new era business that the marketing strategy Need to be driven by data (Data-driven Marketing) because data is what makes us understand customers better. both finding the preferences and needs of customers more clearly Make promotions or campaigns for customers to use our products and services continuously. But businesses that don’t have full access to data still have questions. If a business starts data-driven marketing How should I start?
Mr. Phiphat Praphaphanpong Director and Team Leader of Big Data and Advanced Analytics, Bluebik Group Plc., recommends that businesses around the world turn their focus and focus on data storage and analytics investments to unlock limitations and increase their potential. Growing for profit by doing Data-driven Marketing is one of the marketing tools that will help offer products and services to customers to meet their needs exactly.
Doing Data Driven Marketing involves the process of storing data. Analyze and synthesize data in order to understand the needs of customers in all dimensions. Therefore, before marketers begin to act to drive Data-driven Marketing Succeed and create real results. Therefore, you should know and understand these 4 things.
Business Objectives
Marketers should clearly define what goals they would like to use the results of the analytics for, such as expanding their customer base. Setting clear goals is the first priority that will help determine success. Data-driven Marketing by defining the scope of data analysis that should be carried out at any point the business will achieve its goals.
Once the business goals are clear The next step is to think of use cases (Use Case Generation), which differ according to the type of business and business environment. Including the need to choose use cases that suit the goals of the business.
- Mainly aimed at increasing the efficiency of business operations. by encouraging customers to return to buy products and services regularly to maintain income, such as recommending other related products (Cross-Selling) to increase income that is more than buying a single product or recommending products or services that match the interests of each customer at the right time (Personalized Promotions/Products) etc.
- Mainly focusing on improving the customer experience by giving customers a good experience and keeping customers buying products and services continuously, such as grouping customers (Customer Segmentation) Calculating the purchase value of goods and services over the life of the customer (Customer Lifetime Value) to consider giving special privileges to customers who generate high income for the company, etc.
After thinking of the basic use case The next question is how do businesses know which use cases to actually generate business results? Therefore, there must be a procedure called evaluation and selection of appropriate use cases (Use case prioritization), which can be divided into 2 axes of evaluation:
- Business Impact such as generating financial results Increasing business opportunities, return on investment (ROI) and suitability in line with overall corporate strategy.
- business readiness (Feasibility) such as the availability of information readiness of the system or work process This includes external factors such as PDPA, laws and regulations.
Data Readiness
When it comes to data-driven marketing, it’s important to information Therefore, businesses must explore and evaluate various information. in the organization how the quality of the information is Is there enough data for analysis? and what kind of information
Today, data has a more diverse form than in the past, which can roughly be divided into 3 types of data:
- unstructured data (Unstructured Data) such as images, videos, audio files.
- semi-structured data (Semi-structured Data), such as XML (Extensible Markup Language) format files.
- Structured data such as tables in a database.
Therefore, using data to design a use case will really help create an advantage for the business. Therefore, businesses should look back.
channels for obtaining information that the information has been gathered, from which source, and which parts are still missing and how to use that information, such as collecting customer behavior data using game principles to make campaigns (gamification campaign) to create interactions with customers Increasing the use of a CRM system to help collect customer data more efficiently, or adopting a Centralized Data Lake/Data warehouse to help collect data from multiple sources, etc.
Design and Development of Data Analysis Models
Before starting to design a data analysis model Businesses should first look at what they want to know and why to choose the right data analysis model. Basically, data analysis can be divided into 4 forms as follows:
- Descriptive Analytics is the analysis of past events such as sales data, behavior of customers who have bought products, etc.
- Diagnostic Analytics is to find out the causes of what is happening and what factors are causing it. by analyzing correlation (Correlation Analysis), for example, why did sales increase? Up because of a promotional campaign or not.
- Predictive Analytics Predicting trends that are likely to occur in the future. by analyzing data from the past
- Guided Analysis (Prescriptive Analytics) is an analysis to predict what should be done in the future.
for the process of developing a data analysis model It should be done after the business has a clear goal, choose a use case, and have all the necessary information ready.
- Creating a feature for use in the data analysis process (Feature Engineering)
- Bringing the built features into the learning process (Model Training) to find patterns (Pattern) of data to gain insights (Insight) that can be further developed and applied in business.
- Model Evaluation through various tests such as Confusion Matrix, F1 Score, AUC – ROC.
- Parameter adjustment to optimize model (Model Optimization)
Turning Insights into Business Results (Execution)
Before designing a marketing campaign Businesses should outline the elements of their campaign, such as who is their target audience. What do you want to offer to customers? And how will businesses connect with their customers? After that, use the insights acquired to design a campaign format. There are basic guidelines that can be applied as follows:
- Attracting target customers: for example, the purchasing behavior of each group of customers. It is obtained by analyzing customer segmentation and forecasting the revenue that a business will receive over the course of each customer’s purchase of goods and services (CLV) to see which customer groups should be campaigned. special Customers with high CLV may focus on sending promotional news regularly. Groups with lower CLVs may offer discounts or giveaway promotions. to encourage additional purchases, etc.
- Finding out what products and services should be offered: Using data to create personalized promotions that are tailored to each customer’s needs, such as offering a baby discount coupon for pregnant women.
- Use of communication channels that reach the most customers: Due to the fact that consumers have a variety of shopping channels nowadays, Once a business can collect data from various channels, it can be analyzed to see which channels are used by customers the most. To see which content and campaigns on which channels get the best response. and then to focus on marketing to customers through that channel
In summary, making Data-driven Marketing successful is must start with setting business goals strategy Assess information readiness design and develop analytical models and turn insights into business results. For effective marketing through data and create long-term business growth
