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

The Problem

Sales and marketing leaders often struggle to reach sales goals and achieve marketing ROI targets because they lack a clear understanding of their customers' value drivers and pain points.

The data is there, but converting it into actionable insights is an uphill battle. The lack of usable customer analytics makes marketing optimization and sales optimization difficult, limiting the commercial team's ability to mitigate customer churn, increase upsells and cross-sells and boost win rates.

The Solution

Revology Analytics offers AI/ML-driven solutions that drive marketing and sales productivity. We leverage our expertise in customer analytics, segmentation, and marketing mix modeling to understand the customer better and help create customized strategies to address customer needs and unique pain points in each segment.

Our approach harnesses machine learning to evaluate marketing effectiveness and predict customer purchase behavior to improve sales and marketing ROI.

The Outcome

By leveraging marketing and sales insights from client and 3rd party data, we enable impactful solutions to their marketing and sales challenges, whether building Marketing Mix Models, Insights Tools for the Sales teams, or sophisticated customer lookalike models for better targeting.

Our automated insights capabilities put the key performance indicators of our client's marketing and sales campaigns at their fingertips, empowering them to make informed business decisions. The results speak for themselves: Our clients have reported substantial increases of 5% to 10% in gross profit and impressive improvements of 5% to 20% in marketing ROI.

The Revology Edge

Steering clear of generic, cumbersome, and expensive analytics products, our philosophy is to work with your Sales, Marketing, Data, and IT teams during the critical development and implementation phases.

We deliver bespoke, intuitive AI/ML-powered Sales & Marketing Enablement solutions readily adaptable to your business needs. Our typical engagement timeline is a focused 3 to 4 months, ensuring timely and practical integration.

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Insight to Outcome: Transformative Analytics for Peak Sales & Marketing Performance.

+10-15% EBITDA growth relative to Competition
+2-10% Sales Productivity Increase
+5-20% Marketing ROI Increase

We engaged with Revology Analytics to establish a foundation for our RGM capabilities focusing on an initial diagnostic engagement and on-demand RGM & Sales Growth analytics - mainly trade promotional optimization, promotional compliance, pricing implementation, and top-line opportunities like white space/new distribution. To date, they have helped the organization become a more oriented revenue growth management organization with more rigor, analytics, and, more importantly, providing valuable real experience on implementing with our customers. I recommend Revology Analytics whether you are starting your RGM journey or need a partner consultant for a specific on-demand project. The projects that Revology has delivered to us would help the organization to deliver 2023 Targets.

Alberto Perez - Director of Finance, Nestle USA

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We Will Find an Answer to Your Questions

Where are my most significant retention, upsell, and cross-sell opportunities to drive sales growth?

What is the ROI of my marketing spend, and how can I optimize my marketing mix?

How can I leverage my data assets to drive incremental value for my sales teams and customers, including shortening sales cycles and increasing win rates?
How can I ensure my sales and marketing strategies are continuously optimized for performance?

How can I enhance my customer experience and engagement throughout the customer journey?

Learn About Our Sales & Marketing Enablement Advisory Services

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.

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Example of our Sales & Marketing Enablement AI in Action

Examples of Prior Deliverables

Customer-facing Assortment and Profit Optimization SaaS solution for leading durable goods wholesaler using transactional and customer data that increased Customer profitability and drove Customer Share of Wallet.
Customer Segmentation model for SaaS Corporate Startup using transactional data, demographic and psychographic information, and Call Center data that streamlined and improved GTM strategy.
C-store Assortment Optimization tool for private CPG's Sales Team, used to drive company Share of Wallet through Insights-Based Selling.
Sales Territory realignment & optimization for SaaS Corporate Startup using transactional, CRM, and competitive data that increased Business Development Manager productivity and reduced travel times.
Dealer Churn and Upsell modeling for a specialty Finance company to help prioritize Customer outreach efforts for the Sales organization, leading to greater Sales Productivity and Revenues.
Marketing Mix Modeling for private Food & Beverage company to understand marketing medium and campaign level ROIs that led to following fiscal period marketing budget and mix allocation adjustments for higher Marketing spend returns.
Customer-facing Market & Pricing Intelligence SaaS solution for leading durable goods wholesalers that drove greater Customer stickiness and aided in developing Consultative selling capabilities.
Augmented RGM capabilities for ~ $1B Food & Beverage CPG through on-demand RGM and Sales Growth Analytics capabilities, focusing on promotion effectiveness & optimization, strategic price increases, and white space opportunities for top-line growth.
Sales & Marketing Knowledge Graph for ~$100MM B2C enterprise to visualize customer journeys, optimize marketing interactions and increase marketing ROI.
Sales Enablement Roadmap for a Startup: Developed a product-implementation plan leveraging knowledge graphs and ML for hyper-personalized sales recommendations.
Offline-Policy Evaluation for Cost-Effective Personalization: Implemented frameworks to fine-tune personalization strategies without constant live experimentation, minimizing customer disruption.
Knowledge Graph for Customer Journey & Browsing Paths (Fortune 100 Retailer): Mapped user clickstream behaviors, improving product recommendations, on-site search relevance, and conversion rates.
Product Compatibility Engine for a Major Retailer: Built a hybrid rules-based and machine learning inference system to evaluate product compatibility across large online assortments.
Cross-Selling Recommendations for a Fastener Manufacturer: Developed a recommendations engine supporting field sales reps, resulting in significantly increased attachment rates for related products.
Lookalike Audience Modeling for a Leading Nonprofit: Leveraged demographic, psychographic, and transactional data to expand donor or customer acquisition through high-probability “lookalikes.”
Uplift Analysis Using Causal Inference: Identified customer segments most responsive to marketing or sales actions, driving more cost-efficient campaign targeting.
Unified Voice of Customer: Multi-Channel NLP Pipeline: Deployed a consolidated sentiment-analysis dashboard to track customer feedback across social media, call centers, surveys, and online reviews.
Marketing Mix Modeling for a Thrift Retailer / Nonprofit: Measured and optimized media and campaign-level ROIs for a multi-channel nonprofit, refining budget allocations for higher returns.