How NextDimension AI replaced a Clay, Apollo and Smartlead workflow with one platform

NextDimension’s buyers run procedure-heavy specialty practices, where the front office carries the patient calls, procedure prep and prior authorizations its agents take over: gastroenterology first, then dermatology, ophthalmology and radiology, including groups that private equity owns through a management services organization (MSO).

In Dmand AI, 7,450 single-specialty groups in those four specialties sit outside health systems. 1,881 have 15 or more practitioners, and MSOs own 422 of them.

At each practice the team sells to two groups of people: the physicians who own and run it, and its executives, from the C-suite to operations and IT leaders at manager level and above. Dmand AI holds about 11,000 of those executives at these groups and the organizations that own them.

Ownership is what a domain list hides. An MSO sits above the practice, and one practice can run several sites under several web domains. Org Hierarchy Explorer shows the MSO, each group it owns and every site under the group.

The team built its workflow in a Clay workbook. Getting from a list of practices to a sent email took eight steps across four tools: two of them by hand, and three AI columns guessing at data that a healthcare database already holds.

The output was thin. On that list the workflow found emails for 100 people, and Smartlead’s check marked half of them invalid. Across target accounts, about 40% of the people the team could name had no working email, and a personal email to a high-priority practice took about an hour of research.

Because the workbook keyed accounts by web domain, a site that belonged to a current customer could also land on the target list.

The team had already dropped Definitive Healthcare after an extensive review, and ZoomInfo was out of budget. It had also started to think about building the missing pieces itself. Meanwhile Clay had become the most expensive part of the stack.

What decided it was a walkthrough of the team’s Clay workbook. Dmand AI answered with the GI market, physician first: gastroenterologists in groups of 10 to 40, at ambulatory surgery centers, each tied to its group and the site where they practice. Within minutes the commercial lead had found an endoscopy center in a region the team was not targeting.

The team bought the $249 Kickstarter plan in the app before that call ended.

Every campaign now runs the same five steps in one Dmand AI login, from the practices worth a call to a first email ready for review.

Lists start in Dmand AI’s medical group search: specialty, size, owner, state and the EHR each group runs. NextDimension’s agents work inside the practice’s own systems, so the EHR filter keeps the list to practices the agents can work in, and the team sees how big a segment is before it spends a credit.

Each group opens to its sites of care, from offices to endoscopy centers, and to the MSO above it. Dmand AI ties every physician and executive to the site where they work, not only to the group, and the EHR filter works at that level too: the physicians who practice at sites on a given EHR, and the managing partners, administrators and operations leaders who decide.

Contacts come from waterfall contact enrichment, which checks healthcare-specific sources in turn for each physician and executive and verifies the email before a sequence sends to it. The team pays for the contacts it picks, not for a list.

Introductions from advisors, investors and customers were still NextDimension’s best source of deals, but asking for one depended on who happened to remember whom. On the first call, the commercial lead ran Physician Network Discovery on one of the team’s own physicians and called the result “very, very valuable.”

Now the team adds the physicians it already knows, its physician advisors and the physicians at its customers, and Discover Network lists the physicians they connect to: who trained in the same program, wrote papers together or work at the same group or hospital, with a connection strength from 0 to 100. Before asking for an introduction, the team brings the advisor a short list and one question.

The same check runs before the team brings on a new physician advisor, to see which practices that advisor’s network reaches. The team has used Physician Network Discovery regularly since June.

Zeus AI SDR researches each person and practice and drafts the first email from what Dmand AI holds: the role, the site, the EHR and any new signal. The team reviews every draft before it sends. At onboarding, the Dmand AI team set up sending with NextDimension around four choices.

Clay was the first tool to go, and the other three followed. The practices, the people at each site, their contacts, warm introductions, research and sending now sit in one login, and the money that went to AI columns guessing at rosters and EHRs no longer leaves the budget.

Next, the team plans to take the same playbook beyond GI, to the 6,718 dermatology, ophthalmology and radiology groups in its market.