Propensity Scoring

This model is built-in to enable real-time engagement automation by using scores set by marketers to estimate/predict customer behavior. These predictions can help trigger personalized engagements.

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Real-time recommendations

Built over the unified customer stack, Plumb5 offers recommendation widget, which can recommend products to the browsing visitor, based on both individual and global parameters. This allows the marketer to recommend either based on context of the current session, or based on past data. To know more on enabling recommendations in real time.

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Unified Data Stack

The most important aspect of Unified Stack is that data tagging starts at the customer touch-point and extends across all other touch-points by maintaining a unified document for every customer, irrespective of the touch-point. click on read more to see the advantages of the unified stack.

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Single Customer View

Plumb5 platform comes with a built-in user tagging feature that is tagged across web, email, social, mobile and SMS. The single customer view can be extended by integrating to other sources like CRM, ECommerce Platforms, Call Center data and POS systems. Unified tracking across all customer touch-points help us in maintaining insights in real-time, based on single customer data. This enables the user to configure rules and trigger targeting and personalization in real-time

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Real-time Automation Bots

The Automation bots are a set of automated triggers, where each trigger performs a specific function and the responses of the previous trigger cascades to the next trigger, based on rules or learning, to pursue a specific goal path. The bots can be customized to work on a specific conversion path machine driven marketing automation

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Conversational Model

Plumb5 profile and behavior tags can be used in conversation or personalization of messages, which can be used in customer engagement automation. Plumb5 can be readily integrated with a third party bot program built using Eliza bot framework or AIML. To read up on a use case on how its done.

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