5 Embedded Analytics Benefits for Businesses

You are probably aware of what embedded analytics is and why the embedded analytics market is growing. Companies that keep up with digitalization may now be left wondering why they should consider exposing data to their end-users. Are they at all interested in these insights?

In this article, we will cover the five reasons why it has become a pressing need for data facilitators such as SaaS companies, and digital and IoT services providers to start opening up their data to their customers right now. Learn how client-facing analytics help businesses increase user adoption and customer loyalty.

Let’s go through some practical benefits of embedded analytics for modern businesses.

1. Make your business future-proof with data-driven decisions

Due to digitalization, businesses today are rapidly transforming. Those that keep up with digital transformation are quickly building their competitive edge. For those who lag behind, it will only get harder to catch up.

And within that process of digitalization, data is the core asset. However, the raw data in itself has little meaning. Only when it’s presented in a smart and interactive way, companies can easily derive insights from that massive amount of data.

As so often said “data is the new oil”. You could say that embedded analytics is the engine that gives it meaning. It translates raw numbers into usable business information for everyone, everywhere. Without it, decision-makers are left groping in the dark.

And that’s precisely why analytics adds a future-proof feature to any offering, whether you are a SaaS company, service organization, IoT provider, governmental institute, or non-profit organization. When used in the right way, it adds tremendous value for your end customers.

As a result, companies that have added analytics to their offering are seeing 3 areas of growth:

• They see higher product adoption adoption and more loyal customers;
• Their analytics add-on grows to a new source of expansion revenue;
• They immensely enhance the customer’s experience;

Now what about the final consumers of these analytics? They simply love it. 

For them, data has become a commodity, and not only in a business context. Just think of the spike in consumer apps with built-in analytics: from fitness apps like Strava or Fitbit to banking or productivity apps. End-users now evaluate any product or application on analytical capabilities above and beyond the core.

Examples of consumer apps like Strava & Fitbit that use data visualizations to give their users insights into their sports performance

With that in mind, it won’t come as a surprise that several research studies expect a significant increase in overall analytics adoption to 50% by 2023. 

All it takes is a capable analytics platform such as Luzmo - that covers a variety of use cases.

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2. Avoid loss of business opportunities when you embed data in your product

That brings us to the next question. How much of a priority is analytics, really? Organizations can sometimes be reluctant to start a data project. We’ve seen it multiple times, for many understandable reasons:

• It is not their core business, and they lack in-house expertise;
• They have tech experts in-house but prefer not to distract them from the core product;
• They are not sure if it would be valued by their customers;
• They have no idea of business, functional, or technical requirements;

All valid arguments. However, most organizations work in a hypercompetitive, fast-changing environment. 

We live in an “instant” world when it comes to information, making choices, or actions. Every day, acting agile, fast, and flexible becomes more important. In order to achieve this, end-consumers rely heavily on data:

• Users nowadays take access to crucial information and reporting for granted;
• Data insights speed up the decision process, allowing for faster & smarter actions, such as adding new deals to your CRM;
• Businesses seek to understand the ROI of their digital platforms & products;

As a result, client-facing analytics will not only give SaaS companies – or any other data facilitator – a competitive advantage. It also generates additional opportunities and business growth for the organizations on the other end, consuming the data.

Given data is the new battlefield, late adopters will get run over by their competition. Not only do they lose out on new business and growth, but they also slow down business opportunities for their end-users. No adoption poses a risk, but as will follow in the next paragraph, so does a slow adoption process. Keeping up with the times is going to result not just in more profits, but also in greater customer satisfaction.

3. Faster deployment

There are 2 scenarios to consider when building a client-facing analytics application in-house.

• Data is the core business of the organization;
• The organization is willing to hire adequate in-house expertise, dedicated to the long-term;

But even then, the organization would have to accept a much longer development & deployment cycle. So, it may still be well worth reading through the benefits of working with a third-party tech partner.

In all other scenarios, we strongly recommend sourcing an embedded analytics partner because it’s:

• cheaper;
• faster;
• easier;
• more scalable;

The advantages of embedded analytics solutions

First of all, although the first “back-of-the-envelope” calculations may tell you differently, embedded analytics solutions are in fact cheaper. Hiring dedicated experts is not only very costly but also very difficult if you want superb analytical experiences for your users. 

With the increasing shortage of developer profiles, the right experts are extremely hard to find. In addition to the initial deployment, it requires a long-term staffing cost for maintenance, support, and future feature requests from customers.

Secondly, working with a third-party expert allows for faster deployment because:

• Most off-the-shelf embedded analytics solutions are low-code, plug-and-play building blocks, easy to deploy, and offer real-time insights;
• They have experience with the roll-out of different embedded analytics solutions;
• It minimizes delays that too often occur with development projects;

Companies have been able to speed up their time-to-market from months to just weeks, resulting in a much quicker ROI of their initial investment than with in-house solutions. 

Thirdly, an embedded analytics solution makes life easier for the in-house teams. It allows an organization to stay focused on its core offering while having access to best-in-class analytics with minimal effort:

• Embedded analytics partners keep their platform up-to-date with the latest industry standards and innovations;
• They stimulate knowledge-sharing with others in the industry;

Finally, embedded analytics solutions are much more future-proof and scalable. It is extremely difficult to develop a personalized & customized dashboard experience for an end-user from scratch. Let alone to adapt dashboards to different languages or screen sizes.

 With the right embedded analytics solutions, however, multi-tenant dashboards can be set up with just a few lines of code for thousands of users, instead of one by one. Likewise, localization or screen-adaptive dashboards can be either fully automated through API or managed in the UI at large by business users.

Factors to consider when selecting an embedded analytics solution

When selecting an external partner, there are a few things to keep in mind:

For a faster deployment, tailored to the needs of a specific line of business, go for an embedded analytics solution. It should be composed of smaller analytical building blocks, versus an all-in-one BI solution. 

Modular packages allow more flexibility to deploy and use, and faster response to complex and changing environments. And it’s better for your wallet in case of budget constraints and pricing issues.

For accessibility, use a low- or no-code platform that makes it easy for business users or citizen analysts to churn out good-looking data visualizations. Remember, great user experience is key.

And finally, automation and guided recommendations will significantly increase user adoption of analytics in the future. A high degree of interactivity and actionability will become an increasingly important decision criterion when selecting vendors.

4. Moving up-market armed with business intelligence

Business or product owners naturally look to sell to larger enterprises in order to grow their average deal size. With a growing amount of enterprise companies going all-in on digital transformation, now is an excellent time for well-positioned SaaS companies to get a more significant piece of the pie.

But to stand out in a competitive market, they need a competitive advantage that will knock competitors out of the park. In fact, analytics proves to be a valuable asset to getting a foot in the door and starting with data-driven decision-making.

With more advanced analytics offerings and more informed decisions, a vendor will stand a much higher chance in the enterprise market.

For large enterprises, the analytics offering matters in their buying decision because:

• Robust analytics signals product maturity;
• Insights help larger businesses make sense of their complexity & decision-making for all stakeholders;
• Analytics is typically a straightforward business requirement, and fairly easy to prove ROI to their end consumers; You can use it to add new revenue streams to your existing product;

For product owners, an off-the-shelf embedded analytics solution offers an easy way to meet the above demands:

• Scaling an actionable reporting module that meets the complex needs of a diverse client base now becomes easy, with a faster implementation time;
• It allows to serve large businesses operating globally with localization features such as different languages;
• Enterprise-level accounts expect to be offered premium add-ons such as advanced analytics to meet their evolving business needs;

What about the concern of adding third-party technology to the mix? Enterprise end-users won’t even notice, thanks to native integration capabilities and complete customization through CSS. Embedded analytics solutions completely blend in, feeling truly native to any interface.

On the contrary, companies using third-party embedded analytics solutions will likely be perceived as innovative and future-proof with regard to analytical capabilities. It allows them to continuously offer state-of-the-art analytical features to their end-users, as part of their own product suite.

5. User needs for data insights

Interest in analytics & data insights is organically rising within any type of business, and even among consumers. The same is probably happening within your very own customer base.

Just think of the tons of data a user generates when working with their preferred tool stack. Unfortunately, that data is usually locked inside the SaaS platforms they are using, unless exposed by the platform in the form of interactive dashboards.

All that data could be highly valuable for customers to make better decisions and improve operational efficiency. And don’t just take our word for it. According to several industry surveys, end-users increasingly consider self-service analytics as critical to their business operations.

In addition to this visible trend, there are multiple ways a business can gauge the appetite for analytics among their customers and offer them valuable insights through real-time data.

How to gauge interest in an analytics offering?

To gauge the interest in embedded analytics with the end-users of a SaaS product, there are multiple angles to consider. Following this idea, we’ve grouped a number of key questions to ask customers. This will give a rough idea of their business pains and needs while sparking their interest in analytics.

a. Understand the market competitiveness of your clients

The market a business operates in can have a direct impact on its need for analytics. The following questions could come in handy:

• Do they operate in a highly competitive market? Could data be a competitive advantage? Are any of their competitors already offering analytics in their products?
• Are they operating in a fast, volatile business market where speedy insights from multiple data sources are key?
• How important is it to take rapid actions and decisions based on actual, accurate operational business data to secure business revenue, keep customers satisfied, and respond to market changes?
• How is ROI measured? What metrics are important to monitor and improve? Are these metrics currently visible to them?

b. Identify how smart reporting could help clients in their business

A SaaS platform or service provider should have a clear picture of how their users intend to use the data analytics made available through the platform. This will help understand which exact features clients are looking for, and what they can offer:

• Would a real-time view at a glance on key performance metrics better support their business operations?
• How important is immediate action-taking? Do they currently require extra tools to make smart, tactical decisions based on the data available to them?
• Would domain-specific insights at the right place, within their business workflows, enhance business operations and efficiency?
• Could reporting dashboards directly in communication with their core business application maximize efficiency gain?
• Does the end-customer want to analyze and leverage data insights, without requiring data expertise?
• Does the end-user want to interactively consult reports? Or do they also want the ability to create customized reports on a self-service basis?
• Is collaboration important? Do they need to share data insights and dashboards easily across departments, organization members, or even externally?
• Should findings be consultative for their business on multiple devices? In multiple languages? At any time of day adapted to multiple time zones?

c. Understand the technical implications

To understand how the embedded analytics solution should look like from a technical point of view for the end-users, the following questions are useful to get an idea:

• How easily accessible is the data inside the SaaS platform at this moment? Does it require lots of manual manipulation or high-skilled effort from the end-users, and do they need this to be easier?
• How do end-users typically capture and manage data in their organization? Have they already deployed a traditional BI platform, or built an in-house analytical tool?
• How are data insights used and shared across the organization? What tools do they use to collaborate (e.g. email, Slack,…) and share this information?
• At what level is data used for business decisions: strategically, or on a tactical level where the action is taking place?
• What is the level of expertise in data analysis of the end-users?

Different ways to assess clients’ readiness

There are multiple ways in which a SaaS vendor could assess the interest of their customer base, including but not limited to:

• Sending out regular customer feedback surveys;
• In-depth customer interviews (ideally with ambassadors or heavy users);
• Monitoring online reviews of your product that specifically handle analytics;
• Adding an in-app feedback survey;
• Tracking usage of analytical features that already exist (e.g. data export functions or basic data visualizations in BI tools);

In addition, further market intelligence can be gathered beyond the company’s own customer base. One example is to monitor online reviews of competitors and see what their users say about their analytics offering. 

It’s a great way to stay ahead of the game and save time and gain intelligence on what competitors are doing.

Besides proactively asking for customer feedback, another approach is to gather feedback through actual usage. Companies can consider offering a basic reporting dashboard using embedded analytics to their customers for free. 

Or they could make it available for a select group of heavy users as a pilot project. This will result in true customer feedback, based on actual usage, and will give a much better idea of the actual latent needs. In addition, this is an opportunity to prove the value of analytics to end-users by giving them a taste of it for their business processes.

Grow your business with embedded analytics

It has become clear that hardly anyone will question the importance of data within the ongoing process of digitalization. Businesses who offer real-time, actionable insights within a business application will improve the usability and context of the data for any end-consumer.

In addition, using an off-the-shelf analytical building block removes the need for data-savvy staff, long development cycles, and steep learning curves. On the contrary, it will speed up time-to-market save costs, and even result in better user retention.

That’s what makes embedded client-facing analytics packages a strategically interesting feature for any data facilitator. Especially within the competitive landscape of SaaS and providers of digital and IoT services, it enhances customer experience, ultimately driving business growth.

In the next article, we will dive deeper into what that business growth might look like. We will discuss the different forms of ROI of embedded analytics, both for data facilitators and data consumers.

Interested in making analytics a meaningful investment for your product and its users? Book a discovery call with one of our product experts, and get a live demo of how Luzmo can help you achieve growth.