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Every quarter, my clients’ data footprint continues to expand. Whether it’s customer response rates, leads in pipe, or quota attainment, there is always another metric to track.
The motivation for this? AI tools and capabilities are expanding at a rapid clip, but they only make sales more efficient if they’re powered by data. The problem is, many clients don’t know what data to pull or how to organize it.
That’s where a clear sales data collection and analysis process comes in. Learn how to pull in the right data and analyze it effectively. Use insights from that analysis to frame effective sales strategies, while maximizing the impact of AI on your sales process. Then watch as you outperform every sales team in your industry.
What is sales data?
Why is sales data important?
What are the different types of sales data?
How to find and collect sales data
How to track and act on your sales data
A real-life sales data collection and analysis example
What tools do you need to manage and interpret your sales data?
Connect all your customer and sales data in Data Cloud, and get actionable insights that help you sell smarter.
Sales data falls into two big buckets. The first is external data: any information collected about prospects, including demographics, interest, behavior, engagement, and activity as they move through the sales funnel. internal sales data, which includes deal attributes like product type and pricing; and sales rep performance metrics. Together, this external and internal data is used to inform deal actions and gauge progress toward sales targets or other key performance indicators (KPIs).
Have you ever tried to bake a chocolate chip cookie without the right ingredients? It’s a disaster — whole wheat flour for all-purpose flour, raisins instead of chocolate chips, baking soda instead of baking powder. You can throw them all together, but you won’t get a recognizable cookie — and might not get anything edible.
With the right ingredients — paired with a vetted recipe — you end up with cookies that make your mouth water.
That’s the power of sales data. When the right data is combined and analyzed (with the help of AI), it can surface patterns in customer behavior, interest, and needs that were unrecognizable before. Reps can then use those insights to tailor their sales strategies. The result? Faster, more seamless deal cycles. Delicious.
Sales data can be categorized into data on individual customers and companies, like demographic and buying behaviors; and internal sales performance data, including data collected during the sales process. Here’s a close look at these:
Identify pipeline trends based on a unified view of all your account data and sales activities with Sales Cloud.
Sales data that helps you sell better? Sign us up. But how exactly do you find and collect this information? Invest in a CRM that serves as your single source of truth and tracks all customer engagement, automate data collection to keep your information up to date, and carefully incorporate external data while prioritizing security and privacy.
Once you’ve collected your data, it’s time to interpret and take action on that data. First, identify specific business goals or targets. Then, identify KPIs that will help you achieve those goals. Last, map your sales data to those KPIs within your CRM, so you can track progress toward your goals. Make it easier by creating dashboards to make complex data more digestible. Here’s how it all fits together:
Global consulting firm Korn Ferry uses sales data to increase their efficiency. Recently, they were looking to improve win rates and accelerate deal velocity. With CRM analytics, tracking KPIs like win rate and velocity was easy, but understanding how to impact those KPIs required turning data into insights and actions. What attributes were having the greatest impact on win rate and sales cycles? They started by looking at the data to find the answers:
First, Korn Ferry began capturing more data on their opportunities. They combined deal data captured in Sales Cloud with deal data captured by Korn Ferry Sell, their sales methodology application powered by Miller Heiman, built natively on the Salesforce Appexchange. By combining both, Korn Ferry gets a more complete view of their deals, including qualitative information about sales cycles that would historically get captured off-platform in client conversations, meetings, and the minds of sellers.
Next, they dove into analysis. Combining Korn Ferry Sell with Einstein and Sales Cloud Analytics, Korn Ferry uncovered how certain deal attributes — like the relationship with a key buying influence — correlated to success, allowing them to identify trends and adjust both sales strategy and enablement to move the needle on their KPIs.
Korn Ferry also began leveraging AI-driven “opportunity scores” to track the health of their deals after making strategy and enablement shifts. These scores
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You don’t need a heavy tool belt to manage data-driven sales. In fact, you only need two main tools: an intuitive CRM with built-in AI and security, and a sales analytics tool. Often, these are part of the same platform.
Customer relationship management (CRM) software: A CRM that serves as your single source of truth ensures every customer interaction, from initial contact to final purchase, can be stored in the same place. Automation-equipped CRMs do more than just provide a space to manually store data, however. They store it for you by pulling in relevant details from customer engagement sources like emails, phone calls, and video meetings and dropping them into deal records automatically. A big must-have here: a security layer that masks sensitive data so it isn’t visible to anyone on the outside, and a zero-retention feature that ensures no data is retained by your CRM.
Sales analytics and reporting tools: At the very least, onboard an analytics tool that allows you to see the status of your progress toward business goals and KPIs in real-time. Even better, find one with intuitive, customizable sales dashboards, making complex data easily understandable. If you really want to stay on top of the competition, make sure your analytics platform includes AI functionality that delivers recommendations for deal actions and strategy changes based on real-time updates to your sales data. This allows you to stay on top of evolving customer needs and market trends without falling behind — and potentially falling short of your goals.
Sales data does more than provide information you can turn into trackable metrics. it lights the path toward action. To make the most of your sales data, prioritize regular reviews of CRM-surfaced insights, adjusting your sales and enablement strategies to close more deals. Then focus on delivering value that keeps customers coming back.
See how Sales Cloud speeds up the sales cycle with data and AI, making you more efficient at every step.
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