Customer Journey Data Analytics: Complete Guide for Advertisers

by The MNTN Team

8 Min Read

As an advertiser, you’re always looking for an edge; the insight that will give your campaigns more relevance and assure better results. And the solution you seek may just lie in customer journey analytics.

Analyzing the customer journey sheds light on every touchpoint as prospects move through the sales process. With the data it provides, you can better understand everything from a consumer’s first interaction with your brand to how they continue to interface with your brand after making a purchase.

The following guide to customer journey data analytics will ensure you know how to most effectively integrate the analytics process into your advertising strategy to provide the best results for your business.

What Is Customer Journey Analytics?

At its core, customer journey analytics refers to the process of collecting, analyzing, and interpreting customer information across multiple touchpoints. Each piece of data provides part of the puzzle, and cumulatively, these details will help you understand and optimize the customer experience.

Customer journey data analytics is about more than simply tracking what someone does on your website — it provides you with a full picture of the steps they take so that you can identify patterns and pain points, which ultimately helps you drive more sales.

Customer Journey Analytics vs. Customer Journey Mapping

If you are familiar with customer journey mapping, you might be thinking that the entire concept of customer journey analytics sounds quite similar. And though they are indeed related concepts, there are some important distinctions between the two.

Customer journey mapping is a visual storytelling tool — showing you the path a customer might take based on assumptions, past behavior, or current trends. It’s useful for planning, but it doesn’t give you real-time, data-backed insights.

Customer journey analytics, in contrast, is grounded in data. It relies on information from multiple systems, such as your customer relationship management (CRM) platform, web analytics, social channels, and customer support logs. The more data you include in your analytics processes, the more relevant your analytics reports will be.

Benefits of Customer Journey Analytics

Customer journey analytics can facilitate the following:

1. Improved Customer Experience

When you understand when, where, and how customers interact with your brand, you can cultivate better experiences. For instance, your analytics may reveal that an unusually high percentage of leads are dropping off after visiting your product page.

In that case, you would need to dig deeper to identify which elements of your product pages are applying friction to the customer journey so that you can remove those barriers and encourage more purchases.

2. Enhanced Marketing Effectiveness

Customer journey analytics reveals which campaigns and channels are leading to conversions. You can also identify underperforming channels and reallocate resources away from those mediums, ensuring you make the most of every marketing dollar.

3. Increased Conversion Rates

When your messaging aligns with the stage customers are at in their journey, they’re more likely to act. Your goal is to serve the right offer at the ideal time in someone’s decision-making process.

Suppose that your customer journey data analytics reveals that one of your key audience segments is looking for one of your top-selling products. You could send that segment email marketing content that includes a time-sensitive discount code — tapping into customers’ fear of missing out.

4. Better Customer Retention

Customer journey analytics doesn’t stop at the sale; it can show you how engaged a person is post-purchase and whether they are likely to churn. Use that information to target high-risk consumers with follow-up messaging to keep them around. Retaining customers and driving repeat purchases are critical to long-term growth.

5. Data-Driven Decision Making

One of the biggest perks of customer journey data analytics is that you’ll no longer have to rely on gut feelings or incomplete data. You’ll be able to make data-backed decisions about advertising messaging and channel strategy to capitalize on fleeting opportunities, such as seasonal sales trends or new product preferences.

How Customer Journey Analytics Work

The first step in any analytics journey involves collecting a large volume of high-quality data. Gather information from your website, apps, email platform, CRM, and even in-person store interactions. From there, analyze that data using a modern reporting platform and create different reports so you can identify big-picture trends and market-specific patterns.

Ultimately, the key to using customer journey data analytics is investing in the right platforms. You need solutions that capture and analyze a large volume of journey data so that you can unlock actionable insights. A prime example is MNTN Performance TV, which is changing how advertisers distribute, track, and optimize TV content — more on this later!

Types of Data Used in Customer Journey Analytics

Here’s a quick look at the two types of data used in customer journey analytics:

Quantitative Data

Quantitative data includes hard numbers, such as clicks, time-on-site, and email open rates. These metrics help you measure behavior at scale and identify trends.

Qualitative Data

Qualitative data gives you the “why” behind the numbers. For instance, a customer survey may reveal that many find your chat-based support frustrating, which could explain higher churn rates.

Using both types of data together gives you a complete, nuanced understanding of what’s happening and why.

Customer Journey Analytics Example

Let’s walk through a simplified example to see how customer journey data analytics actually works:

The Journey

A customer sees your brand on Instagram and clicks through to your landing page. They browse a few pages and leave, but a week later, they search for your product on Google and land on a blog post. They then sign up for your newsletter before leaving, and a few days later, they get a promotional email with a discount code — finally spurring them to make a purchase.

The Issue

Let’s say that you have built a strong Instagram presence, and hundreds of prospective customers follow a very similar path to the one described above. You enjoy consistently high website traffic, but your conversion rates are falling below expectations, and your Instagram campaign is underperforming in terms of sales. You’re not sure where potential customers are falling off or why your return on investment (ROI) isn’t higher.

The Analysis

Customer journey data analytics uses information from all of the touchpoints outlined above to provide insights into that ROI challenge. You can also incorporate consumer surveys and historical data from past campaigns to get to the bottom of the issue.

In the same example, suppose that your analytics report reveals that many users interact with your social content but tend to bounce quickly from the landing page. At the same time, those who read your blog and receive follow-up emails convert at a much higher rate, and the feedback you gather from customer service also shows that your landing page didn’t clearly explain your product benefits.

The Resulting Action

Based on the example above, you determine that your landing pages are the weak point in your campaign, and in response, you redesign your landing page to emphasize the value your products offer. You also include a link to the blog and add a newsletter sign-up form to all of your landing pages.

The results include lower bounce rates, higher email sign-ups, and a noticeable uptick in conversions — that’s the power of utilizing customer journey analytics.

How Performance TV Connects the Dots

Want to understand exactly how your audience moves from awareness to conversion on the living room screen? MNTN’s Performance TV platform gives you the tools to analyze the customer journey with real-time attribution and performance insights — so you can see how CTV advertising fits into every stage of your funnel. With AI-powered targeting and automated optimization, your campaigns adapt to how people actually buy.

Here’s how MNTN Performance TV helps marketers unlock customer journey analytics:

Verified Visits™ — An attribution tool that tracks site visits and conversions tied directly to CTV ad exposure, giving you visibility into path-to-purchase behavior.
Reporting Suite — Access real-time insights to analyze touchpoints, map customer interactions, and optimize the full journey.
Premium CTV Inventory — Reach engaged viewers on top streaming networks, driving brand impact across awareness, consideration, and conversion.
MNTN Matched — AI-driven, keyword-based, targeting tool that ensures your ads reach the right audience at every stage of the journey.
Automated Optimization — AI tech that continuously adjusts your campaign to increase efficiency and drive better outcomes at every touchpoint.

Map, measure, and improve your customer journey — sign up today to get started with MNTN Performance TV.

Customer Journey Data Analytics: Final Thoughts

Understanding your customer’s journey is essential in today’s ultra-competitive environment. With customer journey analytics, you can move beyond surface-level insights and truly get to know your audience. If you’re ready to take your brand’s growth to the next level, tap into customer data today and turn every touchpoint into an opportunity to make a sale.