11 May What is Marketing Analytics? Best Practices for Measuring Marketing Effectiveness
The marketing and advertising industries constantly evolve. Before the rise of the web in the early and mid-nineties, marketing and advertising teams relied heavily on traditional marketing which drove results but not without certain limitations and challenges. For one, traditional marketing can be costly, time-consuming, and hard to track. As a result, it was and sometimes still is difficult to evaluate the overall effectiveness of traditional marketing on the larger business objectives.
Then, came the rise of search engines like Google, Yahoo, and later eCommerce sites like Amazon and Gmail; this caused marketers to shift from traditional marketing methods to an agile digital marketing approach Now, with an estimated 1.7 billion people using Google daily, top brands know that reaching consumers online with the right message, at the right time, and in the right channel is the key to the most cost-efficient marketing campaigns. To do this, brands need to use marketing analytics to track and analyze user behavior data so they can act on that data and create custom touchpoints to optimize the customer journey to conversion. More importantly, digital advertisers need to make sure they not only use the right marketing analytics tools but also properly implement them to measure the most important metrics as they relate to the overall brand goals.
So what is marketing analytics and how can advertisers use marketing and data analytics to measure the effectiveness of their marketing activities? In this blog, we’ll cover the marketing analytics definition, why marketing analytics is important for a holistic digital marketing strategy, and some marketing analytics best practices. As a result, you’ll be able to use marketing analytics to measure, analyze and take action on your own data so that you can achieve both your desired marketing outcomes (e.g. increased conversions and better ROAS/ROI) and larger business goals (e.g. increased revenue and business growth) as well.
What is Marketing Analytics and why do you need it?
Marketing Analytics is the continuous practice of gathering, analyzing, visualizing, and actioning on marketing data. Marketing data consists of many data points, which we call metrics, that you gather with analytics tools such as Google Analytics. Marketing Analytics is the process of providing context to those data points.
Giving context to your metrics helps you measure the performance of your marketing efforts, understand how different campaigns succeed, and determine the value of each marketing activity as it relates to driving revenue for your business. You can use marketing analytics to understand what’s working and not working in your digital marketing strategy. This is not only important for determining marketing effectiveness in connecting with your customers, but also for how you make strategic decisions based on historical or current data.
Marketing Analytics also helps you understand your target audience and their behavior, online and offline, so that you can optimize your customer journey touchpoints to fit their custom interests and needs. Optimizing your customer journey drives increased conversions as users are more likely to convert when their experience with your brand is highly relevant and personalized.
When you correctly implement, analyze, and take action on your data with Marketing Analytics, you can also run predictive analytics to understand the potential ROI of new channels and customers. However, it is important to note that predictive analytics are based on existing data, so you’ll need to make sure you have plenty of clean data in Google Analytics already in place in order to build an accurate predictive model.
Now that you understand the Marketing Analytics definition, let’s walk through marketing analytics best practices so that you can ensure accurate marketing and data analytics that drive conversions and deliver data-driven insights to inform a holistic marketing strategy.
Marketing Analytics Best Practices
Following these Marketing Analytics best practices ensures that you maintain an active, continuous cycle of collecting, analyzing, and acting on that data in ways that help drive marketing and business success.
Each phase of the Marketing Analytics cycle must be active and running correctly to adhere to marketing analytics best practices. If any phase is not functioning correctly, or absent from the cycle entirely, you will be acting on an incomplete data analysis.
Without these actionable insights on your data, you also won’t be able to make any improvements to certain touchpoints and channels. Additionally, it will be impossible to optimize specific parts of the conversion funnel, and when you aren’t able to optimize specific parts of your conversion funnel, you won’t be able to deliver the personalized customer experience that drives users to convert.
Most importantly, without a cohesive Marketing Analytics cycle, you won’t be able to prove which specific touchpoint and/or channel adjustments made a positive, or negative, impact on revenue or contributed most to increased ROI.
1. Make sure to gather and track all data, and make sure that data is accurate.
Most brands use a combination of both online and offline channels to advertise to customers. It’s important to make sure that you’re capturing accurate data from all your sources (website, CRM, display, social, paid search, etc.) so that you have a complete picture of how all of your touchpoints interact to drive users down the funnel to conversion.
Investing in the right marketing analytics tools helps aggregate all your data into a single source of truth. Google Analytics 360, for example, seamlessly integrates with other Google Marketing platform products such as Display and Video 360, and Search Ads 360. As a result, you can gather and analyze data from these other platforms in a single place. This helps cut down on any wasted time otherwise spent trying to connect large amounts of data from your various digital marketing and analytics tools.
More importantly, a single-source of truth helps you select the right attribution model to fit your unique digital marketing goals and properly attribute conversion credit to specific marketing channels and touchpoints. You can use this single-source of truth to choose or build the right attribution model that will give you insights needed to appropriately spend your marketing budget on your most effective channels.
2. Select the right Marketing Analytics platform for your business and make sure it gives you real-time insights
There are many different types of marketing analytics tools, such as web analytics tools, testing tools, and social content tools. These tools can help deliver detailed insights about your specific marketing channels, in addition to the general data insights you get about users on your site from your current analytics tool.
Marketing analytics platforms with real-time insights are especially important if you’re capturing a ton of data. If you are only able to see this data weeks or months later then you won’t be able to react until weeks or months later, and by that time it’s likely that these insights are no longer relevant.
Having real-time data at your fingertips allows you to make real-time decisions about how to allocate budget, what types of ad messaging to use, when and where to use those ads, and which strategy delivers the best ROAS/ROI.
3. Make sure you can visualize your data easily by building reports and dashboards that are easy for all your stakeholders to understand
Analytics dashboards and reports need to be easy to understand so that each stakeholder can spend less time deciphering data source names, and more time strategizing how to act on that data. When each stakeholder can easily interpret your data, they are better equipped to make quicker strategy pivots to help optimize the overall marketing strategy. With Google Analytics, you can choose from a variety of data visualization tools such as DataStudio, Tableau, or Power BI to visualize data through graphs, charts, or maps. As a result, stakeholders have a more accessible way to see trends, outliers, and patterns in their data.
Another way to build user-friendly reports is to use Goal setting in Google Analytics. Goal setting in Google Analytics helps you report on the specific user activities and interactions that matter most to your stakeholders and contribute most to your overall website and business objectives. Setting goals also helps you tell google analytics which specific metrics are most important to you, which in turn, sets you up for success with funnel visualizations and reports that are focused, uncluttered, and easy for all stakeholders to understand.
4. Action on your data based on the insights and recommendations from your analytics team and/or partners
Gathering, analyzing, and acting on your data is a continuous process. Your analytics team and/or partner knows best how to keep pushing the needle forward, while also troubleshooting any issues within your analytics solution that might pause or halt this ceaseless process.
Your analytics team and/or partner has the experience necessary to troubleshoot these issues quickly, which prevents additional waste of your team’s bandwidth, budget, and/or resources. Once your analytics team and/or partner troubleshoot these issues, you can rely on them to act on your data.
Acting on your data involves putting different recommendations, made by your analytics team, into practice by optimizing parts of your media approach, marketing strategy, creative assets, content, and even your website. Consequently, you’ll be able to draw accurate conclusions about the effectiveness of those recommendations in relation to your overall business objectives.
5. Use historical marketing analytics data, knowledge, and analysis to make decisions for future campaigns.
There’s a good chance your brand likely has a lot of data, which offers a huge benefit since you can use all of this historical data to make decisions about future campaigns. But lots of data can also present some major challenges, mostly being that you might feel overwhelmed by the sheer amount of data you have. This data could also come from disparate data sources, and otherwise unorganized, which takes precious time and resources to sort through.
One way to build and maintain accurate, clean historical data is to again, choose an analytics solution that acts as a single-source of truth for measuring all of your marketing activities. As we explained earlier, Google Analytics 360 integrates with all of the other Google Marketing Platform products so you can easily access your media and display advertising data alongside your Google Analytics data.
As a result, you not only get a full picture of marketing success across all channels and campaigns in real-time but historically as well. A full picture of your historical marketing effectiveness allows you to pinpoint and optimize exactly which channels, touchpoints, and other aspects of your user experience helped drive conversions in the past so that you can replicate those conditions in new marketing campaigns as part of your holistic digital marketing strategy.
Once you’ve mastered all of the best practices we’ve outlined above, you can build upon this solid foundation of historical data to run predictive analytics with Machine Learning/AI. Predictive analytics can help you advocate for additional budget in new channels since you can show stakeholders what the predictive ROI of each channel is, rather than blindly investing large amounts of media dollars into a new channel with just an estimation as to how successful it will be in driving conversions. This is where an agency or partner like DELVE can once again be helpful. For example, at DELVE we have data analytics experts that specialize in executing predictive analytics.
It’s important to note that you can’t use predictive analytics without strong historical data, therefore using Machine Learning to run predictive analytics is best-used by brands who are already successfully running a marketing and data analytics cycle and want to go a step further and predict marketing effectiveness and potential customer value.
6. Make sure that you have the right people to analyze the data and make actionable recommendations for optimizations and tests
This is where it is important to consider how you want to implement your marketing analytics program. Do you want to use a self-service solution and manage your analytics accounts in house, or work with a partner for a full-service or hybrid solution? Self-service analytics allows you to choose your own team and handle all of the components of your digital marketing tools under a purchased license. The in house or managed option takes things a step further where you not only purchase a license from a partner but also use the partner’s team to set up your tools, run campaigns, and execute your overall strategy. You might choose a combination of these models, but regardless of how you choose to implement your marketing analytics program, a partner can offer specialized expertise.
Your analytics team or analytics partner should have the expertise to seek and identify trends in your data and develop insights out of that data as they relate to your overall business objectives. They can discover and highlight the trends most applicable to your overall goals. A major benefit most businesses find in an analytics partnership is the ability to cut the time wasted on trying to develop complex data insights on your own.
The process of analyzing data and making actionable recommendations always starts by fully understanding the data measurement pain points and opportunities your brand has when it comes to driving insights, regardless of the marketing analytics program you choose. Next, it’s important to review and validate that the data is accurate, clean, and complete. Now you can analyze and visualize the data with different methodologies and approaches through different tools such as Google BigQuery, Google Data Lab, or Google Cloud ML (Machine Learning). Through your visualization tool, you can share your data through servers or packaged workbooks for easy stakeholder accessibility. At DELVE, we follow a specific approach when executing self-service analytics projects.
We offer a variety of options when it comes to cutting waste with Marketing Analytics. No matter whether you choose self-service, hybrid, or full service with us, you’ll work with a dedicated team that has helped us earn our status as a Google Marketing Platform Partner. Our team has demonstrated expertise in all Google Marketing Platform products, including Google Analytics 360, Display, and Video 360, Search Ads 360, and more. Our highly specialized experts in each platform give the brands we work with the flexibility to utilize a wide range of skilled experts that strategize and implement customized marketing and data analytics solutions. You can learn more about our team here.
Marketers and advertisers have come a long way from the limits of relying only on traditional marketing which can be costly, time-consuming, and void of real-time measurable metrics to check performance and evaluate the results of marketing activities.
Advances in digital marketing technology allow advertisers to create marketing campaigns that are more efficient and personalized for a tailored customer experience. In order to know if a campaign is successful, marketers need to make sure they continue to use marketing analytics best practices and continuously track, analyze, and act on data, in real-time. A marketing analytics cycle like this helps advertisers evaluate and optimize their marketing strategy to drive conversions and see ROI that contributes to increased revenue and fulfillment of overall business objectives.
To learn more about how we can help implement a customized marketing analytics plan for your business, visit our website here.