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Ever wonder how brands such as Netflix, Amazon and Spotify remain so popular? They offer great services and people use them, but their brand image and likability is based on more than their services. It is the personalized user experience and the amazing customer relations they have fostered that keep them popular among their audience. Though on the face of it, customer relations and experience seem breezy, it hardly is. To continually keep up the customer experience, industries need to understand their customers and this can only be done with the help of the one omnipresent field – Data Science.
Organizations are rapidly realizing the game changing impact that customer data can have on the various aspects of their business. This data can be leveraged into creating proactive pathways back to the customers.
Data Science & Customer Relations
The manner in which companies interact with customers has changed over the years. With services increasing and marketing technologies advancing, companies can no longer guarantee continuous success. To distinguish a business, you have to focus on enhancing customer experiences.
Harnessing customer data and extracting valuable insight from data with speed and precision falls under Data Science. It helps businesses make better decisions by analyzing customers’ thoughts and behaviors. Understanding what customers want and need makes it easier for businesses to create experiences for them to keep coming back. Companies that use Data Science as their secret weapon to transform analytical data into beneficial information can testify to better customer relations.
Businesses are ensuring stable revenue by focusing more on increasing customer retention and reducing churn. Below are 2 basic ways to build better customer relations using Data Science:-
1) Creating customer profiles:
Businesses need to recognize that customers are the new focal point to marketing. The key to loyalty is to understand customers better than before. For this, Data Science is utilized to create and maintain customer profiles in order to measure a customer’s journey at every touch point across multiple channels.
To construct customer profiles, it is necessary to structure available data according to their demography, buying patterns, log data, etc. It should include all sources of data such as real time customer purchases and historical purchases, tracked through social media, geo-location, web analytics, e-commerce platforms, etc. This integration of data and updating of customer profiles will make your communication messages more relevant and customer centric.
2) Personalized customer interaction:
The key to quick and improved customer relations is to understand unique consumer needs. This will help you generate and improve your personalized responses. Machine Learning, one of the revolutionary branches of Data Science allows businesses to keep tabs on preferences of each individual customer. Predictive Data Analytics which is also an indispensable component of Data Science effectively predicts future activities of a customer and crafts your brand into the ‘helpful, mindreading friend’ that they need. Segmenting customers based on similar attributes and relevant product features has resulted in marketers orchestrating customer experience and increasing customer loyalty.
The personalized recommendation system of Amazon and Netflix has proved just how powerful customer data can be. After learning user preferences, these two online giants implemented software programs to come up a list of recommended items for users. In this way subscribers kept coming back for more. Consumers return for more when they feel that their connection with the organization is personal and individualistic. Thus, the better one uses data to their favour, the better the customer relations.
At every stage of a product lifecycle, companies can deliver the right message at the right time. But this becomes possible only after they collect, analyze and learn how to use customer data. By gaining actionable insight, Data Science can evaluate customer lifetime value and estimate long term profitability. Companies who fail to embrace Data Science and customer relations will not only fail to grow but will get left behind.
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