Interpret Website Activity with Digital Sensory

In a digital world, it can be difficult for the FI to identify needs before the customer has made a decision. Digital engagement is often remote and impersonal, with a much lower chance of influencing the consumer. Digital sensory gives the FI a chance to improve their odds.

• Gather data from the moment the guest touches your website.
• Understand needs based on behavior.
• Filter website traffic “noise” for actionable cues.

ARGO’s digital sensory ‘listening’ converts the FI’s website from passive to active. Digital sensory identifies consumers and then detects and analyzes their actions. This provides an up-to-date view of the intent, interest level, and propensity to purchase for a product or service.

Digital sensory:

• Detects: Uniquely identifies website visitors as guests, prospects, or existing customers.
• Listens: Gathers signals to measure need and readiness to buy.
• Quantifies: Interprets events to measure the chance of engagement success.
• Decides: Uses scores to optimize timing and relevance.
• Engages: Triggers actions and responses through digital and staff channels.
• Stores: Gathers data to provide a 360-degree customer view.
• Reports: Provides insight through KPIs to improve products and processes.

Example

Suppose two people visit the FI’s website. Analytics detect and measure each user’s probable interest and product intent based on navigation time, depth, and frequency signals. Let’s say the first person visits a general product page, stays for less than a minute, and disappears. The other person navigates more deeply to specific product and pricing pages, remains for several minutes, leaves, and returns within five minutes. Clearly, the second visitor is a more viable lead. Probable leads are routed for digital, staff, or blended engagement plans based on data, including the predictor of net worth potential CVI, segmentation, and product. If the visitor is an existing customer, the data used includes current customer and account information available to contextualize the opportunity.

Example

A recent college graduate may be interested in debt management. A more established empty nester may be in the market for wealth management and retirement planning. Based on this data, the solution appropriately engages with offers, education, and helpful tools to meet their specific needs. Based on preferences and opportunity cost, analytics drive contact through emails, texts, third-party marketing, and/or staff outreach. KPIs reveal the success of the intended outcome to optimize CE. A/B testing compares outcomes to improve plans and timing over time.

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