Pricing Analytics & Optimization
Comprehensive pricing, sales and cost data is crucial to performance measurement and process optimization. Pricing and profit analytics are so valuable that many companies are implementing stand-alone pricing software and AI. But real-world order processing and eCommerce typically produce dirty transactional data with minimal customer, product context. Firms eager to adopt pricing best practices like profit waterfalls, customer-level profitability and optimized guidance struggle to feed pricing software the rich, reliable data it requires.
Customer Segmentation & Profitability
The age-old CRM vision of a 360-degree customer view is as compelling and elusive as ever. Interaction channels and touchpoints have exploded requiring data integration and alignment across countless social and transactional marketing and sales systems. The latest iteration on C360, “Customer Data Platform,” is touted as the path to omni-channel excellence but requires the dynamic integration and analysis of ever-increasing, highly varied structured and unstructured data sources.
Merger & Acquisition Data Integration
The consummation of M&A deals are exciting and stressful events. You want to tap into the synergies as fast as possible, but that requires getting the commercial organizations aligned and up-to-speed on new products, customers and approaches. Post-merger sales enablement requires rapid consolidation of data, systems and processes, with the data serving as the most tangible lynch pin between old ways and the new. Commercial data must be prepped fast and accurately, or the entire business case is at risk.
Data Prep for Machine Learning
ML / AI projects are being launched in droves, with especially high hopes related to enhancing customer experience and sales results. Whether they will deliver the expected value remains to be seen, but it is certain that the quality of the data inputs will be a key factor. Machine learning algorithms are best tuned with diverse data that is often discovered through experimentation. While many data scientists can prep data themselves, is it really the best use of their time and expertise? Given the shortage of experienced data scientist, minimizing the time and effort they spend wrangling can make your data science programs much more productive.
Product Portfolio Management
Achieving the full market potential of a product requires a holistic view of its customers, costs, profitability and channel mix. Pulling this information together across your complete portfolio requires tying product master data with ERP, transactional and CRM data. Product managers that do this work by hand (in excel) may spend more time munging than they do managing.
Channel Sales, Promotions & Rebate Tracking
Channel sales can provide critical market insights and deal validation and is thus required of distributors by many manufacturers. The dirty secret is that most POS is little used because it’s too complicated to match customers, products, quotes and orders. Without closing the loop, channel inefficiencies and blind spots can compromise an otherwise strong channel program.