2,468 public LinkedIn posts about HubSpot's renamed conference, written before, during and after the event, read and tagged one by one. What each role should take away, what people talked about, and who got heard.
Independent analysis of public posts. Not affiliated with HubSpot.
The lessons that kept coming up, for five roles, each with one thing to try.
HubSpot came to Boston with one argument: AI only pays off when it knows your business. The crowd repeated it. That thesis, context over models and outcomes over activity, was the biggest single topic, in 468 posts. The word “context” appears in 488 posts, one in five, and those posts hold 21% of all engagement.
The figure from Yamini Rangan's opening keynote travelled furthest. Nine in ten companies use AI, but only 6% see transformational results. More than 70 posts repeat it.
Speakers posting about their own talks wrote 4.5% of posts and collected 13.8% of engagement. Product announcement posts had the lowest median of any topic: 11 engagements.
HubSpot partners and agencies wrote 40% of the posts and collected 26% of the engagement. HubSpot employees wrote 6.5% and collected 23%. The median employee post got 61 engagements. The median partner post got 14.5.
At the very top it is two people. CEO Yamini Rangan and co-founder Dharmesh Shah wrote 9 of the 12 most-engaged posts. The most-engaged post of all is Dharmesh Shah asking for questions for his fireside chat, five days before the event.
Posts about meeting people, meetups and parties got a median of 31 engagements. Posts about product announcements got 11. The guest keynotes show the same pull. Mel Robbins is named in 159 posts, more than any HubSpot product. Breeze Assistant, the most-named product, is in 155.
Before the event, posts were travel plans, meetup invitations and booth numbers. During the three days, the AI thesis and the product launches took over. The biggest single day came after: Monday 21 September, with 457 posts, when the recaps landed.
Every post in the dataset, with its one-sentence summary, its topic and author group, and a link to the original. The summaries are a model's reading of each post. Open the post before you quote it.