Table of Contents
Introduction
Leverage seamless user experience and revenue growth…
Embedded analytics is the incorporation of analytic content and capabilities within applications, like business process applications (e.g. CRM, ERP, EHR/EMR) or portals (e.g. intranets or extranets).
Integrating pertinent data and analytics inside applications assists users in working smarter and more effectively by resolving high-value business issues. Most essentially, embedded analytics is a tool to make data accessible to non-technical users.
At present, about 90% of software companies are embedding analytics tools in their applications, as per the State of Embedded Analytics Report. (Source: Toucantoco)
Many modern businesses know that seizing a new customer can cost five times more than retaining an existing customer. Hence, companies are increasingly making retention a vital component of their business strategies.
Concerning independent software vendors (ISVs), customer retention is directly linked to product adherence. In the present data era, embedded analytics can play an integral role in improving product adherence, as demonstrated by the equation below.
Embedded Analytics + Product Usage = Revenue Growth
Yes, PAL, you read it right! Embedded analytics is capable of improving product usage by augmenting product adherence, which can lead to revenue growth for ISVs.
Embedded Analytics- Vital Considerations
Prosperous embedded analytics projects are not merely appealing depictions of data, they need to generate insights and actions. What will suffice your present customer base and win over novel customers?
Mentioned below are vital factors and features that can make your application’s analytics stand out and drive revenue.
- Take Into Account the Overall User Experience
Primarily, to monetize the embedded analytics in their applications, product managers must consider the complete user experience. Dashboards and reports must integrate effortlessly into the remaining application— both concerning actions and branding. If you’re let down by an unconnected user experience, they might abandon your application completely.
- Incorporate Workflow Action
Analytics must drive action, not merely visualize data. By incorporating workflow capabilities into your embedded analytics, you enable your users to take actions from within your application— whether it’s about sharing findings with colleagues or starting a new process. Integrating analytics in the host application workflow enables you to build captivating and thoughtful use cases that actually differentiate your application from the opponents.
- Embedding Self-Service Analytics
By incorporating self-service capabilities into your embedded analytics, you authorize users to ask novel questions and explore their data for exquisite answers— devoid of help from your tech team. It’s a win-win situation: users customize your application so it fits varying use cases than ever, while you minimize the number of ad hoc analytics requests your tech team has to manage. Self-service analytics can also result in valuable insights into your customers, enabling you to witness what sorts of dashboards and reports naturally emerge in your product in response to customer requirements you didn’t expect.
Product Usage Tomb
There are three vital aspects of this tomb:
- Democratization: Make analytics accessible to all types of users.
- Contextual analytics: Deliver actionable insights within particular contexts of business workflow.
- Deep analytics: Intensify the accessibility of analytics to make the product.
Let’s have a closer look at each level:
1. Democratization
Analytics should be accessible to all is a crucial aspect towards augmented product usage. Modern analytics platforms serve a wide array of self-service proficiencies. Here we present a few strong analytics capabilities ISVs should watch out for given democratization.
– AI-Powered Inline Data Preparation: Formerly, IT teams were responsible for data cleansing and preparation. At present, BI and Analytics platforms deliver AI-powered self-service data preparation proficiencies to swiftly cleanse, transition, and enrich data.
- Conversational Analytics: Users must have the insight they’re looking for by asking simplified questions to an AI-powered conversational assistant.
- Automated Insights: Users can acquire a deeper understanding of their data visualizations, and find out vital insights, through AI-generated auto-narratives.
2. Contextual Analytics
Contextual analytics needs effort at different levels. Let’s discuss three vital elements that authorize this layer below.
- Effortless Integration: Makes certain that both the ISV parent application and embedded analytics are hassle-freely integrated. This is attainable by allowing SSO & SAML authentication, embracing an in-built design studio within the analytics application to ensure look-and-feel uniformity and using a dynamic API library to plug any “bridges” in integration.
- Contextual Embedding: This helps place insightful reports and dashboards within business workflows. Advanced embedded analytics platforms deliver rich and robust dashboards that authorize users to munch insights and interact with the fundamental data for deeper analysis. The responsibility is on the application provider to make sure these dashboards also possess pulverized access control mechanisms in place.
- Embedding AI-Powered Analytics Proficiencies: Such as conversational analytics, automated insights, predictive analytics, and generative AI, can thereby assist users to easily access contextual insights on a real-time basis.
3. Deep Analytics
The profundity of analytics proficiencies a platform delivers is directly associated with a user’s ability to enhance the overall product adherence required for high user retention.
Let’s have a closer look at a few capabilities ISVs should seek.
- Dynamic Visualization Alternatives: Modern businesses operate with a broad range of data types, such as discrete and continuous data, geospatial data, and qualitative data. ISVs should make certain their embedded analytics provider delivers a broad spectrum of visualization alternatives to shield the entire gamut of vital data types.
- Predictive Analytics: Triumphant businesses often have historical data readily available. But to drive decisions successfully, you require foresight. Modern analytics platforms provide predictive analytics capabilities to serve the purpose. A few vital aspects that ISVs should check for include the breadth of the forecasting model and the depth of pre-built ML models supported.
- Trend Analysis: This deep analytics proficiency assists users in understanding the underpinning data over the data (historical and forecasted) available.
- Scenario Analysis: This helps users recognize/ evaluate the impact of decisions made based on outcomes. For instance, it might help them recognize the impact of spending on sales or any modifications in profit percentage on sales.
How Businesses Are Employing Embedded Analytics to Streamline Revenue Growth
Attain Quick Time-to-Market
Committed analytics development needs expertise, resources, and time. It can be challenging to attain speed, reliability, and scale with an indigenous solution. By capitalizing on Software-as-a-Service (SaaS) embedded analytics solutions, the worry of maintaining infrastructure, storage, and computing power is eliminated and you can be assertive that your analytics solution will. Perhaps, the right embedded analytics solution positions you in a place to go to market faster by minimizing the analytics development cycle.
Inflate Revenue Streams
An embedded analytics solution can greatly influence your business as much as it influences your application. Embedded analytics can pave the way to new revenue streams and help develop opportunity size. You can create new lines of business around embedded analytics services- like white-labelled dashboards— as avenues to expand customer loyalty and scale your business. This helps you unleash more upselling and cross-selling opportunities.
Give Rise to Value, Not Merely Reports
Your application developers should emphasize creating novel features and enhancing core functionality, not merely custom-developing an extensive analytics engine or coding reporting features that require constant updates. With the right embedded analytics, you need not start from scratch to cater to customer demands. This helps your developers to enhance core features and functionalities.
Conclusion
Embedded analytics and BI solutions are handy off the shelf, allowing your business to leverage the dedicated R&D, infrastructure, and development effort of a vendor that possesses BI and data. If you lack this core competency in-house, choosing to buy is a definite alternative. By removing the hassle of development, your business will be free to invest in capturing additional value for you, your developers, and your customers.
If you’re an ISV seeking sophisticated and reliable embedded analytics providers, Smartinfologiks Analytics can be a perfect solution. Analytics is an influential BI and analytics platform that can help you meet your business needs.
Witness the impact it can have by getting started with Smartinfologiks Analytics. Wish to have a glimpse of what we deliver? Schedule a personalised demo at your ease.
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