1:00–2:00 pm Central
Sales data is one of – if not your most valuable- resources. But many companies struggle with how to clean and manage their data for better analysis. And every company is on a different stage of its analytics journey. This session will focus on the foundations of successful market analysis – data quality and standardization, segmentation best practice, and sweet spot analysis: where you perform best based on data, and how to use that to target your sales process and prospecting more effectively. When you better understand your core customer segments – your sweet spots of revenue generation – you can identify the best prospects and territories to focus growth efforts.
Key takeaways:
Latest quarterly forecast update for U.S. PT/MC markets
Learn how to transform your data from junkyard to competitive asset!
Best practices to clean, segment, and leverage your customer and product data
Sweet spot analysis fundamentals to help you make data-informed sales decisions
Templates/case studies on segmentation and customer analysis
Presenters
The MDM Analytics team, your presenters for this series, have extensive practical experience in helping manufacturers and distributors elevate their sales, marketing, and data analytics skillsets to drive revenue, make stronger strategic decisions, and improve profitability.
Bob Jordan, VP Analytics.
Bob joined MDM Analytics in 2020 with over 35 years of experience in distribution on both the supplier and distribution side. He has been in leadership roles for strategic account management, customer relationship management and sales management and has been contributing to numerous industry associations over his career.
Donnie Williamson, Analytics Manager
Donnie joined MDM Analytics in 2020 with over 20 years of experience in distribution. He started at the ground level with a large regional electrical distributor and worked his way up to creating and managing an analytics department discovering “actionable” insights to grow this $500M business. Donnie is considered a data expert in his field.
PTDA
www.ptda.org