08 06

With the accelerated adoption of digital transformation, there has been a boom in the adoption of automated MarTech tools and marketers across the globe have understood the importance of delivering personalized solutions to the pain points of their customers in real-time or proactively as soon as possible.

Marketers must combine their digital strategies, data, analytics, experience design, and platform implementation knowledge with their customer experience strategy to reimagine their organisations in the post-pandemic competitive arena.

Combining end-to-end business strategy with customer insights fetched from modern digital tools helps marketers establish a digital experience.

For uncovering customer insights and creating intelligent workflows, marketers need to utilize data science and analytics methodologies to strengthen their customer experience management architecture.

So, if a brand is looking to improve their customers’ overall experience, they need to invest time and resources into technology that enhances business relationships.

Brands need to turn digital conversations into CX insights by featuring the Brand Experience Score and business KPIs need to be derived from the day-to-day digital interactions that brands have with their customers.

Brands must accurately analyze the voice of their customers by aggregating the organic conversions occurring across every digital communication channel to optimize customer retention & bolster revenue.

When unstructured data from diverse digital customer interactions are normalized and analyzed, an omnichannel data set is automatically analyzed and fetches interesting CX insights that are rich in scale, scope, and content & delivers pure, candid customer feedback without one ever having to ask for it.

The BXS dashboard allows users to understand the root causes behind the score of each business area and is guided by topic classification, sentiment analysis, and anomaly detection features.

Artificial intelligence helps in designing a precise model for strengthening the omnichannel sentiment analysis model and adds an emotional dimension to help users quickly and accurately identify the source of customer friction.

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