“Customers who come through Meeton ai are clearly reaching out already nurtured — they have the knowledge and they are interested. We find it extremely effective for converting leads into meetings.”
— Masaaki Semba, EdulinX, Inc.
EdulinX, Inc. leads change in the training industry under the mission of "linking Education × DX." Centered on "Reallyenglish," an English-training platform for universities and companies, it offers training services trusted by both educational institutions and corporations. It stands out for moving on AI earlier than the rest of its industry, and the idea that "we want to be in a position to lead the industry" runs through its decisions.
In the training industry, the lead-to-meeting conversion rate sits around 20%. EdulinX, too, faced the problems that "we cannot see how interested website visitors are" and "the path that carries a visitor to a meeting is weak." Behind them were three factors rooted in the structure of the industry.
The CPA of Google Ads and similar channels did not fit the business economics, so the main battleground for lead acquisition had moved to comparison sites (lead marketplaces where each lead is bought at a set price). In some months, comparison-site leads made up more than half of the total. With these leads, competitors all reach out at once the moment someone registers, so there is little background information and the level of interest is hard to read. Sales reps often invested time without it turning into meetings. How to carry leads who arrive at the company's own website already warm through to a meeting was a make-or-break issue.
In training, contracts that span fiscal years are the norm. "We want a meeting first to secure next year's budget." "We are refreshing our mid-term plan and want to rethink global talent development from next term." It is not unusual for the evaluation period up to sign-off to run to a year or more. In a structure where this year's lead becomes next fiscal year's deal, a mechanism that accurately reveals and builds interest at the first touchpoint was overwhelmingly important.
Within the sales team, the quality of lead follow-up varied widely from rep to rep. Some reps who were serious about winning new business followed up carefully, "call → email → call again," while others "sent one email and stopped if the first call didn't connect." The same lead could end differently depending on who owned it, and this person-dependent structure put a ceiling on the meeting conversion rate.
"If we hit a 20% meeting conversion rate, we're doing well." Breaking through that level stood out as a clear challenge for moving to the next phase.
AI chatbots for customer support were already saturated at the time. AI chatbots specialized in acquiring leads and meetings, on the other hand, barely existed in the market, and Meeton ai left a strong impression as "the first option that answered our problem head-on." Not "an AI that answers customers' questions" but "an AI that actively goes after meetings" — the differentiation was clear.
As another option, EdulinX also evaluated conventional calendar-booking tools. Tools in that category offer segmented form display (fine-grained targeting by company size, region, score, and so on) and active conversion by guiding visitors to a calendar, and they did have real strengths.
Most of those capabilities, however, were also achievable with Meeton ai, and on top of them Meeton ai had capabilities specific to an AI SDR: conversational nurturing that picks up on visitor intent, and personalization based on behavioral signals. Pricing was about the same, so it came down to "broader functionality for a comparable cost," and Meeton ai was the only choice.
The sales contact responded quickly, and questions were resolved smoothly even during evaluation. What settled it was the experience during the trial period: when EdulinX made feature requests, the engineering team reviewed and acted on them quickly, and customization to fit its operations was delivered with a short lead time. Experiencing the vendor's ability to stay alongside the customer after adoption, before signing the contract, built trust.
We felt our challenge was in acquiring leads and meetings. Going after that was new.
At the start, there were more than a few skeptical voices on the internal sales team.
"We want to assign incoming leads precisely to the right rep by industry and location." "Can we really win them if we leave it to AI?" It was a mix of confidence in the existing way of working and doubt about AI. On calendar integration in particular, the initial stance was strongly cautious.
Once operation began, though, the mood changed. Leads coming in through the AI arrived far warmer than anyone had imagined, and the meeting conversion rate was in a different league. The daily numbers kept showing it.
As a result, the sales team itself began to say, unprompted, "Let's lean on the AI more" and "We want the calendar integration in soon." The same sales team that had been skeptical before adoption was now actively asking for those features — a major reversal in under half a year.
Customers who come through Meeton ai are clearly reaching out already nurtured — they have the knowledge and they are interested. We find it extremely effective for converting leads into meetings.
Results also appeared in an area nobody had planned for. Learners (students) using Reallyenglish were sending a steady volume of inquiries about account creation, undelivered emails, how to use the platform, and so on, and the load on the support team had become a problem.
When EdulinX raised this with DynaMeet, a dedicated bot customized for learner support was built in a short time. After it was placed on the help desk page, learners resolved more issues on their own and the number of inquiries reaching the support team itself fell. A tool adopted as a meeting-generating AI went on to deliver the side benefit of reduced support workload — return on the investment accumulated even in an area that was originally out of scope.
In one case, a major customer in the healthcare sector asked a series of in-depth questions in conversation with Meeton ai and then reached out on its own: "Please let us set up a meeting right away." Because the AI went into detailed points such as whether healthcare-related training could be supported and the expertise of the instructors, interest was already extremely high by the time the inquiry arrived. In an industry where long evaluations spanning fiscal years are common, having AI handle the initial spark of interest clearly speeds up evaluation — a case that symbolizes that effect.
In April, at the start of the new academic term, the number of students using Reallyenglish in university classes rose all at once, and inquiries about account creation and initial setup surged. Normally the choice is between adding support staff and accepting slower responses, but when EdulinX consulted DynaMeet, a support-focused bot based on the learner FAQ was built on a short timeline. Once it was on the help desk, students could resolve issues themselves without waiting, and the support team could concentrate on the cases that truly need a person. It is a good example of putting AI to work on both fronts: better customer experience and less internal workload.
EdulinX plans to raise operational precision further through a form handler integration with Salesforce Account Engagement, full operation of the calendar feature through the Microsoft Teams integration, and continued prompt tuning.
It also plans to use the automated follow-up email generation that Meeton ai is newly releasing (the AI sends emails at the best timing based on behavioral signals). By evening out lead follow-up quality, which until now depended on each rep's discretion, and making sure that "no matter who owns the lead, follow-up always reaches it three times," the company aims to lift the whole sales team.
We want to be in a position to lead the industry. In this industry and many others, this kind of AI is going to be used more and more. When we thought about that, not adopting it was not an option.
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