Engagement doesn’t end at the send
Our customer engagement agent is just one tool in the toolbox. Check out these if you’re working on adjacent decisions.
Identify churn risk, basket headroom, and next-best offers per customer. Get a validated target list staged for push to your CRM in under 10 minutes.
Grounded in your transactional, behavioral, loyalty, and CRM data. Covers the entire B2B2C chain.
ISO 9001
ISO 27001
GDPR compliant

You get the questions: “Who’s about to churn? Who has basket headroom? Which channel works for whom?”. And the data exists, but it lives in tools that don’t speak to each other and refresh on different cadences. Transactional history in one warehouse. Loyalty events in another. Behavioral signals in the CDP. Channel engagement in the campaign tool.
Campaigns get built on segments that were accurate six weeks ago, against churn risk that surfaced a month too late, with offers calibrated to averages instead of individuals.
That’s not how you grow CLV today.

The Customer Engagement Agent sits across CRM, transactional history, loyalty data, and behavioral signals.
It identifies who is at risk, who is high-value, who has basket headroom, and what specifically will move each one.
Get the right offer for the right channel at the right level of discount.
Every prompt triggers the same pattern. An orchestrator picks the data sources, KPIs, and models. Four specialized sub-agents work the question in parallel. An advisory layer fuses results and validates them statistically.
You get the target list with offers, channels, and push staging included.
It personalizes CRM at scale, decodes loyalty and retention drivers, and automates targeting and content.
Routing to sub-agents
Retain the high-value cohort by reading each customer’s actual signals, not the segment average.
3,400 customers in the high-CLV / high-churn-risk quadrant – segmented by channel preference and price sensitivity, not just RFM.
Plan:
Targets: churn reduction >15% in 60 days, campaign ROI +22%, retention of high-CLV cohort to baseline.
The Customer Engagement Agent doesn’t depend on your data being clean before you implement it.
SightPulse’s team handles preparation, standardization, and enrichment in the background, so by the time the agent reads anything, it’s analytically ready.




Our customer engagement agent is just one tool in the toolbox. Check out these if you’re working on adjacent decisions.

Sets the positioning and segments that engagement activates against.

Translates the engagement plan into trade and field-side execution.

Coordinates pricing, assortment, and promo around the engagement plan.
A regional retail leader connected POS, loyalty, and e-commerce signals into a single layer.
The Customer Engagement Agent ran predictive models underneath every prompt, and let business users target and activate campaigns three times faster.
No. Sits on top. The agent reads from your CRM, transactional warehouse, and behavioral sources, runs the modeling, and pushes target lists back to your existing campaign tools. Nothing migrates.
Most stacks segment by behavior or RFM and stop there. This agent runs ML churn, CLV, and recommender models per customer, then layers channel propensity and offer logic on top. The output is a per-customer action (channel, offer, discount level) bundled into a list.
The data layer refreshes on the cadence of your warehouse and event streams. The agent reads at prompt time. Churn scores reflect the latest available transactional and behavioral signal.
Bring your toughest engagement question. Watch the Customer Engagement Agent interpret it, run the models on your live data, validate the segments, and stage them for push across the entire B2B2C chain.
All in under 10 minutes. In a live environment, against the real data.