Meeting Title: Default SaaS Pricing Strategy Analysis Date: 2025-11-12 Meeting participants: Hannah Wang
WEBVTT
1 00:00:02.230 ⇒ 00:00:06.900 Hannah Wang: Okay, okay. This is for default. Yeah, this is for default.
2 00:00:08.200 ⇒ 00:00:23.610 Hannah Wang: Okay, yeah, so what’s the… Can I look at the Figma? Sure. I mean, that helps my… Sure. …my thinking more. So, this… the purpose of it is for pricing. So, I guess, starting from the context, so default…
3 00:00:24.070 ⇒ 00:00:34.750 Hannah Wang: Is, trying to roll out a new pricing structure, So that they can.
4 00:00:35.010 ⇒ 00:00:39.050 Hannah Wang: capture…
5 00:00:40.650 ⇒ 00:00:53.789 Hannah Wang: better value from their current customers. They want to see if they are… their current pricing is aligned with customer value, or if they’re leaking value anywhere.
6 00:00:53.920 ⇒ 00:01:00.130 Hannah Wang: And if they… they want to see if the current pricing is.
7 00:01:00.410 ⇒ 00:01:03.599 Hannah Wang: Healthy, sustainable for the future.
8 00:01:03.950 ⇒ 00:01:08.330 Hannah Wang: So they found us.
9 00:01:09.340 ⇒ 00:01:13.590 Hannah Wang: Like, they’re considering a few different pricing models, and they want to know
10 00:01:13.650 ⇒ 00:01:30.460 Hannah Wang: how to decide, because they just don’t… they don’t want to just guess it and try. So, they found us, and then… Was this the first project we did with them? No, no, no, they, like, this is after the first one. Oh, okay. So, they came to us, and…
11 00:01:32.580 ⇒ 00:01:34.160 Hannah Wang: Okay, it’s there.
12 00:01:35.070 ⇒ 00:01:40.550 Hannah Wang: For, like, we have a diagnostic, and then the recommendation, so…
13 00:01:41.090 ⇒ 00:01:45.020 Hannah Wang: The first thing that we found is that,
14 00:01:46.050 ⇒ 00:01:49.180 Hannah Wang: First, their revenue is highly concentrated.
15 00:01:49.290 ⇒ 00:01:55.530 Hannah Wang: Which means that their top accounts take up a lot of their revenue, which means they’re…
16 00:01:56.160 ⇒ 00:02:03.650 Hannah Wang: Downside is that they’re at risk if they turn. They’re very heavily dependent on them.
17 00:02:03.980 ⇒ 00:02:12.379 Hannah Wang: That also means that they’re probably very sales heavy, which means that
18 00:02:12.500 ⇒ 00:02:19.900 Hannah Wang: on the right end of the curve, so people who pay less, it’s harder for them to upgrade, so that they’re always, like.
19 00:02:22.390 ⇒ 00:02:29.319 Hannah Wang: Paying less or not. They can’t upgrade to pay more, it’s harder for them to do that.
20 00:02:29.710 ⇒ 00:02:33.930 Hannah Wang: Which is not good, because then you’re losing value because people are not upgrading.
21 00:02:34.550 ⇒ 00:02:45.119 Hannah Wang: And the upside is that if they… if the big customers do upgrade, you get a… you get a bigger, like, absolute bump, because they are a bigger base.
22 00:02:45.600 ⇒ 00:02:51.150 Hannah Wang: Anyways, that’s the first… I think that’s the first insight we found, and then we started to look at
23 00:02:51.740 ⇒ 00:03:06.610 Hannah Wang: the different metrics of, of usage inside the product versus its relationship with revenue. And that tells us of what we should be pricing on, because if you’re going to price based on
24 00:03:06.890 ⇒ 00:03:10.790 Hannah Wang: The value that customers receive,
25 00:03:11.070 ⇒ 00:03:18.619 Hannah Wang: Usually, people only are willing to pay more if they get value out of your product. So we want to see what do they… who?
26 00:03:19.340 ⇒ 00:03:20.980 Hannah Wang: Or the customer type.
27 00:03:21.150 ⇒ 00:03:25.250 Hannah Wang: For the customers that pay more, what do they use more of?
28 00:03:25.680 ⇒ 00:03:32.580 Hannah Wang: And then, what we found is that currently, the price
29 00:03:32.680 ⇒ 00:03:42.020 Hannah Wang: Based on number of seats, right? So, you pay per seat, plus you get some level of tiers, so you have basic, then you pay a little bit more.
30 00:03:42.020 ⇒ 00:03:52.769 Hannah Wang: And then you have… you pay per seat, so the two things added together. What we found is that the highest correlation, so the highest predictor of revenue is
31 00:03:52.910 ⇒ 00:04:10.070 Hannah Wang: The first thing is number of meetings booked, and then it’s seats, then it’s, like, workflow runs, which is the submissions when someone submits a form to book a meeting, and then, like, the number of workflow runs, which is, like, number of forms.
32 00:04:10.550 ⇒ 00:04:21.370 Hannah Wang: So what does Default do? Default is an inbound… like, their main product is currently inbound automations. So you know when we go on our website.
33 00:04:21.370 ⇒ 00:04:32.599 Hannah Wang: you go click a… book a meeting with us, that’s a form. Like, that’s an inbound form, because the customer’s coming to us. So, they do, they help automate that, and they route it to different people.
34 00:04:32.870 ⇒ 00:04:38.019 Hannah Wang: And they do enrichment, that’s why they use clay, it’s like, oh, this person booked a meeting with you.
35 00:04:38.160 ⇒ 00:04:44.769 Hannah Wang: This is who they are, you better get hurt based on what they have, and this is the best salesperson to tackle this.
36 00:04:45.400 ⇒ 00:04:49.000 Hannah Wang: All right. So, recently, their…
37 00:04:49.170 ⇒ 00:05:04.589 Hannah Wang: the outcome the customer gets from it is a lead, right? Because they… it’s an inbound lead, and the… and that sort of equates to a meeting, right? Because you get an inbound meeting, that’s an outcome.
38 00:05:04.740 ⇒ 00:05:17.259 Hannah Wang: So, that makes our findings make sense, right? Because the meetings has the highest correlation value, because if I book a lot of meetings through you, I would pay you more. Right.
39 00:05:17.730 ⇒ 00:05:27.539 Hannah Wang: But right now, they’re pricing based on seats, which is an indirect indicator, because the bigger your team is, the probably
40 00:05:27.700 ⇒ 00:05:36.059 Hannah Wang: The more meetings you would book, because there’s… you just are a bigger company, you have more leads, and you use it more.
41 00:05:36.710 ⇒ 00:05:47.170 Hannah Wang: But… What the findings… what our findings means is that, One… There’s a certain…
42 00:05:47.440 ⇒ 00:06:01.880 Hannah Wang: value leakage when you only use seats, because people share seats. Like, we share accounts. Yeah. So, reasonably, why wouldn’t they share accounts? That’s a big challenge. The second thing is that…
43 00:06:02.940 ⇒ 00:06:08.080 Hannah Wang: Meetings are the highest indicator of… Put the link.
44 00:06:08.930 ⇒ 00:06:10.920 Hannah Wang: of their value.
45 00:06:11.610 ⇒ 00:06:18.600 Hannah Wang: I don’t know if this counts as a challenge we’re finding. That’s okay. And then, I would say…
46 00:06:19.720 ⇒ 00:06:25.069 Hannah Wang: Let’s think… okay, so that’s the main findings I have. And then…
47 00:06:26.360 ⇒ 00:06:33.490 Hannah Wang: So they’re trying to consider a few pricing models. Like, before, they were just seats plus
48 00:06:33.700 ⇒ 00:06:39.640 Hannah Wang: tears. And right now, they’re thinking of, okay, what other metrics
49 00:06:41.140 ⇒ 00:06:56.719 Hannah Wang: should I consider? They’re considering, like, two main models. One is horizontal pricing, one is vertical pricing, and the type of horizontal pricing they picked is, like, PLG, which is product-led growth, which means
50 00:06:56.720 ⇒ 00:07:08.390 Hannah Wang: like, you don’t have to really talk to sales, it’s like, you go from free, and you want to pay, then you pay. And so it’s like, you like the product, you pay, so why it’s called product, like, growth? So they have a self-served
51 00:07:08.510 ⇒ 00:07:16.580 Hannah Wang: Free tier and self-serve paid tier, and then if you’re really big and you require lots of support, then you become enterprise.
52 00:07:16.970 ⇒ 00:07:24.369 Hannah Wang: So, pretty simple, and they wanted that because, like, we found that there was high concentration, so the…
53 00:07:24.370 ⇒ 00:07:39.929 Hannah Wang: There’s a lot of people who use it but don’t pay, or pay very little, and why they want to use PLG is to make these people self-serve, make their upgrade barrier simpler, so they pay more, so you have a flatter and healthier curve.
54 00:07:40.160 ⇒ 00:07:52.779 Hannah Wang: So that’s number one they’re considering. Number two, option two is, like, they want vertical pricing, meaning marketing uses one, operations uses one, sales uses one, because they have different needs.
55 00:07:53.030 ⇒ 00:08:01.790 Hannah Wang: And that’s what bigger companies do, like HubSpot, when they get really big. They want to go for that, because they just have so many products. And default wants to be…
56 00:08:01.920 ⇒ 00:08:07.609 Hannah Wang: having so many products, they want to be big. So, like, that’s what they’re considering.
57 00:08:08.230 ⇒ 00:08:13.349 Hannah Wang: And, essentially, we’re helping them evaluate if, should you…
58 00:08:13.610 ⇒ 00:08:16.349 Hannah Wang: Should you do vertical pricing?
59 00:08:16.900 ⇒ 00:08:18.369 Hannah Wang: Should you do it now?
60 00:08:18.580 ⇒ 00:08:23.590 Hannah Wang: But if you want to do it, if you can’t do it now, but you want it in the future, how should you design it now?
61 00:08:23.860 ⇒ 00:08:28.549 Hannah Wang: If you end up doing horizontal pricing, what should you base it on?
62 00:08:28.930 ⇒ 00:08:35.460 Hannah Wang: What should you classify the different tiers based off of? Like, what classifies free versus
63 00:08:36.080 ⇒ 00:08:41.800 Hannah Wang: self-serve pay, so you actually upgrade. Like, you get some value, but not enough, so you upgrade.
64 00:08:42.470 ⇒ 00:08:44.909 Hannah Wang: Let’s see…
65 00:08:45.470 ⇒ 00:08:55.060 Hannah Wang: So they haven’t chosen which… yeah, they’re at the… like, that’s the context, right? That’s, like, at the…
66 00:08:55.350 ⇒ 00:09:03.470 Hannah Wang: I guess? So, we had some challenges, it was like, Highly concentrated revenue,
67 00:09:04.160 ⇒ 00:09:12.200 Hannah Wang: Just uncertainty of, like, which pricing would work, and don’t want to make big changes, because you don’t want
68 00:09:12.420 ⇒ 00:09:15.849 Hannah Wang: Big effects, and then losing a lot of customers.
69 00:09:15.970 ⇒ 00:09:19.620 Hannah Wang: And then, I guess the first solution we’re doing is…
70 00:09:20.250 ⇒ 00:09:30.709 Hannah Wang: helping them analyze, like, the relationship between revenue and their current usage. So I guess that’s, like, a feature… feature usage analysis, or just feature analysis.
71 00:09:31.380 ⇒ 00:09:46.849 Hannah Wang: The second thing is, like, a pricing backtest to see if you were to do this, what would end up… what would it end up being? So, if you price it at this, using this variable.
72 00:09:47.000 ⇒ 00:09:52.310 Hannah Wang: How much money would you be getting this month versus that?
73 00:09:52.700 ⇒ 00:09:53.899 Hannah Wang: Bad idea.
74 00:09:54.450 ⇒ 00:10:00.610 Hannah Wang: Okay, that’s two solutions, I can just think of another one. It’s okay, I think two is good. Okay.
75 00:10:02.110 ⇒ 00:10:08.689 Hannah Wang: Mmm… Tool used… I don’t know, I use cursor, we can’t put cursor…
76 00:10:09.090 ⇒ 00:10:14.010 Hannah Wang: Let’s see… what did you use to build the… oh, it’s just cursor?
77 00:10:14.120 ⇒ 00:10:16.830 Hannah Wang: Like, at a, like, the…
78 00:10:17.940 ⇒ 00:10:31.909 Hannah Wang: Well, if we’re talking about this, like, I guess we can also talk about the fact that we put their data together. Okay, so I’ll talk about that, too. So we… we help them put all their data in, like.
79 00:10:32.200 ⇒ 00:10:47.300 Hannah Wang: warehouse, and then modeled it, so… Is this Snowflake, or what warehouse is it? I think we’re in Mother Duck. Okay. Maybe they went from Snowflake to Mother Duck, whatever. Someone else can help me answer that. I cannot. You can ask Mustafa.
80 00:10:47.380 ⇒ 00:10:56.119 Hannah Wang: So we built that, and we built a dashboard. I don’t know if you talked about it here, though. These are just AI browsers. Oh, okay, so we built a dashboard.
81 00:10:56.930 ⇒ 00:11:01.969 Hannah Wang: Yes, that… the dashboard can go on the top. Dashboard 4… Dashboard 4.
82 00:11:02.130 ⇒ 00:11:07.469 Hannah Wang: Their… all their usage, their customer demographics…
83 00:11:07.610 ⇒ 00:11:16.539 Hannah Wang: their revenue, so, like, a KPI, an executive dashboard, so they’re finally tracking and seeing the difference.
84 00:11:17.980 ⇒ 00:11:21.100 Hannah Wang: Oh, another challenge. Some people are not paying, though.
85 00:11:21.270 ⇒ 00:11:34.300 Hannah Wang: They’re not paying what? Like, some of their customers have not been paying, and they’ve only found out, like… Oh, what? Like, they… but they’ve been using the paid version, but they haven’t been paying. It’s hard to track, but you need to hire someone to go track.
86 00:11:34.510 ⇒ 00:11:41.810 Hannah Wang: track payments. Dang. Like, that’s a special person. They’ve been losing money. I guess they’ve been growing fast enough. Well, they’re… there’s…
87 00:11:41.960 ⇒ 00:11:48.859 Hannah Wang: Series A, right? They’re funded or something? I guess that’s why. Like, Uten would never have done that. Yeah.
88 00:11:52.730 ⇒ 00:12:00.809 Hannah Wang: Yeah. I don’t know if we can put it on, though. That’s okay. And we can just say, like, some people are, like, not paying, like, not making their payment times.
89 00:12:01.640 ⇒ 00:12:09.599 Hannah Wang: And so now they… like, I also… Solutions Dashboard…
90 00:12:10.080 ⇒ 00:12:14.400 Hannah Wang: Data warehouse, so that we can actually analyze anything.
91 00:12:14.730 ⇒ 00:12:32.990 Hannah Wang: Pricing backtests, pricing, like, feature analysis, like, also helping them point out their under-monetized customers, so some people who are high usage, low revenue, helping them go after that, so…
92 00:12:33.160 ⇒ 00:12:48.469 Hannah Wang: Oh, yeah, that would be helpful for them. So, like, their customer service success… customer success is using that list to go after the certain people to say, hey, you use it a lot, you’re not really paying us, what do you want to do? Like, do you want to upgrade? Do this?
93 00:12:50.310 ⇒ 00:12:56.660 Hannah Wang: That’s all the solutions. Nice. Right now. That’s a lot. That is a lot. You have a few to choose from.
94 00:12:57.040 ⇒ 00:12:58.749 Hannah Wang: And who was the team?
95 00:12:58.880 ⇒ 00:13:11.130 Hannah Wang: So, that’s Utam, so PMing it, I’m the data analyst for the AI and data engineer? You can put another person, a data engineer, he doesn’t… he doesn’t care.
96 00:13:11.540 ⇒ 00:13:14.489 Hannah Wang: It’s okay, I feel like Listoffa doesn’t care.
97 00:13:16.000 ⇒ 00:13:20.199 Hannah Wang: Yeah, I think we don’t need, like, AI engineer. Just the engineer, yeah.
98 00:13:20.500 ⇒ 00:13:25.649 Hannah Wang: Oh, I mean, there… I guess you also talked about it up there, but…
99 00:13:25.890 ⇒ 00:13:35.710 Hannah Wang: like, the enrichment also helped me. The enrichment that we did there helped me analyze of who is the customer, is that…
100 00:13:36.260 ⇒ 00:13:42.280 Hannah Wang: underpay, or who are the customers who grow a lot, but I don’t know if that’s the most relevant.
101 00:13:42.810 ⇒ 00:13:52.340 Hannah Wang: Okay. Results… I don’t know. TBD. Okay. And then, so this, overall, the project is, like, just…
102 00:13:53.160 ⇒ 00:14:02.100 Hannah Wang: helping a SaaS product price their… Reprice? Reprice their offers.
103 00:14:02.660 ⇒ 00:14:05.819 Hannah Wang: Like, reprice their whole package. Okay.
104 00:14:06.380 ⇒ 00:14:12.639 Hannah Wang: repriced their offerings, I guess. Package offerings? Package?
105 00:14:13.900 ⇒ 00:14:16.250 Hannah Wang: And would that be helpful for other SaaS?
106 00:14:16.730 ⇒ 00:14:22.829 Hannah Wang: companies, like, ideally, obviously, we’d send this to other SaaS companies, so I’m just thinking, like, what would catch
107 00:14:23.340 ⇒ 00:14:29.140 Hannah Wang: a SaaS products, like, attention for the CTA.
108 00:14:29.960 ⇒ 00:14:33.160 Hannah Wang: losing revenue? I don’t know.
109 00:14:35.590 ⇒ 00:14:40.689 Hannah Wang: They wouldn’t know if their value is leaking. That’s true. But they would fear that their value is leaking.
110 00:14:41.030 ⇒ 00:14:51.249 Hannah Wang: Great, you can say… Like, are you getting your full customer value, or…
111 00:14:51.540 ⇒ 00:14:52.710 Hannah Wang: It’s true.
112 00:14:52.850 ⇒ 00:15:00.859 Hannah Wang: are you really pricing the way that’s optimal? Because most people just price, like, randomly, like, a subscription at…
113 00:15:00.940 ⇒ 00:15:11.180 Hannah Wang: Like, mmm, 50 guy. Right. Just a random number, or, like, $29.99. Yeah. Okay. Oh, and also solution, like, we’re trying to find…
114 00:15:11.180 ⇒ 00:15:22.999 Hannah Wang: thresholds for them based on their current usage data. And we’re going to run experiments. So you can probably, in solution, put, like, pricing experiments and back tests
115 00:15:27.340 ⇒ 00:15:45.650 Hannah Wang: We can say, like, still pricing based on a whim? A whim. Most of it is, like, I want this to be 39. They’re just guessing, kind of. That’s it. Okay.
116 00:15:46.350 ⇒ 00:15:51.359 Hannah Wang: And then… question, still pricing based off of a win?
117 00:15:51.510 ⇒ 00:16:06.880 Hannah Wang: Don’t do that. Stop it now. We can say… will help you… Price… I think…
118 00:16:09.120 ⇒ 00:16:11.839 Hannah Wang: Burn more?
119 00:16:12.290 ⇒ 00:16:17.430 Hannah Wang: Earn more. Save money, live better.
120 00:16:20.650 ⇒ 00:16:27.550 Hannah Wang: Let’s change that? Yeah. Okay, sure. Okay, whatever. Okay. Good enough. Yeah.
121 00:16:27.840 ⇒ 00:16:35.110 Hannah Wang: What’s the title gonna be? Oh, I don’t know. I’ll just take the transcript and…
122 00:16:35.590 ⇒ 00:16:40.310 Hannah Wang: Run with it. A data-driven… ugh, data-driven’s used.
123 00:16:41.110 ⇒ 00:16:46.479 Hannah Wang: But it is true. It is true, but it just means nothing.
124 00:16:54.910 ⇒ 00:16:56.530 Hannah Wang: Value match?
125 00:17:00.670 ⇒ 00:17:02.310 Hannah Wang: Value-based.
126 00:17:02.840 ⇒ 00:17:10.059 Hannah Wang: SaaS pricing? SaaS pricing. Or, like, PLG praise, transitioning to PLG pricing? For SaaS?
127 00:17:10.190 ⇒ 00:17:12.320 Hannah Wang: For… yeah.
128 00:17:12.760 ⇒ 00:17:15.790 Hannah Wang: PLGO’s product-led growth.
129 00:17:17.440 ⇒ 00:17:27.389 Hannah Wang: It can either be bad, so we attract people who want to do PLG pricing, or we attract people who, like, are doubtful of their current pricing, but not necessarily for PLG.
130 00:17:30.800 ⇒ 00:17:33.209 Hannah Wang: Yeah, I guess there’s the option. Okay, sure.
131 00:17:33.470 ⇒ 00:17:45.289 Hannah Wang: And then, how… when did you start the… when did we start the pricing stuff? This month, so, like, mid-October. Okay, I’ll just say Q4. Okay. Because it’s still ongoing, right? Yeah. So…
132 00:17:45.890 ⇒ 00:17:48.180 Hannah Wang: Okay, this is the time is…
133 00:17:49.660 ⇒ 00:18:07.930 Hannah Wang: I see. I’m like, the value cheap, I don’t know. Like, pricing analysis? Data analysis? Pricing data analysis. Strategic analysis? Strategic analysis. Strategic pricing… I guess we don’t have to say pricing, it’s just…
134 00:18:07.930 ⇒ 00:18:16.229 Hannah Wang: strategic analysis for, like, sales, or… Oh, like, go-to-market? Go to market?
135 00:18:16.590 ⇒ 00:18:22.429 Hannah Wang: That’s probably the function, right? Go-to-market? Go-to-market, then pricing, same place.
136 00:18:23.080 ⇒ 00:18:30.100 Hannah Wang: Okay, some… somewhere there. Cool, great. Okay, pause recording this one.
137 00:18:31.440 ⇒ 00:18:34.460 Hannah Wang: Wow, that was long. That’s okay. Bye!