Stop guessing, start knowing: Unleash the power of customer insights in marketing
Our world revolves around customer data. As enterprise marketers, we juggle a million customer metrics: cost per acquisition (CAC), customer lifetime value (CLTV), open rates, click-through rates (CTRs) — the whole alphabet soup.
We launch campaigns and analyze metrics for every single campaign on every channel while running analytics on the past quarter or researching new marketing trends. Without the right tools and the right customer data in place, it's hard to turn that data into actionable customer insights that drive real results.
That’s where a Customer Data Platform (CDP) comes in. A CDP is like your personal translator, taking scattered customer information from your cloud data platform and centralizing it into a cohesive view of your customers.
When all of your customer data is consolidated in one place, you can collect valuable customer insights and track trends in behavior and engagement across your entire customer base — and the entire customer journey.
The results? An improved marketing strategy using real-time customer data to create personalized marketing content based on each customer’s interaction with your brand leads to improved metrics and ROI.
Let’s dive into some key customer marketing metrics you should track and how a CDP supercharges your ability to measure and understand them.
How customer insights in a CDP lead to personalized marketing
Ever wished you could see into the future and know what your customers need before they even do? With customer insights from a CDP, it’s possible. A CDP has AI functionality that lets you analyze and understand your customer base in new ways.
For one, it powers predictive analytics, which uses historical data to anticipate customer behavior and potential churn. This lets you proactively engage customers with relevant content and offers, fostering stronger relationships and improving customer loyalty.
Have a segment of repeat customers and want to find ways to increase the membership count of that segment? With a CDP, you can take advantage of every source of data you have and consider what factors lead to a loyal customer.
Not only can you measure data like cross-channel engagement and purchase history, but you can also use AI tools and predictive analytics to understand and implement hyper-personalized strategies to increase those conversions.
Here’s an example. Let’s say there’s a fictional store called “Go Fish.” It’s a mid-sized B2C tropical fish and supply store that has both brick-and-mortar and an online store. Recently, Go Fish implemented a CDP to take advantage of the customer data they have in their cloud data platform.
To market their brand, Go Fish uses:
- SMS
- Mailers
- On-site personalization
All of the metrics from those channels live in their own silos. Go Fish can implement a CDP that will gather its customer engagement data in one place and help build an identity resolution model that creates unique profiles for each of their customers.
Within each unique profile, the marketing team can see how each customer engages with their content and detect differences in behavior between channels or types of content. Once the customer data is centralized, Go Fish can keep track of campaign metrics, web traffic, conversions (online and in-store), and customer demographics in one place.
The next challenge is to analyze and glean customer insights from the centralized data. While the number of purchases is Go Fish’s north star metric, say the company decided to work on creating a healthier audience base.
When comparing unsubscribe rates for email and SMS, they found that their rates were higher than the industry average. Upon further investigation, they discovered that those who unsubscribed had similar characteristics, regardless of which channel they unsubscribed from.
These customers were mostly one-time purchasers from their online store who made their initial purchase during a sale or promotion. Based on this observation, and with the help of AI tools, Go Fish can create a “Welcome” series of cross-channel communication that recommends products and offers discounts tailored to new customers.
By doing so, Go Fish will see lower unsubscribe rates among their first-time customers, increased sales, and an increase in loyal customers.
The moral of the story? Gathering customer insights and using features like AI predictive analysis within a CDP can help indicate which metrics need attention and how they can be used to improve your overall customer engagement metrics.
Measuring the right data for actionable customer insights
Before you can start analyzing metrics like CAC, CLTV, customer churn, and overall engagement, you need to capture the right data from your channels.
A natural place to start is by measuring engagement metrics on your email campaigns, such as:
- Open rates
- Clicks
- Click-through rates
- Bounces
- Unsubscribes
From there, you can start to understand what messaging resonates with your audience. After all, open rates and CTRs are the lifeblood of email marketing.
But generic messages often get ignored, and analyzing basic demographics doesn’t help you deliver personalized content. Thankfully, a CDP helps you dig deeper and create a personalized experience by painting a vivid picture of your customer’s preferences, behavior, purchase history, and paint points.
Armed with this information, you can learn:
- What type of content your customers crave
- Which channels they frequent
- How they like to interact with your brand
These insights ultimately allow you to create laser-focused customer personas that guide your every marketing decision.
Using customer insights to build your marketing strategy
1. Define your goals and identify metrics to improve
The first step is to determine your marketing goals. Do you want to increase website engagement, boost email open rates, or reduce customer churn? Once you have clear goals, identify the key metrics that track progress toward those goals.
If your goal is to increase website engagement, relevant metrics might include average session duration, bounce rate, and page views per visit.
2. Dig deeper: Uncover the "why" behind the numbers
Don't just focus on the numbers themselves — investigate potential contributing factors to the metric. Use your CDP to investigate potential factors contributing to your chosen metrics. Here's where segmentation comes in.
The beauty of a CDP is its ability to segment customer data into distinct groups based on demographics, behavior, or preferences. This allows you to conduct more specific experiments and pinpoint the exact changes that drive improvements.
Imagine you see a dip in website engagement. With basic segmentation, you might analyze visitor behavior across different age groups. However, a CDP lets you create even more granular segments.
You could segment by age group and browsing behavior, revealing that a specific age group bounces off product pages with lengthy descriptions. This targeted insight allows you to experiment with shorter descriptions for that segment, potentially leading to increased engagement.
3. Experimentation is key: Test, measure, and refine
Once you've identified potential contributing factors, it's time to experiment! A/B testing is a powerful tool for measuring the impact of changes you make. You could test a new email subject line against your current one to see which drives higher open rates.
Here's the crucial part: make sure your marketing channels are capturing the right data to measure the success of your experiments. This includes:
- Engagement data: Track how customers interact with your marketing efforts, such as clicks, opens, form submissions, and time spent on specific pages
- Demographic data: Capture basic customer information like age, location, and interests to understand different segments better
These numbers are especially helpful when you combine them with AI and machine learning, which can help you analyze and better understand your customers through these metrics. Once you do, you can build out campaigns like cart abandonment or churn risk to encourage customers to make repeat purchases.
By analyzing the results of your experiments, you can pinpoint which changes had a positive impact on your chosen metrics. This data-driven approach allows you to continuously refine your marketing strategy and optimize for success.
Remember: Don't be afraid to experiment! The more you test and learn, the better you'll understand your customers and craft marketing campaigns that resonate. A CDP empowers you to transform data into actionable insights, ultimately driving real results for your business.
