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Data driven system

Build a data driven marketing system with a combination of four competencies: data collection, predictive analytics, real-time recommendation, and finding innovation opportunities. 

What is Data driven marketing?

Method optimizing marketing performance by predicting behavior and preferences using direct and indirect data from customer interactions

Data driven marketing is a marketing method that optimizes marketing performance by predicting customer behavioral motives, preferences, and future behaviors using data obtained directly through customer interactions and data obtained from third parties.

Data driven marketing ultimately optimizes the performance of all marketing activities of a company and improves customer experience to achieve greater profits.

Analyze internal and external data to continuously improve marketing performance.

Is your brandcontinuously optimizing performance through data driven marketing?

Expected benefits of Data driven marketing

Improvement made by Data driven marketing

Generation MZ customers request personalized content (71%) and are willing to provide personal information for this purpose. Businesses find it difficult to accurately process data and operate them (43%). - Ascend2

6X Annual profit growth
48% CRM adoption in data driven system
67% Speed of campaign deployment
57% Consent to the provision of personal information
Why Data Driven Marketing

Use cases

Data driven marketing understands what happened in marketing in the past and predicts what will happen in the future so that marketing does amplify success or does not repeat the mistakes of the past. It also tracks the performance of ongoing marketing campaigns in real time, helping marketers continuously optimize their campaigns.

Set data driven marketing goal

Set marketing goals such as attracting new customers, increasing sales, increasing profits, improving customer experience and NPS. Based on your goals, determine what data you need. For example, webpage dwell time of target persona, search term-engaged content, social media engagement, lead generation attribution, etc.

 
Data generated from owned channel

Data generated by customer interactions on company-owned media - websites, blogs, emails, chatbots, etc. allows analysis of preferences, behavioral patterns, and motives, rather than using third-party data. Before Google stops providing third-party cookies, you must prepare.

 
Real-time data collection analysis tool

Introduce real-time data collection and analysis tools aligned with the amount and type of possible data in consideration of data insight capabilities. Analyze third-party data by adding interworking between data. 

 
Applications of Predictive Analytics

According to Forrester research, there are three predictive analytics that can help marketers. With the data driven marketing, you can execute those analytics. Prioritize potential customers based on their purchase potential. Identify and acquire prospects similar to existing customers. Deliver personalized messages to potential and existing customers.

 
Correlation and Causality analysis

Utilize big data social listening to understand correlation patterns and use them to predict behavior. Find causality for improvement prescription. For example, immediately after a specific behavior occurs, direct and quick investigation - a quick poll of about 3 questions, etc. is used.

 
Marketing Attribution analysis

If you are marketing using multiple campaigns and channels, you need to analyze which campaigns and channels are contributing to your sales so you can justify your investment and uncover additional opportunities. In the current marketing environment, it is necessary to analyze the contribution factor considering the customer purchasing journey and personalization. Leverage ABM Attribution, Cross-Channel Attribution, Lead Attribution, and more.

 

Seize the opportunity for digital growth

Data driven marketing process

Provides systematic steps for data driven marketing.

1
Build data driven marketing tools

Tools that can implement data marketing - Behavior-based CRM, digital product usage analysis tool, marketing attribution analysis tool, online survey tool, automated messaging tool, etc. are considered.

2
Building data literacy and data collaboration Create processes and principles for collaboration based on data between marketing team, advertising agency, data analysis team, and IT team. Securing performance-oriented capabilities through collaboration based on data storytelling and data understanding.
3
Set data driven marketing goals and KPI Set up analysis goals and KPIs for data driven marketing and conduct workshops with historical data and competitive data. Establish KPI from benchmarking and heuristic evaluation. Build analytics dashboard.
4
Data collection

Secure customer engagement data by using indirect collection methods such as social listening and advertising networks. Direct collection methods such as website cookies, form submission, e-mail behavior, push message, and chatbots are used to secure data and store it in own database/CRM.

5
Data analysis

Analyze performance by KPI and derive analysis insights. It identifies functions used by customers or content that customers engage in, characteristics and motives of customers responding to them, points where customers are having difficulties in their purchasing journey, and channels-content-search words that induce sales.

6
Data driven optimization

Optimize by applying the analyzed contents such as campaign target, content, customer flow, etc. by integrating campaign automation tool, content management system, and real-time messaging tools.

Data marketing system establishment

Data-driven optimization to enhance personalized experiences

Deploy marketing that continuously optimizes by collecting and analyzing data.
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Continuously optimized performance driven by data

Build data collection and analysis tools, implement strategic intuitive data analysis, and save marketing costs and increase performance through automated optimization activities.

 

52%

Customers are willing to change the brand if the company fails to provide personalized communication

63% 

Growing investment  on Data Marketing in 2020