Moving beyond dashboards

Most business intelligence is reactive. Static reports tell you what happened last week, but they don't help when a customer is on your site right now. We built CE 65 to change that by focusing on what happens next.

We’re moving beyond simply reporting on customer data to proactively uncovering insights that drive action. CE 65 is a digital customer experience platform designed to deliver this new level of intelligence. This isn't about better dashboards; it’s about shifting from descriptive analytics – what happened? – to predictive analytics – what will happen? – and ultimately, prescriptive analytics – what should we do about it?

The core idea is to move away from hindsight and towards foresight. Customers expect personalized experiences now, and businesses need the tools to deliver. CE 65 provides that capability by harnessing the power of AI to analyze customer behavior and identify opportunities for improvement. It’s about understanding the "why’ behind the data, not just the ‘what".

AI transforms customer experience analytics with CE 65 in 2026.

Where the data comes from

CE 65’s AI-powered analytics aren’t magic; they’re built on a foundation of comprehensive data integration. We connect to a wide range of sources to create a 360-degree view of each customer, including website interactions, in-app activity, and CRM data from systems like Salesforce. It doesn’t stop there.

We pull in social media mentions, chat transcripts, and voice recordings. By combining these with IoT sensor data, the system finds patterns that humans usually miss. The platform cleans and unifies this mess automatically so you don't have to spend weeks on data prep.

CE 65 seamlessly connects to popular data warehouses like Snowflake and Redshift, as well as marketing automation platforms like Marketo and HubSpot. This allows businesses to leverage their existing data infrastructure and avoid costly data silos. The goal is to provide a single source of truth for all customer-related data.

Predictive Churn: A Real-World Example

One of the most impactful applications of CE 65’s AI capabilities is predicting customer churn. Identifying customers at risk of leaving before they actually do allows businesses to intervene and prevent lost revenue. Our AI models analyze a variety of indicators to assess churn risk.

These indicators include declining engagement with your product or service, negative sentiment expressed in support interactions (detected through natural language processing of contact center transcripts), and decreased purchase frequency. The AI doesn’t just flag at-risk customers; it also provides insights into why they’re likely to churn.

For example, imagine a B2B customer whose usage of key product features has dropped significantly over the past month, and who recently submitted a negative support ticket mentioning frustration with a specific integration. CE 65 would alert a customer success manager to proactively reach out to this customer, offering assistance and addressing their concerns. This targeted intervention can often turn a potential churn into a renewed relationship.

  1. Website visits and feature usage drops
  2. Frustrated comments in support tickets or on social media
  3. Decreased Purchase Frequency: Fewer orders or lower average order value.

Proactive Customer Engagement with CE 65: A 4-Step Guide

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Step 1: Identify At-Risk Customers with AI-Driven Risk Scoring

CE 65 leverages advanced AI algorithms to analyze customer behavior across all touchpoints – website activity, product usage, support interactions, and more. This analysis generates a risk score for each customer, indicating their likelihood of churn or reduced engagement. The 'Customer Health' dashboard provides a clear, visual overview of these scores, allowing Customer Success Managers (CSMs) to quickly identify customers needing attention. Filters allow segmentation based on score thresholds, account value, or other relevant criteria.

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Step 2: Deep Dive into Behavioral Signals & Root Cause Analysis

Once at-risk customers are identified, CE 65 allows CSMs to drill down into the specific behavioral signals driving the risk score. The 'Customer 360 View' provides a comprehensive timeline of customer interactions, highlighting negative signals like decreased product usage, multiple support tickets, or declining website engagement. AI-powered insights automatically surface potential root causes, such as onboarding issues or feature adoption challenges. This eliminates guesswork and focuses attention on the most impactful areas.

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Step 3: Prioritize Outreach Based on Impact & Opportunity

Not all at-risk customers require the same level of intervention. CE 65 helps CSMs prioritize outreach by combining risk score with account value and potential expansion opportunities. The 'Prioritization Matrix' visually maps customers based on these factors, enabling CSMs to focus on high-value accounts with the greatest risk of churn or lost revenue. This ensures efficient use of time and resources, maximizing the impact of proactive engagement.

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Step 4: Proactive Engagement & Automated Workflows

CE 65 facilitates proactive engagement through personalized outreach campaigns. CSMs can leverage pre-built or custom email templates, in-app messages, or trigger automated tasks based on customer behavior. For example, a customer with declining product usage might automatically receive an invitation to a training webinar. The platform tracks the effectiveness of these engagements, providing insights into what strategies are most successful at re-engaging at-risk customers and preventing churn.

Automated insights for everyone

Historically, unlocking the power of AI required a team of highly skilled data scientists. This created a significant barrier to entry for many businesses. CE 65 democratizes access to AI by automating the process of insight discovery. We believe that valuable insights shouldn’t be locked away in the data science department.

Our platform features automated anomaly detection, which identifies unusual patterns in customer behavior that warrant further investigation. It also provides root cause analysis, helping users understand the underlying drivers of these anomalies. Perhaps most powerfully, CE 65 offers natural language query capabilities.

This allows business users to simply ask questions of their data in plain English – for instance, “Why did sales decline in the Western region last month?” – and receive clear, concise answers. This empowers "citizen data scientists" across the organization to find answers and make data-driven decisions without relying on IT or specialized data science teams.

Personalization at Scale: Beyond Basic Segmentation

Standard segmentation is too broad. Grouping people just by age or location leads to generic marketing that people ignore. CE 65 looks at individual behavior to predict what a specific person actually wants to see.

Instead of simply targeting customers based on their age or location, we can deliver personalized content, offers, and recommendations tailored to their specific interests and purchase history. This is achieved through AI-powered recommendation engines and dynamic content optimization (DCO).

For example, a customer who recently viewed a specific product category on your website might receive personalized email offers for similar products. DCO ensures that website visitors see content that is most relevant to their individual profiles, maximizing engagement and conversion rates. This level of personalization isn’t possible without the power of AI.

Traditional Segmentation vs. CE 65 Personalization

FeatureTraditional SegmentationCE 65 Personalization
Data UsedDemographics, basic purchase history, limited website activityReal-time behavior, contextual data, historical interactions across all channels
GranularityBroad customer groups, generalized profilesHighly specific micro-segments based on dynamic attributes
AdaptabilityStatic; requires manual updates and re-segmentationDynamic; continuously learns and adjusts segments in real-time
Impact on CXOne-size-fits-most messaging, limited personalizationHighly relevant and individualized experiences, proactive engagement
Predictive CapabilitiesReactive; based on past behaviorProactive; anticipates customer needs and intent
Segmentation BasisRules-based; relies on pre-defined criteriaAI-driven; discovers hidden patterns and relationships
Resource IntensityLower initial setup cost, but ongoing manual effortHigher initial investment, but reduced manual maintenance and improved ROI
ActionabilityBasic targeting and messagingPersonalized recommendations, automated journeys, and optimized content delivery

Qualitative comparison based on the article research brief. Confirm current product details in the official docs before making implementation choices.

The Future of B2B CX: Account-Level Intelligence

For B2B companies, understanding the health of key accounts is paramount. CE 65 provides account-level intelligence, allowing businesses to understand the engagement and potential of each strategic customer. This is a significant step beyond individual customer-level insights.

Our platform features relationship mapping, which visually represents the connections between individuals within an account. It also provides engagement scoring, which quantifies the level of interaction between your team and the account. Furthermore, CE 65 helps identify potential expansion opportunities within existing accounts.

This allows sales and customer success teams to prioritize their efforts, focusing on accounts that are most likely to generate revenue growth. By proactively addressing potential issues and identifying new opportunities, businesses can strengthen their relationships with key customers and drive long-term loyalty.

CE 65 AI Analytics FAQ