1 00:00:00,000 --> 00:00:02,320 Every single digital product you use. 2 00:00:02,320 --> 00:00:05,000 I mean, think about your fitness tracker, your banking app, 3 00:00:05,000 --> 00:00:06,640 even the news site you scroll through. 4 00:00:06,640 --> 00:00:10,040 They're all generating this massive stream of data. 5 00:00:10,040 --> 00:00:12,400 A constant stream, all about your behavior. 6 00:00:12,400 --> 00:00:13,520 Exactly. 7 00:00:13,520 --> 00:00:15,560 And for the businesses building these products, 8 00:00:15,560 --> 00:00:18,320 the challenge isn't just collecting it anymore. 9 00:00:18,320 --> 00:00:19,600 That was the old problem. 10 00:00:19,600 --> 00:00:21,360 The real challenge now is figuring out 11 00:00:21,360 --> 00:00:22,600 what to do with it all. 12 00:00:22,600 --> 00:00:24,840 And how to do it while respecting user privacy, 13 00:00:24,840 --> 00:00:26,720 which is, that's the crucial part. 14 00:00:26,720 --> 00:00:27,320 It is. 15 00:00:27,320 --> 00:00:30,360 So today, we're doing a deep dive into exactly that. 16 00:00:30,360 --> 00:00:32,800 Modern product analytics, and specifically, 17 00:00:32,800 --> 00:00:35,560 platforms that are built to handle billions of data points 18 00:00:35,560 --> 00:00:38,320 while keeping control and privacy right at the center. 19 00:00:38,320 --> 00:00:41,080 We're going to use a simple framework, capture, analyze, 20 00:00:41,080 --> 00:00:41,600 and act. 21 00:00:41,600 --> 00:00:42,100 Right. 22 00:00:42,100 --> 00:00:44,800 And our mission here is to show you, the learner, 23 00:00:44,800 --> 00:00:47,520 why owning your data, truly controlling it, 24 00:00:47,520 --> 00:00:51,120 has become this new non-negotiable competitive 25 00:00:51,120 --> 00:00:52,360 advantage. 26 00:00:52,360 --> 00:00:54,760 But before we jump in, a quick word from our supporter. 27 00:00:54,760 --> 00:00:56,760 This deep dive is supported by Safe Server. 28 00:00:56,760 --> 00:00:58,720 They handle hosting for this kind of software 29 00:00:58,720 --> 00:01:00,960 and can support you in your digital transformation. 30 00:01:00,960 --> 00:01:05,240 You can find more info at www.safeserver.de. 31 00:01:05,240 --> 00:01:06,720 OK, so let's get into it. 32 00:01:06,720 --> 00:01:09,560 We've got sources on how platforms like Countly work. 33 00:01:09,560 --> 00:01:12,080 And they're not just simple log collectors. 34 00:01:12,080 --> 00:01:16,320 They're designed to make sense of billions of user actions 35 00:01:16,320 --> 00:01:18,040 and turn them into something meaningful. 36 00:01:18,040 --> 00:01:20,640 And that's a really important shift to understand. 37 00:01:20,640 --> 00:01:23,480 Product analytics isn't like old school web metrics. 38 00:01:23,480 --> 00:01:25,320 We're not just counting page views anymore. 39 00:01:25,320 --> 00:01:26,600 No, it's way beyond that. 40 00:01:26,600 --> 00:01:29,680 It's about understanding the journey, the specific actions, 41 00:01:29,680 --> 00:01:32,080 where users get stuck, where they succeed. 42 00:01:32,080 --> 00:01:34,600 You use all of that to build a better product. 43 00:01:34,600 --> 00:01:37,000 But our sources point out these two big tensions. 44 00:01:37,000 --> 00:01:37,560 Which are? 45 00:01:37,560 --> 00:01:40,680 One, data without action is totally useless. 46 00:01:40,680 --> 00:01:44,680 And two, analytics without control is just, well, 47 00:01:44,680 --> 00:01:45,480 it's risky. 48 00:01:45,480 --> 00:01:46,760 You have to solve for both. 49 00:01:46,760 --> 00:01:49,840 And that idea of control brings us straight to this concept 50 00:01:49,840 --> 00:01:52,160 we need to establish right up front. 51 00:01:52,160 --> 00:01:54,560 First party digital analytics. 52 00:01:54,560 --> 00:01:55,760 What does that actually mean? 53 00:01:55,760 --> 00:01:57,560 It means total ownership. 54 00:01:57,560 --> 00:01:58,360 Simple as that. 55 00:01:58,360 --> 00:02:00,560 The organization captures data directly 56 00:02:00,560 --> 00:02:03,120 from the user's device, their phone, their laptop, whatever. 57 00:02:03,120 --> 00:02:04,320 So there's no middleman. 58 00:02:04,320 --> 00:02:05,040 Exactly. 59 00:02:05,040 --> 00:02:07,440 The data is owned, controlled, and stored 60 00:02:07,440 --> 00:02:11,440 by the business itself, not some third party analytics company. 61 00:02:11,440 --> 00:02:14,400 It just cuts out a whole lot of privacy and data leakage 62 00:02:14,400 --> 00:02:16,360 concerns right from the start. 63 00:02:16,360 --> 00:02:19,920 It builds data sovereignty right into the product's DNA. 64 00:02:19,920 --> 00:02:21,660 I like that, built into the DNA. 65 00:02:21,660 --> 00:02:25,240 So that control starts with the very first pillar, capture. 66 00:02:25,240 --> 00:02:28,280 How do businesses even begin to get reliable data 67 00:02:28,280 --> 00:02:34,320 from a website, an Android app, an iOS app, a smart TV, 68 00:02:34,320 --> 00:02:35,000 all at once? 69 00:02:35,000 --> 00:02:36,960 Well, it really comes down to two things, 70 00:02:36,960 --> 00:02:40,080 versatility and good governance. 71 00:02:40,080 --> 00:02:41,880 First, the versatility part. 72 00:02:41,880 --> 00:02:43,600 Platforms like this use a whole range 73 00:02:43,600 --> 00:02:46,080 of what are called SDKs, software development kits. 74 00:02:46,080 --> 00:02:46,600 OK. 75 00:02:46,600 --> 00:02:48,680 Our sources mentioned, Countly has 10 of them, 76 00:02:48,680 --> 00:02:49,600 all battle tested. 77 00:02:49,600 --> 00:02:52,560 They cover mobile, web, desktop, pretty much any connected 78 00:02:52,560 --> 00:02:53,680 device you can think of. 79 00:02:53,680 --> 00:02:55,200 Wait a second, 10 SDKs? 80 00:02:55,200 --> 00:02:56,640 Why is that number a big deal? 81 00:02:56,640 --> 00:02:58,720 Don't most analytics tools have an SDK? 82 00:02:58,720 --> 00:03:01,160 They do, but having a whole native suite like that 83 00:03:01,160 --> 00:03:03,040 prevents what we call data silos if you 84 00:03:03,040 --> 00:03:04,840 use one tool for your mobile app and a different one 85 00:03:04,840 --> 00:03:05,560 for your website. 86 00:03:05,560 --> 00:03:07,160 The data doesn't talk to each other. 87 00:03:07,160 --> 00:03:08,800 It never truly connects. 88 00:03:08,800 --> 00:03:11,480 By using a unified set of SDKs, you're 89 00:03:11,480 --> 00:03:13,120 ensuring that a user action means 90 00:03:13,120 --> 00:03:14,520 the same thing everywhere. 91 00:03:14,520 --> 00:03:16,880 It gives you one clean, unified stream 92 00:03:16,880 --> 00:03:18,360 of data from the get-go. 93 00:03:18,360 --> 00:03:21,100 One source of truth. 94 00:03:21,100 --> 00:03:22,680 That makes total sense. 95 00:03:22,680 --> 00:03:25,880 But what about data that doesn't come from a standard app, 96 00:03:25,880 --> 00:03:28,580 like from an internal system or something custom? 97 00:03:28,580 --> 00:03:31,040 That's where a Good Data Write API comes in. 98 00:03:31,040 --> 00:03:32,240 This is so critical. 99 00:03:32,240 --> 00:03:35,800 It lets the business push data in from literally any system, 100 00:03:35,800 --> 00:03:39,080 internal databases, customer service logs, you name it. 101 00:03:39,080 --> 00:03:41,920 So you can enrich the user's profile with information 102 00:03:41,920 --> 00:03:43,620 from outside the app itself. 103 00:03:43,620 --> 00:03:44,120 Right. 104 00:03:44,120 --> 00:03:47,400 You get a true 360-degree view of the customer. 105 00:03:47,400 --> 00:03:49,800 And again, you're not using some other third-party tool 106 00:03:49,800 --> 00:03:50,960 to glue it all together. 107 00:03:50,960 --> 00:03:54,120 But even with a unified stream, collecting billions 108 00:03:54,120 --> 00:03:57,040 of data points could just be noise if the data is messy. 109 00:03:57,040 --> 00:03:59,360 The whole garbage in, garbage out problem. 110 00:03:59,360 --> 00:04:01,680 And that's where the governance part becomes essential. 111 00:04:01,680 --> 00:04:04,480 You need tools to manage the data, to plan it, 112 00:04:04,480 --> 00:04:07,520 validate it, filter it, sometimes even transform it 113 00:04:07,520 --> 00:04:09,280 before or after it's captured. 114 00:04:09,280 --> 00:04:10,400 What's an example of that? 115 00:04:10,400 --> 00:04:13,640 Well, you could say, validate that every timestamp you receive 116 00:04:13,640 --> 00:04:15,200 is in the correct format. 117 00:04:15,200 --> 00:04:16,920 Or you could filter out all the traffic 118 00:04:16,920 --> 00:04:18,920 from your own company's IP addresses 119 00:04:18,920 --> 00:04:21,480 so you're not analyzing your own employee's behavior. 120 00:04:21,480 --> 00:04:22,600 Ah, OK. 121 00:04:22,600 --> 00:04:24,760 So it's about cleaning the data before it even 122 00:04:24,760 --> 00:04:26,120 hits the analysis engine. 123 00:04:26,120 --> 00:04:27,120 Exactly. 124 00:04:27,120 --> 00:04:28,800 It ensures the insights you get later 125 00:04:28,800 --> 00:04:31,680 are based on clean, trustworthy data. 126 00:04:31,680 --> 00:04:35,160 And this all ties back to that core idea of data sovereignty 127 00:04:35,160 --> 00:04:37,440 because the sources really emphasize 128 00:04:37,440 --> 00:04:40,600 that the organization keeps total control over hosting. 129 00:04:40,600 --> 00:04:42,040 It's the ultimate safeguard. 130 00:04:42,040 --> 00:04:43,360 You get to choose. 131 00:04:43,360 --> 00:04:45,680 Use the platform's cloud or self-host it 132 00:04:45,680 --> 00:04:48,560 on your own servers, either on-premise or in a private cloud. 133 00:04:48,560 --> 00:04:51,000 Which, for certain industries, must be a requirement. 134 00:04:51,000 --> 00:04:51,720 Absolutely. 135 00:04:51,720 --> 00:04:54,760 Think about health care with Hypea, or finance, 136 00:04:54,760 --> 00:04:56,680 or anything dealing with GDPR in Europe. 137 00:04:56,680 --> 00:05:00,200 For them, being able to say, our data lives here and only here 138 00:05:00,200 --> 00:05:02,680 isn't a feature, it's a fundamental requirement 139 00:05:02,680 --> 00:05:05,080 for compliance, for trust. 140 00:05:05,080 --> 00:05:08,280 So CAPTCHA is all about getting comprehensive, clean data 141 00:05:08,280 --> 00:05:10,640 and having complete control over where it lives. 142 00:05:10,640 --> 00:05:12,800 Once you have that, you move to the next step. 143 00:05:12,800 --> 00:05:13,660 Analyze. 144 00:05:13,660 --> 00:05:14,160 Right. 145 00:05:14,160 --> 00:05:16,760 And the goal here is to democratize that data, 146 00:05:16,760 --> 00:05:19,520 to make it useful for everyone, not just 147 00:05:19,520 --> 00:05:21,120 a team of data scientists. 148 00:05:21,120 --> 00:05:22,640 So it can't be something that requires 149 00:05:22,640 --> 00:05:25,760 weeks of manual querying to get a simple answer. 150 00:05:25,760 --> 00:05:26,320 No way. 151 00:05:26,320 --> 00:05:27,800 It has to be team friendly. 152 00:05:27,800 --> 00:05:30,040 A product manager should be able to jump in and check 153 00:05:30,040 --> 00:05:33,000 a conversion rate just as easily as a data analyst can 154 00:05:33,000 --> 00:05:35,920 do a really deep behavioral segmentation. 155 00:05:35,920 --> 00:05:38,240 So it's balancing that accessibility 156 00:05:38,240 --> 00:05:39,960 with real analytical power. 157 00:05:39,960 --> 00:05:40,680 That's the key. 158 00:05:40,680 --> 00:05:44,920 So you'll have ready to use reports for those quick insights. 159 00:05:44,920 --> 00:05:48,200 But you also get these powerful custom dashboards 160 00:05:48,200 --> 00:05:51,000 where you can visualize the data exactly how you need to. 161 00:05:51,000 --> 00:05:53,720 Like tracking trends over time or comparing different user 162 00:05:53,720 --> 00:05:54,200 groups. 163 00:05:54,200 --> 00:05:55,040 Exactly. 164 00:05:55,040 --> 00:05:57,200 You could do a cohort analysis to see 165 00:05:57,200 --> 00:05:58,860 how users who signed up last month 166 00:05:58,860 --> 00:06:01,480 behave differently from users who signed up today. 167 00:06:01,480 --> 00:06:04,320 Or you can build funnels to see exactly where people are 168 00:06:04,320 --> 00:06:06,480 dropping off in the sign up process. 169 00:06:06,480 --> 00:06:09,120 It's about finding those actionable insights. 170 00:06:09,120 --> 00:06:12,040 And the scale mentioned in the sources is pretty wild. 171 00:06:12,040 --> 00:06:15,120 To do this reliably, the infrastructure must be massive. 172 00:06:15,120 --> 00:06:17,120 Oh, the scale is staggering. 173 00:06:17,120 --> 00:06:21,340 It tracks, what, 1.5 billion unique identities. 174 00:06:21,340 --> 00:06:24,880 It's used on over 16,000 applications, 175 00:06:24,880 --> 00:06:27,240 running on more than 2,000 servers. 176 00:06:27,240 --> 00:06:28,800 Billions of data points a day. 177 00:06:28,800 --> 00:06:29,360 Right. 178 00:06:29,360 --> 00:06:31,800 And for you, if you're maybe at a smaller company, 179 00:06:31,800 --> 00:06:33,920 you might think, why does that matter to me? 180 00:06:33,920 --> 00:06:36,800 It matters because it proves the architecture is battle tested. 181 00:06:36,800 --> 00:06:38,840 It's not going to fall over when your app suddenly 182 00:06:38,840 --> 00:06:39,920 becomes a huge hit. 183 00:06:39,920 --> 00:06:40,960 That's a great point. 184 00:06:40,960 --> 00:06:42,360 It's not a vanity metric. 185 00:06:42,360 --> 00:06:45,040 It's proof of resilience for the future. 186 00:06:45,040 --> 00:06:46,960 And speaking of the future, the sources 187 00:06:46,960 --> 00:06:49,480 touch on AI-powered analytics. 188 00:06:49,480 --> 00:06:51,240 That sounds like a game changer. 189 00:06:51,240 --> 00:06:54,440 It's a huge shift in how quickly you can get answers. 190 00:06:54,440 --> 00:06:56,520 The AI can help generate complex reports, 191 00:06:56,520 --> 00:06:58,400 build dashboards for you, and even 192 00:06:58,400 --> 00:06:59,800 recommend things to look at. 193 00:06:59,800 --> 00:07:01,320 So it automates the grunt work. 194 00:07:01,320 --> 00:07:01,840 It does. 195 00:07:01,840 --> 00:07:03,760 But more than that, it can spot patterns 196 00:07:03,760 --> 00:07:05,960 that a human might just miss. 197 00:07:05,960 --> 00:07:09,080 Subtle correlations in huge data sets. 198 00:07:09,080 --> 00:07:11,760 It just speeds up that whole path from seeing raw data 199 00:07:11,760 --> 00:07:14,080 to having a real insight you can act on. 200 00:07:14,080 --> 00:07:16,320 And accelerating that path is the whole point, which 201 00:07:16,320 --> 00:07:17,800 brings us to the third pillar. 202 00:07:17,800 --> 00:07:19,920 Act, because analysis is pointless if you 203 00:07:19,920 --> 00:07:21,200 don't do anything with it. 204 00:07:21,200 --> 00:07:26,320 And this is where that privacy first party model really shines. 205 00:07:26,320 --> 00:07:28,060 All the action you take, the engagement, 206 00:07:28,060 --> 00:07:30,960 the personalization, it's all done with built-in tools. 207 00:07:30,960 --> 00:07:34,080 You're not exporting your private user data 208 00:07:34,080 --> 00:07:36,080 to some third party marketing tool. 209 00:07:36,080 --> 00:07:36,640 Never. 210 00:07:36,640 --> 00:07:39,760 The whole loop is contained in one secure system. 211 00:07:39,760 --> 00:07:42,000 It massively simplifies your compliance 212 00:07:42,000 --> 00:07:44,160 and reduces your security risk. 213 00:07:44,160 --> 00:07:46,720 OK, so tell us about some of those built-in tools 214 00:07:46,720 --> 00:07:47,960 for taking action. 215 00:07:47,960 --> 00:07:49,960 Well, a big one is called Journeys. 216 00:07:49,960 --> 00:07:53,380 This lets you build these automated customer workflows. 217 00:07:53,380 --> 00:07:57,040 So if a user does action x, you can automatically send them 218 00:07:57,040 --> 00:07:58,520 an in-app message y. 219 00:07:58,520 --> 00:08:01,440 If they respond to that, you nudge them towards action z. 220 00:08:01,440 --> 00:08:03,600 So it's like guiding the user in real time 221 00:08:03,600 --> 00:08:05,140 based on what they're actually doing. 222 00:08:05,140 --> 00:08:07,360 It's proactive guidance, exactly. 223 00:08:07,360 --> 00:08:08,880 And that kind of real-time response 224 00:08:08,880 --> 00:08:10,800 makes the app feel super personalized. 225 00:08:10,800 --> 00:08:13,520 Which I guess is where something called Smart Variables comes in. 226 00:08:13,520 --> 00:08:14,640 Am I understanding this right? 227 00:08:14,640 --> 00:08:17,080 Is this about changing the app's UI on the fly? 228 00:08:17,080 --> 00:08:18,280 It can be, yeah. 229 00:08:18,280 --> 00:08:21,100 It can be subtle or it can be a major change. 230 00:08:21,100 --> 00:08:24,560 Smart Variables let you tailor the app's logic and interface 231 00:08:24,560 --> 00:08:25,880 based on user data. 232 00:08:25,880 --> 00:08:27,360 So give me an example. 233 00:08:27,360 --> 00:08:29,880 OK, imagine the app sees you're a first-time user 234 00:08:29,880 --> 00:08:32,560 and you haven't finished the onboarding steps. 235 00:08:32,560 --> 00:08:35,480 A Smart Variable could instantly change the main button 236 00:08:35,480 --> 00:08:38,560 on the home screen, say, complete your setup instead 237 00:08:38,560 --> 00:08:41,360 of explore features. 238 00:08:41,360 --> 00:08:44,460 So it's tailoring the experience without a programmer 239 00:08:44,460 --> 00:08:47,680 having to code every single possible version of the app. 240 00:08:47,680 --> 00:08:48,200 That's it. 241 00:08:48,200 --> 00:08:51,480 It's instantaneous behavioral customization. 242 00:08:51,480 --> 00:08:53,960 On top of that, you need to test these things, right, 243 00:08:53,960 --> 00:08:55,880 to know if a new message is actually working. 244 00:08:55,880 --> 00:08:56,660 Of course. 245 00:08:56,660 --> 00:08:59,080 So you have things like built-in A-B testing 246 00:08:59,080 --> 00:09:01,200 to refine your messages. 247 00:09:01,200 --> 00:09:05,040 But another really powerful tool here is remote configuration. 248 00:09:05,040 --> 00:09:06,080 This is vital. 249 00:09:06,080 --> 00:09:08,080 Remote config. 250 00:09:08,080 --> 00:09:09,240 That sounds a bit abstract. 251 00:09:09,240 --> 00:09:11,360 Can you give us a concrete example of how that's used? 252 00:09:11,360 --> 00:09:12,160 Sure. 253 00:09:12,160 --> 00:09:14,700 Let's say you just launched a big marketing campaign, 254 00:09:14,700 --> 00:09:17,400 and you spot a typo in the main call to action 255 00:09:17,400 --> 00:09:18,740 button in your app. 256 00:09:18,740 --> 00:09:20,440 It's causing people to get confused. 257 00:09:20,440 --> 00:09:22,100 Normally, you'd have to code a fix, 258 00:09:22,100 --> 00:09:25,400 submit a new version of the app to the app store, wait for review. 259 00:09:25,400 --> 00:09:26,600 It could take days. 260 00:09:26,600 --> 00:09:28,740 Right, and you're losing customers that whole time. 261 00:09:28,740 --> 00:09:30,440 With remote config, the product team 262 00:09:30,440 --> 00:09:32,520 can just push the text correction instantly 263 00:09:32,520 --> 00:09:34,000 to every single user. 264 00:09:34,000 --> 00:09:35,840 The fix goes live in seconds. 265 00:09:35,840 --> 00:09:37,520 No app update needed. 266 00:09:37,520 --> 00:09:39,040 It can save you from a disaster. 267 00:09:39,040 --> 00:09:40,040 That's powerful. 268 00:09:40,040 --> 00:09:41,520 And the final piece of the puzzle 269 00:09:41,520 --> 00:09:43,640 is actually listening to the customer, 270 00:09:43,640 --> 00:09:45,000 not just watching their clicks. 271 00:09:45,000 --> 00:09:46,720 Right, closing the feedback loop. 272 00:09:46,720 --> 00:09:49,000 So the platform lets you send out these really targeted 273 00:09:49,000 --> 00:09:49,900 surveys. 274 00:09:49,900 --> 00:09:53,040 You can ask only the users who just used a new feature what 275 00:09:53,040 --> 00:09:53,920 they thought of it. 276 00:09:53,920 --> 00:09:55,720 And then follow up with push notification. 277 00:09:55,720 --> 00:09:56,320 Exactly. 278 00:09:56,320 --> 00:09:58,720 Automated, personalized push notifications, 279 00:09:58,720 --> 00:10:00,340 all sent from within the same system. 280 00:10:00,340 --> 00:10:03,320 So it's a complete private ecosystem. 281 00:10:03,320 --> 00:10:05,920 Capture, understand, and then act. 282 00:10:05,920 --> 00:10:08,600 But this whole structure, capture, analyze, act, 283 00:10:08,600 --> 00:10:10,060 it's all built on an architecture 284 00:10:10,060 --> 00:10:12,840 that has to be secure and compliant from the ground up. 285 00:10:12,840 --> 00:10:14,140 It's the foundation. 286 00:10:14,140 --> 00:10:16,280 Security can't be an afterthought. 287 00:10:16,280 --> 00:10:19,880 Because the platform is designed with this privacy first mindset, 288 00:10:19,880 --> 00:10:21,760 it inherently helps organizations 289 00:10:21,760 --> 00:10:24,160 meet those tough regulations we mentioned. 290 00:10:24,160 --> 00:10:26,120 HIPAA, GDPR, COPPA. 291 00:10:26,120 --> 00:10:28,200 So what's the tech that makes that possible? 292 00:10:28,200 --> 00:10:31,400 What's under the hood that allows it to handle all this data securely? 293 00:10:31,400 --> 00:10:36,000 The stack is built on really solid, popular open source technologies. 294 00:10:36,000 --> 00:10:38,140 It uses MongoDB as the database, 295 00:10:38,140 --> 00:10:41,800 which is great for this kind of unstructured event data. 296 00:10:41,800 --> 00:10:43,800 Then Node.js for the backend, 297 00:10:43,800 --> 00:10:46,920 which is super fast for this sort of thing, all running on Linux. 298 00:10:46,920 --> 00:10:49,880 It's a very scalable and robust combination. 299 00:10:49,880 --> 00:10:53,980 And the source has mentioned that the core server is open source. 300 00:10:53,980 --> 00:10:56,120 What's the significance of that for an organization 301 00:10:56,120 --> 00:10:58,020 choosing a platform like this? 302 00:10:58,020 --> 00:10:59,820 It's about trust and transparency. 303 00:10:59,820 --> 00:11:02,860 When the code is open source, it's not a black box. 304 00:11:02,860 --> 00:11:04,960 Your teams can actually inspect the code 305 00:11:04,960 --> 00:11:06,500 to see how data is handled. 306 00:11:06,500 --> 00:11:09,060 So you can verify the security claims for yourself. 307 00:11:09,060 --> 00:11:11,740 You can. And it means the platform is flexible 308 00:11:11,740 --> 00:11:13,380 and has community support. 309 00:11:13,380 --> 00:11:16,020 Knowing the code is out there under a strong license, 310 00:11:16,020 --> 00:11:18,980 like the AGPL 3.0, gives a lot of confidence. 311 00:11:18,980 --> 00:11:21,120 And that open source core is the foundation 312 00:11:21,120 --> 00:11:23,880 for the different ways you can actually use the platform. 313 00:11:23,880 --> 00:11:25,320 Let's quickly run through those options. 314 00:11:25,320 --> 00:11:27,420 Sure. There are basically three paths. 315 00:11:27,420 --> 00:11:29,820 First, for individuals or really small teams, 316 00:11:29,820 --> 00:11:31,180 there's Countly Lite. 317 00:11:31,180 --> 00:11:33,540 It's free, open source, and you host it yourself. 318 00:11:33,540 --> 00:11:35,020 It's a great way to get started. 319 00:11:35,020 --> 00:11:36,460 Okay. And for bigger companies 320 00:11:36,460 --> 00:11:37,820 that need all the bells and whistles? 321 00:11:37,820 --> 00:11:39,840 They go for Countly Enterprise. 322 00:11:39,840 --> 00:11:43,620 That has the widest feature set, more granular controls, 323 00:11:43,620 --> 00:11:46,740 a service level agreement, and direct support. 324 00:11:46,740 --> 00:11:49,860 And you can choose to self-host that or have them manage it. 325 00:11:49,860 --> 00:11:53,040 And the third option, Flex, sounds like a middle ground. 326 00:11:53,040 --> 00:11:53,880 Kind of. 327 00:11:53,880 --> 00:11:56,980 Countly Flex is their fully managed SaaS solution. 328 00:11:56,980 --> 00:11:58,580 You get your own dedicated server 329 00:11:58,580 --> 00:11:59,920 in whatever region you choose, 330 00:11:59,920 --> 00:12:00,980 but you don't have to worry 331 00:12:00,980 --> 00:12:03,260 about managing the infrastructure yourself. 332 00:12:03,260 --> 00:12:05,260 It's great for small to medium businesses 333 00:12:05,260 --> 00:12:08,540 that need that dedicated service without the IT overhead. 334 00:12:08,540 --> 00:12:10,820 Right. So that brings us to our wrap-up. 335 00:12:10,820 --> 00:12:14,100 For you, the listener, there are three key takeaways here. 336 00:12:14,100 --> 00:12:16,960 Modern product analytics needs reliable capture. 337 00:12:16,960 --> 00:12:18,780 Which you get through unified SDKs 338 00:12:18,780 --> 00:12:20,480 and full control over hosting. 339 00:12:20,480 --> 00:12:23,600 Second, effective analysis, driven by dashboards 340 00:12:23,600 --> 00:12:25,660 that are easy for the whole team to use, 341 00:12:25,660 --> 00:12:27,780 plus new AI tools to speed things up. 342 00:12:27,780 --> 00:12:29,460 And third, meaningful action, 343 00:12:29,460 --> 00:12:31,980 using built-in privacy-first tools 344 00:12:31,980 --> 00:12:34,220 like Journeys and Remote Config, 345 00:12:34,220 --> 00:12:36,700 keeping everything in one secure ecosystem. 346 00:12:36,700 --> 00:12:38,500 And the thread that connects all three of those 347 00:12:38,500 --> 00:12:39,980 is data sovereignty. 348 00:12:39,980 --> 00:12:40,820 Absolutely. 349 00:12:40,820 --> 00:12:41,860 The original vision here 350 00:12:41,860 --> 00:12:44,280 was to build a powerful analytics platform 351 00:12:44,280 --> 00:12:46,580 that fundamentally respected data privacy. 352 00:12:46,580 --> 00:12:48,620 Which leaves us with a final provocative thought 353 00:12:48,620 --> 00:12:50,020 for you to consider. 354 00:12:50,020 --> 00:12:52,700 In this world of constant digital transformation 355 00:12:52,700 --> 00:12:56,300 is the ability to maintain full, verifiable control 356 00:12:56,300 --> 00:12:58,180 over your own data. 357 00:12:58,180 --> 00:13:00,740 Is that now the single greatest way to earn 358 00:13:00,740 --> 00:13:02,380 and keep your users' trust? 359 00:13:02,380 --> 00:13:03,780 It really changes the whole question. 360 00:13:03,780 --> 00:13:06,900 It's not how much data can we collect anymore. 361 00:13:06,900 --> 00:13:09,060 It's how well can we protect and act 362 00:13:09,060 --> 00:13:11,060 on the data we completely own. 363 00:13:11,060 --> 00:13:12,500 This deep dive was made possible 364 00:13:12,500 --> 00:13:13,940 with the support of SafeServer, 365 00:13:13,940 --> 00:13:16,860 your partner for hosting software and digital transformation. 366 00:13:16,860 --> 00:13:20,820 You can find out more at www.safeserver.de. 367 00:13:20,820 --> 00:13:22,540 We hope this gives you a much clearer view 368 00:13:22,540 --> 00:13:24,640 of the power behind first-party analytics.