Monetize insights as an asset and get ahead with cutting-edge features data-powered customers demand.
~5 minute read
In today’s digital-first economy, the volume of business data is exploding. For B2B SaaS providers, this ever-growing sea of operational and consumer data presents a pivotal opportunity to deliver new value to customers and drive internal business outcomes.
It’s more important than ever to make the path to the insights as smooth as possible, for as many types of business users as possible. From the C-suite to the sales floor, access to data helps every employee make impactful decisions that boost business.
B2B SaaS providers can take advantage of this demand for easy-t0-access, easy-to-understand data by implementing enhanced data access features in the software their customers already rely on.
Embedded artificial intelligence built for data access has the power to transform the way customers discover and analyze their data within the software systems they use. With AI, processes that are typically highly manual, time consuming, and resource intensive can be streamlined at reduced cost.
Before we dive into the 3 reasons today’s B2B SaaS companies need to level-up their data access functionality, here are a few stats to take into consideration:
→ Customers demand seamless conversational experiences in digital spaces: In 2019, 58% of customers said emerging technologies such as chatbots and voice assistance have changed their expectations of companies.
→ AI will empower non-technical team members to engage deeper in data processes: By 2025, a scarcity of data scientists will no longer hinder the adoption of data science and machine learning in organizations.
→ Data is an asset, and improving data accessibility enables businesses to achieve outcomes: By 2022, 90% of corporate strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency.
→ AI drives revenue: Businesses that successfully roll out and maintain AI initiatives are nearly three times more likely than those from other companies to report revenue gains of more than 10%.
→ Data drives revenue, too: Insights-driven firms are growing more than 30% annually and are on track to grow eight times faster than global GDP.
With these key industry trends and projections in mind, here are the top 3 reasons why leading SaaS providers need to put enhanced data access on their product roadmap to get ahead in the coming months:
#1 Streamline user data experiences, drive engagement
In today’s digital marketplace, user experience (UX) plays an important role in why customers choose to buy and, even more importantly, why they choose to continue using a product in their everyday workflows. Data-powered businesses rely on their software not only to get tasks done, but also to find meaningful data and discover insights, regardless of where they’re working from (or where they’re working within the software itself).
$$ Continuously enhancing UX in new ways increases retention and boosts LTV. Delivering experiences that delight users and provide new value leads to increased engagement and greater loyalty that drives revenue.
Read more: Going Beyond Digital Transformation in 2021
#2 Reduce manual reporting and intensive analytics processes, cut costs
From writing SQL to compiling reports and building custom dashboards, technical teams spend a lot of time in the data trenches trying to turn around usable data for their customers. Software providers looking to save time (and capital), and leverage their skilled technical team for higher-value tasks need to implement access-oriented functionality that enables customers to self-serve data processes like exploratory analysis and ad hoc reporting.
$$ SaaS teams that effectively solve this problem can save on expensive labor or reallocate that labor to developing other features and driving new value for users.
#3 Democratize data access for a broader range of user types, win net-new customers
One of the hurdles faced by even the most widely-adopted BI tools is that greater functionality and complexity often results in users having to achieve a higher degree of proficiency with the system before they can derive value from it. This prevents analytics tools from providing value for non-technical business users or those with lower data literacy, thereby narrowing the market for these products.
$$ With intuitive data access options, different types of users can get to their data, without needing to be power users or data experts. This allows software providers to vary the price of tiered offerings, or break into new markets with data access solutions that cater to broader classes of uses.