Meraki used a land grab strategy by giving away free access points through webinars to let mid-market customers experience the product's simplicity firsthand.
Andy describes how Meraki, facing entrenched competition from Cisco and HP, used free access points to let mid-market customers experience their simpler cloud-managed networking equipment. ✦ AI generated
Andy · a16z Podcast · 2026-08-13 · original ↗
starts at this moment · 21:09
“How did you think about like these kind of tradeoffs in the early days of Meraki?”
And so what we do is we'd run these webinars and we'd say, 'Hey, you attend the webinar, we'll send you a free access point. You plug it in, try it out.' And the idea was if they if they try it, the lightbulb goes off and they say, 'Wow, this is just so much easier than what I'm using. Why don't I why don't I use that?' And it was it was very very successful for a long period of time and even as the company matured, you know, we were very very liberal in our trial and eval because you just fundamentally want customers to experience the technology. Um and realize that it's better than the alternative.
verbatim transcript · starts at 21:09
20:49have been trained in command line code and and this kind of stuff. Um, and so, you know, our kind of firm belief at that point in time was, well, what's the best way to get them to understand that our networking equipment is simpler to use than their Cisco that they're about to buy? >> Mhm. >> And the answer is get them to try it. >> Yeah. >> And so what we do is we'd run these
21:09webinars and we'd say, "Hey, you attend the webinar, we'll send you a free access point. >> Mhm. >> You plug it in, try it out." And the idea was if they if they try it, the lightbulb goes off and they say, "Wow, this is just so much easier than what I'm using. >> Yeah. >> Why don't I why don't I use that?" And it was it was very very successful for a
21:25long period of time and even as the company matured, you know, we were very very liberal in our trial and eval because you just fundamentally want customers to experience the technology. >> Yeah. >> Um and realize that it's better than the alternative. >> And do you think like there's there's an element of um like that people can kind of learn from that right now? It's it's hard though because there is a
21:46an aspect of configurability with a lot of the new AI stuff, right? Like if you just give somebody this like, you know, Ferrari, they they might not know exactly how to even turn it on and um and so I don't I I don't know how how you even think about like the delivery mechanism for some of these like trial periods, POCs with some of the AI companies you're working with right now.
22:04>> Yeah. I I think it's become more challenging, right, in the world of AI because number one, things are moving so fast. Like things are changing daily. And if you think about like a a proof of of concept or a trial, you know, the whole idea, if you're on the sales side, is I want the customer to experience this, I want to prove that it works for
22:21them, but I want to do it in a in a period of time that doesn't go on forever, right? And so what you what you have to stay away from, and I think one of the real dangers today is these things turn into like science projects, right? Like I'm going to deploy this, well, can it do this? Can it do this? Can you show me this? Can you show me
22:34this? And of course things are advancing every day, so the answer is probably yes, I could, but then you run the risk of these trials or proof of concepts going on forever. >> Yeah. >> And so it just takes a lot of discipline, I think, in today's day and age to to really box that in and say, "Listen, here's what our solution does, and we're going to, you know, define it
22:52this way, and we're both going to agree that if it, you know, has done this after 45 days, it's success and you're going to move forward with the purchase." >> so there's there is a lot of that today. >> And did you um like I guess would you recommend having like kind of auto converts on these as much as you can or Yeah, like I don't know how like other