Walk Into Every Meeting Already Knowing the Account
They already held franchise data nobody else had. It sat in a different system from the people they were selling to, so every meeting started with assembling the picture by hand.
- Zero prep
- Per meeting, the briefing arrives assembled
- Under 2 hrs
- Meeting ending to follow-up sent
- Every account
- Current, not as last remembered
Bayze sells into franchising, and franchising is a domain where the useful facts are specific: who owns which brands, how many stores sit under a given franchisee, who reports to whom, and which of those numbers moved this quarter.
They held that data. The problem was where it lived.
The gap was between two things they already had
Contacts sat in Notion. Franchise data sat somewhere else. Neither knew about the other, so the person walking into a meeting had to assemble the picture by hand, every time, from memory and open tabs.
Everything downstream inherited that gap:
- No structured pipeline, so follow-up depended on whoever remembered
- The pitch deck and website ran two months behind a product that kept moving
- Meeting notes stopped at notes, with nothing carrying them into an action
- Several repositories with no shared system tying business operations together
And a deadline. A conference was coming with five to ten meetings a day, plus a new COO starting who would either inherit a running system or a blank slate.
What we built
Domain intelligence, which here means the franchise data and the people data joined into one thing an agent can read.
Every contact carries their franchise context. Not a name and an email, but the brands, the store counts, and when anyone last spoke to them.
Briefings before the meeting. Talking points and background assembled from that joined record, so preparation stops being a task somebody has to remember to do.
Follow-up within two hours of the conversation ending. Updated notes, a personalised email, and a one-pager tailored to what that prospect operates. This is the piece that decides whether a conference is worth attending: ten good meetings with no follow-up is ten meetings.
Collateral that keeps up. The deck, the site, and the sales material tracking the product instead of trailing it by a quarter.
Why it had to be their data
Any prospecting tool can enrich a contact from public sources, and every competitor selling into the same accounts is buying from the same enrichment vendors.
What no vendor sells is Bayze’s own view of the franchise landscape. That view is the reason a Bayze conversation lands differently, and joining it to the contact record is the whole engagement. The intelligence was never missing. It was in the wrong system to be usable in the ninety seconds before a meeting starts.
The part that outlasts the conference
A new COO joined into a system that already knew the accounts, rather than into a Notion database and a folder of decks. Onboarding stops being a transfer of context out of somebody’s head.
That is the durable half. The conference was the deadline; the operating system is what stayed.
What changed
Preparation stopped being a task. The brief arrives assembled, so the thing that used to cap how many meetings were worth taking no longer costs anything to produce.
Follow-up happens inside two hours. Ten good meetings with no follow-up is ten meetings, and the window where a conversation is still warm is the window that decides whether a conference paid for itself.
Every account reads as it is now. Franchise data joined to the contact means a brief reflects this quarter’s brands and store counts, rather than whatever somebody last remembered.
Why NimbleBrain
The asset was already theirs. Bayze held franchise data nobody else had, and the problem was that it lived in a different system from the people they were selling to. Joining those two is a smaller job than it sounds and a more valuable one than buying a CRM would have been, because the resulting picture is one their competitors cannot assemble.
Nothing was replaced. Notion stayed where it was, the franchise data stayed where it was, and what we added is the layer that reads across both and acts on what it finds.