Bringing All Data Together Can Break Organizational Silos
Unifying a software ecosystem can help organizations break down long-existing departmental silos and improve their digital transformation journey. By bringing together all shreds of consumer data on a cloud-based platform, processing and schematizing it to build profitable business models become easier. Once gathered, the data undergoes a thorough cleansing process to scoop out only high-quality information for simplified decision-making. Subsequently, feeding in machine learning algorithms to create reports aligned with your business model can help you maintain structural consistency to analyze and use data across several applications. The analytical reports can be visualized in interactive Power BI dashboards thereby, allowing agents to seamlessly understand consumer queries and delineate quick and accurate solutions based on relevant data related to the case.
More Sales, Lesser Bounce Rate
Making use of an integrated data platform doesn’t only make way for faster and seamless customer interactions but, also allows agents to work with more than just customer service-use cases. Customer agents, when equipped with schematized data can accurately define a list of product/service recommendations based on their purchasing history. Even if a consumer is reluctant about investing in a certain product, being familiar with all its features and similar items can change his mind and lead to an increase in sales. Besides, the machine learning algorithms are trained to rigorously churn data and find out where each customer stands on the sales pyramid. If needed, the sales agents can intervene with proactive retention strategies and design marketing strategies to attract new and loyal customers.
Customer Identity Matching
By collecting distinct pieces of information about an individual customer, companies can make use of identity matching and curate customized solutions for them. Customer identity matching revolves around recording customer interactions across various channels and comparing them with one another. The right analytics software can look for matches in these separate information sets and establish an identity match for every single consumer. Once the identity matching process is completed and tagged as successful, the clean data makes it possible for the sales team to identify the eccentricities of the unique consumer journeys, produce behavior segments to segregate different trends and preferences, and pitch personalized offers. Instead of suggesting the same products over and over again, recommending items that belong to the same price range and type can assure more sales.
The Sales Approach Is Based On Customer Journey
In order to be successful with creating a single customer view, the wiser recourse would be to head on a journey based on customer interactions alone. It is always better to deal with end-to-end customer journeys as they provide a bird’ eye view of all the important points in there. Rather than noting down the pit stops of customer interactions across each individual channel, evaluating them together can help you identify the areas that should be prioritized the most for greater engagement and satisfaction. The experience that a customer had with your company can be comprehended by considering his past transactions and interactions and needs that are wish-listed. Customer journey analytics is undoubtedly a path-breaking strategy that allows organizations to connect innumerable touch-points created over different time spans and channels.
