Customer Journey is the New Product

Published on Aug 16, 2019

Updated on Oct 16, 2019

Even when the customer has successfully added items to cart, it all means zilch until the purchase is complete. The average cart abandonment rate for all sectors worldwide was 75.6% last year. Simply put three out of every four digital customers leave websites without completing the purchase.

At the customer acquisition phase, you’ve to compete with zero-profit offers, despite the fact that your product is the best in its niche.

Although 80% of businesses claim they offer a great customer experience, only about 8% of customers express satisfaction with their experience.

So, what went wrong? Why are customers leaving your site without purchasing? And more importantly, what can you do about it?

Mastering the art of understanding user persona, discovering bottlenecks in the delivery process, and designing a user-friendly interface will help you build the product that supersedes customers’ expectations.

Mapping the Customer Journey

It involves understanding your customers’ behavior and feelings throughout their interaction with your products/services and visually mapping them to tell a complete story of their overall experience.

More precisely, the journey begins from the moment they first come to know about your product and the phases they pass through while making a final purchase decision.

“For brands, customer journey mapping is like walking a mile in their customers’ shoes and understanding their circumstances with empathy.”

Apart from managing complex user experience problems, you can tweak customer journeys to understand past, present or a future state surrounding a day in the life of your customer.

According to Gartner, Eighty-two percent of organizations have created a customer journey map, but only 47% are using those maps effectively. The mapping of the customer journey begins by creating a cross-functional team led by the CIO, CMO or even the CEO.

A journey map is different from process maps. They detail multiple channels and touchpoints before and during the buying process. Interestingly, the more value-added layers you can include, the better is your view of your customer.

Top Customer Journey Map Layers

Source: Uxpressia

Adding convenience to the customer experience value chain can create powerful moments of truth. For instance, while shopping on your portal, a customer might want to know more information about your product, it’s features, reviews, etc.

A proactive service that goes to the customer first using real-time messaging and custom product recommendations, is how innovative solutions can address such pain points, impacting the overall experience.

Choosing the Right Attributes

Before we look at how to select the most relevant inputs for outlining behavior, it’s important to grasp the fact that customer journey mapping is an iterative process. For instance, the questions answered by customer journey maps a decade ago is totally different from today.

Source: Harvard Business Review | Linear customer journey map in 2010

Source: Medium | The present-day non-linear customer journey map (eg: Ikea)

The goal is to build a comprehensive map that will conclusively identify gaps from multiple touchpoints — areas of customer experience that are disjointed or painful.

To achieve this, it is vital to map out each phase of the pre-buying and actual buying journey and map them alongside data-driven personas. Data is critical for customer journey stages — it is almost impossible to create customer journey maps without it.

The Modern Customer Journey
Source: G3 Com

The modern customer journey map needs to cover the complete omnichannel experience. Customers are now communicating with companies through 10 channels on average. Their expectations are fast-moving and rapidly evolving. They expect communications about the latest products from their favorite brands to happen in real-time.

For instance, Magalu, one of Brazil’s largest retail companies, recognized that its app was growing in popularity. They decided to enable deep linking, so that loyal customers who tapped on a Magalu ad were taken directly to the mobile app they already have installed, resulting in more than 40 percent growth in overall mobile purchases.

Customer journey maps are drawn from the customer’s point of view and are based on people’s mental models (how things should behave, the flow of interactions and possible touchpoints). They combine user personas, user scenarios & user flows to understand and predict how the customer will behave next.

5 Key Attributes of an efficient Customer Journey Map

Most relevant brand goals: The goals should be reflective of the inner aspirations of the organization that outwardly manifest into creating the best experiences consistently for the customer.
Key customer touch-points: Identify touch-points across all channels, and define the action and available paths for each. This layer is critical to understanding how the service structure forces customers into unnecessary interactions and take measures to avoid them.
Empathy Map: This map depicts exactly what the customer thinks, says, does and feels about your product/ service or the complete attitude towards the brand itself. One can also find utility in creating one-user vs multiple-user empathy maps.
Affinity Diagram: This is a great planning tool, and it enables you to organize the data and insights gathered up to this point into bundles.
Sketch the Journey: Now is the time to visualize the structured data into powerful story-driven narratives pointing out gaps in the process. This step will inform what solution or fix will remedy your customer’s pain-point for the long term.

Why You Need Customer Journey Mapping?

You’re doing great if you understand your customers and are able to exceed their expectations. Retaining a loyal customer base might make you think about the essence of understanding the customer journey.

But, how are you planning to face the competitive landscape? Because customers constantly lookout for change. What if your competitors satisfy your customer’s needs with a better emotional connection? Mapping the customer journey will allow you to transform the experience delivery process creating ‘wow’ moments that strengthen loyalty.

“The term ‘customer experience’ won’t exist in the organization of the future. It will be deeply entrenched in a company’s product, process, and culture that it will be synonymous with the brand and represent the only way to do business.”
Ann Lewnes, EVP and CMO, Adobe

We specialize in helping organizations build attractive and easy-to-understand user journey maps for faster omnichannel integration. Reach out to us on hello@mantralabsglobal.com, to learn more.

Let’s rewind the clock for a moment. Thousands of years ago, humans had a simple way of keeping tabs on things—literally. They carved marks into clay tablets to track grain harvests or seal trade agreements. These ancient scribes kickstarted what would later become one of humanity’s greatest pursuits: organizing and understanding data. The journey of data began to take shape.

Now, here’s the kicker—we’ve gone from storing the data on clay to storing the data on the cloud, but one age-old problem still nags at us: How healthy is that data? Can we trust it?

Think about it. Records from centuries ago survived and still make sense today because someone cared enough to store them and keep them in good shape. That’s essentially what data observability does for our modern world. It’s like having a health monitor for your data systems, ensuring they’re reliable, accurate, and ready for action. And here are the times when data observability actually had more than a few wins in the real world and this is how it works

How Data Observability Works

Data observability involves monitoring, analyzing, and ensuring the health of your data systems in real-time. Here’s how it functions:

Data Monitoring: Continuously tracks metrics like data volume, freshness, and schema consistency to spot anomalies early.
Automated data Alerts: Notify teams of irregularities, such as unexpected data spikes or pipeline failures, before they escalate.
Root Cause Analysis: Pinpoints the source of issues using lineage tracking, making problem-solving faster and more efficient.
Proactive Maintenance: Predicts potential failures by analyzing historical trends, helping enterprises stay ahead of disruptions.
Collaboration Tools: Bridges gaps between data engineering, analytics, and operations teams with a shared understanding of system health.

Real-World Wins with Data Observability

1. Preventing Retail Chaos

A global retailer was struggling with the complexities of scaling data operations across diverse regions, Faced with a vast and complex system, manual oversight became unsustainable. Rakuten provided data observability solutions by leveraging real-time monitoring and integrating ITSM solutions with a unified data health dashboard, the retailer was able to prevent costly downtime and ensure seamless data operations. The result? Enhanced data lineage tracking and reduced operational overhead.

2. Fixing Silent Pipeline Failures

Monte Carlo’s data observability solutions have saved organizations from silent data pipeline failures. For example, a Salesforce password expiry caused updates to stop in the salesforce_accounts_created table. Monte Carlo flagged the issue, allowing the team to resolve it before it caught the executive attention. Similarly, an authorization issue with Google Ads integrations was detected and fixed, avoiding significant data loss.

3. Forbes Optimizes Performance

To ensure its website performs optimally, Forbes turned to Datadog for data observability. Previously, siloed data and limited access slowed down troubleshooting. With Datadog, Forbes unified observability across teams, reducing homepage load times by 37% and maintaining operational efficiency during high-traffic events like Black Friday.

4. Lenovo Maintains Uptime

Lenovo leveraged observability, provided by Splunk, to monitor its infrastructure during critical periods. Despite a 300% increase in web traffic on Black Friday, Lenovo maintained 100% uptime and reduced mean time to resolution (MTTR) by 83%, ensuring a flawless user experience.

Why Every Enterprise Needs Data Observability Today

1. Prevent Costly Downtime

Data downtime can cost enterprises up to $9,000 per minute. Imagine a retail giant facing data pipeline failures during peak sales—inventory mismatches lead to missed opportunities and unhappy customers. Data observability proactively detects anomalies, like sudden drops in data volume, preventing disruptions before they escalate.

2. Boost Confidence in Data

Poor data quality costs the U.S. economy $3.1 trillion annually. For enterprises, accurate, observable data ensures reliable decision-making and better AI outcomes. For instance, an insurance company can avoid processing errors by identifying schema changes or inconsistencies in real-time.

3. Enhance Collaboration

When data pipelines fail, teams often waste hours diagnosing issues. Data observability simplifies this by providing clear insights into pipeline health, enabling seamless collaboration across data engineering, data analytics, and data operations teams. This reduces finger-pointing and accelerates problem-solving.

4. Stay Agile Amid Complexity

As enterprises scale, data sources multiply, making Data pipeline monitoring and data pipeline management more complex. Data observability acts as a compass, pinpointing where and why issues occur, allowing organizations to adapt quickly without compromising operational efficiency.

The Bigger Picture:

Are you relying on broken roads in your data metropolis, or are you ready to embrace a system that keeps your operations smooth and your outcomes predictable?

Just as humanity evolved from carving records on clay tablets to storing data in the cloud, the way we manage and interpret data must evolve too. Data observability is not just a tool for keeping your data clean; it’s a strategic necessity to future-proof your business in a world where insights are the cornerstone of success.

At Mantra Labs, we understand this deeply. With our partnership with Rakuten, we empower enterprises with advanced data observability solutions tailored to their unique challenges. Let us help you turn your data into an invaluable asset that ensures smooth operations and drives impactful outcomes.

Customer Journey is the New Product