If you’re responsible for a sales pipeline—whether you’re running a team or just trying not to drown in deals—analytics isn’t just some checkbox. It’s how you figure out what’s working, what’s broken, and where your time’s getting wasted. This guide is for anyone who doesn’t want another dashboard for dashboard’s sake, but actually wants to use Spoke analytics to make better calls and get more deals closed.
Let’s skip the buzzwords and get into how to actually use Spoke to measure and improve your pipeline. No fluff, just the steps, the pitfalls, and what you can actually do with the data.
Why bother with analytics? (And what to ignore)
Before you dive into another tool, let’s be honest: Most sales analytics dashboards are a mess of vanity metrics. You don’t need to track everything—just what helps you make decisions.
What matters: - Where deals are getting stuck - Which activities actually move things forward - How long it really takes to close - Which reps or channels are pulling their weight (and which aren’t)
What you can ignore: - Data you don’t trust (garbage in, garbage out) - Endless “engagement” stats that don’t tie to closed deals - Fluffy charts no one looks at
Spoke can help, but only if you use it with a bit of skepticism and focus on the metrics that matter.
Step 1: Set up your pipeline in Spoke (don’t skip this)
You can’t measure what you haven’t set up right. Spoke is flexible, but that means it’s easy to overcomplicate things.
Do this first: - Map out your real sales stages. Don’t use the default ones if they don’t match how your team actually works. - Define what moves a deal from one stage to the next. Be concrete (e.g., “Demo scheduled,” not “Interest shown”). - Make sure everyone on your team (if you have one) knows what each stage actually means. Write it down somewhere.
Pro tip: Cut the number of stages down to the essentials. Fewer stages = cleaner data and clearer analytics. If you’re tracking whether someone “read your email” as a stage, you’re overthinking it.
Step 2: Get your data in (and clean it up)
Analytics is only as good as the data you feed it. If your pipeline is full of zombie deals from last quarter, your numbers will lie to you.
What to check: - Close out dead deals. Don’t let “maybe someday” clutter your pipeline. - Make sure every active deal has the basics: value, owner, expected close date, and next step. - If you’re importing data from another CRM, take the time to clean it on the way in. If you skip this, you’ll regret it every time you run a report.
Honest take: This part is boring, but it pays off. Garbage data is the #1 reason people give up on analytics tools.
Step 3: Learn your way around Spoke analytics
Once your data’s in, Spoke gives you a bunch of dashboards and reports. Here’s what’s actually worth paying attention to:
Pipeline Overview
- What it shows: The value and count of deals in each stage.
- Use it to: Spot pileups. If deals always stack up in “Proposal Sent,” something’s off.
Funnel Conversion Rates
- What it shows: The percentage of deals that make it from one stage to the next.
- Use it to: See where you’re leaking the most. If only 10% of deals move from “Demo” to “Contract,” dig into why.
Deal Velocity
- What it shows: Average time deals spend in each stage and overall.
- Use it to: Catch slowdowns. If the average deal is taking twice as long as last quarter, you’ll spot it here.
Activity Impact
- What it shows: Which sales activities (calls, emails, demos) actually correlate with moving deals forward.
- Use it to: Stop wasting time on activities that don’t move the needle.
Rep and Channel Performance
- What it shows: How individual reps or lead sources stack up.
- Use it to: Reward what’s working, coach what’s not, and stop pouring money into channels that don’t convert.
Step 4: Dig into the bottlenecks
Here’s where the analytics start to pay off. Look for: - Stuck deals: Are there deals that have been sitting in one stage far longer than average? That’s your bottleneck. - Drop-off points: Is there a stage where deals disappear at a higher rate? Don’t assume it’s “just the market.” - Rep patterns: Is one person closing faster than everyone else? Learn what they’re doing differently.
What to ignore: Don’t chase every tiny fluctuation. Look for patterns over weeks or months. If numbers spike or crash for one week, it’s probably just noise.
Step 5: Turn insights into experiments (not just meetings)
Most teams stop at “we found a problem.” That’s not enough. Use what you find to run small, clear experiments.
Examples: - If “Demo to Contract” conversion is low, try changing your demo script for two weeks. Measure if conversion improves. - If deals are stalling in “Proposal Sent,” follow up with a call instead of another email for every deal in that stage this month. - If a certain lead source converts poorly, pause it for a month and see if your pipeline quality improves.
Pro tip: Pick only one or two things to change at a time. If you change everything, you won’t know what worked.
Step 6: Build a habit (without drowning in reports)
The best analytics setup is one you’ll actually use. Here’s how to make it stick:
- Schedule a quick weekly review—15 minutes—where you look at just the key charts (pipeline, conversion rates, velocity).
- Don’t overreact to every dip or spike. Look for trends.
- Keep a list of “questions to answer” instead of just staring at dashboards. For example: “Why did deals slow down last month?” or “Is our new follow-up approach making a difference?”
What not to do: Don’t spend hours building custom reports unless you actually need them. Spoke’s out-of-the-box analytics will cover 90% of what matters for most teams.
What works, what doesn’t, and what to skip
What works: - Treating your analytics as a tool for action, not just reporting - Cleaning up your pipeline regularly (yes, it’s annoying, but it’s gold) - Focusing on a small handful of metrics that actually help you make decisions
What doesn’t: - Tracking everything “just in case” - Chasing fancy visualizations instead of real insights - Letting old, dead deals rot in your CRM
What to skip: - Endless meetings about the data. Talk about what you’ll do, not just what you see. - Metrics you can’t explain to a new hire in one sentence.
Keep it simple, keep it honest
You don’t need a PhD in data science or a wall of dashboards to run a better sales pipeline. The whole point of using Spoke analytics is to see what’s working, fix what’s broken, and get back to selling. Clean up your data, watch for real patterns, and make small changes—then repeat. That’s how you actually improve, not just measure.
Don’t get fancy. Start simple, and let your questions drive the way you use analytics—not the other way around.