Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    unusual trading activity
    Signal Or Noise? A Decision Tree For Evaluating Unusual Trading Activity
    3 Min Read
    software developer using ai
    How Data Analytics Helps Developers Deliver Better Tech Services
    8 Min Read
    ai for stock trading
    Can Data Analytics Help Investors Outperform Warren Buffett
    9 Min Read
    media monitoring
    Signals In The Noise: Using Media Monitoring To Manage Negative Publicity
    5 Min Read
    data analytics
    How Data Analytics Can Help You Construct A Financial Weather Map
    4 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Using Data Analytics to Map eCommerce Customer Journeys
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Analytics > Using Data Analytics to Map eCommerce Customer Journeys
AnalyticsExclusive

Using Data Analytics to Map eCommerce Customer Journeys

Big data technology can be highly useful for e-commerce stores trying to establish the customer journey.

Annie Qureshi
Annie Qureshi
9 Min Read
big data in e-commerce
Shutterstock Photo License - By fizkes
SHARE

Big data technology is increasingly being used in e-commerce. Analysts predict that global e-commerce companies will spend $6.2 billion on big data by 2025.

Contents
  • Data Analytics is Important for Understanding Customer Behavior in eCommerce
  • What is a customer journey map?
  • The preparation work
    • Step #1. Define objectives
    • Step #2. Set the scope
    • Step #3. Profile your buyer persona
    • Step #4. Gather data on your buyers? journey
  • Actual mapping
    • Step #1. Split the journey into stages and identify touchpoints for each
    • Step #2. Add customer goals and expectations
    • Step #3. Find problems and enlist improvement opportunities
    • Step #4. Include Moments of Truth
      • The Right Process for Using Data Analytics to Map the Customer Journey

There are a number of benefits of using big data in e-commerce. One of the most important benefits lies in understanding the customer journey and optimizing their experience to maximize conversions.

Data Analytics is Important for Understanding Customer Behavior in eCommerce

Nowadays, online shopping is getting increasingly popular, as it is possible to purchase nearly all sorts of goods from the comfort of your home. With the growing interest in e-commerce platforms, the market competition is also getting even harsher?today’s customers seek a personalized and seamless shopping experience.

A lot of companies are using machine learning to create online stores more easily. However, they have also found that big data and AI solutions can be even more useful for understanding their customers.

More Read

New Generation of Technology Will Rely on Analytics, Study Shows
Businesses Use Inbound Comms to Generate Market Data
Big Data Platforms Assist with Spreading Health and Safety Awareness
Find yourself a safer place to swim or fish in the Bay Area
How 250 Milliseconds in Added Latency Can Ruin Online Sales This Holiday Season

This way, it is of utmost importance to be able to easily attract new customers and turn them into loyal ones. Here, a customer journey map (CJM) comes to the rescue.

What is a customer journey map?

A customer journey map is a visual representation of experiences a customer has with your online store: from the first touch with you to completing the purchase. With the help of journey maps, you can capture the end-to-end experience your customer undergoes that resulted in a purchase or a drop-off.

With a CJM at hand, you will understand the desires and expectations of your customers, examine their experience along the journey, as well as see the blind spots and experience flaws that need to be addressed. Based on that, you can improve customer experience to increase conversions and boost revenue.

Building an e-commerce customer journey map with big data will be easier when you know what steps to take.

Now, we will explore some best practices for creating a CJM for an e-commerce store with the right data analytics tools.

The preparation work

Before you get down to your journey map with the right data analytics insights, there is some groundwork to do.

Step #1. Define objectives

First, set clear goals that you want to achieve through customer journey mapping. For this purpose, you can bring together cross-department team members to agree on the target objectives. These may include increasing the conversion rate, reducing the number of refunds, encouraging reviews, etc. When the exact goals are specified, it is easier to implement improvements where needed and measure the results.

Step #2. Set the scope

It might be challenging to map the whole customer journey at once. You might want to begin with journey stages that need your attention as per your current goals or that you are well familiar with. You need to make sure that you have the right parameters established before you can start using data analytics to optimize your customer journey.

For example, if you want to understand why your customers decide to bounce even if they have already added products to the cart, you can pay attention to the checkout stage. For many online stores, cart abandonments occur pretty frequently?this is the way most people browse e-commerce websites. The reasons may vary: extra fees, poor delivery conditions, forced sign-up, website timeouts, etc. This way, it is crucial to get to the root of the problem and explore how to improve customer experience at this stage.

Step #3. Profile your buyer persona

Your customer journey won?t be complete without personas?a generalized representation of your customers with their expectations, goals, and behavior. So split your customers into segments based on common patterns (e.g. behavioral ones) to create personas.

In addition, persona profiles are extremely useful? you will have all customers? data at hand. Apart from the information about goals, motivations, background, frustrations, and other relevant information, you can also add a name and a best-fit photo to make a persona look realistic and relatable. Use the data you already have (e.g., from your CRM software) and do some research. Also, be sure to interview your current customers to better understand their needs and pains.

Step #4. Gather data on your buyers? journey

Now that you have created your personas, it?s time to embark on collecting information about their journeys.

Online data is a great asset that illustrates the real-world behavior of your customers. 

To acquire real-time user data, use such web analytics tools as Google Analytics, Google Tag Manager, HotJar, etc. Furthermore, the Net Promoter Score is a golden standard for measuring customer experience and loyalty. Don?t limit yourself to the data gathered using web analytics tools only?talk to your cross-functional teammates, especially those who work in close contact with customers. After a knowledge-sharing session, you can also ask these colleagues to share some customer quotes and add them to the map for further use.

Actual mapping

Now, you can start visualizing your customer journey. Relying on the scope set, identify the stages your customers go through when interacting with your online store, the goals they pursue, processes, main pain points, and so on.

Step #1. Split the journey into stages and identify touchpoints for each

Outline the points where a customer comes in contact with your business. These may include a website homepage, a checkout page, a courier, a customer service operator, etc. Below are the example stages of your customers? purchase experience with possible touchpoints.

  1. Placing an order. A customer completes the purchase at the checkout page and requests a delivery. 
  2. Order confirmation. Possible touchpoints here are a confirmation email or a customer service specialist.
  3. Waiting for the delivery. The touchpoints may be a confirmation email, a customer service manager, or a GPS tracking service.
  4. Receiving the order. Finally, the order finds its recipient. The touchpoints may be a package and courier service.
  5. Dealing with paperwork. The main touchpoints may be a courier service or documents.

Step #2. Add customer goals and expectations

This will let you see what your customers look for at each stage and how your company can align its services with buyers? needs. The examples are as follows: ?finding necessary products with minimum effort? at the search stage or ?receiving the delivery ASAP? after confirming your order.

Step #3. Find problems and enlist improvement opportunities

Web page timeout, hard-to-navigate product pages, low-quality images, poor delivery conditions, etc., can impact consumer experience greatly. Identify the core paint points that can destroy the experience. Then, brainstorm ideas that help you improve every single point and reflect them on the journey map.

Step #4. Include Moments of Truth

Moments of truth (MoTs) define whether a customer makes or breaks the relationship with your brand. For an e-commerce store, MoTs could be a checkout page or a call center. These are the most powerful moments in buyers? journeys, so make them customer-friendly.

The Right Process for Using Data Analytics to Map the Customer Journey

A CJM provides a comprehensive view of your customers? purchase journey with data analytics. It will help to see how you can ensure buyers have a unique and personalized experience across all touchpoints and channels in your e-commerce store.

Don?t put your customer journey map on the shelf once you complete it and present it to stakeholders. The customer journey is evolving, so should your map. Regularly review and update your CJM, while enhancing it with new findings and insights.

TAGGED:artificial intelligence in eCommercebig data in businessbig data in ecommerceecommerce data
Share This Article
Facebook Pinterest LinkedIn
Share
ByAnnie Qureshi
Follow:
Annie is a passionate writer and serial entrepreneur. She embraces ecommerce opportunities that go beyond profit, giving back to non-profits with a portion of the revenue she generates. She is significantly more productive when she has a cause that reaches beyond her pocketbook.

Follow us on Facebook

Latest News

data migration risk prevention
Best Approach to Risk Management for Data Migration in Data-Driven Businesses
Big Data Data Management Exclusive Risk Management
AI in branding
How Data Analytics and Data Mining Strengthen Brand Identity Services
Big Data Exclusive
Hidden AI, a risk?
Hidden AI, Real Risk: A Governance Roadmap For Mid-Market Organizations
Artificial Intelligence Exclusive Infographic
unusual trading activity
Signal Or Noise? A Decision Tree For Evaluating Unusual Trading Activity
Analytics Exclusive Infographic

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

data-driven email marketing tutorial
Big Data

5 Best Lead Magnet Ideas for Data-Driven Businesses

8 Min Read
data-driven decision-making with lean thinking
Big Data

Using Data-Driven Lean Thinking to Optimize Business Processes

9 Min Read
data visualization with kanban
Data Visualization

Examples of Using Kanban Boards with Data Visualization Tools

6 Min Read
businesses using data analytics for financial management
Big Data

Ways Data Analytics Helps Business Owners Resolve Financial Issues

8 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots
giveaway chatbots
How To Get An Award Winning Giveaway Bot
Big Data Chatbots Exclusive

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?