How Cumul.io CEO Thomas De Clerck grew to $9.8M revenue with a 59 person team in 2024.

yeah so my name is Carl um founder and CEO at cumulio and for the last 15 years I've been living and breeding business intelligence I started my career mainly for larger corporates crunching numbers for years analyzing data for years up until the moment that I realized that I wanted to bring the power of data-driven decision making to all not just to business analysts but really to everybody and and moreover I wanted to bring those insights to the places where we're making the decisions so inside the applications where we're making these decisions and so around seven years ago I created a company called chimulio we're a building block for any web platform that wants to offer analytics and dashboards to their end customers so you can help them make better data-driven decisions I'm excited to be here to talk about some lessons learned along the way but also to share some of the research we've done with the comp finish um so let's see before I start one thing that I do want to get out of the way is when we're talking about customer analytics experience and or client-facing analytics I'm talking about you as SAS companies offering the data to your end users so that they can make better decisions it's not about analyzing your customers Behavior you know it's about giving the insight to your customers deserve so in this talk I'll talk about um why you should care as SAS Founders and what does it mean great customer analytics experience and for the ones looking to step up their game in client-facing analytics I've got you covered with what are the five levels of great customer analytics experience so let's first start with the why why should you even care why should you be interested um well allow me to start with the research done by McKinsey six years ago and they looked at a vast amount of companies from small to medium to large companies and they actually compared how companies were making decisions and they compared data-driven companies to normal companies and they actually figured out that no matter the size data-driven companies were 23 times more likely to attract new customers six times more likely to retain these customers and 19 times more likely um to be profitable and given that you're in SAS I gather you already use data to make decisions on on sales on marketing maybe on Personnel planning but um I can ask you this are you already giving that information to your customers are you already helping them to make these better decisions because like you they also look at to to some Assurance over the outcome of decisions that they're making like you they're looking for these decisions and have the biggest positive impact for their company and with you as a provider they look to you for assistance because you're the domain expert and and if you can help them not only are you helping them to win but you create a Competitive Edge for yourself and so what are some reasons that you should be looking into client facing analytics um I have three examples here one is on reach one is on retention and the other one is on cost savings first one it's a customer of ours uh Greenly it's carbon foot counting and by adding customer facing analytics they were able to attract a vast amount of new customers why well a pretty but also an accurate picture paints way more than a couple of words or a dumb Excel file and so by visually showing what they were doing with their platform on landing pages but also interactive interactive they were able to prove the value of what they doing second one is on retention and it's actually a very interesting case they started to implement client-facing analytics to prove the ROI of their platform to their customers so it's a video first customer engagement platform and what they did is and they compared the data when people were just starting to use their platform with the data after they were using their platform for a couple of weeks and then they came with clear Roi and so nobody will leave your platform if you prove that it makes sense using the platform and then lastly on cost savings um that's a client of ours in proptech and they drastically reduced the cost and the time um to support our customers why well before using customer facing analytics they had customer success and Engineering teams creating reports for their customers specific reports to help them optimize business operations building operations sorry um and by adding a way for their customers to slice and dice and to interact with the data they actually gave the possibility for their customers to immediately react and optimize their building operations um and so if you weren't convinced already before joining the talk I hope with these three reasons I can show you and it you shouldn't disregard a client-facing analytics it can bring you a great value but knowing why you should do it doesn't mean that we know how to do it well and so let's talk about um what is good customer analytics experience and maybe more importantly what it's not um how it can help you drive sticky Behavior to your product um and then um and and then what does it really make great customer analytics experience so let's start with what it's not although that there are great examples out there on average most SAS companies fail in doing client-facing analytics well and why is that well we to to look at that we actually did large scale research specifically focused on SAS companies so what we did is we looked at 250 of the top performing G2 top performing companies on G2 on the main categories and we looked at how their end users perceived the analytical analytical feature set and we actually found out that 89 of all these companies dealt with negative reviews and so why was that well the main reason 61 of all negative reviews indicated that it was too clunky to use they couldn't find their way in there second reason it didn't present the data that they needed to make the right decisions and then three they weren't able to configure or edit the reports to their likings um and when we actually started digging deeper we saw that most SAS companies look at client-facing analytics as necessary something you have to do to check a box a cost center but they all fail to see the huge potential and the benefits that can bring with it and those benefits can be immense they can very well be the difference between losing or winning against your competition think about Strava so back in the days there were many running and cycling apps how many winning cycling apps do you still know today Strava largely beat their competition through great customer analytics experience because if you do it right your customers will go to your platform because in a nice looking interface they'll have access to real time insights that help them make better decisions and they'll share these with their peers with their colleagues which brings in a community effect and if you allow them to dig deeper and to uncover new insights and maybe to create even their own reports you actively Empower them and all while you're educating them in your platform where you become the trusted partner the partner they depend on and then you're building a strong Innovative brand so in a nutshell where is great customer analytics to be found well it's in the intersection of these three areas of course end user business value it has to make sense but then you have personalization um and premium user experience so with that now that we know what great customer analytics experience or taxes let's look at how you can get there um there's actually five levels that we what we created these five levels it's based on research but also customer experiences um and you can go over them one by one but you can definitely also combine them or skip them to get quicker to the cax Walhalla and let's get with let's start with the first one and this is really about getting the basics right so you look at the data you already have a tent and you look at what metrics what charts or dashboards would matter to your end customers for them to make informed decisions and and at this stage you only look at your entire customer base so you don't look at their specific context um great example here is it's from one of our government clients um typically what they do is they share on fertility rates um so it's about bird Birds numbers but here they looked at how can we matter to our end users which are the Belgian civilians um and they created a tool which was based on popularity of baby names and that allowed people to parents to look at a name that would be popular enough so that everybody would like the name but not so popular for example being in the top five that you would risk having your kid in a class where three or more would share the same name so really bring in value for their end users once we have step one let's move to step two and then here we're really going to customer specific here we're making sure that our customers feel special so the charts and dashboards that you'll be creating are specific to the data that that user is looking at um and so you want to make sure that it's secure so that the people only with the right authorizations have access to it um but how do you start with this well a good way in starting in it is you're the domain expert so you know what the important decisions in your industries are that need to be made and also the metrics that influence that so start with these metrics and gradually add data as you go user testing here is crucial because you'll want to build these dashboard templates that actually help your customers so throw away metrics if you see that there aren't used and make sure that you're not cluttering any dashboards it needs to be easy to consume easy to play with it doesn't need all the data just make sure that it contains the data that actually matters to them so an example here it's a broker report on a portfolio of an investment and so weekly report that is sent through email level three here things get interesting in terms of customer engagement because the customer specific insights from level one I have from level two you're actually now embedding in your platform and so here uh it's very important that you do it in a seamless way so it has to fit the style the languages uh the screen modes but also the data that is in there should be in real time so that any change in the platform is reflected in the insights and if you do that well well the value of those customer specific insights is now directly attributed to your application and your brand and what you can do to even increase the engagement here is every now and then send them an email with metrics that you know that matter to them because they'll likely return to your platform and uncover a new metrics that help um that make better decisions example here is a a banking app that shows spend Behavior historical spend but also the categories where they were spending then level four um now that analytics are native to your platform you can start to actively Empower your customers and here interactivity with um the metrics and the dashboards become important and maybe even more important driving the actions or making the decisions from that data and at this stage what you'll see is that your charts your dashboards your analytics become entangled with the day-to-day workflows they burst out of your typical one-page analytics tab now they start appearing in different places in your platform where you need to make decisions where multiple scenarios need to be presented um and so an example that we have here at some marketing technology agency where visually their users can segmented slice and dice um according to historical Behavior according to demographics according to other dimensions and the result they can actually use to as a new Target list for their Campaign which makes data-driven decision making a reality um here to is the case and the cake what you can do is alerting so when thresholds are met and let them know but also collaboration features and they've uncovered some insights let them share with their colleagues and peers and that brings in the community effect um of course the last level that's the Walhalla that's the ultimate level it's like with the levels of fully autonomous driving level five is where you want to go and what is level five well level five is about laser focused Automation and that combined with large degrees of freedom so what you'll be doing here is you'll continuously be monitoring um your end users business context and the result of that you will want to proactively signal to them at that moment in time when they need to make a decision and by doing so you'll create a premium user experience in which they can swiftly operate in your platform which makes them win a huge amount of time but also which leads to fully data-driven decision making and the time gains that they will have the likely reinvest in your platform and that is where the large degrees of freedom enter because you'll have normal users that will just say okay these proactive insights they're good enough for me but you'll always have power users that are looking to investigate all the data that you have in your platform in various ways and there you can give them the freedom of um of freeform reports and did you know that in HubSpot 79 of users prefer their own reports compared to the dashboard templates and so by giving freeform reports not only are you helping them to uncover specific problems uh specific solutions to their problems but it also leads to better adoption more engagement and if you're lucky they'll actually uncover a new Battlefield where you as a company can win and moreover offered it leads to less trains on your teams because no more customer success team anymore to generate custom reports uh the engineering team just gives you the gives the end users the possibility to slice and nice the data so you gain time that your teams can reinvest in the core of your application I hope with these levels you got a clear view on how you can improve in customer facing analytics I think with the technological advancement that we are today there's no excuse anymore for you to be disregarding customer facing analytics as SAS companies you actually should already be on level three or at least working towards that because your customers are expecting you to do so and if you're not doing it you can be very sure your competitor is doing it and then it becomes the difference between success and Extinction and moreover with the economical uncertainty today you have an obligation towards your end customers to help them because what better way to remove that uncertainty through data-driven decision making so I hope I gave you some extra knowledge some ways to improve on customer facing analytics I'll be around the whole afternoon here so don't hesitate to ask me any questions I see we still have four minutes for some questions foreign any questions all clear uh so what well what we're providing with Kim i o it's a building block um that you can add to any web platform and it allows you to have customer facing dashboards so today dashboards are considered a commodity I would say look at all the goods that that they're there everybody has dashboards but because it's a commodity it doesn't make sense anymore for you to build them themselves so you use a building block for winning time and that um but what is important it's not just about painting a pretty picture uh dashboards should be business should be valuable tools and business operations they shouldn't just be visual representations of data they should help you make better decisions and drive um better actions and so it's a native component that you plug in in your own software like you have strive for payments uh algolia first search r0 for authentication well you have cumulio for uh for dashboards that's my question how do you plug in it's a simple web component that you add to your platform you it's Cloud first so you connect your database and then the only thing you have to do if it's a dashboard you have qmlio dashboard you provide the ID of the dashboards a key and token to to make sure that that it's secure and it it adapts to uh to your platform it is a modern day web component so you can listen to events when people click you can pull in data you can influence how the dashboard looks so it's really back and forth communication uh well you do have to have the data or you can link apis to it so um we have out-of-the-box connectors you can connect any API we actually have I think an example on uh what's it called again the open bikes here in New York it's an open API that is connected to it and then you can see which bytes or what spots still have uh you know bikes as long as it's structured and available through the web you can connect it any other questions if the if there are feel free to uh to contact me I'll be roaming around here uh for the next couple of hours thanks [Applause]