The Power of Customer Journey Analytics:
Krithika Ramanarayanan, Data and Insights Manager at Davy voiced that “Excellent service does not simply come from a friendly smile or easy transaction. When an organization puts the customer at its core, empowering its people and unifying its processes then outstanding customer service becomes possible on a consistent basis, from the first greeting to the final meeting.” The discussion at Predict conference under the category: The Business of Data Science at the Blue Stage on the topic “The Power of Customer Journey Analytics” got my maximum attention.
I understand how important a customer is to the company. I believe that customer needs and expectations are the most pressing matters for a company's success. Ramanarayanan mentioned that Davy primarily focuses on identifying what are the exact customer requirements. She broadly discussed the various steps which are involved in Customer Journey Analytics. At first, the business objectives are set on the basis of customer's needs and requirements. Once the objectives are set, market research is conducted by experts who study various customer trends and perform market and commercial analysis. After all this data is gathered, a content strategy is formulated which is customer specific.
In this literature review, I give an overview of existing literature on ‘The Power of Customer Journey Analytics'. The first part of the section gives introduction and presents some examples. Following upon
Following upon definitions, and setting the stage for our own research, we will highlight examples of AR/VR being used in various industries, concluding with applications the context of education and/or professional training.
From the age of early man to the age of the Internet of things, human beings are generating data. Though in the past few years we have produced more data than in the previous thousands of years. Quoting a fact from Content Critical (McGovern, 2002), “There is enough scientific information written every year to keep a person busy reading day and night for 460 years.” There is too much data for humans to understand & analyze effectively. A massive amount of data gets generated from various business sectors such as retail, manufacturing, health care, transportation, financial services, and govt. agencies. Data gathered from all these sectors if utilized effectively can help companies grow their business exponentially.
For any company to excel it must have a strong customer base. Customer Analytics is revolutionizing as we know it. It is clear that now there is no limit in the generation of customer data. In order to handle this data well and produce meaningful results for higher returns companies need effective customer data analytics. For businesses to grow their customer base, it is vital for the business users to understand the customer path. Teradata designed path analysis for this purpose. It helped the business users not just in improving their operations but diminish the most probable issues in their customers' journeys. Overstock is using Teradata Path Analysis for understanding its customer's journey data points. Teradata developed a pathing interface which provides Overstock a path analysis solution to analyse customer data visually. These data points are analysed from various multi-channel marketing campaigns and key customer milestones in their journeys. (DIEGO, 2018)
Customers now interact with firms not just directly during the purchase of a product or service but through various other channels like social media. Thus it is vital for a business to keep a track of their customer's journey. "Path analysis is a critical analytic component for any business looking to understand its customer and yet, with the multitude of channels available today, it's also one of the hardest to get right," said Oliver Ratzesberger, Chief Operating Officer at Teradata. (DIEGO, 2018)
What companies are now trying to do is to personalize various aspects of the customer's shopping experience by integrating data from multiple sources. For example, Macy's, US-based retailer collects customer data about their preferences based on factors such as color, price range, seasonality, price range, demographics, etc. Sentiment analysis is performed on this data by the analytics team to measure the positive and negative comments mentioned on social media. Using this data, predictive analytics is performed that helps in identifying potential opportunities and forecast trends. This also helps Macy's to segregate customers and give them individual and personalized attention so that the customers' interaction with the brand on various platforms leads to purchase of the product. (Dezyre, 2015)
To give a background to the area suitable for a non-specialist, this is what Customer Journey Analytics is about.
With the globalization of business, the success or failure of a company is in the hands of the company's most valuable asset which is its' customers. It is undeniably a powerful factor in the success or failure of modern companies. A company may have a fantastic product, supportive shareholders, or a brilliant team. But without satisfied customers, one is out of the business. I feel that satisfied customers are loyal customers. Retaining the current customers is more efficient and profitable than seeking out new ones, and loyal customers are easier to sell to than those without any experience with the company.
Customer experience is nowadays the most important research challenges. This is because there are multiple channels available which are generating huge amount of customer interactions with a firm. Businesses believe that by creating a strong customer experience they can get higher conversion rates through improved customer loyalty and word of mouth.
(David Court, 2009)
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