When it’s time to build a technology stack, sales teams are faced with hundreds of solutions that offer lofty promises of automation, efficiency, and higher revenue. But without high-quality data to connect them all, many of those tools can essentially turn into empty boxes that fall short of their goals.
When layers of data are tightly integrated with software, sales reps and marketers have the most effective way to successfully engage with prospects and find their next buyers.
“The foundation of go-to-market success begins with data and intelligence,” says Justin Withers, senior vice president of product strategy and product marketing at ZoomInfo.
What is the Sales Tech Stack?
First, let’s lay out some basics. A tech stack is the collection of software, IT infrastructure, and application programming interfaces (APIs) that a business uses to get its day-to-day work done. In sales, this technology forms a system that tracks customer profiles, transactions, communications, financial data, and related information.
Many parts of the sales tech stack have applications beyond just reaching prospects and closing deals. Some solutions, such as ZoomInfo Enrich, are also useful for marketers building email campaigns or executives doing broad research about their total addressable market.
Assumptions About the Tech Stack
There are some pretty common assumptions about the role of the tech stack.
Corporate thinking often starts from the goal and works backward, Withers says. From that perspective, many companies first consider the technology needed to execute quickly on a go-to-market goal.
Take sales reps. Managers want them to close deals as soon as possible, so they view customer relationship management (CRM) platforms, sales engagement services, and sales conversation software as crucial.
“They’ve got to be communicating,” Withers explains. “So you start with the end.”
However, it doesn’t take long for that assumption to be proven wrong. According to management consulting firm Bain & Company, “As sales and marketing software has proliferated, most B2B companies have assembled a mishmash of tools that, at best, limit the return on investment and, at worst, confuse and overwhelm the front line.”
This problem can be pervasive. Companies use an average of 75 technologies, with the amount going up as the number of employees increases, according to 2020 research from ZoomInfo. At the largest companies, there might be more than 200 distinct technology tools used.
Myth-Busting the Tech Stack
If a sales rep spends too much time calling leads that aren’t good fits, deals don’t close. But this doesn’t necessarily reflect the rep’s efforts. Rather, despite all the software available, the underlying data simply hasn’t provided enough high-quality leads.
So-called “dirty data” is a significant problem for the tech stack. At least one-third of CRM data is suspected to be inaccurate, and email lists decay at an average rate of 23% to 30% annually.
“Investments in technology often precede investments in data,” Withers says. “CRM was that way for sure. It’s the first purchase that an organization makes, and then they realize that it’s an empty box. And so they’ve got to put data in it, and they end up putting a lot of garbage data in it. Then they realize they’ve got to clean up their data to make it useful, and so it’s this whole cycle. Organizations that approach go-to-market with a data-first mindset avoid a lot of the costly mistakes made by taking a tech-first approach.”
Data Drives Engagement
When integrated effectively with technology, high-quality data leads to insights that can help sales professionals connect with the right prospects and close deals faster.
“I think all of the focus on big data for the past 10 years … [is] going to shift to be much more of a focus on what we call big ops, which is about the execution of automations and apps around this data,” HubSpot Vice President Scott Brinker said during a recent episode of ZoomInfo’s podcast “Talk Data to Me.”
At ZoomInfo, we define the modern go-to-market tech stack as comprising three distinct layers that build upon each other
Layers of Data Explained
Let’s explore those three data layers and explain how they relate to each other.
Intelligence Layer
Third-party sources provide sellers with various data points, including professional contact information, company revenue and funding, technology installed, and organizational charts. First-party sources, such as web forms, also provide data. All of this information makes up an initial intelligence layer.
This layer surfaces insights that feed the workflow and engagement layers — for example, a company completes a merger (one data point) that also affects the reporting structure under the CEO (a related data point).
Orchestration Layer
Third-party data is often inconsistent. For example, sales reps enter partial records or lead forms are submitted with incomplete, fake, or personal information.
The orchestration layer is the glue that connects the engagement layer with the intelligence layer. It takes a variety of data sources and stitches them together, cleans and enriches them, and removes duplicate records. The orchestration layer then assigns and routes data, leads, and insights to the appropriate owners. It creates a “living” data set that remains updated and can drive automated business workflows, such as adding a contact to a sequence of marketing messages or assigning a task to a sales rep.
Engagement Layer
Individual interactions between buyers and sellers occur at this stage, such as emails sent to a contact or a website visitor engaging with a chatbot.
An approach called multithreading can also take place in this layer. In a multi-threaded sales approach, if an inbound lead doesn’t convert quickly, reps can identify leaders on the team of the original lead and target them for follow-up.
It’s important to note that data moves between the three layers — the flow doesn’t stop at the engagement stage.
“Everything in the engagement layer is generating data that’s fed back into the intelligence and orchestration layers,” Withers says. “It is absolutely a loop. When that feedback loop is in place and the right tools exist to unify and manage data quality, it creates a cycle that leads to more effective and precise targeting and personalized engagement that converts.”
Modern Tech Stacks Need Technology and Data
When high-quality data is integrated with the tech stack, it creates a strategic advantage for sales and marketing teams.
“Most of the systems of record out there don’t come preloaded with data,” Withers says. “So you’ve got to start with a foundation of data and intelligence, and that’s just the beginning of what ZoomInfo provides … All of those systems cannot deliver on the function that they were intended to without data.”
For that reason, ZoomInfo believes data is the starting point for monitoring your total addressable market and uncovering buyer intent signals from target accounts. From there, data-driven sales and marketing plays can orchestrate workflows that boost reps’ productivity and, ultimately, their ability to engage with higher qualified prospects.