4 Data Pillars for a Modern Sales Automation Workflow

Tactics post image
Tactics post image

A sales workflow is more than a series of tasks that you no longer have to perform manually. With the right data, automation can be a key part of keeping customers happy and increasing revenue. 

The key phrase here is “with the right data.” It’s the right data that tells you which accounts to target, which leads are qualified, when customers have problems, or where to direct visitors who come to your website.

For example, intent data can help sales representatives send automated prospecting and follow-up emails, while firmographic data is helpful for sales operations teams that need to more effectively route leads to their sales team. 

Standard demographic and contact information is no longer enough to fuel a well-oiled automated sales workflow. 

“Firmographics, technographics, contact information, and intent are what I call core foundational data elements,” says Amit Rai, ZoomInfo’s head of enterprise product and sales. “You need that foundational data so that you can complete the customer journey and provide personalization at scale.” 

The foundational data to fuel an automated sales workflow

Contact data

Business contact data has been the foundation of a sales strategy since the days of the Rolodex and the White Pages. These days, of course, maintaining robust, accurate, scalable contact data is a massive undertaking. For ZoomInfo, that means advanced tech tools, expert verification, and best-in-class privacy compliance.

Firmographic data 

Firmographics reveal whether an account is a good fit. Are they the right size? What does their org chart look like? How many decision makers would you be dealing with? Which sales development rep or account manager should tackle any given account? 

Technographic data 

Technographics tell you what an account’s existing tech stack looks like. This is especially relevant for software companies — is this prospect already using a competitor? Or is there a gap in their tech stack that your solution could fill? 

Intent data 

Intent indicates what key stakeholders at a good-fit account are interested in. Are they visiting your website? Are they visiting other websites and researching problems your solution solves, or evaluating similar products to yours?

Where contact, firmographic, and technographic information tell you the “what” and the “who” part of the buyer story, intent data tells you when to reach out. And as we know, timing is everything in modern B2B sales. 

Supplemental data for your sales workflow

While the core foundational data elements are essential to an automated sales workflow, they’re not the end of the story. These next-level layers of data can provide a degree of insight and guidance that in the past might have only been available to enormous enterprise teams.

Historical data

Historical data is necessary for business forecasting and regression analysis. Essentially, it’s used to predict the future performance of a company. However, it can also be useful for the modern B2B sales rep who is looking for a company’s buying history, acquisition history, or organizational changes. Sales reps can combine an account’s historical data with their current intent data to prioritize leads within their workflows. 

Conversation intelligence (CI)

Conversation intelligence involves call tracking combined with artificial intelligence-powered analytics. CI can help sales reps determine lead quality and outcomes based on talking points covered in a discovery call. Combined with firmographic, technographic, and intent data, reps can automate next steps and follow-up meetings based on conversation topics, lead quality, and where they are in the buying journey. 

Predictive modeling 

Intent data combined with historical account data powers predictive analytics. If you can predict where your customer is likely to go next based on their online behavior, it allows you to be proactive, get customer success involved, and potentially offer them additional features or capabilities that will stop them from churning. Predictive analytics and machine learning can inform your automated sales workflow by alerting sales reps when an account’s intent data (coupled with historical data) shows they may be looking to opt for a competitor’s solution. 

Use Cases for Foundational Data

Sales workflows can be used throughout the customer lifecycle to optimize customer experience, from prospecting, lead routing, and converting to customer retention

Prospecting and sourcing leads

While using data to power your workflows may save time, it’s more about efficiency and optimization. Technographic, firmographic, and intent data tell you who to reach out to, why they would benefit from your solution, and when to reach out to them. 

When you have first-party data (such as a contact database or CRM info) you can combine it with a third-party database (like ZoomInfo) to come up with insights. These insights help determine whether the customer you’re going after is a good, bad, or at-risk account. 

“All of these things are examples of a modern go-to-market platform where sales ops and marketing ops are utilizing this core foundational data, combining that with the first-party data that they may already have about the customer to build automation tools,” Rai says. 

Lead routing/scoring/nurturing

Data identifies a lead or customer problem, then tells you where to direct them to find a solution. For example, if you have a lead whose intent data shows they’re looking for a go-to-market solution, you wouldn’t send them to a customer success representative. You’d send them to sales or business development reps. 

While it may seem elementary, missed connections happen. Making sure that data is backing these everyday decisions can ensure that the prospect or existing customer is connected with the right resources. 

Customer retention

Consider this example: You have an existing customer whose use of your platform is low. Intent data shows they’re conducting web searches for other solutions. 

“In this case, the customer success manager should reach out to them right away,” Rai says. “It’s about combining first- and third-party data together.” 

Without the data layer, you run the risk of losing customers — and every revenue professional knows you’d rather keep an existing customer than chase down one to replace them.

The future of data-driven sales automation software 

In the future, sales professionals can expect more predictive modeling and AI capabilities to enter their day-to-day workflow. But it’s important to remember that without good data, those things aren’t worth much. When you strip away all of the fancy computing and machine-learning functions, you need a clean, standardized database free of duplicates and stale data. 

“If you’re using software, you need to provide intelligence to that software. AI would be useless if you don’t have the underlying data,” Rai says. “That’s why those core foundational data elements are very, very important. And that’s where ZoomInfo specializes.”