Using discovery to impact win rates

Using discovery to impact win rates

~ Guest blog by Mark Garrett Hayes - an inspir'em coach & trainer.

Discovery is the process of revealing a prospect’s real priorities, pains, and decision drivers, so we can position our approach as the obvious next step. That has always been true. What has changed is how much information is available, and how quickly buyers expect us to make sense of it.

In today’s environment, discovery is no longer optional. It is the foundation for qualification, deal confidence, and win rates. And while technology, including AI, now plays an increasingly large role in how we prepare and execute discovery, it does not change the fundamentals of what good discovery looks like.

Consistently strong discovery is one of the clearest predictors of sales performance. Teams that run disciplined discovery close more deals, forecast more accurately, and spend far less time chasing opportunities that were never real.

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Why discovery is where deals are won or lost

Everyone agrees discovery matters. Yet in practice, it is often rushed or treated as a gateway to the “real” sales conversation. Sellers move too quickly to demos and proposals without fully understanding what is driving the deal.

Discovery is legwork. Even when it is done from behind a laptop, it still requires preparation, curiosity, and the confidence to ask uncomfortable questions. This is where we qualify opportunities properly by understanding:

  • What pain exists, how urgent it is, and what happens if nothing changes.
  • The Metrics which quantify and validate the pain.
  • Who are potential Champions - who mobilises change in the account.

This maps directly to MEDDIC and MEDDPICC - the M,I & C. When discovery is weak, gaps show up later as stalled deals, late-stage surprises, and no-decision outcomes. When discovery is strong, win rates improve because deals are grounded in reality.

 

Raising the standard of discovery with better preparation

The bar for discovery has risen. Buyers expect sellers to be informed and relevant from the first conversation. Generic questions and surface-level research are easy to spot and quickly erode credibility.

This is where AI has started to change how sellers prepare. Used well, it helps us do the groundwork faster and more consistently, without replacing judgement or experience.

Before a call, AI can be used to research the prospect’s company, recent news, funding activity, earnings calls, and LinkedIn signals. This typically provides the majority of the context upfront, allowing us to focus the conversation on validation rather than basic fact-finding.

The outcome is not a scripted call, but a more intelligent starting point.

 

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Using AI to support structured discovery

AI is most effective in discovery when it reinforces structure rather than bypassing it. For example:

  • Feeding AI your ideal customer profile and MEDDPICC fields can help generate discovery questions tied to pain, Metrics, and Economic buyer priorities.
  • Conversation intelligence tools, such as Gong and Chorus, can highlight when key areas were missed, such as failing to quantify impact or clarify decision criteria.
  • Live prompts during calls can nudge sellers to probe deeper, for example by exploring the commercial impact of identified pain.

These tools act as guardrails. They support consistency and discipline, particularly in complex deals, but they do not replace the need to listen, think, and adapt in the moment.

 

Strengthening discovery through review and practice

Discovery does not end when the call does. Reviewing conversations against a qualification framework is where much of the learning happens.

Post-call analysis can help teams spot patterns such as deals stalling when access to the Economic buyer is weak, or when Champions lack influence. Over time, this connects discovery quality directly to win rates and forecast accuracy.

AI-enabled role-play tools can also support practice away from live deals. Simulating discovery conversations allows sellers to test questions, sequencing, and messaging in a safe environment. The value lies not in the novelty of the tool, but in creating space for deliberate practice and reflection.

 

Four discovery principles we always come back to

As tools evolve, a few principles remain constant. These sit at the heart of effective discovery, with or without AI.

  1. Research the account properly
    Arrive informed. Use available tools to understand the customer’s context, then validate your assumptions in the conversation.
  2. Map stakeholders early
    Identify who is involved, who influences the decision, and who signs it off. Do not wait for this to emerge organically.
  3. Anchor discovery to a business case
    Keep conversations grounded in commercial outcomes. If pain cannot be tied to measurable impact, it rarely drives action.
  4. Prepare and rehearse
    Strong discovery is not improvised. Preparation and practice build confidence, flow, and consistency.

 

Why human judgement still makes the difference

One final point matters. AI is not emotional intelligence. Artificial intelligence can surface information, patterns, and prompts, but it cannot read the room.

Buyers do not always say what they mean. Politics, risk, and personal credibility shape decisions as much as facts do. Understanding nuance, hesitation, and motivation requires intuition and empathy.

The strongest sales professionals combine structure with curiosity, data with insight, and technology with human judgement. Discovery works best when we think like humans, supported by the right tools.

Discovery will always be the engine room of sales performance. When we get it right, win rates improve, deals move faster, and sales becomes more predictable. AI can help, but disciplined discovery is what ultimately wins deals.

 


This blog is one of our Discovery series. These blogs are accompanied by our newsletter and a live webinar.

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