As a small business, you might not have access to top business intelligence talent to analyze data to build better insights that lead to success. Here’s a beginner’s guide to digital marketing analytics to help you achieve your goals including key metrics and tools you need.
Introduction: In the digital age, data is the lifeblood of effective marketing strategies. Unlike the meager data available from traditional marketing campaigns, digital marketing analytics are robust and able to empower businesses to make informed decisions, optimize campaigns, and drive better results. However, beginners might find the world of digital marketing analytics overwhelming, with too much data that leads to analysis paralysis.
For instance, if you don’t know what you need for your analysis, looking at a screen capture from the Google Analytics dashboard is overwhelming. Even displayed with good data visualizations that make analysis easier, the sheer volume of information can quickly result in that glazed-over look that indicates you reach information overload where you can’t process the data to derive insights. In this guide, we’ll break down the essential key metrics and tools that every novice marketer should use to get the most from digital marketing analytics.
A guide to digital marketing analytics
The biggest piece of advice I can share with beginners and experts alike is that your first task is to determine which metrics you should focus on, which you should ignore, and how to determine which metrics you need for specific problem-solving. So, let’s start this guide to digital marketing analytics by looking at the analysis problem you face.
Effective strategies as a guide to digital marketing analytics
As portrayed in this Dilbert cartoon, data isn’t the solution to your digital marketing analytics. Instead, you must analyze accurate data to develop insights and then use those insights to guide decisions about the future if you want to achieve greater success. Here are some strategies to do that:
Set clear goals
Define specific and measurable objectives for your marketing campaigns to align your analytics efforts. These should consist of SMART goals that, as the acronym implies, are specific, measurable, achievable, relevant, and timely. An example of a SMART goal is to increase sales by 10% over the next 12 months.
Determine relevant metrics
Focus on metrics that directly contribute to your goals and provide actionable insights. Which metrics are relevant and actionable should flow naturally from your SMART goals. Later in this post, I share some examples of metrics worth assessing as they impact your performance.
Regularly review and analyze data
Dedicate time to analyze your data regularly and identify trends, patterns, and areas for improvement. That means it isn’t enough to simply collect data into reports. Analysis means you work to determine the impact of metrics on performance, how to improve your metrics, and translate that into concrete plans for the future.
You should monitor key metrics on a daily basis. Also, consider that employees might need different data to guide their actions. For instance, a CEO might need an overview of the organization’s performance, the supply chain manager might need data related to on-time delivery and inventory levels, the social media manager might need data on conversion rates by channel, and the email marketing manager might want data on clicks and conversion from various messages. Hence, you likely need multiple reports and each report should allow for interactions with the data. A CEO might want to break down data into divisions to assess the performance of each one while the brand manager might want to view the performance of individual products under his/her control.
Invest in learning and training
Stay updated with industry trends and enhance your skills through online courses, webinars, and industry publications. As you can see below, analytics is one of the most in-demand skills for digital marketers and the need for these skills increases over time. It may be impossible for brands, especially small businesses to hire the right people to manage their digital marketing analytics. So, training staff with an aptitude for analytics may be your best bet.
Marketing intelligence [source]
is everyday data that is relevant to the marketing efforts of an organization. Once collected, this data can be analyzed and used to make informed decisions regarding competitor behaviors, products, consumer trends, and market opportunities.
With marketing intelligence, your first task is to determine which metrics to collect. Generally, we refer to metrics related to your success as KPIs or key performance indicators because it’s these metrics that translate into success or failure. An obvious KPI is sales since this is the ultimate measure of success. We call these terminal KPIs or, in Google Analytics, they’re called goals. Of course, sales don’t occur in a vacuum so you must also create KPIs that help by supporting sales. Some of these intermediate KPIs are:
- Reach: the number of potential buyers (your target market) that see your content. This is often expressed as a number or the percentage of your target market that saw your campaign content.
- Cart abandonment rate: the proportion of those that began your conversion process to those that completed the process.
- Frequency: how many times your ad or content was displayed to your target market. b.
- Clicks and click-through rate (CTR): explores the number of clicks your ad or content received and the percentage of clicks in relation to impressions, a metric related to reach.
- Conversion rate: how many users completed a desired action, such as making a purchase or filling out a form, relative to the total number of visitors.
- Return on investment (ROI): measures the profitability of your marketing campaigns by comparing the cost of investment to the generated revenue.
- Bounce rate: an analysis of the percentage of visitors who leave your website after viewing only one page, indicating a lack of engagement. Not only that, but a high bounce rate is an SEO (search engine optimization) ranking factor so a high bounce rate means your content ranks behind pages with lower bounce rates. Plus, when users bounce, you lost the chance to make a sale.
- Customer lifetime value (CLV): an assessment of the total value a customer brings to your business throughout their lifetime as a customer. This is a function of not only how much they buy but how long they continue buying from you. Often, you find groups with different CLVs, which determines your marketing efforts aimed at each group. For instance, in the ’90s banks assessed the CLV of customers to build offerings aimed at each group. Those with the lowest CLV were charged fees to compensate for the small value of their accounts while those with higher CLV saw more perks and greater efforts to meet their unique needs through personal bankers. The idea is to keep your best customers happy while making your worst customers more profitable or discouraging them from remaining with your business.
- Engagement rate: which is also used to assess your social media marketing efforts. Engagement on social media refers to the number of users who liked, commented, or shared your content. It’s important to note that your number of followers is a vanity metric, meaning it doesn’t directly impact your performance. Instead, we talk about your number of engaged followers.
- Share of voice: which reflects the relative mentions of your brand versus competitor’s brands.
- Cost per action: this is a metric to assess the cost of getting a user to take an action, such as the cost per click (CPC) for your advertising campaign.
- Average retention rate: this reflects loyalty to your brand. We can also talk about other loyalty measures such as repeat visits to your website and growth in your follower counts.
- Average order value (AOV); this metric reflects how much money visitors spend, on average, for each purchase.
- Net promoter score: is similar to CLV in that it helps segment your target market. However, this metric looks at how likely a user is to recommend your brand.
- Of course, I could go on but these are the main KPIs to consider when assessing the performance of your website and social media campaigns. There are additional metrics for other marketing priorities, such as
- the number of backlinks and domain authority to assess your SEO, which greatly impacts many other KPIs
- your quality score for search advertising determines how much you pay for each click and where your ad ranks in search results
- email marketing metrics such as open rates and churn (loss of subscribers over time). We find similar metrics to assess your SMS campaigns.
The key to starting the analysis of marketing intelligence is to create interactive dashboards like the one shown earlier for Google Analytics, which you can customize any way you wish to show KPIs related to your website performance and, when connected, your ad performance (on Google Ads platforms only), and some social media and email marketing analytics. Thus, you create reports from the raw data, accomplishing the first two septs in building insights from your data as shown in the graphic above.
As you can imagine from the large list of KPIs shown above, you must choose a few (10-15) that match your goals and use a tool to create a dashboard that combines data from multiple sources. More on this later.
In contrast to marketing intelligence, which you use daily, market research is designed to address specific problems and starts with a hypothesis about how factors impact your success. In the old days, this meant creating expensive market research studies that required skilled designers and researchers or faced the disaster of making the wrong decision, such as in the Coke research that led to New Coke, now defunct.
Now, I can build custom analyses to address any issue I want using the data provided by my analysis tools. For instance, I might hypothesize that my product appeals to women more than men or that a certain demographic group represents and higher average order value. Below you can see a custom report from Google Analytics to assess visits from different demographic groups. The same analysis might include a better KPI such as conversion rate or AOV.
With market research, we’re entering that next stage in the analysis process shown earlier, the analysis stage. By evaluating the results from our segmentation of the data, for instance, we can gain insights such as whether we need to change our content to attract more visitors that fit with those we currently don’t attract well or focus our content on those we already resonate with.
We can also analyze the data shown in our reports to glean insights, as well. For instance, if we see a particular social media platform sending a lot of traffic to our website, we might decide to drop platforms that underperform or at least spend less on these platforms.
Using tools as a guide to digital marketing analytics
It should be obvious from my earlier discussion that you need tools to help collect data. Some tools also help you analyze the data and Google Analytics professes to provide insights from your data based on their AI but I will tell you the insights generated are pretty anemic, so I wouldn’t stop there. Some tools are available for free, others offer limited free tool features, and others are expensive. I list some of my favorites below.
- Google Analytics: Explores the features and capabilities of the most popular web analytics platform for tracking website performance and user behavior. This tool is free although there’s a paid version (very expensive) that provides more insights. Google Analytics recently introduced a new platform, GA4, which provides more tools to help users understand visits to their website, where they come from, what visitors do, and much more. GA4 is driven by goals and events to provide a more nuanced view of your data, while also integrating with Google Ads, YouTube, and the app store to provide a more well-rounded view of your performance. Learn more here.
- Social media analytics: You’ll find some native analytics tools provided by social media platforms, such as Facebook Insights and Twitter Analytics, to measure engagement, reach, and audience demographics. The best metrics come when using these platforms for advertising and, since organic reach on social media declined over the last few years, advertising is pretty much the only way to succeed on some social media platforms. These tools are free but limited.
- Listening tools: these tools help you manage content on social media platforms such as comments from users and influencers. As far as I know, none of these tools are free and some are fairly expensive. Brandwatch and Sproutsocial are the ones I have some experience with. You can also use some market automation tools for rudimentary social listening, tools such as Hootsuite and Buffer are less expensive alternatives for this task. You can also do market research with your Google Analytics to provide better insights. For instance, multi-channel attribution modeling allows you to assess which channels are involved in conversions when visitors came through several channels on different visits before conversion.
- Email marketing analytics: Most email service providers provide analytics to track open rates, click rates, and conversions from your email campaigns. As with social media, Google Analytics allows you to track conversions from email clicks.
- Heatmap tools: These tools help you gain insights into user behavior and interaction on your website through visual representations, such as heatmaps, scroll maps, and click maps. A heat map, for example, shows where visitors spend the most time on your page.
- A/B testing tools: A/B testing and more involved multivariate testing lets you see which versions of your campaigns perform best. Some tools are baked into the platform, although I’ve had limited success doing A/B testing on Facebook/ Instagram with more than 2 options. Google Ads now has multi-variate testing baked in, which really improves the performance of your search ads. With these tools, you can experiment with different variations of your website or campaign elements like email subject lines, CTA (calls to action), and headlines. Obviously, you want to only test elements that are likely to have a large impact on the campaign’s performance. You’ll also find a bunch of ad graders, like Wordstream. Most of these are free with limited functionality and limits on how much you can use them but they provide a way to help improve your ads.
- CRM and marketing automation platforms: these platforms integrate customer relationship management (CRM) and marketing automation tools to track and analyze customer interactions throughout the buyer’s journey. Salesforce and Hubspot are two of the best-known tools for this but both are fairly expensive.
- Data visualization tools: Like Tableau, these tools transform your data from tables of numbers to graphical elements that really help reduce the workload involved in deriving insights but can obscure your analysis if displayed improperly. The great thing about graphics is that they can capture a bunch of complex data then break it down for easy analysis like in the graphic below.
- Dashboarding tools: these tools bring data from various sources together in one place to make analysis easier, since campaigns often involve efforts across multiple platforms. The one I use is Cognos, which is an IBM dashboarding too.
Digital marketing analytics is a powerful tool that can revolutionize your marketing efforts and I hope this beginner’s guide to digital marketing analytics helped you get a good start on building a more intelligent strategy to improve firm performance. By understanding key metrics and utilizing the right analytics tools, you can make data-driven decisions, optimize campaigns, and drive better results. Remember to set clear goals, track relevant metrics, and consistently analyze your data to stay ahead in the dynamic digital marketing landscape.
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