While the startup world listened for better news in the aftermath of a volatile 2022, a new salvo of bad news emerged: global venture capital funding declined about 49% within the first six months of 2023 alone. Worsening inflation and rising interest rates are putting pressure on startups across all stages of venture funding to reframe their tech stacks or business models along the tech-scape’s collapsing edges.
The hurdle startups now face, however, isn’t how to stop the economic storm—it’s how to navigate it. Adapting to challenges is now the most valuable skill for startups in the evolving business environment. As technological landscapes shift, startups are seeing new paradigms emerge that hold enormous potential for future growth. Here are five trends that startups should keep an eye on in the months ahead.
1. The growing role of data science in the modern business
Today’s businesses are facing an unprecedented expansion of unstructured data that can permeate every department in an organization. The sheer quantity and growth of data in recent years essentially requires efficient predictive analysis to have any material value for growing businesses. As a result, data science has become the darling of every corporate department, from software engineering to marketing to finance, and they’re all clamoring for easier data access and better analytics. Startups feel this pressure keenly, as their lean teams need consistent, constant and up-to-the minute data to stay agile and respond to changing market and competitive conditions.
It’s difficult to extract and classify data from thousands of PDFs and images, not to mention the burden of quality management and data cataloging. The profuse amount of unstructured data begs the assistance of LLMs and generative AI (gen AI) to enhance productivity, whether in deriving analytic insights or making data pools more functional. It can also help automate manual or repetitive coding for developers working in already labyrinthine code bases.
The question for modern organizations, then, is no longer whether they should integrate gen AI and LLMs into their tech stacks to help make sense of all this data, but rather an urgent how and where. To get the answers to these questions and learn about incorporating AI and LLM into your solutions, check out Snowflake’s Data Cloud Academy for Generative AI & LLMs.
2. Data-driven apps and their place within the changing SaaS-scape
Data doesn’t merely fill your repositories, it also contextualizes or illuminates new avenues for development within SaaS solution spaces. Commercial SaaS offerings, for example, are not always a good fit for startups. Designed for general purposes, they present gaps when more specific needs arise. Perhaps Google Workspace’s calendar feature falls short of your organization’s complex scheduling demands. Or maybe a file-sharing application that would solve your team’s specific needs doesn’t yet exist.
Cloud data platforms enable organizations to develop their own monetizable solutions with the help of powerful yet simple development environments. The Powered by Snowflake Startup Program can help startups natively launch their data-intensive applications in the Data Cloud.
3. The increasing popularity of consumption-based pricing
Consumption-based pricing is arguably the most appealing business model for startups, because they can benefit in two ways:
- As consumers, they can minimize their costs for using a certain SaaS service.
- As businesses, they can streamline the sales cycle and improve customer satisfaction.
Startups generally enjoy more flexibility from vendors that offer pay-as-you-go pricing than they do from those with subscription-based services. They can scale their expenses up or down according to actual usage rather than paying upfront and worrying about wasting money when the service is not needed.
Likewise, startups that set their own consumption-based pricing models achieve a similar result: their customers have a real incentive to actually try the service without the risk of incurring significant overhead. If the service falls short of their expectations, they pay only for what they used—but if it’s a great fit, it’s simple to scale usage up to meet business needs.
And so it isn’t surprising that the adoption of consumption-based pricing has nearly doubled within B2B SaaS in the past five years, and reflected the pricing models of approximately 46% of the general SaaS index in 2022. Consumption-based pricing is becoming a preferred pricing model through which startups can effectively sell their own services. To further explore how it can fit into your business’ pricing strategy, Snowflake provides a helpful guide for startups to leverage consumption-based pricing.
4. The expansion of product-led growth as a business model
Consumption-based pricing is just one component of a larger, consumer-facing business model. Product-led growth (PLG), which OpenView Partners describes as a “democratization” of software buying power, is really just a model where the product itself—rather than sales or marketing initiatives—drives user acquisition, retention and growth. The user tries the product, keeps using it and eventually upgrades to a paid subscription.
Think Slack or Calendly: these kinds of products are attractive to users, many of whom want accessible interfaces and “try before you buy” opportunities without the nuisance of sales interactions. From a user-based perspective, it’s fast. You skip the middleman (the sales rep, for example) and simply register for the product. From a startup and entrepreneurial perspective, you avoid incurring any marketing or sales overhead, and are instead free to focus on developing the product. To learn more about product-led growth strategies and how to successfully implement them at your startup, watch Snowflake’s webinar with PLG experts from two venture capitalist firms.
5. The advantages of modern cloud-native applications
Because traditional enterprise applications lack scalability and suffer from inefficient batch development, they can be sluggish, stiff and monolithic. Modern cloud-native approaches expedite enterprise application development into more agile processes and discrete microservices or containers—all while using minimal computing resources. The added advantage of built-in automated building, testing and deployment in cloud-native applications makes cloud-native development not only a much more developer-friendly approach in comparison to traditional development, but also a faster and more manageable process.
What all this means for startups
New developments in gen AI and the unprecedented growth of data are technological paradigm shifts reshaping the tech ecosystem. As startups navigate recessionary bumps in the road, these five trends can guide startup leaders toward more efficient and accessible means of development and marketing.
Generative AI and LLMs are among the leading generators of business growth in the SaaS solution-scape; data-driven apps and cloud-native development are disrupting the app dev status quo; product-led growth and consumption-based pricing are inspiring companies to try new approaches to growing and keeping their customer base. Adopting some or all of these new technologies can help your startup hone its competitive advantage and flourish in the ever-evolving tech market.