SaaS Interviews with CEOs, Startups, Founders
The 5 levels of great customer analytics experience
28 Jun 2023
Chapter 1: What is the main topic of great customer analytics experience?
I'm very excited to share this recording with you guys, which happened at our conference, sasopen.com, with over 100 speakers, all founders of B2B SaaS companies. We have a very high bar for what speakers share on stage, so you're going to enjoy this episode where we dive deep into revenue graphs, real tactics, and real growth metrics.
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So, my name is Carl, founder and CEO at Accumal.io, and for the last 15 years I've been living and breathing 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 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 QMLIO. 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.
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 company and 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
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Chapter 2: Why should SaaS founders care about customer-facing analytics?
or client-facing analytics. I'm talking about you as SaaS companies offering the data to your end users so that they can make better decisions. It's not about analyzing your customers' behavior. No, it's about giving the insights your customers deserve. So in this talk, I'll talk about... why you should care as SaaS founders, 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? 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 to be profitable. And given that you're in SaaS, I gather you already use data to make decisions on sales, on marketing, maybe on personnel planning.
Chapter 3: What are the five levels of great customer analytics experience?
But 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 to some assurance over the outcome of decisions that they're making. Like you, they're looking for these decisions that 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 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? 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, Greenlee. It's carbon footprint 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.
Chapter 4: How can data-driven decisions impact customer retention?
And so by visually showing what they were doing with their platform on landing pages, but also interactive, they were able to prove the value of what they were doing. The 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 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, that's a client of ours in PropTech.
And they drastically reduced the cost and the time to support their 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.
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. And so if you weren't convinced already before joining the talk, I hope with these three reasons I can show you that you shouldn't disregard client-facing analytics.
It can bring you great value.
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Chapter 5: What common pitfalls do SaaS companies face in analytics?
But knowing why you should do it doesn't mean that we know how to do it well. And so let's talk about what is good customer analytics experience, and maybe more importantly, what it's not, how it can help you drive sticky behavior to your product, and then what does it really make great customer analytics experience. So let's start with what it's not.
Although there are great examples out there, on average, most SaaS companies fail in doing client-facing analytics well. And why is that? Well, to look at that, we actually did large-scale research. specifically focused on SaaS companies. So what we did is we looked at 250 of the top performing companies on G2 on the main categories.
And we looked at how their end users perceived the analytical feature set. And we actually found out that 89% of all these companies dealt with negative reviews. 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.
Chapter 6: How can customer-specific insights enhance user experience?
And when we actually started digging deeper, we saw that most SaaS companies look at client-facing analytics as necessary ebook, 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 about 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?
Chapter 7: What role does interactivity play in customer engagement?
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 and premium user experience. So now that we know what great customer analytics experience or CACS is, let's look at how you can get there. And there's actually five levels that we created.
These five levels is based on research, but also customer experiences. And you can go over them one by one, but you can definitely also combine them or skip them to get quicker to the CACS Wallhalla. And 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 at hand.
You look at what metrics, what charts, or dashboards would matter to your end customers for them to make informed decisions. And at this stage, you only look at your entire customer base. So you don't look at their specific context. A great example here is from one of our government clients.
Chapter 8: What does the ultimate level of customer analytics look like?
Typically what they do is they share on fertility rates. So it's about birth numbers. But here they looked at how can we matter to our end users, which are the Belgian civilians. And they created a tool which was based on popularity of baby names.
And that allowed people, so 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 bringing 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. And so you want to make sure that it's secure so that the people only with the right authorizations have access to it. 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. 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 they 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 two, you're actually now embedding in your platform. And so here, it's very important that you do it in a seamless way.
So it has to fit the style, the languages, 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.
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 new metrics that help them make better decisions. Example here is a banking app that shows spend behavior, historical spend, but also the categories where they were spending.
Then level four, now that analytics are native to your platform, you can start to actively empower your customers. And here, interactivity with the metrics and the dashboards become important. And maybe even more important, driving the actions or making the decisions from that data.
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