By tracking customer movement from Loyal to Churn Customers or from new customers to VIP customers by the level of customer activeness and engagement. This analysis allows a brand to determine appropriate actions, trigger targeted marketing automation messages, and deliver relevant content to retain valuable customers and attract potential ones.

Harness advanced data analytics and AI algorithms to attract and retain families. Leverage personalized recommendations and targeted rewards to drive collective mission progress, enhancing familial engagement.

Our system can provide detailed segment trends, such as the number of customers, purchases, and revenue over time. With additional filter ideas like website traffic, enrollment, active subscribers, and date and week time charts, businesses can identify patterns and make informed decisions to optimize their marketing efforts.

Aggregates data points from various platforms such as websites, Email, SMS, WeChat, Facebook, WhatsApp, Line, and more, providing a comprehensive view of customer interactions across multiple platforms to reveal how platforms relate to customer behavior.

Simplifies grouping customers based on behavior using automation and machine learning. It automatically identifies segments like “High-Spending”, “Frequent Buyers”, “Prospects”, and “Inactive”. This streamlines contact management, delivers targeted messaging, and alerts brands.

To kickstart your efforts, our CRM system provides default customer/member segments and templates. You have the flexibility to refine, add, or remove segments over time as your business evolves.

Tags provide distinct records for precise segmentation, generated automatically from customer actions, encompassing service types, demographics, lead sources, and company sizes. Automation simplifies tag applications and adjustments, saving time and minimizing manual errors. AI-driven algorithms analyze customer data, ensuring consistent and accurate tagging across a diverse customer base, ultimately enhancing segmentation capabilities.

Use AI to assign sentiment tags (positive, negative, neutral) to customer feedback, social media posts, and reviews. This aids in tracking customer sentiment and making data-driven decisions.

After gathering data, an AI-driven system extracts meaningful information aligned with tag definitions and automatically assigns tags to customers. These customer tags are then utilized to suggest products, content, or services tailored to their interests, continuously improving recommendations through machine learning algorithms.

Streamline customer complaint resolution and support by easily staying in touch with customers throughout the process. When a customer registers a complaint or creates a support ticket, our system includes follow-up features to promptly provide updates to the concerned customers, assuring them that their issue is being addressed. This proactive approach enhances customer satisfaction by keeping them informed and reassured that their concerns are actively being resolved.

Employ standardized survey templates to collect feedback from customers across various platforms like WeChat, Email, SMS, Facebook, WhatsApp, and more, utilizing geotargeting to optimize survey outreach.

CLV estimates a customer’s total revenue potential throughout their relationship with a company. Parameters account for purchase history, retention rate, customer lifespan, referrals, upselling, social factors, and more. This informs decisions on acquisition, retention, and targeted marketing, maximizing revenue from high CLV customers and enhancing lifetime value.

Using machine learning, AI determines customer value by identifying the benefits of specific services and the costs associated with accessing these services. This evaluation is crucial when businesses want to find high-value customers for targeted marketing efforts, allowing for better resource allocation across different platforms.

An analytical resource for visualizing user journeys and conversion funnels. Detect drop-offs, optimize website flow, guide users to desired actions such as visiting specific pages like the blog, and enhance user experience.

Our retention software identifies the most effective event or behavioral trigger to automate message delivery, ensuring timely and relevant communication with customers.

Studies preferences through surveys, feedback, and purchase history. Customizes offerings for enhanced satisfaction, fosters brand loyalty, and drives repeat business.

Examines customer visit frequency and timing for optimized staffing, marketing strategies, and resource allocation, improving overall operational efficiency. For example, a retail store can determine peak hours for higher foot traffic.

Quantifies customer interaction consistency based on visit frequency, purchases, or other interactions, aiding retention strategies and helping businesses identify and reward loyal customers effectively.

Evaluates loyalty program engagement through reward redemption, guiding program refinement, and offering more compelling incentives.

Evaluate EDM marketing performance across multiple platforms, including email, social media, printed materials, and SMS text messages, by analyzing key metrics like Click Rate, Conversion Rate, Response Rate, Open Rate, Subscribers (Opt-ins, opt-outs, and unsubscribes), revenue (cost, conversion, and purchasing history), and Deliverability to enhance marketing strategies effectively.

Evaluating various ad campaign types (YouTube, Facebook, Instagram) based on Revenue, Clicks, Impressions, CTR (Click-through Rate), and Leads generated, to gauge the effectiveness of advertising efforts.

Measuring registration, Conversion (Sales), and Traffic to evaluate the success and impact of events, helping businesses understand attendee engagement and event outcomes.

Analyzing how customers respond to certain variables like price changes, new products, discounts, or new brands, using a Single Customer View to tailor marketing strategies and offerings to customer preferences.

Categorizing churned customers by age, payment behavior, and other factors, and creating Customer Churn Profiles with churn dates, churn risk assessment, and spending history to identify patterns and improve retention strategies.

Integrates data for valuable customer insights and data-driven decisions, improving overall business performance and customer satisfaction.

AI analyzes customer attributes at touchpoints for personalized engagement, helping businesses build strong relationships and improve customer journeys.

Utilizing AI-powered models, businesses can provide targeted suggestions regarding the next purchase category and item for new customers. This capability enhances personalized marketing campaigns by predicting what customers are likely to purchase next. For instance, new customers often start with popular products. AI can recommend focusing on promoting these best-selling products in upcoming campaigns to maximize sales opportunities.

AI algorithms can forecast the next purchase date, aiding businesses in strategizing marketing campaigns and promotions. For example, a restaurant can anticipate increased demand for breakfast sets during holidays, based on AI predictions indicating higher breakfast customer traffic. This data is also valuable for identifying inactive customers who may be at risk of churning, enabling proactive retention efforts.

AI algorithms can recommend complementary products based on items in a customer’s shopping cart, facilitating cross-selling strategies. This process is streamlined by leveraging real-time data to propose relevant bundles, thereby enhancing the customer’s shopping experience and encouraging additional purchases. Businesses can incentivize bundled purchases through discounts, leveraging AI insights to identify bundles that are likely to appeal to customers during the checkout process.

Using AI, businesses can intelligently categorize their products and provide tailored recommendations based on customer preferences. For instance, customers who prefer caffeine-free options will receive recommendations for drinks without caffeine. This capability is particularly beneficial for businesses with products containing multiple ingredients or components, enhancing the accuracy and relevance of product suggestions for each customer.

Predictive analytics identifies the optimal personalized offer tailored to individual preferences, behaviors, and interactions, which can be directed at individuals, events, or specific target groups. This enhances cross-selling, upselling, and ultimately elevates customer satisfaction.

Predict shifts in customer segments and business trends to proactively address customer needs and capitalize on market opportunities. For instance, when customers transition from the “Active” segment to the “Churn” segment, merchants can target them with winback emails.

Predicting customer responsiveness to business suggestions, such as alterations in product pricing, packaging, discount levels, or rewards, enables the customization of strategies for optimal impact, refining approaches for pricing and incentives.

AI predicts the future value of both new and existing customers, assisting in decisions related to retention and engagement. This helps merchants optimize their customer lifetime strategy and reduce churn with churn propensity modeling, ultimately leading to improved customer relationships and business success.