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Here is what happens before most discovery calls. The rep opens the CRM record, sees a name, a company, maybe a job title. They Google the company, skim the homepage, check LinkedIn for 30 seconds. Then they get on the call and ask the prospect to tell them about their business.
That is not discovery. That is winging it.
The best sales methodologies in the world cannot help you if the rep has no context before the conversation starts. And right now, most reps have almost none. Not because they are lazy, but because the systems they work in do not give them any.
This is where AI actually adds value. Not writing emails. Not automating follow-ups. Not replacing the rep. The real value is in pulling together buyer context before the rep ever picks up the phone, so discovery starts from a position of intelligence rather than ignorance.
Every company I work with has the same issue. There is a massive gap between what you could know about a prospect before the first conversation and what the rep actually knows.
Your CRM has a record. Maybe it has a lifecycle stage and a lead source. Your enrichment tool has firmographic data. Your website analytics might show which pages the prospect visited. BuiltWith can tell you what technology they are running. LinkedIn can tell you who they have recently hired. Public filings can tell you if they have raised funding.
All of this information exists. Almost none of it reaches the rep before the call.
Instead, the rep opens a mostly empty CRM record and starts from scratch. They ask questions the data could have already answered. They miss signals that would have changed the direction of the conversation entirely. And then they log their notes and move on to the next call, where the same thing happens again.
This is not a training problem. It is a systems problem. The intelligence is available. It is just not assembled and delivered to the point of need.
Winning by Design's SPICED framework breaks the sales diagnostic into five dimensions: Situation, Pain, Impact, Critical Event, and Decision. The idea is simple. Diagnose before you prescribe. Understand where the buyer is before you pitch what you sell.
Most of these dimensions require a human conversation. You cannot automate Pain discovery or understand a Critical Event without talking to the prospect. But Situation is different. Situation is the factual context about the buyer's world: who they are, what they run, how they are structured, what has recently changed. And nearly all of that can be enriched automatically before the rep ever gets involved.
This is the unlock. If you can pre-populate the Situation dimension with real data, your reps walk into every call already knowing the lay of the land. They skip the "tell me about your company" preamble and go straight to the questions that actually matter. Discovery gets sharper. Calls get shorter. Pipeline quality goes up.
Here is the practical build. Using Clay as the enrichment layer, we created a set of automated columns that populate Situation context on every inbound lead the moment they enter the table.
Technology stack from BuiltWith. This tells you what the prospect is currently running. CRM, marketing automation, sales tools, analytics platforms. If they are on HubSpot already, that is a different conversation than if they are on Salesforce. If they are running no marketing automation at all, that tells you something too. We also pull the "first seen" date for key tools, so you know whether they adopted HubSpot six months ago or six years ago. A recent adoption signals they are still building. A long tenure signals they might be looking to optimise or migrate.
Headcount by department. We pull open roles and current employee counts segmented by function. Specifically: number of salespeople, number of marketing people, number of CS people, and total GTM/RevOps roles (job titles matching patterns like GTM Engineer, RevOps, Revenue Operations, Sales Operations). A company with 200 employees and zero RevOps headcount is a very different prospect than one with a five-person ops team. The first needs architecture. The second needs optimisation.
Hiring signals. If the company is actively hiring for Sales, RevOps, Marketing Ops, or GTM roles, that is a signal. It means they are either scaling and need infrastructure, or they have a gap they are trying to fill. Either way, it is a conversation starter that the rep would never have found in a 30-second LinkedIn scan.
Recent funding and news. Funding rounds, leadership changes, acquisitions, product launches. These are Critical Event signals disguised as Situation data. A company that just raised a Series B has different priorities and urgency than one that has been bootstrapped for ten years. A new CRO joining means the GTM strategy is about to change.
Industry and company size. Basic firmographics, but mapped to bands that mean something to your sales motion. Not just "51-200 employees" but categorised in a way that aligns with your pricing tiers, your ICP definition, and your typical deal complexity.
LinkedIn headline and role. Confirming the contact's current role and seniority. This seems basic, but it is remarkable how often the CRM has stale job titles. The enrichment layer keeps this current.
Each of these columns populates automatically when a lead enters the table. By the time a rep sees the record, they have a briefing, not a blank page.
The shift is subtle but significant. Instead of "tell me about your company," the rep can open with "I see you are running HubSpot and Outreach but you do not have anyone in a RevOps role. How are you managing the integration between those two today?"
That is a completely different conversation. The prospect immediately knows the rep has done their homework. Trust builds faster. The conversation moves to Pain and Impact quicker because the Situation context is already established.
It also changes what gets logged. When the rep has structured Situation data already populated, their discovery notes focus on what they actually learned in the conversation: the Pain, the Impact, the Critical Event, the Decision process. Instead of half the notes being firmographic context the CRM should have had already, the notes capture the information that only a human conversation can surface.
Over time, this compounds. Your CRM stops being a database of names and starts becoming a genuine intelligence layer. Each record carries context that makes every subsequent interaction smarter.
Here is where it gets interesting for leadership. If you are scoring Situation completeness automatically, you have a leading indicator of pipeline quality that most companies do not have.
A deal where the Situation dimension is fully populated (you know their tech stack, their team structure, their recent changes) is a deal where the rep had the context to run a proper diagnostic. A deal where Situation is thin is a deal where the rep is guessing.
Winning by Design's research shows that deals with incomplete diagnosis across multiple SPICED dimensions tend to stall or lose. If you can see which deals have strong Situation context and which do not, you can flag pipeline risk before it shows up in a missed forecast.
This is not about replacing the rep's judgement. It is about giving them and their manager a data-backed view of whether the foundational work was done. Did the rep go into this deal with real context, or did they wing it? The enrichment data answers that question before anyone has to ask.
You do not need to build all of this at once. Start with one or two enrichment sources that are most relevant to your sales motion. If you sell to companies based on their tech stack, start with BuiltWith. If you sell based on company stage, start with funding and headcount data.
Build it in Clay or whatever enrichment tool you use. Connect it to your CRM so the data flows to the rep's view before the first call. Then measure the difference. Are discovery calls getting shorter? Are reps asking better questions? Is the information they log after calls more focused on Pain and Impact rather than basic context?
The point is not to automate the sale. The point is to automate the homework. AI is not going to close deals for your reps. But it can make sure they never walk into a conversation blind again. And that changes everything downstream.
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