Fundamentals of Digital Analytics: How to Make Data-driven Decisions

You can use data to make educated and objective decisions based on data-driven decisions. There is no marketing strategy without quality analytics and data. Is there an alternative to data-driven decision-making? An alternative might be to make assumptions and make emotional decisions. You can get lucky several times, but in the long term, you don’t stand a chance to make the best possible decisions in real-time. 

 What is data-driven decision-making?

Data-driven decision-making has become a crucial aspect of business success. Marketers can analyze customer behavior and interests to effectively segment their audience and deliver personalized messages and offers by utilizing digital analytics tools. A/B testing enables us to determine what performs better based on data-driven metrics, while conversion rate optimization aims to improve the likelihood of conversions by identifying and addressing pain points in the conversion funnel. 
Additionally, analyzing content engagement metrics helps marketers to develop a targeted content strategy that resonates with their audience. Keyword optimization assists in improving website visibility in search engine results. With the help of predictive analytics, marketers can also anticipate future trends and behaviors, allowing for the customization of campaigns to meet anticipated customer needs. 
Finally, attribution modeling helps allocate resources effectively across various channels by analyzing the contribution of different touchpoints in the customer journey. With these powerful tools at their disposal, data-driven decision-making has become indispensable for businesses looking to thrive in the modern market.

Data-Analysis

Where to find digital analytics data?

We rely on online data when we want to analyze data for making business decisions. The first tool to use is Google Analytics or similar software that will give us a big idea of the overall situation. Google Analytics is a great all-rounder tool that shows us user behavior in three phases on a website for all acquisition channels. ABC phases of Google Analytics are acquisition, behavior, and conversions. 

Google Analytics

The acquisition channel report shows how people have decided to visit our website. The most frequent acquisition channels are paid search, organic search, and direct traffic. Among others are social, referral, display, and email. 
Interpreting user behavior on a website might be the trickiest part of analysis. It’s much easier if we have mapped the customer journey in advance, so we can measure and compare expectations with aggregated behavior. 
The conversion part of Analytics is always the most important to business owners. It answers the question, “Where is the money?”. If we reverse engineer the process from conversions to acquisition, we have a good overview of what part of marketing investment made a return on investment.
The most used alternatives to Google Analytics are Adobe Analytics, Matomo, Piwik, and Plausible. Different overall website analytics software types are Hotjar, Clarity, Crazy Egg, VWO, and Mouseflow, often used for heatmaps, screen recording, and funnels. 

Google Search Console

Google Search Console, previously known as Google Webmaster Tools, is a tool that gives us much information about organic traffic. There are some great tools for various analyses suitable for search engine optimization, like Semrush, Ahrefs, Moz, Screaming Frog, and similar. A huge difference between Google Search Console and all others is that GSC shows the actual numbers of your website. 
What is the difference between Google Analytics and Google Search Console? GA4 will show you much more than just organic traffic, and organic traffic will show you the impact that it made on business. However, when you want to dive deep and understand better what keywords made organic traffic and the technical aspects of your results, GSC is a tool for you. 

Advertising platforms

Google Ads and Facebook Business Manager are the most used advertising tools. They provide very insightful data about ad performance, from impressions to conversions. While core metrics are visible in Google Analytics, you can’t judge advertising potential or understand advertising setup, funnel, and more details before diving deep into advertising platforms.

Social Media platforms

There are more social media platforms that people usually think of. LinkedIn, Facebook, Instagram, and TikTok are the most obvious social media platforms, but YouTube, Reddit, Pinterest, Quora, and TripAdvisor are social media platforms.   
Google Analytics can measure social media only when someone from social media clicks an outbound link and comes to our website. This is a great feature, but social media is much more than just that. One of the most important metrics of any social media is daily time within the media. That means that each social media KPI is to try to discourage people from leaving it to go on our website. There are multiple metrics that we can track and should consider while people use social media. 

How to do data-driven decision-making?

Audience Segmentation

Marketers can effectively segment their audience and deliver personalized messages and offers if they understand their target audience. Analyzing customer demographics, behaviors, and interests is a crucial step in data-driven decision-making for marketers. 
This segmentation allows them to tailor marketing strategies to specific groups, increasing the likelihood of engaging with the audience on a deeper level. Marketers can understand insights by using data-driven analytics. Customer preferences and behaviors are also visible, enabling them to create targeted campaigns that resonate with the audience.
There is no effective alternative to use data-driven decision-making in audience segmentation. Otherwise, we could only assume audience segments, leading to much bigger problems. 

A/B Testing

A/B testing is a powerful tool in data-driven decision-making for marketers. By running A/B tests on different versions of marketing materials, such as website, email subject lines or ad copies, marketers can determine which version performs better based on data-driven metrics.
This testing allows them to understand what resonates with their audience and make informed decisions about their marketing strategies. By analyzing the results of A/B tests, marketers can refine their messaging, optimize their campaigns, and ultimately improve their overall marketing performance.

Conversion Rate Optimization (CRO)

Conversion Rate Optimization (CRO) is a key aspect of data-driven decision-making. Marketers can identify pain points in the conversion funnel and make improvements to increase the likelihood of conversions.
It’s possible to gain insights through data analysis into where customers are dropping off in the conversion process and take targeted actions to optimize the user experience. We can make data-driven decisions to improve conversion rates, ultimately driving higher levels of success for their businesses by constantly monitoring and analyzing conversion data.

Predictive Analytics

Predictive analytics is a valuable tool in data-driven decision-making for marketers. By using historical data, marketers can predict future trends and behaviors, enabling them to tailor their campaigns to anticipated customer needs. By analyzing past customer behavior, marketers can identify patterns and make predictions about future consumer trends.
This knowledge allows them to proactively develop strategies that resonate with their audience and meet their evolving preferences. By leveraging predictive analytics, marketers can stay ahead of the curve and drive successful marketing campaigns that result in higher levels of customer satisfaction and conversion rates.

Attribution Modeling

Would you like to know which part of marketing investment made a return on investment? Benefits of attribution modeling are clear. There is no perfect attribution model and it’s impossible to measure 100% precisely, but attribution models are efficient enough to be an important aspect of data-driven decision-making for marketers. 
By analyzing the contribution of different touchpoints in the customer journey, marketers can allocate resources effectively across various channels. This analysis enables marketers to understand the impact of each touchpoint on the overall customer experience and conversion process. 
Marketers can make informed decisions regarding the distribution of their marketing budget and resources by attributing value to each touchpoint. Within Google Ads platform, attribution models are: data-driven, last-click, first-click, linear, time decay and position based.
Any multi touch model is better than standard last click attribution. Data-driven attribution modeling provides marketers with a holistic view of their marketing efforts and helps them optimize their strategies for maximum impact.

Data-Driven Decisions

How to use digital analytics for data-driven decision-making?

Making data-driven decisions without digital analytics would be impossible. To be able to make good analysis crucial is to have relevant data. Data has to be accurate and meaningful. We need to understand what we collect, and why we collect it and it is best to have in advance defined measurement protocol where we will understand what to do for any metric going under or above defined values. Analytics job in advance is to set up tracking codes, pixels, tags, and events. 
To be able to do all that, the best scenario is to start with defining clear objectives. Running a digital business seems to be easy as there are only two things to do: you need to acquire relevant people to your website and then convert them. However, there are 7 ways to get people to your website and for each of them, you can have a different set of metrics. Once they are on your website, you don’t want them to drop immediately.
So that you get them to convert on your website, your responsibility is to give them the content they expect in the order they expect. That means that you need to have a deep understanding of your target audience and their customer journey. 

Benefits of Data-Driven Decision Making

How to do it if you are not sure that you know your audience well? Create a customer journey map as best you can, measure user behavior and where you see drop-offs bigger than expected and what the industry standard is, analyze what went wrong, and change that section. That’s called data-driven decision-making.
An alternative might be to arrange a big meeting, call as many highly paid officers, and brainstorm what could be the issue. Most sentences will begin with “I think that problem might be this”. Then you make a list of suggestions, starting from ideas of the most important person in the room, and start making random changes on the website while eventually you have enough luck or the project fully fails. You don’t want that scenario, do you?
If you have 10-15 metrics on average from 7 acquisition channels and additional 10-25 metrics about the website, the next step will be to define what are key performance indicators. If you are trying to keep up with 100 metrics, none of them is key. 
There have to be different reports based on who will read them and what is expected from the person to do with that report. The CEO shouldn’t go into details about what ad creative brought more conversions or which CTA on the landing page made more conversions. There should also be a different set of reports based on whether it’s daily, weekly, monthly, quarterly, or yearly. 
Quality measurement protocol will have a defined column on what to do with each metric in case it’s too low or too high. If your project hits a major crisis, there will be informational overload, and during a shitstorm, it’s almost impossible to have a clear vision of what to do. In situations like this, you want to have a previously prepared document “for dummies”. 
Another huge advantage of a customer journey map is that it will have anywhere between 5 and 100 steps. Again, what is an alternative? I have seen it dozens of times: people invest money in advertising just like they pay in the lottery.
They pay and hope they will succeed. Input is cash, outcome is 0 or 1. If they win – major happiness, but the problem is if the result is bad. They can’t know what exactly to do, so they randomly choose any details, change them, and start over. 
If you have a map with benchmark drop-offs, you will be able to see on each step how effective you are in comparison to the industry. Furthermore, you will come to the point where the customer journey map breaks. There is no more only input-outcome, there are 100 steps in between. Can you fail multiple times? Of course! There is a possibility to fail on each of those steps several times. But, once you nail it, you are sure that you won’t come back to that point again. The process is predictable. 

Conclusion

Data-driven decision-making is a crucial aspect of modern marketing strategies. It allows marketers to gain valuable insights into their audience’s preferences, behaviors, and needs. By leveraging data analytics, marketers can make informed decisions, optimize their marketing efforts, and drive higher levels of success for their businesses.
Whether it’s through audience segmentation, A/B testing, conversion rate optimization, content strategy analysis, keyword optimization, predictive analytics, or attribution modeling, data-driven decision-making empowers marketers to connect with their audience in a meaningful and impactful way. So embrace the power of data, and let it guide you towards marketing success!