Industries

AI SDR for B2B software and AI companies, from our own year and a founder's six months

B2B software is the largest group of Sellinger customers. Two studies show what it looks like. Sellinger's own LinkedIn outbound messaged 27,737 people, 40% replied and 351 showcase meetings were booked, but meetings per person fell below 1% from June. A solo founder booked 19 discovery calls from 935 conversations.

Published by Sellinger AI. Numbers and settings checked on 19 October 2026 against the fact register. Report an error.

people messaged on LinkedIn by Sellinger's own agents, September 2025 to October 2026: 27,737
replied: 10,978 conversations. 351 showcase meetings booked, 33 confirmed held: 40%
discovery calls booked by a solo founder from 935 conversations (2.0%), 10 documented as held: 19
calls booked in the last 12 months using on average 7.5 LinkedIn accounts (owner statement, 19 October 2026): 1,500+

Who software companies write to

Sellinger wrote to founders, heads of growth, sales and revenue leaders and agency owners, from up to 43 LinkedIn profiles of real people, mostly after they engaged with a post about sales automation or go to market. The solo founder wrote to people who engaged with growth marketing creators and competitor pages, matching one of his three products to each person.

Which list produced meetings
Study	List	Result
Sellinger own, October 2025	Intent signal lists	54.6% replied, 4.54% meetings per person messaged
Sellinger own, October 2025	Untagged lists	37.2% replied, 1.16% meetings
Sellinger own	Sales Navigator search	21.7% replied, 0.71% meetings
Solo founder	Intent lists (three creator and competitor audiences)	16 of 19 bookings
Solo founder	Title and keyword searches	1 booking in 225 conversations

The playbooks behind the numbers

Find people already thinking about outbound: intent signal start, observation opener, up to three follow ups, a one line answer to what is this.
Founder led LinkedIn discovery calls: a compliment, one product matched to one person, and the booking link only after a yes.
Observations out replied questions by 10 to 15 points within the same month in the own study.

What did not work

Meetings per person messaged peaked at 2.4% in November 2025 and drifted below 1% from June 2026, while reply rates held at about 40%.
Cutting reply time from 19 to 2 minutes did not lift meetings. The list was the bigger lever.
Only 5 of 30,000 openers mentioned the post that put the person on the list. That is the next experiment.
Of 351 meetings booked, 33 are confirmed held with a recording or a team mark. The calendar marks a meeting completed when the slot ends, whether or not anyone joined, so those are not counted.
The solo founder's title and keyword searches booked 1 call in 225 conversations. Pivoting a thread to a second product rarely converted.
The 1,500 calls figure counts every call booked in 12 months. The 351 is the part we can reproduce from the database for one window, so quote the two with their definitions.

Fit for software teams

It fits when

your buyers are on LinkedIn and engage with content about the problem,
you can name the signal that shows someone is thinking about it,
a person can take the call quickly.

It fits less when

you need enterprise procurement contacts who rarely engage in public,
your offer has no clear first call,
you expect reply rate alone to predict meetings.

Common questions

Does an AI SDR work for SaaS?

In Sellinger's own year, 40% of 27,737 people messaged replied and 351 showcase meetings were booked. The meeting rate fell over the year, which the study explains by the list and the offer.

What is the best list for a software company?

Lists of people who just engaged with relevant content booked four times as many meetings per person as untagged lists in October 2025 in the own study.

Why do the numbers say 1,500 calls and 351 meetings?

1,500 is the owner statement of all calls booked in 12 months with 7.5 accounts on average. 351 is the showcase meetings booked through the agents' booking link that we can reproduce from the database.

Is this a customer or Sellinger itself?

The first study is Sellinger's own outbound. The second is a solo founder who was a customer for a six month subscription.

Sources and method

Every number comes from the linked case study, which states its base, its data date and what did not work. Sources: Sellinger case study (own workspace, snapshot 9 October 2026) and ShortVibe case study (snapshot 10 October 2026). The 1,500 calls figure is an owner statement dated 19 October 2026.