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Learn from the brightest minds how to predictably and efficiently grow revenue.
Mastering the Art of Relationship Building with Jaime Konzelman, Vice President, Sales at Unisys
In this episode of the Revenue Insights Podcast, host Lee Bierton is joined by Jaime Konzelman, Vice President, Sales North America & Canada at Unisys. They explore the intricacies of cultivating meaningful connections with individuals, delving into various subjects that encompass the significance of relationships and effective strategies for building them in the year 2023....
Establishing a High-Performance Business through Efficient Change Management with Zach Gropper, Founder and CEO at Insight Revenue
In this episode of the Revenue Insights Podcast, host Lee Bierton is joined by Zach Gropper, Founder and CEO at Insight Revenue. In their discussion, they cover several topics, such as the significance of a business operating at a high level, the impact of change management on a business, techniques to enhance business and customer...
Building Trust and Credibility Through Data-Based Feedback with Basil Murray, VP of Enterprise Commercial Sales at DHI
In this episode of the Revenue Insights Podcast, host Lee Bierton sits down with Basil Murray, VP of Enterprise Commercial Sales at DHI, a SaaS platform with AI-enabled products for talent acquisition. The conversation covers several touchpoints in the sales and revenue space, including adapting selling and revenue operations to the current environment and coaching...
Data Driven Sales Ops with Adam Ecevedo, Former Sales Operations Manager at Tableau Software
In this episode of Sales Ops Demystified, Tom Hunt is joined by Adam Ecevedo, Former Sales Operations Manager at Tableau Software. They discuss using data to enable sales reps to be more effective, how to be more data-driven, and handling data quality issues in sales ops.
Adam’s colourful journey through anthropology and army careers into Sales Ops
Every operation uses data, whether it’s choosing a Starbucks store location, learning about anthropology, or being in the army. The common theme in Adam’s career across all fields he ventured into was data. Throughout his career, his ability to analyze proved to be his “highlight skill”. Adam also applied this skill to his work with Boeing’s test and evaluation team, where they had to replace legacy BI systems and unify data from multiple sources.
Using data at Tableau to help sales reps be more effective
Data is used in Tableau to make decisions across the sales cycle, from sourcing leads to closing opportunities. A key function of using data is finding knowledge gaps in this end-to-end process and eliminating any follow-up/hand-off delays.
Tableau’s Sales Ops structure
Strategic Account Executives have a crew of resources to help their customers understand and deploy Tableau at an enterprise level. They also have account executives focused on the small and medium business (SMB) category. The sales ops team helps all levels of sales teams monitor stats and direct them using data-driven strategies.
Tableau’s Sales Ops focus in 2021
Tableau had the opportunity to serve public sector businesses in 2020. The US government’s infrastructure plan will affect the business of their public sector clients. In 2021, they are looking to explore the impact of this plan on their business.
Examples of Tableau using data to improve Sales Ops
Adam’s team uses granular pipeline coverage data to talk to their VP and offer help to improve stats. The goal of the conversation is to “flag the issues,” using their soft skills to convey their willingness to help. They also use historical close rates (up to one and three years) and linearity to validate their forecasts.
Becoming data-driven in Sales Ops
Data-driven is not just an adjective, it’s a way of thinking and a core pillar of your lifestyle. Adam likens this shift to switching to healthier food. At a company level, having a few evangelists with a data-driven decision-making approach helps grow the culture within a company. This approach should permeate all employees across a company and not just teams who need it as a part of their job.
The key to enabling all of this is having a real grasp on the customer’s journey and deeply knowing how you can help them succeed from the data.
Cleanup of historical data
Cleaning up dirty data can be frustrating, but your priority should be simply cleaning up the relevant data set that will affect results and your goal. You should not be focused on changing historical data that will have no business value, as it will waste time and resources with little to no impact. To get value from data, you don’t need it to be perfect. Small imperfections can often be explained and managed.