A business’ marketing can encompass a wide range of activities and efforts, from paid ads to social media to email, influencers, SEO and more. And that means that marketing analytics is a wide-ranging topic, too. You’ve probably heard the phrase “marketing analytics” thrown around before, but what does it mean, really? Here, we’lll cover what marketing analytics is, what sources marketing data typically comes from, common KPIs and use cases, and why marketing analytics is important for businesses.
What is marketing analytics?
Simply put, marketing analytics is the process of using collected data to find patterns and identify opportunities for improvement in your marketing efforts. It’s based on analysis and observation of trends and outliers that help determine the return on investment (ROI) of your marketing efforts. By managing and studying your marketing data, you can gauge your successes and failures, as well as develop a successful roadmap for future marketing strategies. Something to note: two words that are often used when talking about marketing performance are metrics and analytics. And while they do go hand in hand, they’re not exactly the same. What’s the difference? Metrics refers to the actual data points themselves. Examples of metrics include revenue, conversion rate or churn rate - all different types of data that you can collect. Analytics, on the other hand, is the process of putting that data to use in the context of your business, deriving insights and developing a bigger picture about what’s going on. Analytics uses calculations, statistics, predictive modeling, machine learning and other techniques and technologies to make discoveries from different sets of data. This analysis can then be used to reveal insights, answer questions for stakeholders and drive growth for your business.
Used the right way, marketing analytics can have a major impact on your company’s performance, goals and future planning.
Why does your company need marketing analytics?
“Time and money are your scarcest resources. You want to make sure you’re allocating them in the highest-impact areas. Data reveals impact, and with data, you can bring more science to your decisions.” - Matt Trifiro, CMO at Heroku
As a business owner, marketer or analyst, it’s important to be aware of how customers interact with your company, how traffic flows through your site or store, and which of your marketing efforts have the most impact on the behaviors of your clients and customers. Since time and money are limited resources, as the quote above states, it’s important to understand that guesswork can cost you both when it comes to marketing. A data-driven strategy, powered by strong marketing analytics, can help you invest in the right marketing efforts, use limited resources more effectively and drive more results. Investors, board members and other stakeholders need to be able to see that you can back up marketing decisions with data. If you can directly correlate marketing efforts to new customers and revenue, you’ll be able to carve out a more successful path for your business.
How marketing analytics helps your business:
If you’re marketing your business, marketing analytics are necessary to help you understand your performance, identify opportunities for improvement and continue to drive growth. Here are just a few things marketing analytics helps you do:
- Understand current trends and seasonality and more accurately predict future trends in your marketing performance
- Gain insight into your customer base and their behavior in greater detail
- Identify your most valuable customers and determine what you need to do to attract more like them
- Determine which marketing channels and campaigns are successful in terms of customer acquisition and ROI
- Determine which marketing channels and campaigns are inefficient, not profitable or not a good use of your marketing resources
- Create successful, data-driven plans for future marketing efforts
In today’s digital ecosystem, using marketing analytics is crucial to understanding and predicting the behavior of your customers, so you can optimize your marketing activities and your user experience to drive revenue and growth.
What’s included in marketing analytics?
Depending on the type of marketing your business does, your marketing data can come from a range of different sources: Website analytics:
- Google Analytics
Marketing automation and CRM:
At the most basic level, a KPI (or key performance indicator) is a measurable value that shows how effective a company is at achieving strategic business goals and objectives. They indicate progress towards a set of intended results. There are a number of different KPIs that businesses might focus on, from high-level KPIs for overall business performance, such as revenue or growth, to more granular KPIs for individual departments or teams. Since marketing activities can be so wide-ranging, it can be useful to break marketing KPIs up into several categories: Overall marketing KPIs:
- Website visits
- Customer acquisition cost
- New customers acquired
- Profit per new customer
- Revenue and profit generated from marketing activities
- New customer acquired by channel
- Ad spend by channel
- Return on ad spend by channel
- Orders by channel
- Revenue and profit generated by channel
- Profit per new customer by channel
- Average order value by channel
- Customer lifetime value by channel
Individual campaign or ad set KPIs:
- Click through rate
- Email open rate and click rate
- Conversion rate
- New customers acquired by campaign or ad set
- Orders generated by campaign or ad set
- Revenue by campaign or ad set
- Profit by campaign or ad set
KPIs like this - as well as breaking marketing analysis down by channels, campaigns and even individual ad sets and ads - are useful when you need to break down complex performance data into smaller, more accessible chunks of information. Seeing growth or decline in certain KPIs over time can help you decide if your marketing strategies are working well, or if you need to adjust to make improvements in certain areas.
Attribution modeling is a specific type of marketing analysis that aims to accurately track the steps a customer takes before conversion, in order to attribute that conversion to the correct source (or sources). This type of analysis follows one or many touchpoints along the customer journey to the completion of a sale, with different touchpoints being weighted or credited differently depending on the attribution model you choose. Attribution modeling helps you see where your customers are coming from and understand which of your marketing efforts are effectively driving customer acquisition and revenue. That helps you understand the true performance of your marketing channels and campaigns and more effectively allocate your marketing resources. It can work through cookies, pixels, UTM tracking on your links, or a combination of different technologies. There are a number of different attribution models you can use, and there isn’t a one-size-fits-all approach. Each model varies slightly, and you’ll want to utilize the model (or models) that best fits your company’s business model, objectives and marketing strategies. Using more than one attribution model can be helpful when it comes to viewing your marketing data through multiple lenses - for example, Glew’s standard marketing analytics allow you to easily toggle between first-order and last-click attribution.
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Consider these common attribution models when deciding how to attribute your orders: One-touch attribution assigns credit to only one engagement/touchpoint along the user journey:
- First-click or first-interaction: Attributes credit for a sale or action to the first interaction a user has with a brand before making a purchase.
- Last-click or last-interaction: Attributes credit for a sale or action to the last interaction a user has with a brand before making a purchase.
- Last non-direct click: Attributes credit for a sale or action to the last interaction a user has with a brand before making a purchase, but excludes direct traffic, attributing the sale to the last channel a customer clicked through prior to visiting your website directly.
Multi-touch attribution assigns credit to multiple touchpoints along the user journey:
- Linear: Attributes credit for a sale or action to every touchpoint along the user journey, with each receiving equal credit.
- Time-decay: Attributes credit for a sale or action to every touchpoint along the user journey, with the touchpoints closer to conversion receiving more credit.
- Position-based/U-shaped: Attributes 40% of the credit for a sale to the first and last interactions in the customer journey, with the remaining 20% spread out over all touchpoints in between.
In using attribution modeling to analyze your marketing efforts, you’ll be able to discover the different ways customers discover your brand and the different paths they take to purchase, as well as understand which marketing efforts and channels are helping you drive the most sales.
Split testing, also called multivariate testing, is a method of conducting A/B tests - testing two versions of a website or campaign creative concurrently to observe which performs better in terms of a specified metric. Just like a scientific experiment, an A/B test includes a control (a website or campaign in its current/original state) and a variable. In order for this type of analysis to be successful, the single metric being tested should be the only variable in the experiment, so you understand what’s driving any changes to your KPIs. This could include changes to visual elements, text/copy, layout or visitor flow. In a split test, incoming site, ad or email traffic is evenly distributed between two (or more) variations. Over a period of time, a difference in user behavior will usually emerge, and the versions can be compared to see which delivered better results. Ideally, you would then implement the version that performed best more widely. Split testing can be used to find best practices for landing pages, social media ads, abandoned cart email campaigns, calls to action, checkout processes and more, and data from these tests can give businesses the upper hand when it comes to marketing decision-making and driving results.
The benefits of marketing analytics
Now that we’ve covered some of the basics of marketing analytics and some of the different ways you can gather and think about marketing data, it’s important to know why - and how - marketing analytics is beneficial for your business. Understanding how to collect the right data is one thing, but being able to understand what that data says about your business’s successes and opportunities is where the value of marketing analytics lies. Let’s look at how the data you’ve collected can help you take your company to the next level.
Test and develop successful marketing campaigns, and be more targeted in your marketing efforts
The most successful marketing efforts don’t appear out of thin air. Rather, they’re the product of many iterations of a site, product, message or campaign. Listening to your customers and carefully analyzing your marketing data will allow you to develop a successful strategy that fits your business model. Through marketing analytics, you can see who your customers are, how they perceive your brand and what types of messaging resonate with them. With this information at hand, you’ll be able to develop marketing campaigns that are fine-tuned to what your target demographic is looking for. Important questions to explore with your marketing team after analyzing your data include:
- Who is coming to your site and buying your products, and from where?
- What are users focusing their time and attention on most while they’re using the site?
- What is your conversion rate - across your website as a whole and for individual marketing channels and campaigns?
- What kind of campaigns attract the most attention and drive the most results?
- What campaigns don’t perform as well? Why?
- What can you change to better target your audience and marketing channels?
- How can you further develop your processes for gathering and analyzing data?
- What additional questions should you be asking about your data?
Allocate ad spend more profitably across channels
A major benefit of optimizing your marketing campaigns with data is the ability to put your marketing dollars to better use. When you know what works and what doesn’t, it’s easier to avoid putting time and money into channels and campaigns that don’t product results, and instead focus your resources on efforts that do. For instance, you may look at your marketing KPIs and realize that you’re getting a lot of new customers from your Facebook ads, but less from your Google Shopping campaigns. In that case, you may want to allocate more resources to Facebook to boost your efforts there, while dialing back Google Shopping. Or, you may find that you are driving orders through a particular marketing channel - but the revenue from those orders isn’t enough to offset the marketing costs. You may want to pull back spend, advertise higher-value products or brainstorm other ways to increase your average order value to ensure that channel is profitable.
Forecast trends and performance
Finally, a major advantage to having clear, consistent marketing data is that you are better equipped to predict future performance. Observing trends over time helps you plan for what’s coming and adjust your marketing strategy accordingly, whether that’s seasonal shifts in demand or the holiday sales season. A business intelligence platform can help you easily interpret historical data to identify trends and plan for the future, from seeing what day of the week or time of day you tend to get the most orders from certain channels to evaluating the performance of past marketing campaigns to develop future iterations. Most importantly, understanding your baseline marketing KPIs - from conversion rate to revenue and profit generated - can help you more accurately forecast your business performance from month to month.
Marketing analytics challenges
As with any type of reporting, marketing analytics comes with its own unique set of challenges. Below we’ll cover two of the most common ones - and what you can do to find solutions that work for you.
Focusing on the right metrics
One of the bigger challenges in marketing analysis? Figuring out which metrics to focus on in the first place. Especially in the beginning stages of collecting and analyzing your marketing data, it’s hard to know exactly what you should be paying the most attention to. There are countless metrics you can track, from the most important financial KPIs to so-called “vanity metrics.” What you choose to prioritize will depend largely on your company’s business goals. Is it retaining loyal customers? Driving website traffic? Simply acquiring more new customers? What you focus on from a marketing standpoint may also depend on how established your company is. If you’re just starting out with marketing analytics, basic metrics like overall site traffic, conversions, bounce rates and search trends may be most important as you begin your marketing journey. If you have a more established marketing presence, you may delve deeper into more granular metrics, like KPIs by channel and campaign, attribution reporting, and revenue and profitability.
Connecting data across platforms
Lastly, a common challenge with marketing analytics is connecting all of the disparate data sources that make up your marketing efforts - and being able to tie it together and report on it in a meaningful way. Most businesses use more than one platform to run marketing campaigns and collect data, from Facebook and Instagram to Google Ads to email marketing platforms and more. That means the data from your marketing efforts is stored separately in all of those platforms - and to get a true understanding of all your marketing efforts, you need to be able to pull it together for comprehensive reporting. You can do that manually, using data exports, spreadsheets and manual calculations - but it’s a lot easier with a business intelligence or analytics platform that allows you to easily connect your marketing data sources and automatically syncs data from all your channels, so you can monitor marketing performance and create reports in one place.
Connect all your marketing data in one place With 75+ user-friendly integrations, Glew helps you easily connect, analyze and visualize all your marketing data in one place, from Facebook and Instagram to Google Ads to email, influencers and more. Connect your data to get multichannel marketing insights, faster:
No matter what kind of marketing you do, marketing analytics are critical to your business. They help you evaluate your marketing performance, understand your customer behavior and purchase paths, and develop smart marketing strategies across all your channels that drive growth while using your marketing resources effectively. Getting started with marketing analytics first requires an understanding of your marketing data sources and the KPIs you need to track. Don’t forget these key takeaways:
- Marketing analytics is the process of using collected data to find patterns and identify opportunities for improvement in your marketing efforts
- Marketing analytics helps you understand your customer journey and use your time and money more effectively to drive results
- Marketing analytics can include data sources like email and marketing automation platforms (Klaviyo, Mailchimp), CRMs (Hubspot, Salesforce), advertising platforms (Facebook, Instagram, Google Ads) and more
- Marketing KPIs can include metrics like revenue, profit, orders, new customers, impressions, clicks, conversion rate and more, and can be evaluated on the channel, campaign and ad level
- Attribution modeling is a specific type of marketing analysis that helps businesses track the steps a customer takes before a conversion, in order to attribute that conversion to the correct source
- Marketing analytics can also be used to evaluate the results of A/B tests, where a business may test variations of creative or copy for landing pages, emails or ad campaigns to see what produces the best results
- Marketing analytics can help you test and iterate successful marketing campaigns, allocate ad spend more profitable, and forecast performance
- Common challenges with marketing analytics include focusing on the right KPIs and connecting your disparate data sources