eBusiness Weekly
Phillip Jonhera
Whenever a company implements an effective digital strategy and starts to apply digital marketing as a method of marketing, this means that the company is then exposed to larger amounts of data being collected by various methods.
This data analytics has become an important factor in digital marketing and it measures the value of every customer action and touch point across multiple channels and devices.
Digital marketers must, therefore, make their decisions based on data, using advanced analytic tools to evaluate digital marketing campaigns at every step of the customer experience.
The future of digital strategy belongs to those who know how to use these sophisticated tools to gain valuable marketing insights.
In this article, we take a deep dive into data analytics in digital marketing — what it is, where the data comes from and how it can be used to make digital marketing campaigns more successful.
Data analytics in digital marketing — What is it?
In marketing, data analytics is the practice of gathering and analysing data, from various digital sources to gain actionable insights into a company’s digital marketing strategies.
Digital marketing analytics tools can be used to inspire new approaches, minimise churn rate (when customers stop interacting with a company) and increase existing customer value by creating a personalised experience.
Since the end of the pandemic, study shows that businesses must view data and analytics as essential for their digital transformation and growth. However, only a few have a clear strategy and an understanding of data analytics.
Data analytics helps businesses be more efficient, by removing the guesswork from marketing strategy and generating optimal value from a company’s marketing budget.
There are three models of marketing analytics
To plan, manage and optimise marketing campaigns, there are three models professional marketers use as analytic models.
Descriptive: Historical data is collected from earlier campaigns, and this information is used to provide insight to help plan strategies for future campaigns.
Predictive: These data analytics models use insights from prior marketing campaigns to try to predict customers’ behaviour so that the company can develop a better-informed, more targeted campaign.
Prescriptive: These models gather data from all available touchpoints, analysing the impact of each company initiative and customer interaction, to help the organisation create highly targeted campaigns that influence customer behaviour.
Together, these analytic models form a complete picture of the effectiveness of marketing campaigns and how each company can achieve its desired results more efficiently.
Where does the data come from?
The raw data for digital analytics comes from many different sources, and it can be overwhelming if a company lacks the in-house expertise to use it effectively. Information about customer interactions can come from:
Website data (tracking)
Product data (most/least liked features, conversion events, areas of friction)
Digital marketing data (keyword analysis, social media interactions)
Internal customer data (accounts, transactions, complaints)
It is now possible to gather this type of data in real time, without direct customer contact.
How marketing analytics is used
Marketers use data analytics to make sense of a large amount of customer data, using these insights to guide their product strategy, brand and marketing campaigns.
Using sophisticated data analytics techniques, companies can better understand their market and customers, which can lead to effective digital marketing tactics, more personalised customer interactions, greater customer satisfaction, higher efficiency and bigger profits.
Compile comprehensive customer profiles
Bringing together data from various sources lets you see the complete user journey in one place. For example, you can see how customers arrived at your website (ad, social media, etc.). You can also see all their events and actions, such as inquiries or product purchases.
Data analytics can show you the entire customer lifecycle, from an unmet need and awareness of your products or services, to interaction with your company, to purchase and engagement.
These same customers may even go on to become product/company advocates, sharing their experience with potential new customers.
Align product performance with customer expectations
With actionable data, your company marketing team can secure better results by more effectively aligning marketing campaigns and product features with customer expectations. This can minimise the churn rate.
Understand customer behaviour
To acquire customers, you must be able to understand and predict customer behaviour patterns so that you can adjust your marketing and advertising campaigns to respond to their needs.
For example, mail marketing platforms let you track subscribers to see what they are responding to, including social media sharing and likes.
Greater customer engagement leads to increased sales.
Develop new product features, new strategies and new revenue streams
With current data about consumer preferences, a company can more safely experiment with customer acquisition. It might create a new marketing strategy, enhance product features or develop an entirely new product, based on what the data says about customer needs.
This could also pave the way for new revenue streams.
Create targeted personalisation
A Google marketing survey found that 90 percent of professional marketers attributed personalised marketing to greater business profits.
Marketing analytics gives you the detailed information you need about customers to create highly targeted materials. Analytics software can predict and determine what consumers want — which also leads to a better customer experience —based on their profiles, purchase histories and browsing behaviours.
Monitor campaign performance
Using the right analytics tools lets you track your marketing campaign performance in real-time, which helps your company to be nimbler at refining strategies and optimising campaigns.
This is especially important for paid marketing initiatives because it helps you maximise your ad spend.
In this way, marketing campaigns can be directly tied to important metrics such as your company’s website traffic and you can see the impact that various marketing channels used (web, mobile, social media, etc.) have on customer behaviour.
This can then inform future strategies and improve efficiency. Return on investment (ROI) is key in the marketing industry. Marketing analytics ties a company’s marketing initiatives to ROI, validating its marketing budget.
Forecast demand
By using timely data and examining historical records, you can recognise patterns and trends and anticipate demand for products and services.
Predictive analytics gives a company the power to see the future, which can be extremely helpful, especially when a business is on a tight budget.
Data analytics in digital marketing gives your organisation a competitive advantage. With it, you can better understand not just your business and customers, but the environment that surrounds them.
You can use the insights to design marketing strategies, attract new customers, keep existing customers, discover which marketing campaigns are under-performing and focus on your most successful products.
You can also use web analytics tools to gather information about competitors, which keeps your company up to date on the market so you can prepare for future challenges and adjust campaigns to be attuned to market sentiment.
Marketing analytics — What skills do you need?
When it comes to data analytics in digital marketing, there is a lot to know. To be successful in digital marketing analytics yourself, you will certainly need statistical analysis and data visualisation skills, and also creative skills such as copy-writing, content strategy and storytelling, to communicate your findings effectively.
You should also be proficient with data analytics tools such as Google Analytics for websites and Semrush for campaign analytics. These tools collect metrics that include website traffic, customer retention rates, cost-per-clicks, conversion rates, sales revenue, social engagement and more.
Knowing how to make sense of all this data requires these specialised skills; having this insight can greatly enhance a company’s bottom line.
Phillip Jonhera is a creative digital marketer and brand identity specialist. He is also a founder of Nova Digital.
