Unlock Sales and Marketing Potential with AI/ML-Powered Analytics Solutions

Customer Churn Modeling: Providing your Sales reps with high-likelihood-to-churn customers along with detailed insights on why the customer was deemed high-risk. This includes presenting analytically driven strategies to retain the customer and reduce churn rates effectively.

Customer Cross-Sell Optimization: Giving your Sales teams machine learning-driven, actionable insights on cross-sell opportunities for high-potential customers based on historical transactional patterns and similar customer behaviors. This enhances upselling potential and customer value.

Customer Lifetime Value (CLV) Modeling: Partnering with your Sales and Marketing teams to determine the financial value for each customer over the duration of your relationship. Predicting CLV helps you allocate the right resources for marketing, loyalty programs, and sales targeting efforts, ensuring long-term profitability.

CRM Data Opportunity Analysis: Helping your Sales and CRM groups evaluate the depth and breadth of your CRM platform. Ensuring that you have the correct tactical information paired with crucial customer performance insights and predictive behaviors, such as CLV, propensity to churn, or upsell. This drives Sales ROI and rep productivity upwards of 2-10%.

Sales Mix Optimization: Helping you maintain the right balance between growing your unit sales, maximizing transactional gross profit, and driving incremental cash generation from manufacturer or distributor rebate programs. This ensures optimal sales performance and profitability.

Customer Journey Analytics: Mapping and analyzing customer journeys to identify key touchpoints, pain points, and opportunities for engagement. This enables tailored marketing and sales strategies that enhance customer experience and conversion rates.

Marketing Mix Modeling: Leveraging best-in-class open-source Machine Learning algorithms to understand and decompose the marketing and promotional drivers of your sales performance. This includes breaking down your sales volume into baseline vs. incremental effects from advertising, enabling effective budget allocation.

Marketing Campaign Effectiveness: Helping your Sales, Finance, and Marketing teams evaluate the effectiveness of each marketing medium and campaign. This includes granular insights like saturation curves and the share of marketing spend vs. share of impact, laying the foundation for optimizing your marketing budget.

Marketing Spend Optimization: Utilizing optimization algorithms to allocate your marketing dollars to suitable advertising mediums for the upcoming planning year. This maximizes sales or profit impact, ensuring efficient use of marketing resources.

Marketing Knowledge Graph: Using cutting-edge graph database technologies (Neo4j) and machine learning, we construct a detailed map of your customer journeys and marketing touchpoints. This solution excels in providing multi-touch attribution, tracing the complete customer journey, and offering insights into channel, campaign, and message effectiveness. Businesses can optimize customer paths, tailor experiences, and elevate their marketing ROI through clear visualization of customer and channel pathways.

Customer Sentiment Analysis: Using Natural Language Processing (NLP) to analyze customer reviews, feedback, and social media mentions to gauge customer sentiment towards your brand and products. This helps in adjusting marketing strategies and improving customer satisfaction.

Personalization Models: Creating models for personalized customer experiences and recommendations.

Multi-Touch Attribution: Building ML models to understand omnichannel marketing effectiveness.

Sales Knowledge Graph: Leveraging state-of-the-art graph database technologies (Neo4j) and machine learning, we design a comprehensive blueprint of your sales activities and customer touchpoints. This system pinpoints the most effective sales interactions, maps the entire customer engagement process, and delivers insights into touchpoint, pitch, and follow-up efficacy. By illustrating sales trajectories and customer interactions, businesses can fine-tune their sales strategies, customize outreach, and boost their sales ROI.

Total Profit Analytics (TPA): Partnering with your Sales teams and key clients to develop Sales rep and Customer-facing tools customized to your business and B2B customer profiles. Our Total Profit Analytics tool integrates each customer's historical transactional sales and profitability data with manufacturer or distributor rebate information and syndicated market insights. This produces profit-maximizing sales strategies for your customers, augmenting your sales transformation from tactical to insights-based selling, increasing customer profitability, and driving customer stickiness and repeat purchases.

Customer Segmentation: Equipping your Sales, Marketing, and CRM teams with custom-built customer segmentation models based on purchase patterns (RFM analysis), communication preferences, email and phone call sentiment analyses, survey responses, and other relevant attributes. Updated behavioral customer segmentation capabilities help drive sales conversions, improve customer service, and increase customer loyalty.

RFM Descriptive & Predictive Insights: Gaining deep insights into your customers' purchase patterns (Recency, Frequency, Monetary) to inform surgical sales and marketing efforts. Extending classical RFM analysis by building predictive models to understand which customers will purchase again in the next 30/60/90 days, how much they will spend, and which customers need proactive engagement to maximize sales results.

Sales Territory Optimization: Analyzing and optimizing sales territories to ensure equitable distribution of opportunities and workload among sales reps. This enhances sales coverage, reduces costs, and increases sales effectiveness.

Sales Pipeline Analytics: Providing insights into the health of your sales pipeline, identifying bottlenecks, and forecasting future sales performance. This helps in making informed decisions to improve sales processes and outcomes.

Sales Incentive Optimization: Designing and analyzing sales incentive programs to align with company goals and drive desired sales behaviors. This ensures that incentives are motivating the sales force effectively and contributing to overall business objectives.

Automated Machine Learning models (MLOps): Automate and enhance the entire ML lifecycle, ensuring continuous integration, reliable performance, and scalability of marketing models.

Real-Time Business Intelligence Integration: Combine machine learning with BI tools (e.g.: Power BI, Tableau) or custom-built web apps to deliver real-time data visualization and actionable insights, empowering marketing teams to make informed decisions.

Expert Model Refinement & Redesign: Provide expert guidance to refine and redesign AI/ML models, ensuring improved performance, reliability, and scalability to meet evolving marketing needs.