Data Sharing and Monetization: A growth booster for B2B SaaS Companies
In today's data-driven world, businesses possess valuable information that can be transformed into a lucrative revenue stream. Data monetization has emerged as a powerful strategy to capitalize on this potential, and one approach to gain traction is sharing data with customers.
- Data sharing
- Data monetization
- Data sharing with AWS
- AWS Data exchange
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Data Sharing for B2B SaaS Companies
Data sharing can be a strategic advantage for B2B SaaS companies, offering numerous benefits that contribute to increased customer engagement, enhanced product value, and a more competitive market position. Here are the key reasons why companies should seriously consider data sharing:
- Enhanced B2B Customer Engagement: Data sharing fosters a stronger connection with customers by giving them access to valuable information that aligns with their needs. By offering relevant data insights and analytics, companies can create a more engaging and interactive customer experience, increasing overall satisfaction and loyalty.
- Demonstrating ROI and Value: When B2B SaaS companies share data with their customers, clients interact with your product more deeply. Access to real-time data and analytics empowers customers to measure the impact and value of the product or service they have invested in, validating the ROI and justifying the continued use of the solution.
- Strengthening Product Offering: Data sharing allows B2B SaaS companies to go beyond basic functionalities and transform their products into comprehensive platforms. By providing customers with market insights and data-driven intelligence, companies add value to their solutions, making them more attractive to existing and potential clients.
- Competitive Differentiation: Data sharing can be a powerful differentiator for B2B SaaS companies in a crowded marketplace. The ability to offer rich data sets and actionable insights sets the product apart from competitors, positioning it as a sophisticated and forward-thinking solution.
- Building Trust and Credibility: By sharing data and insights, B2B SaaS companies demonstrate transparency and build trust with their customers. Clients appreciate the willingness to share valuable information, which fosters a sense of partnership and collaboration.
- Customer Empowerment: Data sharing empowers customers to make data-driven decisions within their organizations. This empowerment leads to a deeper reliance on the SaaS product, increasing customer retention and reducing churn.
- Upselling and Cross-selling Opportunities: Data sharing can open doors to upselling and cross-selling opportunities. As customers gain access to valuable insights, they may identify additional areas where the SaaS solution can address their needs, leading to expansion of the product’s usage and potential upselling to higher-tier packages.
In summary, data sharing is a strategic move for B2B SaaS companies that want to deepen customer engagement, strengthen product value, and gain a competitive edge in the market. Companies can foster long-lasting relationships and drive sustainable business growth by empowering customers with data-driven insights.
Data Sharing Options
We identify three levels in the data-sharing process, each with its own pros and cons.
1. Raw Data Sharing for Valuable Insights
- Organizations offer access to raw data to customers for a fixed monthly fee or usage-based charge.
- Data is made available through user-friendly interfaces like APIs or cloud-based storage.
- Customers can leverage this information to gain valuable insights and make informed decisions, driving business growth.
2. Insights as a Service: Empowering Decision-Making
- Businesses provide actionable and tailored insights to customers through a subscription model (monthly or annually).
- Customers can access these valuable insights via intuitive web and mobile applications.
- This service empowers customers to navigate complex challenges confidently.
3. Analytics Enabled PaaS: Enhancing Customization
- Analytics Platform as a Service (PaaS) allows clients to bring their datasets to better understand their data landscape.
- The platform offers comprehensive data exploration capabilities, enabling customers to uncover patterns, gain critical intelligence, and foster innovation within their organizations.
Data Sharing in Practice: An Overview
There are several ways to approach data sharing in practice, below we go into the best approaches to sharing data with customers.
Raw Data Sharing via APIs or Cloud Buckets
A compelling and straightforward approach to empowering B2B customers with data is directly sharing the raw information. This empowers them to integrate it into their existing reporting and analysis systems seamlessly. This is a significant benefit, as most businesses already have their reporting in place and would prefer to integrate this data source instead of creating another tool that they need to look at.
In today’s landscape, leveraging cloud-based storage solutions or offering accessible APIs stands as the optimal way to facilitate direct data sharing. Cloud storage, known for its robustness and cost-effectiveness, offers an attractive avenue.
Commonly, Amazon S3, or cloud storage buckets serve as the foundation for this approach.
An alternative to explore is AWS Data Exchange, a comprehensive solution by AWS. It handles intricate aspects, such as streamlined monthly billing based on data exchange usage.
In sharing raw data, a judicious assessment of the implications is essential. It’s worth recognizing the substantial value in your data, underscoring the importance of discerning distribution strategies that resonate with its inherent worth.
Exploring Data Sharing on AWS through AWS Data Exchange
In data sharing, Amazon Web Services (AWS) introduced a sophisticated solution known as AWS Data Exchange. This innovative service provides two distinct avenues for seamless data exchange: AWS Data Exchange for Redshift and AWS Data Exchange for S3.
AWS Data Exchange, a creation of Amazon, empowers users to publish and potentially monetize their datasets. For those utilizing Amazon Redshift, the process entails setting up AWS Data Exchange specifically for Amazon Redshift, as detailed in the AWS Data Exchange for Amazon Redshift resource.
The procedure for publishing a Redshift dataset follows these logical steps:
- Initiate an Amazon Redshift datashare asset.
- Establish an Amazon Redshift dataset.
- Craft a revision, acting as a container for one or multiple assets residing in S3.
- Integrate Amazon Redshift datashare assets within a revision.
- Effectuate the publication of a new product encompassing Amazon Redshift datasets.
- (Optional) Duplicate a product.
For more comprehensive guidance, refer to the detailed documentation provided here.
AWS Data Exchange boasts a range of valuable advantages:
- Access Control: The service incorporates robust access control, allowing data sharing with designated individuals.
- Monetization Ease: Data monetization becomes streamlined, enabling subscription charges for access, all managed seamlessly by Amazon.
- Business Intelligence Reporting: Gain insights into subscriber behavior, such as which tables are being accessed.
Nonetheless, there are some considerations to take into account:
- AWS Account Requirement: Subscribers must possess an AWS account.
- Redshift Database Necessity: Subscribers need access to a Redshift database.
- Producer Obligations: Producers must register as an AWS Data Exchange provider.
- Provider Registration Challenges: Registering as an AWS Data Exchange provider involves certain complexity (see below).
Becoming an AWS Data Exchange Provider
Becoming a provider of AWS Data Exchange necessitates adhering to specific requirements:
- Establish a well-defined customer support process and organizational support framework.
- Ensure regular data updates and maintain vulnerability-free datasets.
- Adhere to established marketing best practices and guidelines for product promotion.
- Maintain good standing as an AWS customer, fulfilling stipulations outlined in the terms and conditions for both AWS Marketplace sellers and AWS Data Exchange providers.
- Qualify as a permanent resident or citizen in an eligible jurisdiction, or represent a business entity organized or incorporated in these regions.
- To offer data products, initiation of the qualification and registration process via the Create case wizard for AWS Support is required. The AWS Data Exchange team will subsequently facilitate the completion of the registration process.
Furthermore, if the intent is to offer products for sale, further details and a US bank account are required.
The cost structure for AWS Data Exchange involves distinct aspects for providers and subscribers:
Providers (You Pay):
- Tiered fulfillment fees, with specific amounts and potential applicability to free datashares yet to be clarified.
- Data transfer fees estimated at around $0.02-$0.09 per GB, if the transfer is to a region outside of where the data resides.
Application of the aforementioned provider costs may vary, as detailed here.
Subscribers (Customers Pay):
- Data product fees, if configured (offering subscription or pay-as-you-go models).
- Data transfer fees, approximately $0.09 per GB, when data resides inside another region.
- AWS service costs related to data product storage, processing, or analysis.
A comprehensive breakdown of associated costs is available for review here.
Similar options are available for AWS S3, which you can find here.
Insights as a Service & PaaS: Delivering Insights
Among the options available to cater to customers, this particularly stands out for its exceptional value. In short:
- Businesses extend actionable and personalized insights to their clientele through a subscription-based model, offering choices of monthly or annual plans.
- Customers can access these valuable insights via intuitive web and mobile applications.
Once you’ve made the choice that you want to offer insights as a service, there are a number of delivery options available to you. Instead of developing analytics in-house, you should consider employing one of the options the many BI tools offer you. Prominent ones like Tableau, Power BI and others all have one, if not multiple ways to share reports and dashboards with customers.
One challenge is how to share your dashboards and reports with customers. Many businesses take the route of least resistance, but lose out on many of the benefits a full-fledged solution could offer. Should we classify the avenues for sharing reports and dashboards with customers, there are several options available. Ranging from very simple to complex:
- Direct Sharing of Reports and Dashboards — A straightforward point of entry, albeit accompanied by limitations. While this option facilitates easy initiation, adopting a comprehensive solution like Power BI might entail per-user licensing costs. Furthermore, users could procure licenses from the BI vendor rather than you, potentially posing challenges in direct monetization. Full white labeling of shared dashboards may not be feasible via this route.
- Embedded Analytics — Integrating analytics within a web portal or application, tailor-made for end consumers and businesses. This approach affords meticulous user management, row-level access control (RLS), authentication, and more. Although the initial costs may be higher, the increased flexibility offers tangible advantages. Here, users aren’t required to purchase their licenses; instead, you can bill users for their analytics usage, and there is no per-customer fee to be paid. Embedded analytics empowers you with comprehensive control, enabling full white-labeling and complete customization of user experiences.
- PaaS Analytics — Let users customize their dashboards, insights, and visuals, for extra gain. A direct step up from offering Insights as a service.
Challenges with Data Sharing
Data sharing offers numerous advantages, but also challenges that require careful consideration and proactive measures to ensure successful implementation. The key challenges include:
Data security is a critical concern when sharing information with external parties. While tools like BI dashboards with shareable links may offer a quick and convenient solution, they can also pose significant security risks. Unauthorized access to sensitive data through these links could lead to data breaches and compromise confidentiality. Businesses must adopt robust security protocols, such as encryption, access control, and regular monitoring to safeguard against potential threats.
2. Cloud Storage Management
Sharing data often involves utilizing cloud storage solutions like AWS S3 Buckets. While cloud-based services offer scalability and accessibility advantages, businesses must protect these buckets from unauthorized access. Additionally, organizations need to manage the costs associated with cloud storage, as (high-volume) data transfers out from the cloud can be expensive. Careful planning and cost optimization strategies are essential to ensure efficient use of cloud resources.
3. Data Quality and Customer Experience
When sharing data with customers, ensuring data quality is of utmost importance. Customers need accurate and reliable data to make informed decisions and gain valuable insights. Poor data quality can lead to erroneous conclusions and undermine the company’s and its clients’ trust. Structured data validation and cleansing processes are crucial to maintain high data quality and provide a positive customer experience.
Addressing these challenges requires a holistic approach to data sharing. Businesses must prioritize data security through robust encryption and access control. Implementing secure data transfer protocols and monitoring data access can help mitigate security risks effectively.
Managing cloud storage involves implementing proper access control, monitoring usage, and optimizing costs to ensure efficient resource utilization.
To enhance data quality, companies should establish rigorous data governance practices, including data validation and cleansing, to provide accurate and reliable information to their customers.
By addressing these challenges proactively, B2B companies can capitalize on the benefits of data sharing, while ensuring the privacy, security, and quality of shared information, fostering stronger customer relationships and driving business growth.
Conclusion: Navigating the Path to Data Sharing Excellence
In the landscape of data-driven business, the concept of data sharing has emerged as an important strategy, offering many advantages beyond mere revenue generation. This practice holds the potential to forge robust relationships with customers, amplify product value, and set a company apart in a competitive market. However, successful data sharing demands careful consideration and strategic decision-making.
Recognizing the high value inherent in data sharing, B2B SaaS companies are presented with a transformative opportunity. The potential to elevate customer engagement, reinforce product utility, and achieve market differentiation is undeniable. Yet, this path is not without complexity. Choosing the optimal data-sharing solution demands a thoughtful approach that transcends the path of least resistance.
It is paramount to address the challenges that lie ahead. Security and the quality of shared data must be paramount considerations, safeguarding sensitive information while ensuring its integrity.
In summary, data sharing with customers is a transformative feature for B2B SaaS companies, promising enhanced engagement, improved product offerings, and competitive distinction. By thoughtfully selecting the path that aligns with their objectives and navigating the challenges with a resolute mindset, companies can unlock the potential of data sharing, nurturing partnerships, and improving their growth.
About the author
Maximilian is a machine learning enthusiast, experienced data engineer, and co-founder of BiteStreams. In his free-time he listens to electronic music and is into photography.Read more
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