Document BDR outreach hypotheses, tag prospect groups, and track results per experiment.
Choose a company above to see its hypothesis groups.
Scans all prospects and outreach for the selected BDRs and assigns each contact to the best-fit hypothesis group based on that group's description. Organization backgrounds are always looked up. Each contact is assigned to only one group.
Load outreach for selected BDRs, see when each first connection was sent, then define date ranges to bulk-assign contacts to hypothesis groups. Great for campaigns tied to specific time periods.
Automatically find move, import, and group batches that strongly overlap with your existing hypothesis groups. When a batch is ≥85% inside a group (or vice-versa), the system flags it and lets you approve the assignment in one click.
A batch is flagged when this % of its contacts are already in a hypothesis group.
Loads connect_queue records that were already sent live — i.e. actually pushed to HeyReach from Fast Connect Review, not just sitting in Queue 1/Queue 2 — and buckets them by generation batch ID (or by send date when no batch ID exists) so you can see groups of messages and when they were submitted. Leave the hypothesis group blank to review every sent-live message for the BDR(s) below and assign each batch to a hypothesis group (and optionally a variation). Or pick a group first to load only messages that already belong to it (matched by tagged contact URL, batch ID, or an existing group stamp) and assign the right message variation. If a selected group's match count looks too low, expand the "Why aren't more matching?" debug panel under the results — it shows real sample URLs from both the group's tagged contacts and the loaded messages.
Counts connect_queue records for the BDR(s) selected above that were actually sent
live — pushed to HeyReach, not just sitting in Queue 1/Queue 2 review — bucketed by hypothesis group
and variation, across every group, not just the one picked above. A message's group is
resolved the same way Outcomes
resolves it — an explicit hypothesisGroupId stamp if present, otherwise a match against
the group's tagged contact URLs / batch IDs — so the counts here should line up with Outcomes.
Variation still requires an explicit hypothesisVariationId stamp (assigned via the
batcher above), since variations aren't tagged onto contacts the way groups are. Use this to see how
many sent messages still need a group and/or variation assigned — then leave the group dropdown blank
above and assign those missing groups on each batch.
Hypothesis groups are intended to be mutually exclusive — one contact, one group. This scans every hypothesis group for the company currently selected above and flags any contact that's saved in more than one group (most often caused by a partial-overlap batch approval in the Correlation Scanner). Pick which group each contact should stay in and it will be removed from all the others.
Load every contact owned by the selected BDR(s) that isn't assigned to any hypothesis group yet (whether or not outreach has been sent) — matches the "Unclassified" count on the Monthly Research Plan page. Use the dropdown next to each contact to assign them, then save all at once.
Fetches every document from the hypothesis_groups Firestore collection with no filters applied.
Use this to locate a group that may have been hidden by company/BDR filters.
Click "Load All Groups" to fetch raw data from Firestore.