Every company is a data company. In Embed to Win, we dig into the ways companies are evolving to include embedded analytics in their products as a market differentiator and revenue generator with stories from builders, product shots, and more.
The power of data and analytics extends far beyond dashboards. Countless people within both big and small organizations benefit from insights gleaned from analytics platforms, but will never crack open a dashboard. Embedded analytics are the solution, whether you’re putting the right insights and data points in front of the right people at the right times or you’re embedding analytics into your product or service as a product differentiator or new revenue stream.
I sat down with the head of our Go-To-Market team, PeggySue Werthessen, to talk more about what embedding means today and tomorrow.
Jack Cieslak: Where are teams putting embedded analytics right now?
PeggySue Werthessen: Everywhere. That’s the power of embedded analytics, right? In the traditional sense, it’s the ability to take individual visualizations, individual KPIs, and embed them directly in your workflow. So, as you’re using your favorite tool, you just get a little bit of data, right at the point where that data is going to be the most helpful. Instead of 20 KPIs, like you would be in a dashboard, you’re just getting just the right information at the right time.
However, increasingly companies of all kinds are embedding analytics right into their products. Users love seeing how they’re interacting with an app or service. It increases stickiness for the company and increases user engagement. Sometimes there’s a basic level of analytics available, which users can then pay to augment.
In the Hive project management platform, users can check how long it takes them to finish their tasks, identify bottlenecks, and gauge efficiency using Sisense embedded into the platform. Recurring Insights, which makes a platform used by a large number of charitable organizations, built embedded analytics into their software to help their users drive strategic, predictive decisions and get the most out of every fundraising campaign.
Internally, a couple years back, Sisense made it possible for you to embed analytics into your Alexa. So now you can just ask Alexa a question and she can answer back. You can think of that as a way to embed analytics into people’s lives. You’re in a conversation and they’re saying “Oh no, I’m doing fine this quarter.” And so you say “Alexa, what’re my Q3 results?” And she answers.
JC: How does embedded analytics build on traditional BI?
PSW: From a CEO’s perspective, embedding analytics is a great way to make sure that everyone in your organization is following the same process and making smarter data-driven decisions. From the frontline worker’s perspective, we all naturally want to do our best work whenever we can, and to be our best selves. However, a lot of people are not data oriented and can feel overwhelmed by data (especially too much data).
That being said, when it’s the right one or two bits of data, presented with easy-to-understand visualizations, users don’t need to comprehend the math behind the analysis to understand the insight and adjust their behavior accordingly. Everything we’re doing is trying to make BI more accessible to more people, really to people who don’t even care but could use the insights from their data to do better work.
On the product manager/team side, embedding analytics opens a slew of doors for internal and external use cases: Internally, you can build an analytic app or embedded widget that lives in your colleague’s workflows and helps them in the ways described above. Externally, we’re talking about delighting your customers with embedded analytics that can change how they see your product or service, serve as a new revenue stream, and help set your app apart in a crowded market.
JC: What are product teams’ options for embedding analytics?
PSW: The right data and analytics platform gives you the ability to completely customize the look and feel of your in-app analytics. Contrast this with the traditional embedding model where you usually just take a single visualization and you stick it somewhere, or else maybe you embed one dashboard in a webpage.
When you’re embedding with Sisense for example, you can take it and embed any visualization into your product and whitelabel it. You can customize the fonts, colors, graphics, URL, and everything, so your clients will never know they are using Sisense. Some Sisense clients take them white labeling to the next level and actually give their users the ability to build their own dashboards and even data models.
JC: How do enterprises embed?
PWS: For Enterprises, embedded analytics is a way to mature their BI offering. You have data people already working with data and business users doing reporting, but integrating embedded analytics throws developers into the mix. They can start by putting analytics into their app, but then they can take Sisense even further, putting it into employee portals, systems such as Salesforce.com, and even offering analytics to customers and partners.
Sisense covers the whole gamut, which means enterprises can get a lot of re-use out of things that they do. Why wouldn’t you want the same data model, definitions, and visualizations to benefit everyone both internally and externally? Being able to do that all from the same platform means when we say “single source of truth” we mean “all the way through.”
JC: Are dashboards dead?
PSW: No. They’re totally not dead. Embedded analytics is, for some users, all they’re ever going to see. They’re not going to go to the dashboard, but frankly, they’re not going to the dashboard today. They may have access, but they’re not opening up the dashboard. They’re just not. So, embedded gets analytics to those people.
For those people that do use the dashboards and also have analytics embedded in their workflow, it a nice reminder, right? I do my deep thinking at a dashboard: I’m really thinking through a problem, I’m thinking through a space, I’m trying to really understand it. They’re still plenty of people who need a dashboard. It’s still a workplace to play with your analytics and I don’t think it’s going away.
JC: How are builders embedding augmented analytics?
PWS: The simplest version of augmented analytics is “the computer makes charts for you.” Not very exciting, but easy to understand. Sisense for Cloud Data Teams allows data experts of all kinds (engineers, scientists, etc.) to take their data even further with in-warehouse data preparation, materialized views, and capabilities that harness the power of advanced coding languages like Python and R.
Sisense’s cloud-native architecture also allows the platform to seamlessly connect with cloud data warehouses from the likes of AWS, Snowflake, Google BigQuery, and others. This means you can more easily pull in-depth insights out of these huge, fast-moving, modern datasets. It also allows you to put those insights into your product or service easily and present your users with the latest insights from all your/their data, no matter where it lives or how often it gets updated.
Endless opportunities for embedding
This has been just a brief glimpse into the world of embedded analytics, both present, and future. As more organizations are realizing just how important understanding their data is, they’ll keep finding more and more places to put the right data in front of the right people at the right times. And Sisense will be right there making it easier than ever to do that. Whatever you’re building, build boldy.
Jack Cieslak is a 10-year veteran of the tech world. He’s written for Amazon, CB Insights, and others, on topics ranging from ecommerce and VC investments to crazy product launches and top-secret startup projects.