If you can’t answer any of these questions yet, don’t worry. Customer insights like these are “archaeological finds” that you need to mine with automated data analytics. In this guide, we’ll show you how.
As you read this, 52% of B2C companies and 25% of B2B companies already rely on customer data to guide marketing decisions.
So let us get you ready with everything you need to turn your customer data into actionable insights and business growth.
What is customer data analytics?
Customer data analytics refers to the methods and technologies used to collect argentina phone number resource structure and interpret customer information in real time.
These could be:
Web traffic data
Transactional data
Information about product/service usage
Behavioral patterns
Feedback data etc.
From the definition, you can distinguish three main tasks of customer analytics:
Task #1. Collection → capture raw data from various sources (CRM system, social media platforms, email, website, etc.)
Task #2. Structure → classify customer details and organize them into pieces for further interpretation
Task #3. Interpret → gain customer insights and make informed decisions.
The importance of data analytics in driving customer success
If the nineteenth century was about the gold rush, the twenty-first century is about the “data rush.” Literally every business is after customer data and the invaluable insights it can glean. 84% of customer service leaders say data analytics are critical to their business goals.
So why all this fuss, you ask?
Because no one can deny the incredible benefits of customer data analytics. Discover them all below.
Visualized customer journeys
Real-time data analysis allows you to see every step your customers take during their purchasing journey, allowing you to examine all layers of the customer journey, such as:
Stages (awareness, consideration, conversion, purchase and loyalty)
Steps (browse, click on promotion, add to cart, etc.)
Touchpoints (landing page, chatbot, newsletter, and others)
Departments (marketing, inventory management, logistics, customer support, etc.)
Customer journey mapping with data analytics and customer insights - BrightVessel
Source: Brightvessel.com
By mapping the customer journey in this way, you can identify every pain point and eliminate roadblocks.
Identifying trends in customer behavior
One of the key benefits of data analytics is predicting customer behavior based on the details collected. With predictive analytics, you can see how your customers tend to behave and what actions you can expect from them.
For example, one of today’s consumer behavior trends is the increasing demand for sustainable products: 66% of customers put sustainability first when making a purchase. Recognizing this trend in your target audience, you can make sustainable products more visible to web visitors by displaying them directly on the homepage of your e-commerce website or highlight sustainable packaging as your top priority.
Personalized marketing strategies
Personalization is key to customer satisfaction because consumers want it from brands. In fact, 71% of shoppers expect companies to deliver a personalized experience, and 76% are disappointed when they don’t get it.
This is where data analytics becomes a game-changer. It helps you uncover all customer needs and demands to personalize customer experiences with tailored marketing campaigns . It’s like you’re feeling the pulse of your customer and ensuring your promotional messages resonate with them.
Higher customer loyalty
Who doesn't dream of reducing customer churn and retaining customers forever?
This is possible if you use data analytics and the customer insights gained from it.
This way, you can even turn your customers into lifelong fans. How exactly? By choosing the most effective retention strategies for each customer based on their likes/dislikes, personality traits, values, lifestyle choices, etc. For example, you can diversify the rewards list in your loyalty program and offer the most desired benefits based on your customer’s interests.
Improved SEO
Once you gain customer insights, you can significantly improve your SEO efforts. Knowing your user intent and search intent will help you:
Smoother website browsing
Keyword-fueled homepage
High converting blog posts
Optimized product descriptions
Geo-targeting
Regarding the latter, it opens the doors to local SEO . Imagine this. Your customer data analysis shows that you are not reaching your local audience. Your web traffic is geographically dispersed. In this case, you can start optimizing for local searches and get targeted traffic and leads.
Increased sales and revenue
With customer insights extracted, your marketing and sales teams are empowered to push the right buttons and grow your business. Your marketers will know what works best for lead generation to generate more qualified leads and convert them into buyers. Meanwhile, your salespeople will be able to develop a personalized approach to selling products or services to deliver great customer experiences.
In addition, here’s a fact worth sharing: Companies that use customer data analytics extensively outperform their competitors by 131% in sales and 126% in profits .
6 tips for using automated data analytics for customer insights
Below, we'll cover the most important things to keep in mind if you want to excel at customer data analysis.
Turn to AI-powered data analysis tools
The rise of artificial intelligence (AI) has brought about new business opportunities and has truly reshaped the way brands manage customer data.
Manual data analysis takes a lot of time and effort. Forget about the mistakes we tend to make as humans. On the contrary, AI tools for data analysis provide faster and more cost-effective solutions. They also provide error-free reports for data-driven decisions by examining customer insights more accurately and comprehensively.
Here is a list of AI-based tools that perform customer data analysis automatically:
AccuRanker: to determine search intent
UserIQ: to calculate user health score and track in-app activity
ChurnZero: to generate customer briefs and ideas to reduce customer churn
Hotjar: To visualize buyer journeys
MonkeyLearn: to perform sentiment analysis
Treasure Data: to synchronize data from all touchpoints into a unified customer profile
Thanks to predictive analytics algorithms, AI easily detects correlations and trends in customer behavior that are often unnoticeable to the human eye.
Ensure data privacy and cybersecurity
According to IBM , 44% of data breaches during the pandemic leaked consumer information (names, passwords, emails, and even health records). A recent study suggests that 95% of organizations will experience at least one data breach by 2023.
When cybersecurity risks are so great, you should be very careful when collecting individual customer information for further data analysis.
First of all, it is essential to comply with regulations such as the General Data Protection Regulation (GDPR) in the European Union or the Privacy Act in the United States. It would also be useful to clarify the local data privacy laws in force in 13 US states.
On another note, you may need to reconsider your cybersecurity measures for greater consumer data protection :
Develop a transparent privacy policy and obtain explicit consent from individuals before processing their information
Encrypt sensitive data
Using web server firewalls and intrusion detection systems
Setting up multi-factor authentication
Conduct cybersecurity awareness training for employees
Design a cyber incident response plan
Only 5% of companies implement all practices and policies for the security and privacy of customer data.
What about your company?
To start, you should revisit your privacy policy and outline all third parties that have access to your customer information. Also, make sure you display a GDPR cookie consent message on your website with clear options to accept, decline, or customize cookie settings.
For example, check out this post from s360 .
Customer data analytics - s360
Source: s360digital.com
Take a multi-channel approach to data analysis
To get a more holistic view of your target audience and create a solid digital marketing plan, you should gather customer insights from different channels. The first three are your website, social media, and email.
Website
With website data analytics, you can delve deeper into user data like overall traffic, unique page visits, content interactions, etc. For example, you can gather rich user insights from a heatmap or an A/B test.
Let’s say you want to drive more leads into your sales funnel, but they’re not coming in. You may not even realize it, but obvious mistakes in CTA design are hurting your conversions. You can run A/B testing and see which CTAs are more effective at attracting leads.
Tools for website data analysis: Google Analytics 4 (aka GA4) – for traffic and engagement, AB Tasty – for A/B testing, Mouseflow – for heatmaps
Social media
Social media data analytics will give you in-depth insight into customer engagement with your posts and ads.