Businesses today have a lot of data, regardless of whether it is assembled, it is still a lot. Marketing analytics can turn this mess into a strategic advantage. Advanced marketing analytics services use methods like predictive modelling, machine learning, and data mining to go beyond basic reporting and find insights.
Traditional marketing insights show you what happened with your last email campaign and how many people clicked on your latest promotion. Advanced analytics display marketing KPIs and metrics, providing marketing teams with instant and continuous visibility into their performance. Here, we will discuss everything you should know about advanced marketing analytics and its services.
What is Advanced Marketing Analytics
Advanced marketing analytics involves techniques and tools used to extract additional value from their data. It helps to deliver precise customer targeting and adapt quickly to market changes. Companies use advanced marketing data analytics to get more value from campaigns and improve ROI. Advanced marketing analytics services involve everything from describing what happened (descriptive analytics) to predicting what will happen (predictive analytics) and prescribing what to do about it (prescriptive analytics).
Types of Advanced Marketing Analytics
The following are the types of advanced marketing analytics.
1. Regression Analytics
It involves examining and predicting the relationship between outcomes of dependent and independent marketing variables affecting it. Examples of regression marketing applications are:
- Understanding customer behavior
- Sales forecasting
- Website conversion rates
2. Predictive Analytics
It helps to find a solution to the unknown by using various techniques, such as data mining, AI, machine learning, and modelling, to conduct a deep analysis of available data for prediction. In this, previous customer interactions and campaign results are assessed to identify patterns of sales. Examples of marketing include:
- Lead scoring
- Campaign optimization
- SEO and advertising
3. Prescriptive Analytics
It involves assessing past events or recommending specific actions to achieve goals. It is done by using methods like optimization algorithms and simulation to provide guidance for the best marketing channel or personalized email content to increase conversions. Examples of marketing include:
- Channel optimization
- Personalize campaigns
4. Operational Analytics
This type focuses on day-to-day operations and optimize performance and efficiency. It provides immediate insights for immediate action, such as adjusting a social media post time, optimizing an e-commerce layout, or tracking email campaign performance in real-time. For example, performances of:
- Email marketing
- Social media engagement metrics
- Website traffic
Marketing Analytics Techniques
These are the techniques used for marketing analysis:
Marketing Mix Modelling (MMM)
In this technique, statistical methods are used to calculate the impact of various marketing activities on sales. It analyzes past data, including both online and offline marketing spend, along with external factors to measure effectiveness, optimize budget allocation for maximum ROI, and forecast future results.
Marketing Attribution Modelling
It involves giving credit to different touchpoints in a customer’s journey that lead to a conversion, rather than relying on a single click. It helps to build insights, optimize campaigns, and allocate budget more effectively.
Customer Lifetime Value Analysis
It predicts the total revenue a business can expect from a single customer over their entire relationship. In this customer’s past purchases, help to estimate the future earnings and help to make data-driven decisions on retention and marketing strategies.