to it. Tracking URLs allow marketers to track where specific traffic originated.
Anyone who has accessed your website at any point in time is a unique visitor. This is tracked by a cookie placed on the browser or device of a visitor along with their associated IP address. As long as the visitor comes back to your site from the same browser and device, they’re counted as one unique visitor. If, however, a visitor clears their cookies or visits your site through a different browser, they’re counted as two unique visitors.
UTM parameters (also known as UTM codes or UTM tags) are essentially source descriptions that are added to the end of a URL. They allow marketers to identify the exact source of traffic coming to their website and tie activity on specific channels to business results.
Without a UTM tag, you might be able to identify that a visitor came to your site from social media, but you wouldn’t know which post or campaign drove that traffic. With a UTM tag, you can include the source (e.g., Twitter), the medium (e.g., email), the content (e.g., “Why Marketing Is Awesome”) and the keyword associated with that campaign for clear attribution. [Read related article: 5 Cringey Brand Fails on Social Media]
Data can provide marketers with deep insight into the performance of their campaigns. Nowadays, analytics tools either come built in or can be integrated with many types of business software services, including the following:
If you’ve made it to the end of this article, you’re well on your way to becoming a data-driven marketing expert. While the definition of many of these terms can fluctuate slightly depending on how your organization analyzes data, a basic understanding of how marketers speak of and analyze data will allow you to turn your data insight into proactive action.
Elle Morgan contributed to this article.