| | JUNE 20199CIOReviewAccording to research cited by McKinsey, organizations that leverage customer behavior data to generate behavioral insights outperform peers by 85% in sales growth and more than 25% in gross margin.3. Use artificial intelligence to get predictive recommendationsGiven the immense amount of data that exists today, product managers can apply AI/deep learning and machine learning methods to develop recommendation engines. Machine learning can provide guidance on trends product teams may have missed. Once data is cleansed, normalized and analyzed, product teams can more easily predict what their next move should be. Our own proof of concept for resume and job recommendations predicts which candidates are most likely to be hired using AI and ML,so recruitment teams can fill roles faster in a time when jobs outnumber talent. Other features like candidate search, job search for candidates, content and salary recommendations are initial ideas that we're working on feasible solutions for using AI and ML. 4. Use data to make better informed decisionsBefore analytics were in the picture, product decisions were based on gut notions. Instead, use data to drive more informed decision-making.Wal-Mart uses data to its advantage by browsing behavior data to constantly learn and improve the understanding of its shoppers, their habits, and their needs. This information is used to ensure the business maximizes profits. Vanguard and Fidelity investment firms use customer data to recommend them investment opportunities, retirement planning and more, which in turn, boosts the company's own profits. 5. Incorporate analytics to inspire your roadmap and end-to-end strategyProduct development is a critical part of being a product manager. Roadmaps must be driven by a strategy that has built-in analytic components with ample feedback from the above steps, and should contain a checks and balances approach that's scalable, easily susceptible to automation with replicable dependencies (nosand-pile approach).Once you have digested the data, you should have the tools to build an entirely unified approach integrating all pillars of the business (sales, marketing, technology, etc.). It's a significant effort where different parts of the business contribute. For instance, the results from our work with Google for Jobs is worth mentioning here as it is guiding our roadmap strategy to create better can didatesourcing products for our customers. Our partnership with Google is driving more relevant talent directly to our client's career sites (a 134% increase in candidate traffic) instead of third-party job boards.Product managers that best utilize insights derived from past data will have the most success now and in the future. From initial concept to product deployment, if you're not taking advantage of the insights your data offers, your business -- and your customers--could be missing out. Knowing what customers want to solve with a product is more important than what customers are saying about the productPeter Modica
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