So, it’s kind of a dramatic improvement, as I referenced earlier in the call, holding customer acquisition cost content, we think that’s very, very favorable to also lay a better experience for our learners on the platform, both consumers as well as now institutional customers that are leveraging — that underlying membership capability with per students.
Jason Pello: And then I think the second part of your question was what do we see with month-to-month versus contract customers? We believe it’s important to offer the customers the flexibility to choose the pricing plan that best suits their needs and preferences. Month-to-month leads to higher conversion for certain customers who don’t want a long-term contract. It’s also worth noting that the month-to-month has a higher ARPU of about 15% to 20% for that flexibility. And then all of our customers, including month-to-month and contract can consume beyond their membership with what we call supplemental hours and so there’s kind of an unlimited ability to engage with us in tutor-based products during the month, and we’ll just build on a supplementary basis thereafter. So, net-net, we think having both options is important to drive conversion and customer satisfaction and growth over time. So we feel good about that flexibility.
Unidentified Analyst: Got it. Thanks. And so also on the flip side of your consumer segment, what are you seeing from active experts? Like what benefits are they seeing their currently to stay and join your platform?
Jason Pello: Sure. So one of the things that we sought to do and this occurs naturally through how all of the AI algos work on the platform is that the top tutors get allocated more work. And on average, they tend to be better in general. And so they’re sticking around on the platform at higher and higher rates because they’re getting a higher volume of students. They’re also really appreciating the fact that with learning memberships, there’s a much higher level of recurrence to those students so they meet more frequently and that kind of combined with higher volume allocated to them, that allows for them to generate more income. And these also tend to be students that are oriented toward a long-term goal and the feedback that we’ve gotten about that kind of relationship.
And the matches that are occurring both by the very nature of the product, but then also because our matching algorithms continue to get better and better and better with more data is something that has actually improved the relationship that experts have on the platform with both the students and with the platform itself. So we feel good about that relationship. We purposely, as we said, for many quarters in a row, decreased the number of active experts on the platform because it drives operating efficiency because we’re leading into the best folks? And then separately, I guess we’re just getting smarter about figuring out how to find the right people for the platform as well. So we feel great about the liquidity, going to source great operating leverage.
And we think we have a kind of good model here for providing both a good experience for the experts and then separately making sure that we are constantly improving the experience for the owners themselves.
Unidentified Analyst: Got it. Thanks.
Operator: [Operator Instructions] It appears we have no further questions. So with that, I thank you all for joining this event, and you may now disconnect your lines.
