What will the price of embedded analytics be in 2024?

Embedded Analytics, what is it? 

Embedded analytics integrates advanced data analysis and visualization directly into software applications, significantly improving their native functionality. This enables users to perform complex data analysis seamlessly within the app, which is a critical feature for SaaS solutions that aim to provide a comprehensive user experience. Its applications, such as user behavior tracking and personalized customer interactions, are designed to meet the needs of software companies looking to provide superior in-app analytics. 

Embedded Analytics Products 

• One chart or two: Whether it is a chart or two on the page of your application, all we want to accomplish is that users get the data/insights that is relevant and they desire. Often, pointed and relevant information is best rather than giving a whole lot of information in a complex and all-encompassing dashboard. 
• Embedded Dashboards - Dashboards are needed where multiple KPIs need to be tracked and reported upon. Doing so, in an embedded manner, is supremely efficient as it avoids moving the data out to another location/data store and then build dashboards to offer insights – which adds latency to insights. Embedded dashboards are dynamic, real-time/near-real-time updates . Classical dashboarding tools when embedded do not offer much interaction-ability and users have to rely on BI developers to make changes including layout, data sets, and visualization types. Dashboards are ideal for a wide range of applications, including sales tracking and customer behavior analysis. 
• Report Builders: Report builders can be useful tools for creating and customizing detailed reports that capture a specific moment in time. It is intended for ease of use, allowing users of all skill levels to easily compile and organize data. This feature enables users to focus on relevant business metrics using user-friendly interfaces and intuitive controls such as drag-and-drop. Reports can range from simple data summaries to in-depth analyses, catering to a variety of business needs. Furthermore, automation features improve the reporting process by saving time and ensuring consistent data monitoring. 
• Generative AI for Self-Service: We strongly believe that future of data is in  Generative AI - embedded analytics has been slow to adopt GenAI capabiliites mostly because no solution is available for enterprises that require high standards of security and features.  
   
  GenAI from Quaeris will make it extremely easy to implement Embedded Analytics for one or two charts, whole dashboards or reports. Users can interact with the system in natural language, making it more intuitive. Beyond simplifying data analysis, generative AI offers predictive insights that improve decision-making by providing timely and relevant information tailored to specific queries. 
  

Comparing Embedded Analytics Pricing 

Looker Embedded Analytics:  

Looker, known for its advanced analytics capabilities, enables users to explore deep data and discover insights. It was acquired by Google in 2020 and is integrated into the company's product suite. Its unique LookML language improves data modeling, making it an effective tool for complex analyses. 

Capabilities: 

• Data Exploration: The Looker platform excels at advanced data exploration, allowing users to delve deep into their datasets to uncover insights.  
• Customization and Integration: Looker's tools are highly customizable, so they can be tailored to specific business requirements. Its integration capabilities make it an adaptable solution for a variety of business environments. 
• Advanced Data Modeling: Looker uses a proprietary modeling language called LookML, which provides a robust layer to ensure that all users receive consistent data and results. However, this proprietary language has a steep learning curve when compared to pure SQL-based modeling layers. 

Pricing: 

Looker's embedded analytics pricing structure starts at about $120,000 per year. They no longer offer a free trial and do not publicly advertise their pricing information, but some customers have reported negotiating lower prices based on company volume. Their pricing scales are based on individual viewers. This higher per-user cost can be a deterrent to embedded analytics, particularly because embedded analytics typically require widespread user access to data. Looker also outsources its support, so basic support and setup are not included in their pricing. They rely on outside consultants and agencies, which can significantly increase the startup and ongoing costs for Looker. 

GoodData 

GoodData is intended for large-scale data reporting and analytics needs. Its comprehensive suite of analytics tools, combined with an easy-to-use interface, make it ideal for a wide range of business intelligence applications. 

Capabilities: 

• Scalability and Security: GoodData is designed to handle large-scale deployments, making it an excellent choice for businesses that require extensive data reporting. Its emphasis on security ensures data protection, which is critical for enterprise-level analytics. 
• Comprehensive Analytics Solutions: GoodData provides a diverse set of analytics tools to meet business intelligence needs ranging from basic reporting to complex data visualizations. 
• User Friendly: Despite its comprehensive nature, GoodData maintains a user-friendly interface that is accessible to non-technical users. 

Pricing: 

GoodData provides a distinct pricing structure for internal and embedded analytics. For internal analytics, the startup plan is reasonably priced at $360 per user per year, plus a $1,500 platform fee per year. They provide a 30-day free trial to test their platform. However, the cost of using their embedded analytics features to provide high-quality analytics to your customers is significantly higher, at $18,000 per year ($1,500 per month) for their base platform fee plus additional costs for each workspace or customer that you serve. To gain access to data source managers, which is critical for embedded analytics, businesses must upgrade to a more expensive bespoke Enterprise plan. 

Tableau 

Tableau, the oldest business intelligence solution, is well-known for its complex visualization capabilities. Its main strengths are the ability to create impactful data visualizations and the wide range of connectivity options. 

Capabilities: 

Intuitive User Interface: Tableau's point-and-click interface enables users to create visualizations and dashboards without coding. 

Robust Visualization Tools: Tableau's strength is its powerful data visualization capabilities, which allow users to create compelling and insightful data representations. 

Wide Range of Connectivity Options: It provides a wide range of connectivity options, allowing users to seamlessly integrate data from multiple sources. 

Pricing: 

Tableau's server licensing pricing structure is tiered, with three user types: Creator ($840 per year), Explorer ($420 per year), and Viewer ($144 per year). Each tier caters to different user needs, with Creators having the most extensive access and capabilities, followed by Explorers and Viewers, who have fewer functionalities. 

Tableau offers two licensing options for embedded analytics, each tailored to a specific external use case, such as integrating with customer-facing applications. Explorer and Viewer are eligible for the Named User license, which costs $315 per year and $108 per year respectively. This pricing is based on embedding dashboards for a company's external customers and increases with product usage. Alternatively, the Core-based license, which costs $72,000 per 8 cores per year, is intended for scenarios with variable user numbers and concurrency rates, focusing on server capacity rather than individual users. This license gives businesses more flexibility at a much higher cost. 

 Quaeris

Quaeris is AI driven natural language based self-service insights platform for business users. It is a platform to create, interact and collaborate on insights. It builds and presents insights on corporate data by asking questions in natural language. No coding or dashboard developers needed.  

Quaeris complements your BI footprint and addresses the needs to field and remote workers such as sales, marketing, warehousing and supply chain teams with an intuitive mobile app that is voice enabled. BI addresses the need of deep visual and cusal analysis while Quaeris is a simple insights delivery layer. Quaeris can even read BI data model for communication of insights to end-users. 

Capabilities: 

• Ask anything, get answers in seconds: No coding, just natural language questions for immediate understanding. 
• True self-service BI: Drive insights yourself, without relying on analysts. 
• Full collaboration suite: Work together on data, share insights, and discuss findings seamlessly. 
• Personalized pinboards and storyboards: Share key findings with internal and external stakeholders clearly and securely. 
• Predictive insights: Uncover hidden trends and anticipate future impacts with the self-learning engine. 
• Guaranteed lowest cost of ownership: Quick implementation, minimal training, one simple price for unlimited users. 

 Pricing: 

Quaeris is priced on consumption, and the only flavor it is available is full-featured. So, customers can on-board 100s of users and if their users are ‘casual users’ you could pay under a dollar per month per user. And if your users love the analytics provided and use your platform extensively, then will you mind paying for your heavy users – i think you will be happy that users are loving your product. Even in that case, on a per user, per month, basis, you are expecting to pay less than you will pay for a few Starbucks latte.  

The real savings in case of Quaeris are really in the cost of development. Quaeris’ AI model does all the heavy lifting, so you/your team can implement Quaeris in a matter of hours/days - and will never have to code new charts/graphs.  

The other real advantage of AI driven solution is ‘Speed-to-market'. No more lengthy requirements gathering and weeks long development work and refreshed requirements that will keep changing resulting in dependence on Consultants. 

Conclusion:  

In 2024, embedded analytics solutions offer a wide range of pricing options, influenced by the provider, deployment scale, and feature sets. When choosing the best solution, businesses must consider factors such as implementation simplicity, prompt access to insights, customization opportunities, and the potential for white-labeling. Quaeris merits careful consideration due to its harmonious blend of speed, data reliability, unrestricted PDF and PowerPoint export capabilities, user-friendly interface, and cost-effectiveness. For enterprises seeking to elevate their analytical capabilities, exploring Quaeris offerings is a worthwhile move in the decision-making journey.