When they're building a technology stack, sales teams have to contend with hundreds or even thousands of solutions that offer lofty promises of automation, efficiency, and higher revenue.
But without high-quality data to connect them all, most sales tools will eventually fall short of their potential.
When layers of data are tightly integrated with software, sales reps and marketers have the most effective way to engage with prospects and find buyers. Here's how to make sure your sales tech stack is able to deliver on its promises and set your go-to-market team up for long-term, sustainable success.
What Is a Sales Tech Stack?
A sales tech stack is the connected set of software and data systems that sales teams use to find prospects, engage buyers, and close deals. The term "stack" refers to how these tools layer together, with data infrastructure at the foundation and user-facing apps at the top. Each layer shares information with the others to avoid silos and keep reps focused on selling instead of manual data entry.
The key is treating your stack as a connected system, not a collection of isolated tools. When tools operate independently, you get data silos, manual handoffs, and reps wasting time on duplicate entry. A properly integrated stack tracks customer profiles, transactions, communications, and pipeline data so teams can engage prospects efficiently and move deals forward.
Why Your Sales Tech Stack Matters for Pipeline and Revenue
The growth of go-to-market tools and services has led to more options than ever before. But in too many cases, this can result in a clashing, overlapping series of tools. One industry survey estimates that companies use an average of nearly 300 SaaS tools, which can cost upward of $50 million every year.
As Bain & Co. has put it, "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."
An unfocused sales tech stack threatens data integration and usefulness. The result is data silos, tool fatigue, shadow IT issues, and workforce inefficiencies that cost time and deals. A well-integrated stack fixes these problems by delivering two critical outcomes:
Seller productivity and time to value: Reps spend less time hunting for contact info, updating records, or figuring out which tool to use. They get faster access to the accounts that matter, cleaner handoffs between teams, and automation that handles the repetitive work so they can focus on conversations that close deals.
Visibility and reporting for sales leaders: When your stack shares data across tools, you get accurate forecasting, pipeline health monitoring, and the ability to coach based on what's actually happening in deals. No more guessing which deals will close or why reps are missing quota.
CRM: The System of Record for Your Sales Tech Stack
Customer relationship management (CRM) software provides a unified, accurate source of data on prospects, leads, contacts, and opportunities.
With the right tooling and CRM strategy, this software also serves as a portal for tracking and building upon every encounter with leads and customers.
But not all CRMs are revenue-ready. A CRM becomes the foundation for your stack when it has:
Clean, consistent data: No duplicate records, outdated contacts, or incomplete fields that force reps to hunt elsewhere for information.
Standardized deal stages: Everyone on the team defines "qualified," "demo completed," and "negotiation" the same way so forecasts actually mean something.
High adoption: If reps aren't logging activity in the CRM, it's not your system of record. It's just expensive software.
Integration requirements: Engagement platforms, intelligence tools, and conversation intelligence all need the CRM as their source of truth. If your CRM can't connect to downstream tools, you'll end up with fragmented data and manual workarounds.
Common CRM platforms include Salesforce and HubSpot. But the platform matters less than how you maintain and use it.
Sales Intelligence and B2B Data
When sales reps spend too much time calling low-quality leads, deals don't close. And worse, reps are wasting effort that could have been spent pursuing good-fit prospects that actually want to hear more about their products but could instead wind up going with a competitor who reaches out first.
How big a problem is dirty data? A survey from CRM data management company Validity found that over half of CRM managers believe the accuracy and integrity of their data is less than 80%.
Additionally, as much as 30% of email addresses go bad after about a year. This low-quality data causes fallout company-wide:
Bad data consumes sales teams' time and budgets
Working with low-quality, productivity-stunting data can drive out top employees
Poor data quality sours the experience for prospects and customers who continually receive impersonal messaging
A lack of reliable data drives a wedge between teams that should work closely, such as marketing and sales
Poor sales data means poor goal setting and business planning
Sales intelligence platforms solve this problem by providing accurate, comprehensive B2B data that every downstream tool depends on. These platforms deliver:
Data Type | What It Provides |
|---|---|
Contact Data | Direct dials, verified emails, and mobile numbers for decision-makers at target accounts |
Firmographics | Company size, revenue, funding, location, and industry details that help you qualify accounts before you reach out |
Technographics | The tech stack installed at each account, so you know which tools they use, which competitors they've bought from, and where integration opportunities exist |
Intent Signals | Behavioral data showing which accounts are actively researching solutions like yours, so you can prioritize outreach to buyers who are ready to engage |
CRM Enrichment | Automatic updates to keep contact and company records current without manual data entry |
When companies approach go-to-market with high-value B2B sales prospecting data, they avoid the mistakes of a purely tech-centered approach that elevates tools over quality information.
"What we really believe is that the data underlying customer outreach needs to be incredibly accurate, totally enriched, and really deep," ZoomInfo CEO Henry Schuck recently told LivePerson. "We are in this unique position as a company, with an offering to really fuel that."
Data enrichment combines information from various sources, including public, third-party, and internal, to provide context and insight to inform the sales approach. Third-party and first-party sources provide sellers with datapoints like professional contact information, company revenue and funding, technology installed, and organizational charts.
Sales Engagement: Turning Data Into Outreach
With a sales engagement platform monitoring interactions, teams can zero in on what works and what doesn't to improve and duplicate successful strategies.
Sales engagement platforms connect intelligence to action. Once you know who to reach out to and why they matter, engagement tools handle the execution across multiple channels:
Multi-channel sequencing: Coordinated outreach across email, phone, and social so you're not just spamming inboxes.
Email tracking and call disposition: Visibility into which messages get opened, which calls connect, and which touchpoints move deals forward.
Personalization at scale: Templates and dynamic fields that let reps customize outreach without starting from scratch every time.
Cadence management: Automated follow-up sequences that keep deals moving without manual tracking.
Clean data improves reply rates and reduces bounces. When your engagement platform pulls from accurate contact records, you're not wasting sequences on bad emails or outdated phone numbers. Outreach and Salesloft (now part of Clari) are common examples in this category.
Conversation Intelligence: Visibility Into Every Deal
Conversation intelligence software analyzes sales calls and meetings. It makes a record of these interactions and pulls out unbiased insights missed in the moment.
Conversation intelligence platforms give sales leaders and reps visibility into what's actually happening on calls, not just what gets logged in the CRM. These tools deliver:
Deal risk identification: Spot stalled deals, missing stakeholders, or objections that signal a deal is slipping before it shows up in your forecast.
Coaching insights: Analyze talk-to-listen ratios, objection handling, and which messaging resonates so you can replicate what top performers do.
Win/loss analysis: Understand why deals close or fall apart based on actual conversation data, not guesswork.
Conversation data flows back to the CRM and informs forecasting. When call recordings and transcripts are tied to deal records, you get a complete picture of pipeline health and can coach based on what's actually being said in customer conversations. Gong is a common example in this category.
Pipeline Management and Sales Forecasting
Forecasting tools depend on clean pipeline data. If your CRM has duplicate records, inconsistent deal stages, or reps who don't log activity, your forecast is fiction.
Pipeline management and forecasting tools help sales leaders understand:
Weighted pipeline: Not all deals are equal. Forecasting tools apply probability to each deal stage so you know what's likely to close vs. what's still early.
Commit vs. upside categories: Separate the deals you're confident will close from the ones that could close if everything goes right.
Deal velocity metrics: Track how long deals spend in each stage and identify where they stall so you can fix bottlenecks before they kill your quarter.
Accurate forecasting requires three inputs:
Standardized deal stages: Everyone on the team defines pipeline stages the same way.
Data hygiene: Clean CRM records with no duplicates or outdated information.
Conversation intelligence insights: Call data that shows which deals have real momentum vs. which ones are just sitting in the pipeline.
AI in the Sales Tech Stack
AI fits into the modern stack by automating the repetitive work that slows reps down and surfacing insights that would take hours to find manually. But AI is only as good as the data it's trained on.
This becomes critical as GTM teams adopt generative AI apps like ChatGPT for prospecting and outreach. Generative AI produces content at unprecedented scale, which means a shaky data foundation gets amplified faster than human teams can catch. Without a strong data quality strategy, you can't have an AI strategy that makes sense for GTM.
AI-powered tools in the sales tech stack handle:
Prospecting and prioritization: AI analyzes intent signals, engagement history, and account fit to surface which leads are most likely to convert.
Meeting prep automation: AI pulls relevant account data, recent news, and conversation history so reps walk into calls prepared.
In-workflow guidance: AI suggests next-best actions, flags at-risk deals, and recommends which accounts to focus on based on pipeline health.
ZoomInfo Copilot is embedded in GTM Workspace to provide AI-assisted insights and automation without forcing reps to switch between tools. The AI surfaces the right accounts, suggests the right message, and automates the follow-up, all within the workflow reps already use.
How to Evaluate and Build Your Sales Tech Stack
Before you add another tool to the mix, you need a framework for evaluating what belongs in your stack and what's just adding complexity.
Start With Your Data Foundation
To identify which GTM activities are working for you, put goals in place along each stage of the sales funnel:
Funnel Stage | Goal Examples |
|---|---|
Awareness | Increase website visitors (total, new, repeat), boost page views, grow trial signups |
Education | Grow qualified leads viewing demos, webinars, product pages, and how-to content |
Trial | Improve conversions from trial signup to usage, and from trial usage to paid usage |
Land | Increase deal value for won opportunities; improve follow-up and re-engagement for lost deals |
Expand | Hit upsell targets; engage new decision-makers within existing accounts |
After you set GTM goals and success metrics using the SMART method, think about the tools needed to meet them. But before you add any tool, ensure your CRM data hygiene is in order. Clean data is the prerequisite for every other stack decision.
Integration and Workflow Considerations
Which tools work together well or integrate easily with your existing programs? This is an important question because data silos arise from dissonant tools.
Look for tools with native connectors to your CRM and other core platforms. API availability matters, but native integrations reduce the risk of data sync issues and manual workarounds. Tools should share definitions and records so a "qualified lead" in your engagement platform means the same thing in your CRM and forecasting tool.
When evaluating integration requirements, ask three questions:
Does this tool sync data bidirectionally with our CRM?
Will it create duplicate records or require manual data entry?
Can it pull from our existing data sources without adding another login?
Avoiding Tool Sprawl and Stack Bloat
Conduct an audit before adding more tools to the mix. Ask which existing tools are meeting your needs, what's extraneous or outdated, and which tools work but need optimization.
Look for signs of tool sprawl:
Redundant tools: Multiple platforms doing the same job because different teams bought their own solutions.
Low-adoption software: Tools that were purchased but never got rolled out or that reps actively avoid using.
Consolidation opportunities: Platforms that combine multiple functions (like ZoomInfo's GTM Workspace) can replace three or four point solutions and reduce the number of logins reps need to manage.
Look for SaaS tools that overcome key friction points slowing your internal sales process and pipeline. Where are leads stalling? Sales engagement software helps you figure that out. Is the ball dropped during handoffs? A conversation intelligence platform gathers intel on leads for smoother transitions.
Build a Sales Tech Stack That Drives Revenue
High-quality customer data integrated within your sales tech stack creates a competitive advantage for sales and marketing teams.
GTM Workspace and GTM Studio provide the data foundation and orchestration layer that connect intelligence to action. Data-driven plays orchestrate workflows that boost rep productivity and their ability to engage higher-qualified prospects.
ZoomInfo delivers accurate, comprehensive B2B data with real-time signals that turn foundational data into actionable insights. Your sales tech stack becomes the infrastructure that separates your GTM team from the competition.
Talk to our team to see how ZoomInfo can become the data foundation for your sales tech stack.