 Hello, my name is Brad Zomek. I'm VP of Marketing and Analytics Experience evangelist at CumulIO. I'm here to present on the topic of empowering, engaging your customers with analytics. Here's a little overview of what we're gonna cover today. I'll do a quick introduction to myself and my background as well as the background of CumulIO, the sponsor of this webinar. I'll share some research that CumulIO recently did looking at market sentiment of analytics features in SaaS. And I'll drill a level deeper into the top 10 complaints about these analytics features paired with some really cool visuals to show what's good and what's bad. Then I'll go into what is a good customer analytics experience, how can we do better? Finally, I'll share a little bit about how you can get started, how you can crawl, walk, run, then fly and be a customer-facing analytics expert. About me, I'm not your typical product school instructor. I'm a marketer and not a product manager, but I'm coming to you today with a user perspective. I'm a performance marketer. I spent 20 years in software technology. I'm a super user of software, and I'm a buyer of software. I bought dozens over the years, and I'm an analytics super consumer. Marketing is one of the OG SaaS verticals. It's been around since the late 90s, and marketers are very performance-driven. Everything we do, we're investing money. We want us to return on investment, but we measure at multiple different levels. Traffic, click-through, conversion rates, and we spend a lot of time in analytics. So I bring that experience with me today, and I also enrich with the knowledge of our founders. Our founders were data scientists and data visualization consultant at DXC Technology. That is a formerly HP consultant, and they worked on high-impact, multi-million-dollar decision support projects where they'd build a set of dashboards over the course of six months for clients to inform critical decisions, and sometimes a multi-million-dollar project to decide not to do something. From that experience, they wanted to build a tool that could empower any business user, and that was affordable and easy to use, and that led them to building Camille I.O. And today, we help over 200 customers deliver an amazing analytics experience with less time and resources using embedded analytics, which is a low-code and to help product managers quickly develop and deploy dashboards. We'll get started with some market research. Recently, our team did a deep dive into G2, the most popular software review site. We looked at the most popular categories. We looked at the top seven categories. We looked at the top 20 companies in each category, and we collected the most 50 reviews. And we see this as a proxy for what the market thinks of analytics. Often in any given category, there's a lot of drop-off. The quantity of reviews after the top 20 to 50. So here's a little bit about what we found. Customer-facing analytics is a hot-button issue. 20% of the total reviews across all the vendors addressed analytics features, and that amounted to 6,400 analyst reviews collected and analyzed. And of those reviews, there were 27% were of a negative sentiment. And I put an asterisk next to that. There's a little bit of gamesmanship and incentives for a lot of SaaS companies to get people to go to reviews. And a lot of us here who are practitioners have received some sort of promotion to leave a review for a gift card and just thinking about your own buyer behavior if you're at a restaurant. Yeah, you're not often gonna go out of your way to leave a good review, but if you have a bad experience, you're gonna leave a bad review for free, right? So that's the asterisk there. And we found that 90% of vendors had at least one negative review. Even the best of the best have people wanting more from them in terms of the experience with analytics. We also looked at analytics as a part of pricing and packaging on websites. Visuals of analytics are pretty engaging and they help sell and promote the product. 94% of companies are featuring analytics in some way on their promotional materials online. We also looked at the pricing and packaging and more than 50% are in some way charging extra for analytics features. So that's premium pricing tier and upsell package to add on the analytics module. When you put that together, there's a disparity, right? Everyone is promising data-driven confident decision making, but the truth is 90% of companies are actually getting negative reviews. It's a big opportunity for SaaS companies, for product managers to look at how we can bridge that gap with a better analytics experience. All right, moving along, we're gonna get into some of the complaints that we hear from SaaS users. And we're gonna go top 10, David Letterman style and talk about all these things that people are not too crazy about. We'll start with the smallest one, we'll move on and we have some fun visuals to share. Number 10, clocking in at 7% of complaints, a reference complication of the sharing and who hasn't had the experience of seeing a cool chart, screenshotting it and putting it to slack, it's inefficient, but the more robust vendors are doing embedding features or widgets to allow sharing and that could be sharing a link, sharing a picture in an email or even sharing the whole chart to put into some sort of wiki or blog. That's the way of the future. Number nine, being disconnected from the normal workflow. So the screenshot I have here is of Excel who hasn't had the experience of doing some analysis to find an insight in Excel outside of the core application. But other ways this manifests itself is asking for a custom report from a CSM or having to go to a side application, which is not the main module or even the different panel from where the actions take place. Another top 10 complaint at number eight is no collaboration or alerts and 60% of references cited lack of collaboration or alerted features. So this can come in a few different forms. It's the emails you might get that are a monthly report or a weekly report. It's the notifications that you see when you come to the app and it's also the ability to talk to a colleague and comment on a chart about a certain insight. Because ultimately a lot of this stuff is to inform a discussion and decide what to do next, hopefully as soon as possible. And number seven, design. It's a common complaint and design comes up in a few different ways. Charts that have too much going on, they're too busy, maybe the color scheme is off, they chose the wrong chart type or even a really simplistic chart that looks like you iframed in an Excel chart and happens quite a bit, you'd be surprised. 20% of people complain about design. Slow performance. This is the classic hourglass or if you're a Mac user spending beach ball of death, 26% of the analytics reviews reported a slow load time. And we know the attention span of the internet is like a goldfish. People don't see what they need in three seconds. People are abandoning the page and getting frustrated. Number five, lack of interactivity, almost 30% of reviews cited lack of interaction. And this is one of those things that if you don't know, you don't know. A lot of what we see in analytics features today is static view only analytics. And I've prepared this nice gift to see what good is. That's the ability to click and I see it having interlinking charts where they resize. In some cases you can click on a part of that chart and have an option to drill through and look at it by a different dimension. And number four, pulling data and reports again, 30% of people reporting limitations and data and chart exporting. This can be the not having to fix the feature or just clunkiness. It's something that a lot of people want. And what most people don't realize is that we've been trained to expect export to Excel. But to us, that's actually part of the bad user experience. And as a marketer, one day a week, I'm spending a couple of hours in Excel, slicing dice and data because I don't necessarily have the insight that I need. And then now export to Excel won't go away. It's necessary for cross-platform analysis. But vendors can definitely take part of this away and deliver more insight in the product and deliver more delight. Given it's the top three here, with complaints referencing the inability to customize and this comes in many shapes and forms. There's branding, there's filtering the chart and slicing it by date or different dimensions. There's chart and dashboard building itself. We see this is a data studio type of functionality that just most vendors don't have. And if they do, it's clunky and very hard to use. But this is an area where there's a lot of Delta and in fact, almost 40% of HubSpot users are one of the most popular CRMs in marketing automations. They have a data studio element and 40% of users prefer the HubSpot charts they build themselves aside from the ones that are out of the box. All right, rounding out the last two comes in many different flavors with a lack of relevant insights. There could be too much information, not enough insight, a one size fits all approach. So for instance, I'm a sales manager and I wanna see everything globally but I log in as a line regional manager and I see that same global chart. I just wanna see the New York area on the regional thing, all sorts of things that can go wrong, the wrong geography, wrong currency, wrong language. Another issue is the being delayed in the reporting of data and we wanna make decisions based on what's happening now not yesterday or last week. Generally missing critical insights that are needed to inform a good decision. So maybe not tied to the higher order. It could be, for instance, in learning there often need track completions but what does that have to do with how the company is performing and improving revenue and just generally that you can't make a decision confidently and quickly. And then finally, the catch all is poor user experience with 71% citing the user experience and this comes again in many varieties. It's everything that we talked about before but also a steep learning curve. You can't find what you need, lots of clicks and discovering, gotta ask for custom reports. Generally just, you don't know the whole experience leaves more to be desired. So yeah, that's the top complaints and I thought it might be interesting to talk about why you see all these subpar experiences happening with customer analytics and the truth is customer facing analytics is a really nuanced and complex challenge. There's three layers to it, right? And it's a pyramid, they stack on top of each other. You have your data modeling and that's getting the right data stack and being optimized for an analytics data model not your transactional data model to deliver information. There's the development of the application. So this is the coding of features, the shipping of the software and timely and predictable manner and then finally the top of the stack of the visualization and that's really what end users care about the most that they're having a great experience and unfortunately what happens is the technical components can delay and hinder UX benefits and that puts a kind of traffic light here. Things are all going good on the data model but where if you hit the skids during development you don't see the UX benefit or the user doesn't, right? So data modeling, it's a big project, a weak model or inefficient tech stack can lead to performance issues and slow load time. These are big thorny projects. It's the bottom of the iceberg. And then what we see a lot is application development is often an area where there's just delays projects and in a resource constrained environment we only have a certain amount of engineers often any given software has a core differentiating feature set to its product that they're working on delivering value to their clients and often that stuff whether it's a bug or a new feature will take precedence over with analytics which is a side dish and often not thought about as differentiating feature it can be. And yeah, and delays in those technical areas just slow down the overall benefit to the user. This day and age we're fortunate to live in the golden age of software as a service there's all sorts of fun point solutions and either bifurcated the top and the bottom of this the data pipeline is a project that's itself you have most companies will have data engineers or they can work on all this there's many different parts of this puzzle there's a warehouse there the analytics database, the ETL authentication layer that data model needs to be good regardless of any of the next steps but where you can catch up and get speed at the top of the stack is with embedded analytics so this is a glimpse into what we do we take away that whole application development part of it and decouple from the engineering sprint because with a low code solution product managers can drag and drop and build charts on the fly and in fact we have a lot of customers who are co-building with their customers and doing a better experience with less time resources you can take off a couple of $300,000 engineers away from analytics and let them focus on the core features which is a benefit to the organization. So let's talk about what is analytics experience is the overall experience of a person using analytics features in SaaS and that's how useful it is or they're getting value and how easy and fun it is to use and it could be an amazing experience it could be terrible there is an experience that your users are having with it most people aren't thinking about that too much how to make that good so there are three value pillars that we see through all of our client interactions so we have first and foremost end user business value that they're successful what they're trying to do then we have the premium user experience and then personalization so we'll talk a little bit more about each and each one has its own nuance so first we'll talk about the premium user experience and as few different layers here there's the design element does it look cool? is it attractive? is it easy on the eye? there's the experience what is it? do they have to do their analysis of another app? do they get what they need? is it easy to use? there's often a very steep technical learning curve on business intelligence and a lot of schools on the market interaction kind of user do things change or filter what they see is there chart interaction? the speed how many clicks does it take to get to the insight? and is it integrated? is it its own modules or blended into workflow? personalization so this is all about context but does the user the stuff that is specific to their role and what they need to do in the product? so I think classic example is a manager role and line employee so in sales it's pretty common to see a global view versus a micro view HR Tech is a great example of an admin user and an end user doing two completely different things in the product the admin user wants to see analytics and performance and then the end user is you want to do something like what am I going to learn today related to my job? access can the user see data access data beyond what is presented to them? can they control it and manipulate it and do different things with it? and finally empowerment this idea of manifesting your destiny can a user or an admin choose their own venture build their own charts and build a set of dashboards the data studio type experience and finally the end user business value this is all about being successful whatever you're trying to do every software out there on the market today is eating up some part of manual paper operations where somebody's trying to do something more efficiently is the next action clear? can they take the action quick? are they confident and self-assured that they took the right action? is the business satisfied with the outcome? you put all that together and you're gonna get spot and it's good for the business more interaction in the product more time spent in the product if customers are getting the insights they need to make confident decisions they trust you they look at you as a credible source of information that they want to keep on coming back to that leads to less churn increased customer advocacy they want to have customers raving about you and also your analytics become a differentiating aspect of your product and then finally a lot of companies we saw before more than half the companies are looking to monetize and upsell analytics so let's talk about how to get started and that sounds great in theory to have an amazing customer analytics experience but it's easier said than done so based on our experience with customers there is five levels of customer analytics experience and they're incremental and it's baby steps and crawling before you walk and walking before you run and running before you fly so the basics is a universal insight it's before you even start sharing user specific data it's general insights on how your customers are using the product and getting value from it and actually this stuff also tends to be really great for thought leadership but this is an example of something that we did for the government of Belgium but less software oriented but Gong Labs is a great example of companies sharing universal insights across their customer base so customers could do better work in their product and this could be delivered anyway email direct conversations next we get into customer specific assets so a good example of this is an investment portfolio this is what is your investments doing in the market today and do I need to buy and sell things and this may also not necessarily be at this point in the application yet this could be coming through a custom report it'd be coming through an email but that's where things get interesting because it can inform it has a context to inform decisions for specific users next is the embedded step and this is when you actually are deploying analytics into your application and where the analytics are side by side with the actions and this is how most people think about analytics customer facing analytics and software most people skip right to this and maybe that's part of the complexity too and the problems because people aren't necessarily crawling before they walk another thing that we see that happens here is people go straight till we need everything the whole kitchen sink but the truth is you can start with one insight at a time and get one insight and slowly build out your dashboards with one chart or one metric one module at a time where things start getting really interesting where you layer in the customer analytics experience or is being interactive and actionable and this example that we are showing here is a mock example of an email tool where you can click on your audience segments and ship an email right from that there are all sorts of applications like that but these two things in the animation is that there's interaction between charts and there's action taking place and this is where you start delivering a lot of value to your customers because they can find insights and do things quickly but the pinnacle of self actualization analytics is choose your own adventure and this is where you can do a few different things you can create a custom report or you can clone a report you can augment and change charts and this is super advanced five to 10% of SaaS companies are doing this today but with an incremental approach many companies can do this and do it successfully so there's your five levels of customer analytics experience and remember it's first crawl, walk, run and then fly the role of helping your customers becoming data-driven is critical if you're affecting their P&L and helping them be more profitable it's good for business if data-driven companies are more likely to track new business and retain customers and be profitable and if you're helping your companies do that with your software you're in a good position to grow and scale as a company and become a unicorn all right and this webinar was brought to you by Humilio and we help companies deliver an amazing analytics experience with less time and resources using the low-code solution of added analytics and we have some further learning resources for you to continue your learning journey related to the analytics experience how to build a winning SaaS experience and that's a little bit more detail on that Venn diagram that we shared and also if you wanna drill deeper into some of the complaints that we shared earlier we have a full report on this data SaaS analytics and we have a bunch of more granular detail and how different SaaS verticals that we reported on the different types of complaints and percentages vary from vertical to vertical and that's all thank you very much for your time and consideration I hope you learned a bunch and if you have any questions you can email me you can reach out to me on LinkedIn or you can check us out on our website and learn more