RevOps leaders: How to set your teams up for a successful end of quarter

The acronym “EOQ” can strike fear (and excitement) into even the most seasoned RevOps leaders’ hearts.

EOQ is characterized by a two-headed challenge: Push deals over the finish line while setting the company up for a successful next quarter. You only have so many reps, and in the closing hours of the quarter, you’d rather they focus on getting key deals in on time. But you’re accountable for accurate forecasts, and you need a lot of good data to forecast well. The problem, though, is that data is often incomplete or missing entirely from the CRM, stuck in the minds of your reps.

Having spent more than two decades in sales and finance leadership roles, I’ve been through more than 80 EOQs. I’ve seen them handled well, I’ve seen them handled poorly, and I’ve developed a framework for what RevOps leaders should be thinking about. I’ve also seen RevOps solutions undergo significant evolution and add a lot of clarity to EOQ goals.

1. Accurate EOQ deal forecasts

EOQ is a period of resource scarcity — especially for leaders, whom reps will be hounding for help. Your success hinges on how efficiently you can inspect and triage deals, glancing at deal boards and seeing which ones need you the most.

To inspect deals well, you’ll need scaled insights based on accurate forecasting data — which is notoriously hard to come by. It often lives in a wide variety of locations, and it can be very difficult to synthesize in a common location that serves everyone’s needs. What you don’t want is to have to play the elaborate game of ad-hoc texts, Slacks, calls, and emails that getting this data often requires.

This is an area where revenue AI can make a big difference. Revenue AI platforms automatically collate all the information associated with a customer or prospect and turn it into actionable insights. In its ideal form, revenue AI solutions analyze a complete history of customer interactions, extract insights, sort those insights according to your sales methodology, and render forecasts around closing likelihood and timelines. 

Moreover, they provide intelligent responses to queries about why deals are or aren’t advancing. You’ll still need to send out the occasional ping, but it will be for 2% of deals, rather than most or all of them. This “why” data will also be essential for setting up future QBRs — more on that in section three.

2. Accurate pipeline projections

“EOQ” is a slightly misleading acronym. The quarter may be ending, but the end of one quarter has everything to do with the beginning of the next. As Semisonic sang, “Every new beginning comes from some other beginning’s end.” The success of the subsequent quarter hinges on generating qualified pipeline — and if you’re behind, knowing well in advance, so that you can address shortfalls proactively.

At EOQ, RevOps leaders want their reps focused on deals, so they tend to base pipeline projections in part on historical data, combining coverage numbers with historical funnel conversion metrics. This isn’t valueless, but it doesn’t have a strong predictive element. RevOps leaders tend to wait until the first or second week of the subsequent quarter to generate these predictions due to this lack of reliable data about what’s coming.

Revenue AI gives leaders proactive predictive power (without solely relying on reps updating the CRM). By synthesizing all historical and conversation data, revenue AI platforms can apply unique qualification parameters to existing pipelines and give leaders earlier access to more accurate pipeline projections — all without piling additional burdens on their reps. This acts as an accelerant to leaders’ strategic capabilities, letting them visualize clearer futures while reps shore up the present.

3. Performance analysis

When QBRs fail, the reason is usually that they focus on quantitative data, not qualitative data. That is, leaders depend on these live sessions to understand whether reps hit their performance goals and to understand why or why not.

In my view, all of this should happen before the QBR starts. QBRs are more valuable as forward-looking strategy sessions than backward-looking data-parsing sessions. If you already know what happened and why, you can spend the time figuring out how to counter those challenges and be ready to attack future quarters.

Revenue AI can be a powerful asset in making QBRs about strategy. Revenue AI platforms can analyze all deals according to your sales methodology — e.g., MEDDPICC — and in doing so, show you where and even why, deals fell through. It’s one of the best ways to pinpoint trouble areas for the sales organization as a whole, for teams or regions, and for individual reps.

RevOps leaders expect EOQ to be a time of heightened anxiety. It will likely always feel like some species of monster you have good reason to fear — but frameworks and tools exist today that make its claws a lot less sharp.

The best EOQs happen when everyone on a team uses their scarce time effectively. Revenue AI helps everyone do so. 

Reps get to focus on closing deals, and leaders get an accurate big-picture view — which they can drill into to get specific — that shows them where they’re most needed, and when. Not to mention RevOps finally getting to focus on strategic initiatives and what will help leaders drive the business forward — rather than spending time chasing answers on deals or fixing bad data.