12 Behavioral Data Types: Building Truly Data-Driven Marketing?

“Hello there! We’re back with Data Content from Data Club, just like before. This Monday, we’ll introduce you to 12 Behavioral Data Types that help marketers gain better Customer Insight, paving the way for true Data-Driven Marketing. Let’s dive in! Source: everydaymarketing.com

What Is Behavioral Data? Behavioral Data is information about actions taken by customers in real-life scenarios. It’s obtained from features customers interact with, such as A/B Testing, rather than observations or surveys. This data provides genuine insights and is ideal for further analysis. What Types of Behavioral Data Are There?

1. Website Analytics Data

Website usage data, if you have your own page or website, you must have tools like Google Analytics to analyze consumer website usage, such as the number of people who come to read, the time they read, the number of pages they read, the time they use, mouse clicks, or even web browser and internet networks used.

 

2. App Analytics Data or User Journey

Application usage data is different from website usage data in that it focuses more on the user journey to see what makes customers use our app more or stop using it. For example, Netflix once tried to give new users a free 1-month trial, with and without credit card information. The results were very different. The version without card information had more users, but fewer actual customers. This data is very beneficial for future marketing strategy planning. Recommended User Journey Tracking Tools: Mixpanel, Amplitude, KISSmetrics focus on what happens in the app.

 

3. Search Data

You can see what people want to know or search for on web browsers using tools like Google Trends, Ubersuggest, Keywordtool.io, and more.

 

4. Ad Clicks Data

Advertising on various social media platforms also requires tracking engagement to see how much our target audience sees our ads, how many clicks, what they do next, and which of our ads actually lead to product purchases. Customer clicks on ads provide valuable data for planning future advertising investments and marketing strategies.

 

5. Review Data

Information about product and service reviews that anyone can read, and every review, whether good or bad, is real behavioral data (even though some may be paid!). It may be a bit difficult to use because it is textual data, not numerical data, but it is very useful data.

 

6. Customer Feedback Data

Customer feedback data is different from review data in that it is data directly from customers to the company. When you receive data, you must analyze the context to find the root cause of that feedback. For example, a bank received feedback that its app was difficult to use. When looking deeper into the feedback, it was found that most of it came from baby boomers who were not tech-savvy and preferred to visit the bank in person rather than use the app.

 

7. Social Media Data

Likes, comments, shares, or emoji clicks are all behavioral data that occur on social media. To access data on these social media platforms, tools are needed to monitor trends and process data into useful information, such as Social Listening Tools like Zanroo, Wisesight, Real Smart, Melt Water, Talk Walker, and Mandala, among others. When used continuously, you will find new trends and opportunities that are unexpected. Year after year, you will find new and interesting trends or things you have never heard of before. For example, in 2020, people in Thailand wanted green spaces to relax in condos. But in 2021, the trend for green spaces wasn’t just for relaxation but also for growing edible plants.

 

8. Cursor Tracking

Tracking mouse movements to see where website users tend to place their mouse or click on the screen. If customers keep their mouse hovering or clicking on the buy button or share button but don’t actually click it, it may be because the headline is well thought out, but the content at the end may make customers hesitate to share.

 

9. Eye Tracking

Eye tracking data is similar to cursor tracking but uses the user’s gaze on the screen instead of the mouse. It helps determine what users are looking at on the screen, how long they look, and the direction of their gaze. This provides even more precise behavioral data, although it requires the installation of gaze-detecting devices suitable for vending machines or advertising signs.

 

10. Offline Data

Real-world data, not just online data, includes counting the number of people entering and exiting shopping malls each day using AI-powered closed-circuit cameras to prevent double counting. Or identifying who is a rider wearing a green jacket, orange jacket, or mall employees wearing a specific uniform, and not counting or counting separately.

 

11. Facial Expression Analysis

ข้อมูลความรู้สึกบนใบหน้า อันนี้ล้ำยิ่งกว่า Eye Tracking มาก เพราะไม่ได้จับแค่ดวงตาแต่จับทั้งหน้า ว่าผู้ใช้งานกำลังแสดงสีหน้าแบบไหนหรือรู้สึกอย่างไรตอนใช้งานผลิตภัณฑ์หรือมองป้ายโฆษณาของเรา โดยกล้องที่จับใบหน้ามี AI ที่ฉลาดสุด ๆ คอยตรวจจับกล้ามเนื้อบนใบหน้าและตีความออกมาเป็นความรู้สึกต่าง ๆ แต่ก็ยังไม่ค่อยแม่นยำเพราะบางครั้งสีหน้าก็ไม่ได้แสดงอารมณ์ความรู้สึกที่แท้จริงของมนุษย์

 

12. Transaction Data

ข้อมูลพฤติกรรมการซื้อ อีกหนึ่ง Behavioral Data ที่สำคัญและเข้าถึงง่ายที่สุด ว่าลูกค้ากลุ่มไหนชอบซื้ออะไร มีนิสัยการซื้อเป็นอย่างไร ช่วงเวลาไหน ช่องทางไหน จ่ายเงินอย่างไร และถ้ายิ่งมีการซื้อซ้ำ ยิ่งสะท้อนได้ว่าลูกค้าคนนั้นต้องชอบสิ่งนั้นมาก ๆ เมื่อเอาข้อมูลพฤติกรรมการซื้อมา Analytics ในหลายๆ แง่มุม จะยิ่งเข้าใจ Customer Insight ลึกขึ้นอีก

 

จบไปแล้วกับ Behavioral Data ทั้ง 12 ประเภท อ่านจนตาล้ากันเลยทีเดียวค่ะ? แต่ทุกประเภทล้วนเป็นข้อมูลที่อยู่รอบตัวเรา อยู่ที่เราจะนำมาประยุกต์ใช้อย่างไร และจะใช้เครื่องมืออะไรเพื่อเข้าถึงข้อมูลเหล่านั้นนั่นเองค่ะ หวังว่าคอนเท้นต์นี้จะเป็นประโยชน์สำหรับทุกท่านที่กำลังวางแผนจะนำข้อมูลไปใช้ประโยชน์ในการทำงานนะคะ มาร่วมสร้าง Data-Driven Organization กันค่ะ❤️