One of the more significant changes underway in organizations is the shift from a new customer sales focus as the main driver of growth to an equal emphasis on the overall customer experience as a driver of renewal and expansion. Driven by customer demand, more vendors are adopting alternate pricing and revenue models over and above the traditional one-time sales model. For selling organizations, these newer revenue models are being implemented through the addition of new products and services, by modifying existing models or by acquiring new revenue models through merger and acquisition (M&A) activity. We refer to this as the mixed revenue model, where both individual and bundled products and services can be priced or monetized as a flat fee subscription, based on usage, linked to a milestone event as well as the traditional one-time sale.
This growing adoption of these mixed revenue models leads to an increasing need to focus on customer retention to protect that portion of recurring revenue from subscription customers as well as to develop upsell and cross-sell opportunities. For many, the sales department is being superseded by the revenue department with responsibility for a super-set of traditional sales functions to include not only new business sales, but also to include existing customer retention, expansion, and cross-sell. An indicator of this shift has been the growth in the number of organizations adopting a Chief Revenue Officer (CRO) title.
The CRO will need to focus on both existing and new customers, and the increasing portion of revenue coming from digital and self-service channels as well. To aid in this shift, many organizations are evolving their sales and marketing operations teams towards a revenue operations team. This revenue operations team is responsible for supporting the need for these teams to be working in concert across the life cycle of the customer from lead, through engagement, sale and on through provisioning, adoption, renewal and expansion.
Whether these are separate or unified teams under revenue operations is not as important as having a shared common purpose and a standard way to set targets and measure
To drive these new organization and process changes, new metrics are necessary for individual teams that link back to the overall target and organizational objectives. Traditional deal metrics such as lead generation, sales stage progression, deal velocity, average deal size and pipeline management effectiveness do not go away, but they are complemented with an equal focus around customer health, churn propensity, and cross and upsell opportunity identification. It will be more important than ever that individual and team metrics and analytics are linked to overall corporate revenue objectives.
As marketing, sales and customer success have been viewed as separate, independent teams, metrics and analytics have also been defined based on a narrow view of these teams’ roles. As such, many organizations rely on either embedded analytics within supporting, operational applications or an inflexible and cumbersome Extraction, Transform and Load (ETL) data warehouse with custom-built dashboards and tools using general business intelligence tools. Viewing the entirety of the customer life cycle reveals the shortcomings of this approach. Dedicated applications form data silos and make it difficult to understand and analyze the processes that cross teams and enable an exceptional customer experience.
An additional area where existing, single-team applications can hinder better processes and understanding is revenue forecasting. As opposed to judgment-based sales forecasts, revenue forecasts should also include statistical and more advanced methods, such as machine learning (ML) to supplement the sales forecast. Judgment-based sales forecasts rely on data and information from opportunities, typically managed in a CRM. But revenue forecasts include all revenue types, and the needed data will be sourced not from one source, but from multiple source systems such as support and service, e-commerce, customer success, order management and finance.
The revenue forecast will deliver a more comprehensive set of data and with more granular precision. More comprehensive in that it covers not just new business, but renewals and expansions as well as self-service, e-commerce sales and those not tracked by the CRM as opportunities. And more granular in that the forecast will also have details about the mix of volume and value for product and services, often needed by the rest of the organization to plan for the allocation of resources. As in the example of the need for data that is sourced across teams and siloed applications, these more accurate and representative revenue forecasts are also dependent on data from a variety of different systems. And these forecasts and projections are also the key to monitoring progress towards planned-for objectives and to providing actionable feedback to alert leadership and management with enough forewarning to adjust and course correct. Revenue operations teams can also use analytics and performance measurement to identify steps in the process that are impeding the overall objectives so that processes can be continuously fine-tuned, especially in the face of new market entrants, increased competition or market changes.
These more complex needs require data to be utilized across a variety of source systems—including CRMs, customer service and success, finance, billing, and subscription management—that entail alignment and normalization as well as attention to aspects such as data latency. To successfully undertake a shift to the revenue operations approach, it will not be enough to change titles and create new responsibilities. Organizations must make a serious effort to ensure relevant and timely data is made available to support these endeavors.