Beyond the Traditional Customer Journey: Why Most Companies Get It Wrong

By M Science   |   August 11, 2022 5 MIN READ

What most companies are missing from their customer journey insights

Most companies analyze their customer journey and their marketing conversion funnel through similar procedures. The stages of analysis are often described as awareness, consideration, and decision— or more simply — the top, middle, and bottom of the funnel.

In reality, path to purchase for a customer is much more complicated than those three stages suggest; however, most companies continue to adhere to this outdated approach, further limiting their insights.

From when they enter the market, to when they purchase the final product, a shopper will make countless decisions. Brands routinely fail to follow the complete customer journey, especially if the process takes weeks. Time and time again, companies prove to be ill-equipped with the tools or the data to process these trends into digestible and actionable insights.

How are companies measuring the customer journey today?

The customer journey often includes multiple touchpoints beyond a website visit. Consumers often read product reviews, browse multiple retailers, and search for comparisons or competitors.

During these early stages of the decision-making process, many companies rely on targeting technologies to reach prospective customers. Although with this model, visibility into this activity is severely limited. Analytics resources, such as Adobe Analytics or Google Analytics, offer insights into how a customer reaches their website, but those tools are unable to provide any context outside company-owned websites.

For most consumer products, the research and path to purchase go beyond a single website session. In fact, it may take weeks for higher-priced goods or niche products with long decision-making cycles. All of the complexities in the process warrant a path to purchase outline. No matter what attribution model a website uses, relying solely on analytics providers will cause data blind spots.

Traffic source and session insights are great for assessing owned DTC performance. But for companies that sell through marketplaces and retailers,  the customer journey is harder to track. Additionally, it’s a challenge for these companies to accurately assess their competitors’ performance. Evidently, businesses with omnichannel strategies face mounting gaps in path to purchase behavior.

How can I actually measure the full path to purchase?

Many brands have yet to harness the power of clickstream data, which acts as a window into user behavior online, including browsing details on multiple websites. You can read more about this in our blog: The Essential Guide to Clickstream Data.

At M Science, we help companies map the full path to purchase with insights from clickstream data. We capture the entire customer journey from initial category browsing activity, to demonstration of intent, to purchase for our clients and their competitors.

M Science’s customer journey module helps companies answer the following questions:

  • Where does the customer journey start?
  • What is the customer journey duration? What percentage of my customers spend <1 day, 2-7 days, 2-4 weeks, or 4 weeks+ on their journey?
  • How many brands are considered throughout the customer journey?
  • Which brands are considered most frequently?
  • Which retailers capture the most browsing attention for my product category?
  • How many retailers are considered throughout the customer journey?
  • What non-retail sites do customers visit by magnitude of sessions?
  • What irrelevant activity do customers engage in while they are on their journey? What buyer personas come to light?
  • What does purchase intent look like on a weekly basis? Do holiday periods have a higher purchase intent for my product?
  • Do customers who purchase during the holiday period spend months researching and waiting for holiday sales? Or do they have a shorter journey than non-holiday shoppers?
  • How do non-Amazon shoppers differ from Amazon shoppers?

Being able to answer these questions helps companies inform key strategies, including:

  • Media placement
  • Partnerships (brands and content creators)
  • Customer affinity
  • Product placement and allocation to retailers
  • Marketing activities such as blogs, YouTube videos, social media
  • Marketing investment in Amazon PPC or paid search
  • Buyer persona identification
  • Prospective customer reliance on blogs and reviews
  • Non-retail touchpoints along the journey

Where does the path to purchase actually begin?

The journey’s end can be defined as the demonstration of purchase intent.

M Science believes the journey starts as soon as the person engages in any digital activity related to the product category. This marks earliest date and domain with any activity. It can involve browsing a specific product on a retailer or e-tailer (including Amazon) or searching terms related to the product category on a search engine.

Being able to define this date is key to segmenting customers by journey start and duration.

Where does the path to purchase end?

Determining the end of the path is extremely important.

This process is difficult to assess without the right data and tools. A customer can visit a DTC website, only to make an in-person purchase. On the other hand, a customer can view multiple sites then make a purchase on only one.

How long does the customer journey last?

The customer journey can range from minutes to months.

Identifying the journey start and intent to purchase actions will inform the journey duration.

How many brands are considered, and which brands are considered the most during the customer journey?

Browsing brands and products on DTCs and retail websites are collected in clickstream data. The findings can identify which competitors are considered most frequently and how competitive the category is. Understanding which brands command the greatest share of browsing can help answer key questions:

  • Do people review multiple brands before making a purchase?
  • Are incumbent or disruptor brands browsed the most?
  • Which competitors are taking the most mind share? Which competitors are lagging?

How can knowing irrelevant activity help me drive more sales?

You can uncover buyer personas by visualizing consumer activity outside of your product category during browsing sessions. For example, analyzing irrelevant activity can uncover that customers who are browsing kitchen appliances are also browsing home renovation and technology retailers.

How M Science can help

M Science is a global data-driven research and analytics firm, with nearly 20 years of experience uncovering new insights for some of the world’s largest corporations and financial institutions. We revolutionize research by discovering new datasets and pioneering methodologies to provide actionable intelligence. Learn more at: intelligence. M Science is a portfolio company of Leucadia Investments, a division of Jefferies Financial Group Inc. (NYSE: JEF).

Interested in talking to a member of our sales team for a demo of our solutions? Reach out to our team!


Important Disclosures

© 2022 M Science LLC. All rights reserved.

All material contained in this blog post is the property of M Science LLC (“M Science“) unless otherwise indicated. All trademarks, service marks, logos and trade names used in this blog are proprietary to M Science or other respective owners. All research notes, blogs, data and other information obtained from M Science are proprietary to M Science and may not be redistributed to or shared with any individual, company or entity without the express prior written consent of M Science. All such information obtained from M Science is the property of M Science unless otherwise indicated and no portion may be directly or indirectly copied, published, reproduced, modified, displayed, sold, transmitted, or redistributed in any medium without the express prior written consent of M Science. Specifically, and without limitation, such information may not be disclosed to members of any sell-side research team, within or outside of your organization. M Science monitors and takes seriously our responsibility to protect the assets and value of our products and services.

This blog is intended for informational purposes only. Under no circumstances is this blog to be considered as an offer to sell or solicitation of an offer to buy any securities of any company. M Science provides the information and data contained herein on an “as is,” “as available” basis, without representations or warranties of any kind whatsoever, expressed or implied. The information in this blog may be incomplete and may not contain all material information relating to the subject matter of the blog. M Science has no authority whatsoever to give any information or make any representation or warranty on behalf of the company or companies that are the subject of this blog, any of its shareholders or any other person in connection therewith and this blog has not been authorized or approved by said company or companies.

This blog is provided solely to clients or potential clients of M Science. The recipient assumes all risk and liability with regard to any use or application of the data included herein. The data provided herein is not intended to be used as the primary basis for investment decisions and nothing contained herein is, or is intended to be, predictive of the movement of the market prices of the securities of the company or companies discussed in the blog. Nothing in this blog is, or should be construed to be, designed to meet the particular investment needs of any investor.  This blog is being furnished on a confidential basis and is provided for information and discussion purposes only and is not, and may not be relied on in any manner as, legal or tax advice. It is the responsibility of each recipient of this blog to satisfy itself that its receipt and use of this blog is in full compliance with the laws and regulations of the relevant jurisdiction(s) and, if in doubt about such compliance, to seek appropriate legal advice.

All proprietary analyses provided by M Science in this blog are derived from M Science’s analytic expertise, market knowledge, and use of the data it collects and licenses.

This blog reflects the results of our research as of the date of this blog. Our research results are subject to change at any time as new or additional data and information is received and analyzed. M Science undertakes no obligation to update this blog, or to provide supplemental information to any client receiving this blog, absent a specific arrangement to the contrary between M Science and individual clients. Specifically, M Science provides custom research blogs to certain of its clients which may be distributed on different frequency schedules from syndicated research blogs. Such custom blogs may provide different depths of analysis or a different specific focus and more frequent updates based on levels of service and fees selected by clients. Furthermore, these custom research blogs may reach conclusions that differ from this blog which could impact the price of a security.

Any opinions, forecasts or estimates in this blog may present a possible outcome on the basis of assumptions set out herein and represent only one possible outcome and are the independent view of the author(s) of this blog only. These opinions, forecasts or estimates are subject to risks, uncertainties and assumptions and there can be no assurance that future results or events will be consistent with any such opinions, forecasts or estimates.

This blog is not directed to, nor intended for distribution to or use by, any person or entity (1) that is not a client or potential client of M Science or (2) that is a citizen or resident or located in any locality, state, country, or other jurisdiction where such distribution, publication, availability, or use would be contrary to law or regulation or which would subject M Science or its affiliates to any registration or licensing requirement within such jurisdiction.