LinkedIn engagement in ecommerce customer-service AI

London pull, August 2026, 90 day window.

We started with the people who reacted to or commented on the category's posts, then filtered by title. That left 264 people. The table uses the 170 most active of the 264, ranked by how often they engaged anything in the category.

Most active favours people who use LinkedIn heavily, and we say so on every page. A buyer who reads without reacting is invisible to this method.

The title filter for this category covers customer experience and support leadership. Title is a proxy for authority rather than proof of it, so we write the sampled market and not the buyers.

Sample: 170 most active of 264. Window: 90 days, August 2026. Region: London pull. Counted: reactions and comments from those 170 on each vendor's public posts.

The two columns disagree in places, which is the point of printing both. Yuma took 29 reactions to Ada's 31 and still beats Ada on rate, 2.2 to 1.3. Fewer posts, more per post.

Siena pulls the largest raw crowd of any vendor in the category, 444 engagers before the title filter. Inside the sampled market it converts at 3.1 per post, about half Kustomer's rate. A big crowd and a well-targeted crowd are two different assets.

Gorgias recorded 18 market reactions across the window, averaging 0.8 per post.

The audience definition may explain some of the difference between vendors: this sample focuses on people engaging with customer-service AI content and carrying relevant roles. The study does not establish why Gorgias recorded fewer reactions, or how it performed with other audiences.

Kustomer's average was 6.6 reactions per post, compared with 3.2 for the next vendor in the table. Posts about CX Day, certification, awards and professional communities appeared in the reviewed content.

Those examples are worth testing in a relevant content plan. This observational study does not isolate the cause of Kustomer's higher average.

The creator table records how many of the 170 sampled people engaged with each account during the window.

Siena's company page recorded engagement from three sampled people. The two founder rows report 26 and 14; those counts must not be added as unique reach without checking overlap between them.

The result supports including individual accounts in the research. It does not establish a general multiplier for founders versus company pages.

Fifty of the 170 sampled people engaged with the CX Professionals Association during the window. That was the highest account overlap reported in this study.

For a vendor, this is a reason to investigate the association's topics and calendar alongside commercial creators. It does not show that the association endorses a product or that sponsoring it would reach all 50 people.

The research grouped 116 of 264 people with ecommerce communities and 148 with customer-experience professional communities.

Use this classification to investigate both kinds of community. The totals do not prove exclusive membership, event attendance or the reach of a future campaign.

The rooms in this market belong to the profession rather than to any vendor. CX Day is the anchor, the date the profession marks each year. CCXP is the profession's certification, and certification content is part of the mix that put Kustomer at the top of the table.

These are company level findings, derived from which events sit inside the market's most-reacted posts and from desk research on the category's calendar. We do not know who attends anything and we never claim to.

Three posts reviewed in this category recorded:

These individual examples attracted different levels of engagement within the sample. They are not a controlled comparison of post types and do not establish a two-to-one benchmark.

Full method, including where it is weak: /data/method