These days, marketing technology (MarTech) companies are white-hot. No one can deny the incredible opportunity these startups have presented for venture capitalists. The value of these applications is the ability to enable marketing teams to identify prospects more quickly and convert them into qualified leads for sales more effectively.
And venture capitalists have responded by investing more than $21 billion into the category, according to recent reports. Furthermore, over the past several years, MarTech companies have had several significant IPOs (e.g. Marketo, HubSpot) and acquisitions (e.g. Eloqua, Pardot).
While people are marveling at the rapid adoption of MarTech and its fundamental impact on how companies of all sizes acquire revenue, there is an even bigger revolution underway in enterprise software applications.
This new category of enterprise applications builds on the success of transactional customer relationship management (CRM) systems, and consists of enterprise applications targeting revenue. We’ve coined the term “RevTech” to define the emerging category of these revenue-centric technologies.
RevTech applications use the transactional data captured by CRM systems to generate predictive guidance at the moment of value: the precise instant when a decision needs to be made by an individual, manager or executive.
RevTech enterprise application software converts subjective data (e.g. a sales forecast based on a sales representative’s best guess as to which deals will close in a quarter) into objective data (e.g. a sales representative’s forecast based on machine-learning algorithms that have scored and weighted each opportunity in the pipeline to determine which are more likely to close in a quarter). This enables companies to optimize revenue across their entire revenue supply chain — another term we created to describe how we thought about the creation of revenue.
The idea behind the revenue supply chain comes from the traditional supply-chain concept, in which discrete materials and components are converted into finished goods. Creating revenue works similarly. In nearly all businesses, whether large, small, business-to-business (B2B) or business-to-consumer (B2C), revenue is generated through a series of discrete steps, actions and resources.
A revenue supply chain consists of the following segments — and they require increasingly larger investments of time and resources by a company:
- Advertising. This is the part of the revenue supply chain where people are still unknown to the company. The objective is to get people to raise their virtual hands with an ad that piques their interest. This is typically the most expensive part of a B2C business model.
- Marketing. In this stage, people have identified some aspects of themselves and indicated potential interest, but the company may still have very limited information about them.
- Sales. By the time a prospect reaches this stage, companies know a lot about them. This is typically the most expensive part of a B2B and B2B2C business model.
- Support/Service/Customer Success. These are now customers who need to be kept satisfied to maximize their lifetime value.
The objective is to move the prospective customer across the revenue supply chain as cost-effectively and as quickly as possible. The total cost of acquisition should be significantly less than the lifetime value of that customer.
This is why companies that use a recurring revenue business model must carefully monitor and manage their revenue supply chains.
Key metrics include: Customer Acquisition Cost (CAC) ratios, Customer Lifetime Value (CLTV) and a new SaaS metric, the Customer Retention Cost (CRC) ratio, developed in conjunction with one of our portfolio companies, Totango.
We’ve had our eyes on a few RevTech companies that are leading the charge in modernizing the revenue supply chain:
- Clearslide, a sales engagement platform;
- Fliptop, which provides predictive applications for marketing and sales;
- InsideSales, which offers a sales acceleration platform;
- Infer, which builds personalized predictive models tailored to potential customers;
- Clari, which uses data science and predictive analytics to help sales people do their jobs; and,
- C9, a revenue forecasting application that uses big data and machine learning.
Each of these providers are enabling companies to better engage and understand their prospects and customers in order to drive, optimize, predict, and secure revenue.
For example, C9, an InterWest portfolio company, ingests transactional data generated by Marketo and Salesforce and uses its machine learning algorithms to help companies predict which deals will and will not close — on the first day of a sales period.
After two to three sales cycles, their algorithms can determine which sales reps will and will not achieve their forecast with better than 80 percent levels of accuracy.
Some key trends in technology are driving RevTech’s revolution of the revenue supply chain, including the adoption of mobile devices, the use of real-time analytics, and the growth of collaborative computing.
Mobile. Brands and e-commerce companies are just now moving to mobile and are at the early stages of learning how to successfully engage with prospects and customers at precisely the right moment in time, location and context.
It is now possible for manufacturers to target customers directly while they shop, thanks to micro-geolocation technology. For instance, a company that makes diapers could send a message directly to its loyalty program customers offering them 20 percent off diapers just as they pass the baby section.
Predictive, Real-time Analytics. These are the next generation of business analytics that use transactional data and machine learning to automatically drive predictive and personalized customer relationships in real-time. As an example, Marketo and NCR Corporation are both leveraging C9’s solution to identify opportunities that have the highest likelihood of closing in the quarter based on previously closed deals.
C9 does this by automatically identifying which past deals have followed a similar path as a salesperson’s current deals, using algorithms running in real-time in the background against billions of sales opportunity transactions. The system scores thousands of deal attributes and provides feedback based on real data rather than the salesperson’s best guess.
Collaborative Computing. New, data-driven, front-office applications that are process-oriented: forecasting, support, etc. These applications are designed to enable teams to execute their jobs faster and with higher quality. They contain pre-built and functionally specific analytics, workflow, workgroup organization, scheduling and reporting.
Using Opal Labs, for example, marketers such as Nike can now quickly set up in-house and agency teams around a project. They can share schedules, due dates, and deliverables all within a single application — anywhere, anytime using mobile devices. Global campaigns can be quickly executed across hundreds of countries with legal sign-off, localization, and timed delivery, thus, dramatically reducing the time-to-delivery for critical ad campaigns.
IDC estimates the overall SaaS market will reach $50.8 billion by 2018 and that the SaaS CRM market will be $31.8 billion.
However, CRM applications don’t help individuals make better business decisions. RevTech applications, on the other hand, are designed to deliver business insights and guidance in real-time, providing greater value than transactional CRM solutions alone. For this reason, we are forecasting the RevTech market to eventually equal or exceed the size of the existing CRM market.
Since we are still in the very early stages of the market, we believe RevTech growth rates could easily double CRM market growth rates over the next five to ten years. And we don’t think the market opportunity built on data-driven applications supported by machine-based learning stops here.
The “next” next big thing
Right behind RevTech, we are beginning to see the emergence of another disruptive class of data-driven applications, which we’ve labeled “EmpTech,” or Employee Technologies. These enterprise back-office applications enable companies to optimize their talent supply chains. We believe they will forever change the way we manage human resource capital.
Just as RevTech is commoditizing CRM, we believe EmpTech will commoditize human capital management (HCM), enterprise resource planning (ERP), enterprise performance management (EPM), and sales and operations planning (S&OP).
VoloMetrix, a people analytics technology company, is an example of how EmpTech companies can apply big data to optimize activities and relationships within an organization. By extracting and analyzing aggregated and anonymous data from corporate communications systems, VoloMetrix creates measurable behavioral profiles around a company’s everyday processes to provide insight into the real costs and return on activities such as sales calls, customer service operations, brainstorming sessions and weekly update meetings. And it does all of this without compromising employee privacy.
Another company, Entelo, is leveraging big data, predictive analytics and social signals to help recruiting organizations find, qualify and engage with in-demand talent. Its suite of products includes a search algorithm, an intelligent candidate recommendation engine, a cross-platform browser extension, and an email analytics and tracking tool built exclusively for recruiters.
EmpTech applications share some similarities with RevTech. They’re mobile first or best, predictive, real-time and collaborative. EmpTech applications will enable companies to acquire employees more cost-effectively, and once on board, enable them to collaborate easier to dramatically improve overall productivity.
Employee Acquisition Costs, Employee Productivity Rate, Employee Churn, and Employee Retention Costs will emerge as key metrics for companies to monitor and measure the health of their operations.
Together, RevTech and EmpTech applications are revolutionizing the productivity and performance of workers, executives and enterprises just as the assembly line revolutionized productivity more than a century ago when Ransom Olds invented it.