When Customers Need Analytics w/ Jeanne Ngo, Senior Product Marketing Manager at Pentaho

Hey everybody, this is Mike Belcedo with Product Collective, and we're back for another session of Product Lunch. For those of you that are joining us for the first time, these are meant to be a lot of fun. I mean, basically this is sort of like a live video Q&A chat where we have a different guest on every single time. We do these twice per month, and they're really made for product people, so we cover all sorts of topics. I'm really interested in today's topic because this is something that I have had to deal with a little bit in the past, as in my life as a product person, but definitely not something I'm an expert on. So, but we have the expert with us, who is Jeannie Ngo from Pentaho. So I'm excited to introduce Jeannie in just a moment. Before we do that, just a few sort of housekeeping items. If we were kind of dealing with some audiovisual type issues in the beginning, Jeannie and I, If for some reason there's any sort of issue, I'm going to type my questions to Jeanne in the chat. Hopefully you can see and hear us just fine. Maybe you could let me know in the chat if that's the case, but hopefully we've, we've covered those and we're all good there. A couple of other things. I think I mentioned this last time during product launch, but we have a brand new podcast at Product Collective and we're really excited about it. Feedback's been really positive, but it's called Build Launch Scale. So you could search for that and then Apple, Stitcher, you know, wherever you get your podcasts from. And I'd love it if you could check it out. We, in fact, have like 10 conversations recorded that we haven't even released yet. I think we have about 8 episodes released already. So, keep an eye out for that as well. And of course, hopefully, we're gonna be seeing a lot of you at Industry. And of course, we have that coming up in just about 6 weeks or so. Now, that is in Cleveland, Ohio, on September 14th and 15th. So, I'm pumped for that. It'll be great to meet all sorts of you in person. So, and in fact, if you are coming to Industry, maybe you could mention it in the chat there too, because other folks that are coming to Industry that maybe, maybe we could start the connections now. That would be awesome. And somebody else that I know is coming to Industry who's here with us for this live Q&A product launch chat is Jeannie Ngo of Pentaho. Jeannie, thank you so much for joining us today.

Of course, Mike. Thanks so much for having me, and thanks everyone who's on the line right now for joining us today.

Well, I am excited to get to meet you in person too in a few weeks at Industry. But in the meantime, I thought this topic would be great to cover because again, this is one of those that I don't really know a whole lot. So this is partly, this is just me learning from you, but why couldn't everybody else learn at the same time too? But I know oftentimes people have products that, you know, it's at one point you launch them, you get people using them, but at some point those customers, especially if they're living in your product, and it's so important to them, analytics becomes something that's pretty darn important, right?

Yeah, absolutely. And we're seeing it more and more out there in the space.

So yeah, well, that's great. I want to cut— I have definitely a few questions to run by you. Maybe we could just start with you just giving a brief intro. I mean, I know some folks probably already looked at your background, but maybe just give a little brief intro.

Yeah, sure, absolutely. So, um, as Mike mentioned earlier, my name is Jeannie Nowell. I'm on the product marketing team over at Pentaho. And Pentaho itself is a data integration business analytics platform, but a huge, huge chunk of our business is what we call embedded analytics. What that really is is being able to take our analytics, whether it be reporting, visualizations, ad hoc analysis, any of those, and being able to basically plug that into and integrate it with any third-party software. So as a product manager at Pentaho— sorry, product marketer at Pentaho, I work with a good amount of product managers, and those are usually our target market for embedded analytics. Because as you are developing your software, as Mike mentioned, and as customers start to come to you asking for analytics, or you start to see it as a competitive advantage to build analytics into your software, that's really when Pentaho comes into the story. So happy to be here today, happy to, you know, talk to everyone, answer any questions on what I do know about embedded analytics. It's actually a favorite topic of mine because I focus on it day in and day out.

So, well, that's awesome. And I don't want to cut into the questions. One thing I do want to mention, everybody else, there's a specific section called questions and answers. So you see the chat, and that's great, you can connect with people there. But if you have a question that you want me to ask Jeanie, go to the question and answer section and list your question there. I'm going to be checking that frequently. Feel free to upvote other questions that you might see. Within the conversation, I'll probably pull some questions. Definitely at the end, I'm sure we'll have some time to take your questions. So I definitely encourage everybody to do that. But maybe we could just start, you know, I was curious in your experience, you know, working within embedded analytics and working at Pentaho, when do you start to see customers tend to start to require analytics out of the software platforms that they use? I'm curious if that has anything to do with stage of the company, or, you know, just what other variables are sort of a factor there.

Yeah, yeah, sure. That's a great starting question. So when do product managers usually come to us when they need embedded analytics? I mean, I wouldn't say— I know you mentioned stage. I wouldn't say there's a specific stage, right, that analytics is required within a product, but we do see a couple of different use cases and trends among our product managers who come to us. One of them, pretty straightforward though, is if you have a— like, we work with product managers from very small small startups who are looking to launch a product that is purely analytics. And essentially they're selling that data to their customers. Good example of this is IMS. They sell a lot of driver data and how people actually drive with their data to insurance companies. And they wanted to build out a full platform of this data, but they didn't want to build those analytics in-house. And so that's when they took Pentaho and they white-labeled that and made that their product, and essentially they're monetizing off of our software. So that's one example. The other two are the more common ones, I would say. With the other two, one of them is the fact that competitors are starting to offer analytics. And this is a huge, huge sign that once your competitors start to offer up analytics, that's when we start to see surrounding softwares in the similar space start to ask for it as well. Because you don't want to fall behind. And if you can get ahead of those competitors and be proactive about analytics as that feature set in your product, a lot of times you can monetize it. A lot of times it's that value-added feature versus just being a reactive part of the product that customers start to ask for over time. So that's a really good way to get ahead of the market with it. We do see quite a bit of that with those, when people start to come to us because analytics is a competitive offering. It usually drives down from the executive team. It usually drives down from, you know, CIO, CTO, people who are really monitoring that competitive space. And then the classic example is when customers start to ask for it. Usually these are more mature customers. They've been using your software product for a little while, and they want to be able to prove the value of it to both their internal stakeholders that your product is actually worth keeping around. Or to their external stakeholders, to their customers. They want to take it one step further and be able to take their data, their customers' data, and use it in a way where they can provide more value to their end customers. So kind of three different scenarios I mentioned. One is, you know, if your software is data analytics itself, we can help out with that. The other one is when competitors in the space start offering it up. And then the third is really, you know, when customers start to ask for it because they want to prove the value of their product.

Yeah, that's great. That's great. And those last two feel like it's like you never want to be too late with those. Nobody likes playing catch-up with competitors, and it's like on one level, if customers are asking for it continually, maybe, maybe you should have had some sort of offering beforehand. So I think, I think it's great. I'm glad that you sort of set the stage there.

I'm curious, when customers do start requiring analytics, yeah, so Mike, I might be having a few technical issues again. Can you just ask the next questions on the screen? Because—

Sure.

I'm not quite getting the audio coming through.

Sure. And I'll ask via audio too, in case others can hear. But, well, the question was—

Okay, so apologies for the technical issues. So the next question was, when customers start requiring this, where is the product person to start? Is it more critical to focus on a few metrics that matter most, or build up analytics as an offering that is robust for your customers? And the answer to that, I would say, is the very typical answer that I'm going to give to product managers for any feature set, right, is always, always, always start with your customers. So when you start to hear that need for the initiative for analytics, whether it's from your executive team, whether it's from your customers, start with your most valuable customers. Start with the customers that are asking for it the most. Identify those minimum requirements that are necessary. So when you're talking to those customers, good questions to ask are, you know, what value would that analytics provide to you as a business? And then kind of go into the level of sophistication of those analytics. You know, do you need static reports? Do you need visualizations? Do you actually really need to dig into that data? And a lot of that ties back into what value the analytics And then the other part of that is trying to figure out for your customer how you can actually increase usage from their stakeholders. So are there certain feature sets that would help increase usage around their teams? That could be something like email alerts, but usually start with those loose open-ended questions to vet out the initial minimum requirements. And that's a good starting point for that. Now the other part of this is talk to your engineering team because there's a number of technical requirements for building analytics into your products. Whether it's security, whether it's looking at the number of data sources, whether it's integration requirements. If you do partner with someone like Pentaho or a third-party analytics vendor, what type of APIs are necessary? How much control do you have over white labeling those analytics so it looks like your own? So once you have all of these requirements stated out from your customers and from your technical team, That's usually when a lot of product managers actually come to someone like Pentaho because they're in that stage where they're deciding, do I want to build these analytics in-house? And a lot of times product managers shy away from that because it's not a core competency. It would take a lot of engineering resources to build it from scratch and it would take them away from other, you know, parts of the, the next release that are being built out, and it's a little bit slower. And so a lot of times customers will choose to talk to a few different vendors as they're vetting out, do I want to build this in-house or do I want to partner with a third-party analytics vendor? So talk to a few different vendors, make sure you have those requirements in place at the very minimum so that you know exactly where to start with that. And that's, that's kind of the best starting point that I can advice.

That's great. That's great. Are you— can you hear me at all right now, or shall I type the next question? I'm going to go ahead and type that next question.

So, okay, so next question: can you walk through a specific use case of when a company began providing analytics for their customers and things that went well? What contributed most to that success? Yeah, this is an absolutely— this is a great question. So as I mentioned, embedded analytics is a huge part of Pentaho's business. So 30% of Pentaho's business is actually working with product managers like yourself and being able to, you know, take our analytics and embed it into there. So we have a good sense of what's going to provide success for the customer. The customer that I actually love talking about is Marketo. And so I think most people who are on the call today do know who Marketo is, but they're a marketing automation software, and they're one of the one marketing automation softwares that are out there, and anyone who's in the marketing space is going to use them because they basically build that link from a company to a customer, and they help facilitate all the different channels. So in, I think it was 2010, so it's been, it's been about 7 years now, they came to us because they wanted to build out a part of their product called Revenue Cycle Explorer. And we That part of the product was supposed to allow marketers, who are their end customers, to take analytics, to take the data, the campaign data that they've been working with it, one step further, and to really run the analytics and figure out how do we get one more step in front of our customers. So they kind of did the due diligence, right? They talked to their customers, identified the fact that they wanted really sophisticated reporting, and then they talked to their engineering teams on the security requirements, on the integration requirements, And they got to that stage where they were deciding, do I have my developers build this in-house? And it would have taken them 4 full-time engineers about 3 months to build this out, which didn't quite fit into their release cycles. Or should they partner with someone like Pentaho? And this is when they utilized Pentaho and our services team to get them to market in 2 months, so it could fit into their release cycle. So I would say that what contributed most to their success is the fact that they identified their requirements early on with both their technical teams as well as their customers. They got to market in the timeframe they did, which they identified when the market actually would require these analytics, and they kind of stayed one step ahead of it instead of having it be a reactive feature. They were able to successfully implement within their given timeframe. And they had, of course, a go-to-market strategy so that their customers were well aware of this. So they've been a customer for 7 years. They have a lot of customers that are actually using these analytics. And of course, the number one thing for all product managers is adoption, and we were able to help them accomplish that.

That's great. I'm going to type my question to Jeannie. So for everybody else that can hear me, I'm going to let Jeannie just read the question.

If a product isn't providing analytics today, are there things that What are some things that product people can start to do now knowing that they may have to provide this in the future? And could product people be doing things to set the stage well for the future? Yeah, when it comes to analytics, I mean, essentially it's— analytics is a feature just like any of the other features that you're going to look at for the future. So no, you don't want to start looking at the implementation of it, of course, today, but I would say biggest thing is keep in touch with your competitors and keep in touch with your customers. I'm sure you're already keeping in touch with your customers, but make sure, because data is becoming more and more relevant in today's world, and the amount of data within an organization is actually growing exponentially, so it's going to become a major driver for every touchpoint in a business decision. So make sure that you talk to your competitors— or not talk to your competitors, sorry, But make sure that you keep in touch with your competitors and when they start to offer up analytics as an option, because that's a good sign from the market that your customers are going to start asking for it soon. And you want to be able to get ahead of that curve. You want to be able to get ahead of it so that you can monetize it, and obviously so that you have a competitive stance within the market. How do you recommend handling conflicting requirements from customers is a question I'm getting in the chat window. Yeah, so I would say come into it with an actual framework, with very structured— not, not super structured questions, but for, you know, value. I would say talk to 10 different customers, understand what the value is, and obviously you want to be able to build for the masses, not build for just one specific customer. The other part of it, like I said, was come into it with structured questions in terms of what types of analytics do you want? Do you want reports? Do you want visualizations? Do you need to be able to dig into the different visualizations? Do you need to be able to build your own reports? Look at those options ahead of time and then actually vet those out with all your customers. So you have the quantitative questions and you have the qualitative questions as well. We also do have an embedded kind of build or buy guide that has these types of questions that you can ask as you're vetting this out with your customers, and I can have that sent out afterwards, and I can have Mike send that to all the attendees today. What are common mistakes that product people make at this stage in the beginning, and what should product people know that many don't know when facing this challenge? Okay. So this is a really great question, right? Learn from everyone else's mistakes. So like I said, embedded analytics is a huge part of our business. We've seen really, really successful implementations, and we've also seen the not so successful. And so we've definitely been able to learn a lot from this and really improve the product that we offer and improve the services that we offer to get ahead of that. So worst case scenario is you don't get to market in time. And that's, that's always a huge concern for product managers. And I'll kind of talk about ways to alleviate that. The other big thing is that analytics is something that is constantly evolving. And so you want to make sure when you're building out analytics into your product that it's not simply a one-time feature because analytics is going to evolve. The data sources that you're using in order to build out those analytics are going to evolve over the next few years. And so you want to be able to implement analytics that are flexible and can change with your customers' needs. So a few ways to kind of alleviate the fact of not getting to market in time or having rigid analytics One of them is that I do see a lot of product managers and product people kind of come to us and they've vetted out, you know, they've talked to analytics companies. And the thing is that there are analytics vendors and there are also embedded analytics vendors. And there are lots and lots of analytics vendors out there that offer reporting visualizations. They offer those tools up, but unless you talk to a vendor that has open APIs, that has the front end for white labeling, that has customization options, then you're not talking to an embedded analytics vendor. And another way to kind of look at this is the fact that look at the companies and the vendors that you're talking to, look at how many embedded customers they've had in the past, try to see if there's a structure for implementation. And then also, like I said, look at the flexibility and customization options, because that tells you if you're talking to an analytics vendor or an embedded analytics vendor. The other part of that is kind of that a lot of product people don't think about, and their engineers do though, is the security aspect. Try to see if your vendors have a number of security options upfront, because that kind of tells you if they've done a lot of embedded analytics implementations. And then the data part of it, like I said, that's going to keep you flexible for if your customers start to ask for other data sources, you can start plugging in different data sources in the long run. So with a lot of analytics vendors, they offer business analytics, but they might not offer that data integration component, and that's a manual process. So in the future, if your customers want more data, more analytics of some sort, you're going to have to vet that out as a completely different project. So make sure that whoever you're working with actually has built-in data integration tools, is flexible, has had the experience, has the services team, has the structure in order to get you up and going. Yeah, what sets Pentaho apart from competitive platforms? Great question, especially because I mentioned to keep up with your competitors, right? So I would say, you know, like I said earlier, 30% of Pentaho's business is embedded analytics. So we've done it before. We actually have an 8-week onboarding program and can get you to market in as fast as 8 weeks. Our services team, when you initially start on, actually sits down with the product person and with the product, the teams, the engineering teams, and really sits down and comes up with an onboarding timeline so that you're guaranteed to get to market when you want to. That's probably the biggest thing that I can say is our experience. And then aside from that, we have, you know, REST APIs for almost every aspect of our analytics, which is very, very robust. Everything from visualizations to really custom ad hoc reporting. That's probably the biggest part. And then the other thing of that is we have that data integration component. So a lot of competitors, when they're working with embedded analytics and embedding their analytics into software, they actually need to have this complete custom backend process in order to prepare the data so that it can be analyzed. And Tahoe has a built-in tool for it. So I guess our experience for sure, our open platform, which includes the security standards as well, and then, and then the fact that we have a data integration tool that's built right in so that in the future you're not stuck vetting out a completely new project if your customers want to add other data sources or want to analyze different sets of data. "Any advice on tracking different user cohorts or types within the embedded analytics? What are the best ways to increase your number of power users?" Yeah, I mean, I guess this, this comes down to two different aspects. One of them is when you're first vetting out the requirements, and this actually goes to the, the other question that was asked earlier, conflicting requirements from customers. You can map out a few different use cases and have the different go-to-market strategies for those different use cases, if you use a platform that's advanced and sophisticated enough. And then in terms of the best ways to increase the, increase the number of power users, I know this might not sound as conventional of as, as an answer, but look at multi-tenancy and look at the fact that different users are going to have different access to data. And set that up in a way that you can tie it to those different use cases. So it has to do with the best ways to increase the number of power users is really giving them access to the data that they are particularly asking for instead of giving them access to all data so that you are really customizing the analytics for the different groups of people within each organization. Okay, final question. What's the best way for folks here to keep in touch with you and the resources Pentaho offers? Yeah, I mean, I can, I can send out my contact information afterwards, and then we can— with the resources Pentaho offers, if you go to Pentaho Embedded Analytics, you'll kind of see all of our offerings. We also have build versus buy guides. We have, you know, some analyst white papers on there that can really help you understand the space a little bit more. In terms of the best way to keep in touch with me, you know what, contact me directly. I will have Mike send out my email afterwards. So if you have any additional questions, feel free to reach out. Definitely helping that— hoping that these answers are helpful and that we can continue to keep that conversation. Thank you everyone. Thanks so much for for joining us, for having me on.

For folks that could hear me, uh, sorry for some of those technical challenges, but thank you for being here and hope to see you at a future product launch. You go to productlaunch.com to learn more about upcoming sessions. Thanks so much.