Picture this: You’re at work (home or office) and need a burst of energy to finish the day.
Instead of going for the good ol’ filtered coffee, you decide to treat yourself to a premium frappuccino coffee from Starbucks.
You get to Starbucks, head to the counter, and no one’s there to take your order. How long would you stick around?
A few seconds, it’s fine. 2 minutes? Maybe. But 15 min of waiting will likely turn into frustration and you’ll head back to the office.
Starbucks just lost a $7 order.
The same thing happens to your revenue when sales are too slow to engage product-qualified leads.
Let’s get it 👇
This guide is for: Sales Management & Rev Ops people at companies with a high-volume self-serve motion.
Why is speed-to-lead so important?
Lack of speed = fading buying intent from prospects.
The harsh reality is, the faster you engage a lead, the higher your chances are of converting that lead into a paying customer.
Indeed, responding within five minutes versus 30 minutes increases the chances of connecting with a lead by 100x and the chances of qualifying that lead by 21x!
Not convinced? More speed-to-lead stats:
- 78% of B2B customers purchase from the vendor that responds first
- Responding within the first minute increases lead conversions by 391%
- Shockingly, the average B2B business’s speed to lead is 42 hours!
- Only about 27% of leads ever get contacted
In a nutshell: Slow speed-to-lead = fading interest from prospects = fewer deals closing 📉
Not so fast. If only leads were this forgiving…
There is a “drop off” point at which a lead’s buying interest will drastically fall. It’s different for every company and finding it is very difficult.
For one of our customers (that I can’t name), they found that if sales don’t reach out within 4 hours of a lead signing up and taking a key action in the product, chances of converting go to almost 0% 😨
And this only accounts for losses in revenue. Let us remind ourselves that marketing dollars are also being wasted when engaging leads too slowly.
You don’t invite someone for dinner with the intention of not opening up when they ring your doorbell, don’t you?
You got it wrong. It’s not a sales issue
Speed-to-lead has always been considered a sales problem.
“Reps ignore alerts.”
“Reps don’t reach out quick enough.”
“Reps don’t personalize outreach to get leads’ attention.”
Slow speed-to-lead - at the core - is not a sales problem, it’s a data problem.
❌ Slow speed-to-lead usually happens because GTM teams focus on improving the time between identifying a lead and having sales engage. Which is a sales execution issue.
✅ Yet you should start by reducing the time between tracking product actions and surfacing that user/account. Which is a data issue.
Here’s why: great sales execution in a bottom-up motion (sales assist, expansion, upsell) comes from 3 things.
⚖️ Prioritization: Are sales focusing on the most qualified accounts and leads?
🎯 Context: Can sale outreach in a contextual manner that either speeds up user’s success in the product or helps them avoid roadblocks (while suggesting upgrades and upsell opportunities)?
⏰ Timing: Are sales engaging leads when there’s intent to have a purchasing conversation?
Wait… What does that have to do with data?
In PLG, the data contains answers to your prioritization, context, and timing problems.
Let’s use the same statements as above and explain what causes them.
“Reps ignore alerts.” → Because the quality of leads sent to them is a mixed bag and requires another round (or two) of filtering down.
“Reps don’t reach out quick enough.” → Because they have to dig into countless tools to manually research account activity.
“Reps don’t personalize outreach to get leads’ attention.” → Because they don’t have the insight they need to make outreach contextual and personalized.
It is Revenue Operations’ responsibility to enable sales reps to act fast.
Let’s break down how Revenue Operations teams can improve speed-to-lead for sales:
⚖️ Prioritization: How to know which leads are actually worth sales’ time
Some leads show intent but SHOULDN’T BE TOUCHED by sales.
- Don’t have enough revenue potential to justify reps’ time
- Can reach their full revenue potential without sales help.
I call it the lead blindspot 👇
Lead blindspots are caused because we humans are very bad at discerning between good and bad leads when the data volume is high, which is the case in PLG (more on why you shouldn’t have humans score leads here).
Furthermore, you can cannibalize organic conversions by having reps reach out too soon.
Lead prioritization fixes that problem and ensures that the right leads are touched at the right time.
Below is an example of criteria Grammarly’s rev ops team takes into consideration when prioritizing accounts that are ready for enterprise sales.
From Riley Harbour, Grammarly’s head of Business Development:
First, we look at product usage. We stack rank based on free users, premium users, and weekly active users within a given account, as well as recent sign-ups within the last 30 days. We monitor trends, such as increases or decreases in active users, over time. Second, we look at whether or not the account’s firmographics match our enterprise criteria, meaning that the account either has a revenue potential over $X of annual revenue or the employee count is greater than 5,000.
Read Grammarly’s complete enterprise expansion playbook here.
A other key piece of advice from Jared DeLuca, Marketing Ops at Appcues is to automate prioritization efforts as much as you can and leave the subjective prioritization to reps:
We’re starting to explore ways to incorporate PQLs and usage-based metrics into our scoring, such as inviting a new user or visiting a specific area of the product. This will make everything from our go-to-market messaging and sales conversations that much more sophisticated.
Learn the 5 pivotal changes to Appcues’ PLG strategy here.
Even after setting up a prioritization funnel like Appcues, you might still have too many sign-ups coming in and want to minimize the additionalprioritization done by reps.
Consider AI scoring models.
Top PLG companies like Netlfiy and Jasper leverage AI prospecting models to find leads with the highest potential. AI can look at all your past paid conversions and find correlations between product usage patterns and potential to be worthwhile for sales.
🎯 Context: How to give reps the information they need to act, in one place
When David Barron first introduced the sales-assist motion at HubSpot, reps resisted it. They saw sales-assist deals as more complicated to approach and with less revenue potential.
When they get a lead, David told us that tell reps need to know EXACTLY what they have to do:
Let’s say you have this crazy freemium funnel with volume coming through, you must give your team all needed information to take action and get quick wins.
Here’s what Hubspot did 👇
Every time a new Product-Qualified Lead would be flagged, reps would receive a video recording of their exact usage of HubSpot, along with information about the account and its users. When seeing the user moving around the product, reps were able to understand exactly where they’d get stuck or see value.
After 1 min, reps understood why the account was qualified and why they needed to reach out. This cut speed-to-lead times and increases pipeline.
Another option is to provide your sales reps with a dashboard that gives them an overview of an account’s product usage history, along with key users and important business context, like below.
⏰ Timing: How to get leads to sales in time
By now, you should have a good idea of which leads are worth passing to sales, along with the context they need to take action.
Next is getting to leads in front of them asap. But before you rush things, it’s important to know where your drop-off point is.
Your drop-off point is the point in your customer journey at which a qualified user’s intent to purchase your product decreases significantly.
Remember the graph at the beginning of this article? Here’s where the drop-off point is:
Finding your intent drop-off point (most often) resorts to collaboration between Product, Data, and Rev Ops.
2 popular frameworks to find it ⬇️
1️⃣ Look at your self-serve funnel.
What is the time between the aha moment (activation) and a frequent conversion point (monetization)?
Chances are, the drop-off point is around your self-serve conversion point. So try to get sales to reach out before that time.
This is where a lead prioritization layer comes into play, you only want to engage users that are qualified and want to hear from sales.
2️⃣ Look at historical product usage.
Where do people churn? Where do you see a drop in usage? Start at that point in time and work your way back until you find your drop-off point.
Now that you have assumptions around drop-off, how do you actually reduce the time it takes for a lead to get in front of sales?
Most internal data syncs or manually built reporting between tools happen once a day (or in 24hr periods), so even if your sales rep picks up the dialer or sends an email the second he/she gets an alert, it’s too late!
A few remedies ⤵️
Increase the frequency of your internal data updates
You can increase the frequency of your internal system’s data updates. Similarly, you can increase the frequency of your reporting.
If cost is in play regarding your data, you can leverage a Product-Led Sales platform to sync product data in real-time. With a PLS platform, leads are routed to sales workflows as soon as they take qualifying actions.
Send alerts to sales
Slack or email alerts that are often ignored by reps. But since you followed this guide and now know how to prioritize, that won’t be an issue 😉.
When new leads become qualified, you can send reps notifications with a call-to-action redirecting them to the sales play they should run.
Set up automated routing for leads that are users of your product yet.
Tools like Chilipiper or Intercom can route leads automatically when leads take qualifying actions like submitting a form on your site or booking time with an SDR. Fields are updated in your CRM so reps don’t have to manually entry this information.
Set up automated routing for product-qualified leads
Similarly, Product-Led Sales platforms like Calixa allow you to set up automated workflows when leads become qualified, like creating opportunities in your CRM, adding to a sequence, etc.
Final thoughts: Keep track of outcomes when doing speed-to-lead experiments
How do you know if your speed-to-lead improvements are affecting revenue?
Here’s a simple formula:
Step 1: Look at the number of PQLs who became SQLs last quarter.
Step 2: Reduce your time to lead by following this guide.
Step 3: After a quarter, evaluate your PQL to SQL conversion again.
Notice a difference? More opportunities? Higher close rate? Faster sales cycles?
Note that as a product-led business, you’ll need to iterate on sales processes as your product experience evolves.
Pricing updates, onboarding changes, shifts in paywalls, etc. may affect how fast your GTM teams need to engage leads. So keep experimenting and documenting results!