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Data Analytics Can Help Your Customer Journey Featured

Data Analytics Can Help Your Customer Journey Vlad Bagacian

For any organization, aligning marketing and customer experience is a matter of critical importance. According to a report by Huffington Post, more than 34% of leading businesses said that customer journey was a top priority to them in 2020. Understanding how technology can benefit businesses before settling on the helpful ones is crucial for any organization. One of the most beneficial technologies in this era is data analytics. With this technology, you can map out various behavioural scenarios of your customers and potential clients and achieve a deeper understanding.

What is customer journey analytics?

Customer journey analytics entails processes that help organizations manage customer experience across all channels. It is software that allows tracking and measuring customer interactions across various channels. This software helps businesses to various activities in real-time and execute behaviour-driven strategies.

With customer journey analytics, companies can improve their customer experience and increase retention and lifetime value. This approach also allows them to grow their revenue. With a clear picture of the customer, you will be able to see how customers behave on your website or other platforms where you are available. It allows you to visualize how they navigate the platform and see the difficulties they encounter.

Customer journey analytics streamlines the customer experience

Customer journey analytics can come in handy in adding requested features and curating recommendations. This is crucial for the personalization of products or services. It is used by brands like Netflix and Spotify, leaders in their respective markets. According to Forrester Research, customers are 2.4 times more likely to stay with a company when the latter can resolve customer issues faster. Furthermore, they are 2.7 times more likely to spend more when there is clear communication and ten times more likely to recommend their products to others when all their questions can be answered.

Over the years, the bar for customer satisfaction has been raised. Therefore, one has always to do better. It is the only way of ensuring customers spend more to buy products or recommend them to others. Since customers provide crucial feedback that can be useful, analyzing customer journey data is the best way to find the right marketing messages and where messaging might be confusing. The analysis also allows identification of common issues or questions and employees to be trained on how to resolve the identified issues.

Rising customer expectations are leading to the growing importance of brands’ customer experience

With customer experience becoming one of the key points of competition, companies are doing all they can to ramp up their focus on this area. At the same time, marketers see the challenges brought about by the traditional approaches characterized by a lack of adequate data. Customer journey analytics paints a clear, complete, actionable and dynamic picture of the customer. It interprets millions of data points immediately and in real-time, allowing teams to find and root out the cause of different pain points.

Challenges of mapping customer journey

Although the concept of customer journey analytics is meant to improve customer experience and the entire mapping journey, the process of doing so comes with various challenges. The challenges mostly emerge when the right tools are not used. Some of the challenges in mapping customer journeys include data aggregation, timing, and complexity. Another bigger issue can come from missing the bigger picture concerning focusing on different touchpoints without looking at the entire journey.

The solution to these challenges is to ensure that journey analytics software brings everything together under one roof. Furthermore, time-stamped event data is important to know exactly when and in what sequence certain actions will occur.

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Scott Koegler

Scott Koegler is Executive Editor for Big Data & Analytics Tech Brief

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