How These 4 Bay Area SaaS Companies Are Taking Over Enterprise Operations

Once a niche corner of the wider tech market, software platforms are now taking over tech. Late last year, Gartner predicted that the public cloud services market would grow by 17 percent in 2020 to a total of $266.4 billion. While it’s unclear how the pandemic may have affected those figures, larger companies continue to follow small and medium-sized businesses into the cloud.

There, enterprises are finding that real-time collaboration, data sharing and visualization, automation, and other benefits of cloud-based business operations come with a few requirements. These include new security practices, an elevated standard for business forecasting, customer support that utilizes the full capacity of modern technology, and an ability to wring all possible value from CRM software. And each of those requirements can be covered by a separate SaaS platform.

A survey of a handful of Bay Area-based companies shows an industry that is quickly growing into new fields across the economy. 

Security Monitoring vs. Performance Monitoring

As business operations have migrated to SaaS platforms, a new breed of performance monitoring solutions has emerged to track how systems function across multiple applications and third-party vendors. For some, performance monitoring doubled as a security tool, highlighting irregular behavior that could belie the presence of an intruder within a system.  Think additional connections to a command-and-control server, or the appearance of new identity and access management credentials.

However, cyberattackers have learned to infiltrate business systems without tripping the kind of metrics a performance management solution might be looking out for. And for enterprise organizations running millions of API calls or billions of transmission control protocol connections per hour, a few hundred extra events here and there might sneak through unnoticed.

Even when one of these connections happens from a new application...we will find it.”

In response, companies like San Jose-based Lacework are building platforms based around security monitoring systems. The idea here is to build behavioral models for each application — Lacework calls them Polygraphs. Over time, they create behavior models for a business’ users, applications, services, containers, images, pods and so on, allowing IT admins to track activity and understand their systems in depth.

“It does not matter how many of these processes or containers run over different virtual machines, in different data centers or how many different S3 IP addresses they talk to over different client ports,” co-founder and CTO Vikram Kapoor wrote in a recent blog post explaining the technology. “The behavior models remain stable. This gives us low false positives, but still excellent detection capabilities. Even when one of these connections happens from a new application...we will find it.”

Customer Support Gets Its Own Digital Transformation

While consumer-facing businesses across industries have invested heavily in technology across product, marketing, sales and other departments, customer support tends to lag behind. Support teams are often stuck with disparate tools and platforms communicating through old APIs, creating a frustrating experience for both employees and customers.

Companies like San Francisco-based UJET see opportunity in this discrepancy between a technologically impoverished customer support team and other facets of a business. The company has built a cloud-based support platform using multiple voice, messaging and mobile features to help agents handle requests. With the shift to remote work in recent months, UJET has seen demand surge, channelling customer support through an internet browser rather than a physical call center.

The customer support industry has traditionally not been as quick to adopt modern technologies as other industries.”

In a recent blog post, Founder and CEO Anand Janefalkar wrote that UJET’s experience helping customers like Instacart and Google Nest uniquely positioned the company to scale its operations over the last several months.

“The customer support industry has traditionally not been as quick to adopt modern technologies as other industries, thinking that the investment wasn’t immediately necessary,” he wrote. “Now that consumers fully engage in digital-first experiences, modern customer support won’t survive within the walls of a physical contact center.”

Planning Software Needs A Rethink

Business planning and revenue forecasting models traditionally draw conclusions based on historical data, assuming some level of ambient growth across the market. However, the coronavirus pandemic has upended that fundamental assumption, and many organizations now find themselves flying blind into a potentially volatile future.

For Evan Quasney, who serves as VP of global supply chain solutions at San Francisco-based Anaplan, this transition didn’t necessarily come out of the blue. Rather, he argues it has simply accelerated an underlying trend away from using historical data as the source of all truth in a forecasting model. Quasney’s team had been tracking this for years and forecasting, he says, must now complement historical data with other, less traditional forms of information. Anaplan’s software plugs into data systems across enterprises and the wider world — from market performance to social media trends and even pollen count — to help finance, HR, IT, sales and marketing teams plan ahead. Built on a calculation engine called Hyperblock, Anaplan’s forecasting platform works on the assumption that the modern enterprise no longer comprises a collection of autonomous units, but operates as a unified organization that functions on timely data delivery.

While historical signals will always maintain some level of utility, market-based forecasting instead incorporates many input signals to create a robust, multi-faceted picture.”

“As we look at where we’re going now, it’s critical for companies to assess not only their forecasting process, but also the external market forces that drive demand,” Quasney wrote in a May blog post. 

“Combining the process [with] internal and external data in a modeling platform gives the insights necessary to better understand where the market is going and how to respond with maximum profitability and service,” Quasney wrote. “While historical signals will always maintain some level of utility, market-based forecasting minimizes historical data as the overriding signal and instead incorporates many input signals to create a robust, multi-faceted picture to sense demand over multiple horizons—short-term through long-term.”

CRMs Rule Everything Around Me

A SaaS platform that provides a single place to input, organize and draw data for every function has become a central pillar of business operations over the last decade. Salesforce is the most obvious example, with a platform that now supports hundreds of thousands of businesses.

However, a one-size-fits-all CRM solution doesn’t quite meet the need of larger organizations, and so companies like Vlocity have emerged to fill the gap. The company, which was acquired by Salesforce in February, builds six industry-specific customer relationship management platforms for the communications, media and entertainment, energy and utilities, insurance, government and health industries. These all run on top of the Salesforce platform, with readymade platforms to support everything from governmental health and human services programs to insurance claims management.

In a blog post, Vlocity’s VP and GM of Media and Entertainment Christopher Dean wrote that his company “provides industry-specific customer consoles that integrate every facet of a customer’s interaction journey, product and service ownership, order status, social relationships, churn propensity and other variables designed to help employees instantly understand who they are interacting with and how to best add value to the relationship.”

Digital leaders know that a digitally-enabled front office is, by itself, insufficient to achieve real digital success—it is just one, albeit very necessary, piece of the puzzle.”

Process automation, process optimization through machine learning and data visualization are all key tenets of this ongoing digital transformation in his industry, Dean wrote.

“Digital leaders know that a digitally-enabled front office is, by itself, insufficient to achieve real digital success—it is just one, albeit very necessary, piece of the puzzle. To avoid becoming a DINO-saur (Digital-In-Name Only), companies must execute end-to-end transformations to fulfill the promise of the digital enterprise, while also working tirelessly to change the collective mindset and bring forth a transformative digital culture.”