How to stay ahead of risks with a proactive sales data strategy

What separates a good sales data strategy from a great one? It’s not more data — it’s better, high quality, actionable data.

Instead of focusing on predictive insights, too many teams drown in vanity metrics, misaligned dashboards, and CRM clutter. The result? Bad forecasts, slow deal cycles, and reps chasing dead deals.

The best revenue teams do it differently. They prioritize high-impact data points like deal momentum, buyer engagement, and predictive risk scores. This shift leads to faster cycles, more accurate forecasts, and reps focusing on winnable deals, not dead ones.

This approach can work for your team too.

In this article, you’ll learn how to build an effective data strategy that offers insight, drives action, and accelerates revenue.

What makes a great sales data strategy?

A great sales data strategy turns metrics into meaningful actions. It drives momentum, enables informed decisions, and empowers sales teams to deliver predictable results.

While most companies just focus on reactive dashboards and reports, leading revenue teams design successful data strategies that move them from predictions and alerts to action in real time.

Predictive, not reactive

Reactive strategies reveal what has already happened, such as activity metrics or closed deals. Predictive strategies, on the other hand, show you what’s ahead and how to respond. Instead of reacting to problems, you see them coming and proactively address them.

With a predictive strategy in place, sales teams can anticipate risks and save deals before they’re lost.

Action-oriented

Dashboards are great for visibility, but they don’t drive action. If sales reps have to analyze a dashboard to decide on their next move, they’ve already lost too much time.

The best sales strategies replace dashboards with action-driven playbooks that automatically suggest the next step. This improves rep productivity, prevents deals from slipping through the cracks, and most importantly, allows your team to focus on closing deals.

Complete, unbiased data

Bad data leads to bad decisions. That’s why a data-driven sales strategy prioritizes the maintenance of complete, reliable, and unbiased data under sound governance policies. Effective data management results in more accurate reports, forecasts, and at-risk deal indicators, which gives you a competitive advantage.

How to build a winning sales data strategy

A successful sales data strategy doesn’t just happen — it’s designed with business goals, reliable data, and a focus on action. When it’s done right, you can turn data into a powerful driver of sales performance. 

Here’s how to get started:

1. Define strategic business outcomes

Too often, companies start with asking, “What data do we need?” when the real focus should be on the outcomes that drive success. Choose which data you’ll focus on only after that. So, first define what success looks like for your entire organization. For example, you might prioritize:

Shorter sales cycles: Reduce time to close from 90 to 75 days.
More accurate forecasts: Improve accuracy from 70 to 90 percent.
Higher win rates: Increase win rate from 30 to 35 percent.

Outcomes like these should guide the metrics and actions you prioritize in your strategy. Without them, you risk collecting irrelevant data, slowing decisions, and overwhelming your team.

Want even better results? Tie each business outcome directly to its revenue impact. For instance, cutting 15 days from the deal cycle improves cash flow predictability and minimizes end-of-quarter pressure.

Pro tip: Focus on two or three strategic outcomes at a time, like forecast accuracy, sales velocity, or rep efficiency, and build your strategy around them. Tracking three metrics is far easier than spreading your efforts across 30. That approach is much more likely to lead to success.

2. Identify the metrics that matter

The right metrics can make or break your sales data strategy, so focus on tracking the metrics that drive success. This includes leading and lagging indicators:

Leading indicators provide actionable insights into future trends, enabling you to adjust your strategy in real time.
Lagging indicators, such as revenue and win rates, are valuable for reporting results, but they often come too late to influence outcomes.

For example, if your business goal is improving win rates, don’t just measure win rates alone. Instead, track leading indicators like buyer engagement and deal momentum.

It’s really important to establish those leading indicators, things that are going to tell you that you’re on the path towards the successful outcomes you’re trying to achieve. And then make sure you have a clean signal of data to support the measurement of your progress against those early indicators.

Joe Marcin, Former CRO at Kyriba
Reveal Podcast: Mastering the science of selling

3. Build a data infrastructure

Everyone knows that collecting data is important, but not everyone realizes the value of strong data infrastructure. This makes measuring and analyzing challenging, as Forrester research shows: 40 percent of respondents cite data distrust as a major barrier, while 38 percent blame fragmented data sources.

Worst of all, poor data also impacts customer relationship management. So, set your team up for success by building better data infrastructure:

Keep data clean, consistent, and real-time: Inaccurate, incomplete, or duplicate data undermines forecasts and insights.
Automate data hygiene: Use tools to automatically remove duplicates, enrich contact information, and eliminate junk data.
Provide a single source of truth: Combine data from your sales, marketing, and customer success platforms to break down silos and improve alignment.
Set data quality rules: Require that reps complete critical fields, such as “Next Steps” or “Buyer Role,” before they move deals to the next stage.

Pro tip: Instead of only cleaning your data quarterly, implement real-time data hygiene automation so your CRM data is always accurate and up-to-date. Gong, for example, is able to log calls and emails, improving data quality while giving your team more time to focus on selling.

4. Automate data capture

Manual data entry is slow, error-prone, and often incomplete. Automating data capture eliminates these issues.

Use activity-capture software like the Gong Data Engine to automatically log emails, calls, and meetings in your team’s workflows. Gong captures 100 times more data than a typical CRM, giving you a richer, more dependable dataset.

But automation doesn’t stop there. Artificial intelligence (AI) takes it further by turning captured data into valuable insights. For example, Gong AI analyzes activities to create deal health scores, pipeline trends, and risk alerts.

By automating data capture and analysis, your team can gain a competitive edge, work smarter, and close more deals.

5. Operationalize the strategy

A sales data strategy is only as good as its execution. To make it work, turn your strategy into a playbook that sales, marketing, partner and customer success teams can easily follow. Automate processes wherever possible to drive consistency and efficiency across those teams.

Also use alerts and triggers. In 2023, 44 percent of deals were lost to inaction, while 41 percent were lost to silence. Real-time alerts can address these issues by prompting immediate action from reps and sales managers. Set up platforms like Gong to flag deals that haven’t progressed in 14 days.

Create playbooks for common scenarios. For example, if a deal goes quiet, trigger a playbook that tells reps to send a follow-up email or re-engage potential customers.

Operationalizing your data-driven strategy ensures that deals stay on track and momentum is never lost.

6. Automate decision-making

Automation and AI can take you beyond tracking metrics to automated decision-making. It’s also great for revenue growth. Companies leading in automation see up to 20 percent higher revenue and 20 percent lower service costs.

Instead of relying on dashboards to identify risks, let AI surface them for you. Solutions like Gong use predictive models and scoring techniques to spot at-risk deals before they’re lost. Gong will then automatically suggest the next best actions for reps, such as “Reach out to [PROSPECT’S NAME] today.”

Don’t forget to automate pipeline alerts as well. For example, you can have your solution notify reps and managers if a deal stays in “Proposal” for more than 10 days. The alert could even include an email template for the rep to personalize.

Automated decision-making around next best tasks ensures faster, smarter actions that keep deals moving and revenue growing.

7. Review, adjust, and optimize

Building a sales data strategy is just the beginning. Continuous improvement keeps it effective over time. Make sure you regularly track performance, review results, and adjust to meet market conditions.

Hold monthly strategy reviews to evaluate lagging indicators (win rate, revenue, etc.) and leading indicators (deal momentum, conversion rates, time-in-stage, etc.). Gather feedback from reps, managers, and sales leaders to identify what works and what doesn’t.

Always incorporate lessons learned into your playbooks, preferably automatically. For instance, if you see recurring problems (like deals getting stuck in “Proposal”), turn them into a playbook or alert so you have a roadmap for what to do when they happen.

Optimization keeps your strategy agile, effective, and ready for what’s next.

Don’t forget these high-impact data points

Sales teams run on data, but missing certain metrics means you leave opportunities on the table. Some of the most impactful data points are those you aren’t tracking yet — but should be. Here are the high-impact metrics you can’t afford to overlook:

Buyer engagement data for deal health

Buyer engagement is one of the strongest predictors of deal success. If buyers aren’t opening or replying to your emails, attending meetings, or interacting with your sales materials, the deal could be at risk.

Keep an eye on these key engagement metrics:

Email opens and clicks
Email replies and email velocity
Content views
Meeting attendance
Call participation
Document interactions

This data can highlight the early warning signs of disengagement. Use it to trigger deal health alerts so your team can intervene and keep deals moving forward.

Deal momentum data for forecast accuracy

Momentum is a powerful indicator of whether a deal will close on time, as it reflects how quickly deals are progressing through the pipeline. Steady movement often leads to success, while stalled deals are less likely to close.

Monitor these essential data points to gauge momentum:

Time in stage
Days since last movement
Days since last buyer activity
Overall deal velocity

Use these metrics to trigger “stuck deal” alerts for reps and flag high-risk deals for managers.

Deal health data for proactive intervention

Don’t wait for deals to fall through. Instead, track their health in real time and act before it’s too late. Deal health scores combine multiple data points — like engagement, velocity, and activity — to predict whether a deal is at risk.

You should track these critical deal health metrics:

Deal health scores: Predictive AI-based scores combine buyer engagement, momentum, and risk signals.
Risk factors: These are also AI-driven, and include “deal stuck” warnings, missing decision-makers, or new competition entering the picture.

Pro tip: Leverage AI-driven deal scoring to automatically prioritize likely deals. Then, use AI-driven insights to forecast risk, coach reps, and close more of them, more often.

Act on the right data at the right time with Gong

If you want to win more deals, don’t focus solely on tracking more data. Focus on acting on the right data at the right time.

With a proactive, action-driven sales data strategy — backed by AI — you’ll know which accounts to focus on, when to engage, and how to keep deals moving. 

No more chasing unqualified leads or missing opportunities. With the Gong Data Engine, you can spot risks, drive action, and stay ahead of the competition.

Gong’s Revenue AI platform lets you turn your sales data strategy into action. From buyer engagement to predictive risk scores, it will show you exactly where to focus, and when. 

Book a demo today.