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Key Questions to Ask When Ordering embedded module

Author: Shirley

Jan. 13, 2025

A Buyer's Guide to Embedded Analytics: Questions to Ask ...

In a world where information technology has changed every aspect of human life, businesses must capitalize on data-driven decisions because they give them a significant competitive edge. This is why companies should adopt embedded analytics, which is becoming essential for placing digitalized analytics inside applications that users use daily.

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Nevertheless, when many of these solutions are available, choosing one may be overwhelming. Asking the right questions before committing to any embedded analytics platform will help you make an informed decision.

1. What&#;s your data integration capability? 

Data integration is essential for every successful analytics product or service. Check if this platform can easily connect with your existing sources, which include databases stored on clouds or third-party apps, e.g., Salesforce (Customer Relationship Management). Ask about supported data formats, real-time data streaming abilities, and how easily one can establish such connections.

2. How easy is the model in terms of user experience? 

Embedded analytics should have an interactive model that any end-user can understand. This is why you need to look into the system's user interface (UI) and be sure it matches design and branding guidelines and overall application usability approaches used by DRM Software Solutions Ltd or other providers in this field. Good UI design leads to higher levels of user adoption, hence engagement.

3. What customization and white labeling options are available? 

Customization and white labeling are necessary to maintain a consistent user interface throughout the system. Choose those that support white labeling, enabling users to incorporate their brands&#; unique visual identities into embedded analytics.

4. Does it scale? 

As businesses grow, their analytic requirements inevitably increase. Assess the scalability of existing solutions regarding increases in data stored, the number of concurrent users accessing it, or other computational cost features like Location-Based Services, which may traverse many users. 

Enquire more from vendors about what kind of implicit assumptions underpinning those vendors&#; infrastructures are about caching mechanisms&#; reliance upon either volatile or nonvolatile memory; performance optimization techniques applied such as those that utilize spacial locality in programming languages for hardware instructions execution order determination through reordering them considering both the instruction data and branch dependencies etcetera.

5. What available data visualization and reporting tools does the vendor provide?

Data visualization forms an integral part of any meaningful analytics process. Evaluate what kind of visualizations (like charts, graphs, or dashboards), including report-giving mechanisms, are supported there through web development technologies like XML or HTML5 as well as any other common programming language for website designing like PHP; determine if these provisions can suit your industrial sector prerequisites and behind which one can tell stories using his/her data without formal training on this issue etcetera.

6. Is the embedded analytics platform secure and compliant enough? 

Most importantly, when dealing with regulated industries, ensuring data security and compliance is paramount. Find out from vendors how these platforms have been secured, including mechanisms like using data encryption at rest or in transit, role-based access control policies, or following well-known industry standards such as GDPR, HIPAA, etcetera.

7. What levels of support/training do we get?

 Implementing and maintaining an embedded analytics solution is not an easy thing. There is the need to find out what level of help is being provided by the vendor, like a documentation library available online; FAQs area where most frequently asked questions are answered; and training resources you up with experts who will help understand better what should be done such as web instructor-led classes on how to use software applications offered within this package; tutorials plus dedicated support channels available for any emerging issues that may arise in the course of implementing such solutions, etc.

Reasonable customer care significantly reduces lead times needed during implementation stages, thus ensuring smooth ongoing operation.

8. Does it have a flexible pricing model? 

Embedded analytics solutions often have varied pricing methods based on user data volumes or utilization. The vendor&#;s prices should be understood and linked to the customer&#;s budget and future growth needs. Ask if they charge for additional features, technical assistance, or any software integration peculiarities within their ecosystem&#;and see if they can be integrated into your toolsets.

9. What changes to the software features do I anticipate shortly that can help me keep up with the times?

Phenomenal alterations may happen within the analytic sector, demanding a forward-thinking vendor. Learn what visions and plans exist under the vendor roadmap and how inclined they are towards innovation and delivering new improvements promptly.

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10. How much can existing tools and workflows harmonize with this solution?

Embedded analytics only work correctly if integrated with other daily applications users use, such as CRM. Deliberate integration abilities concerning current business intelligence systems, including collaboration suites.

11. Who is entitled to control data? 

Control data&#;why does it have such a name? Data governance made compliance and data integrity mandatory. Get informed about the platform data governance system and understand its capabilities, like data lineage tracking, version control, and audit trails. Besides, you must know how to manage and control your data.

12. How does the vendor drive customer success and support?

This journey starts with you and the vendors in collaboration and accountability. Enquire about the CS approach, whether it is a designated manager working together throughout the process or regular discussions between sales voices on one side and support personnel who keep stepping, thus aiding the maintenance of the analytics process.

Conclusion

By thoroughly evaluating these key aspects and asking the right questions, you can make an informed decision when selecting an embedded analytics solution that aligns with your business objectives, technical requirements, and long-term growth strategy.

At Quaeris, we take pride in delivering cutting-edge embedded analytics solutions that empower organizations to unlock the full potential of their data. Our team of experts is always available, ready to guide you through the evaluation process and ensure you find the perfect fit for your unique needs. We value your time and needs, and we're here to support you every step of the way.

15 Key Questions to Ask any Embedded Analytics Vendor

The decision of which embedded analytics solution to acquire is of strategic and financial importance to your organization, having a direct impact on business performance as well as employee or customer happiness. However, the field of embedded analytics is not short of complexities and, as such, it is often easy to overlook many of the underlying aspects that have the potential to start hampering your teams, your business, and ultimately, your ambitions.

How can you avoid these potential pitfalls?

By asking the right questions of any analytics vendors you approach in your pursuit of embedded analytics. Being armed with what to look for will enable you to invest in the right solution, thereby, increasing your potential for a successful analytics-powered product or application and, in turn, the potential to successfully grow your business.

Some of the questions you should be asking

This list of questions is intended to help your data, product, and management teams to evaluate various platforms smoothly and find an analytics solution that will satisfy your organization, use cases, and users, in the long term.

Advanced embedded analytics capabilities are especially crucial for software companies, enterprises, and large-scale, distributed organizations and use cases.

Wondering what some of the terms in this article mean?

  • Non-technical users - users with no/limited skills in working with data analytics - e.g. business managers, sales reps., branch managers, accountants, etc.
  • Visualizations - a broad term to describe graphs, tables, and other data depictions
  • Dashboard - a collection of graphs, charts, tables, and other visualization types placed together within one page, for example.
  • Metric - to simplify this term, for the purposes of this article, think of a metric as a piece of data/information displayed in a visualization.

Embedding dashboards into your application

  • What options do I have to embed graphs, charts, and dashboards with your analytics platform?
  • Is there any simple, do-it-yourself option of embedding for non-technical users?

Customizations for a consistent visual style

  • What customization options are available to ensure a consistent visual style between your embedded analytics solution and my business application/software product?
  • Can I make your analytics interface look totally different, unlike traditional analytics?

Data visualization for all users

  • What types of visualizations are available right off?
  • Can non-technical users easily create (or adjust preexisting) dashboards and graphs?

Scalability to 100s or s of users/user groups

  • What size of deployment is your analytics solution able to support? Does scaling to more users affect performance?
  • How does pricing change with increased/decreased customer/user numbers?

Data preparation and change management

  • What options are available for data preparation? Where does data preparation occur?
  • What control mechanisms (semantic layers, reusable metrics, layered security) exist to ensure that visualizations do not give inaccurate or unreliable data outcomes?

Data integration from multiple sources

  • What data sources are supported by your embedded analytics platform?
  • Can users easily upload data themselves (via CSV, for example)?

Data security operations and compliance

  • What are the security standards supported by your embedded analytics solution?
  • Is your platform certified to handle highly sensitive healthcare/financial data?

Monetizing data and software products

  • Does your embedded analytics solution enable the segmentation of customers by tiers, to develop a software product with priced tiers of data (for example, Basic, Advanced, Premium)?

This is just a selection of the most common questions to ask embedded analytics vendors. For the more technical questions, your team should be asking, continue to download our Embedded Analytics Questionnaire.

Want more information on embedded module? Feel free to contact us.

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