Is RevOps ripe for Observability?
The RevOps model has allowed B2B SaaS companies to drive the mandate of full-funnel accountability. However, many questions that RevOps teams ask remain unanswered. It can greatly benefit from an observability layer to enable end-to-end visibility, insights, and collaboration.
The Observability Explosion
Observability has seen an explosion in the DataOps, IT, and CloudOps space. Companies like Datadog, New Relic, Splunk, and Dynatrace have been leading this trend and helping expand the applications of Observability.
Observability is the ability to measure the system's current state by examining its outputs. The term originated in the academic world of "control theory" and is now used extensively in the context of highly dynamic and distributed systems that exhibit a combination of scale and complexity, and where it becomes difficult to track and trace the root causes of issues of system performance.
The most practical definition of Observability is that it goes beyond routine monitoring to encapsulate three essential aspects:
- Metrics: Measurement of key aggregate or granular metrics of system behavior over some time
- Logs: Records of activities/events that have occurred at specific periods along with associated contextual information surrounding the event or activity
- Traces: Tracks the end to end journey of a process, request, or transaction as it moves thru a distributed system to drive better analysis of the sequence of activities, nodes
Although Observability has seen applications in data and technology systems, its application to business systems and processes has been slow to evolve.
One would expect that operationally-intensive, fast-moving businesses with distributed and interdependent activities would benefit from Observability. In fact, there has been an associated trend around supply chain visibility and real-time tracking in the supply chain and logistics world. However, most efforts toward business observability are limited to spreadsheets and BI dashboards.
Revenue Operations in B2B SaaS
The Revenue Funnel is a Dynamic & Distributed Operation
The revenue funnel consists of marketing bringing in visitors, nurturing them into leads and marketing qualified leads, and handing it off to the SDR teams. SDRs pick up the MQLs, work on the prospects to see if they can be sales qualified (SQL), and turn them into opportunities along with the Sales team. The Sales team then picks these opportunities and nurtures them through the different pipeline stages toward conversion. Once converted, the Customer Success teams take it over to drive adoption, expansion, and retention.
As the GTM teams drive this revenue funnel, customers/buyers are going thru their journey from Research, Consideration, Trial, Evaluation, Purchase, and Fan/Referral.
Between the revenue funnel and the buyer journey occur complex, high-speed, high-volume interactions (emails, marketing campaigns, SDR outreach, trials and evaluations, and AE conversations). And if you have a business across multiple products, regions, and channels, the complexity accentuates.
Heterogenous and Disparate Systems Across the Funnel
As teams scale their GTM Operations and motions, they invest in SaaS tools across the Revenue Funnel. Even a Series A B2B SaaS company could be using 15-30 SaaS tools across the revenue funnel, including CRM, Marketing Automation, Buyer Intelligence, Forecasting, Planning, Billing & Accounting, Customer Success, etc.
The systems don't necessarily talk to each other out of the box, and special integration efforts are needed to extract data from these systems into a typical data lake.
While each tool enables and optimizes certain aspects of the revenue funnel, it adds to the problem of low visibility across the revenue funnel due to disparate data and disparate intelligence.
"Just in the sales and revenue org (CSM, pre-sales, etc.) – 45 to 50 tools ex marketing (CRM, commission, prospecting tools, etc. ). Marketing has its tools (all are SaaS tools). Trying to figure out how to simplify, yet as we scale, we don't have a system with the entire customer journey. Data about prospecting, sales, and after-sales are all in different tools. That is a primary problem that we are trying to solve.
Program Manager, Revenue Operations, ~$40M SaaS Company.
Human Collaboration Friction and Context Leakage
At the intersection of the revenue funnel and buyer journey, there are multiple touchpoints and hand-offs across teams with various points of failure.
As each team scales, so does the operations aspect across SalesOps, MarketingOps, and Customer Success Ops. And they start investing in their processes, systems, and tools. Naturally, one starts seeing silo behavior and the proverbial leaky funnel problem, with mixed messages across the revenue funnel, unqualified leads, dropped leads, context leakage, missed opportunities, and renewals.
"Customer information is not transferred from one function to the next. I work with the SDR team. I often find SDRs making calls without necessarily understanding what the customer did on the website. When the opportunity transfers to the AEs, they also start from scratch."
– Program Manager, Revenue Operations, $300M SaaS Company.
Visibility remains a problem despite best efforts
B2B SaaS RevOps companies have made tremendous progress in maximizing the revenue funnel. A key aspect of RevOps is to drive better alignment on processes, metrics, and hand-offs.
RevOps teams spend much time orchestrating tools and becoming the single source of truth and integrated insights along the funnel.
However, due to the complexity of the revenue funnel operation, disparate tools, and human collaboration friction, they face difficulties in driving end-to-end visibility.
Marketing does not have a clear view of what happened to the leads after they were handed off to SDRs and the AE team, while the SDR team usually picks up leads without detailed context into the behavior and interest displayed.
RevOps teams try a mix of in-house, time-consuming, unsustainable, and band-aid efforts.
"Data & Analytics…growing very fast…all systems are playing catchup, we decided to do the hard work and create our data warehouse and reporting on top…however it is very difficult to design systems looking forward, don't know what kind of sales motions will scale up in the next three years. So, on the whole, playing catch up"
– Director of Revenue Operations, $300M SaaS Company.
BI tools don't cut it since they are limited to aggregate and mostly outcome metrics and trends rather than being able to drill down into the most granular level activities.
"We have invested in a Snowflake data warehouse to bring all the data into one place and create dashboards using Power BI. However, we have the basic dashboards, but for the second level and detailed analysis, we still spend much manual time putting datasets together"
– Director of Revenue Operations, $300M SaaS Company.
The CRM as a single source of truth remains a myth, and existing Revenue Intelligence tools are limited to only certain aspects, either the Marketing, Sales, or Customer Success.
Problems beyond visibility
The problems don't stop at visibility. Of course, visibility is the first aspect; however, to truly drive more effective RevOps, teams need to track and trace the journey of the leads from the source to the conversion and beyond.
Much of the aspect of driving predictable revenue growth is impacted by how fast leads move closer to a purchase. Therefore, it is about getting insights into what granular activities and messages help maximize stage-to-stage conversions of the buyer aligned to the overall customer journey.
"It is not just visibility that we need. What is needed is understanding of what each function should do to move the customer closer to a purchase…take an example of a prospect downloading a white-paper for one product…but my company is a company of multiple products…all functions need to be alerted to the interest of the prospect…but is the SDR incentivized on that?……if there is an SQL that dropped ..we still don't know what went wrong…what did this customer want…did the touch point happen…how many touch points …in how much time….we are unable to track the customer… that's also because if it happens over one month…website- -> download -> three people might have reached out to them…with similar or dissimilar conversations with …and then what happened in that one month….. have I really moved the customer from interest to purchase?"
– Lead Program Manager, RevOps, $300M SaaS Company.
RevOps is ripe for Observability
The RevOps operating model has made it possible for B2B SaaS companies to drive the mandate of full-funnel accountability and reduce the friction in the revenue funnel across Marketing, Sales, and Customer Success.
According to Gartner, 75% of the Highest Growth Companies in the World Will Deploy a RevOps Model by 2025.
Further Gartner defines the three attributes of the RevOps model as
- The process design is end-to-end and supports the entire customer life cycle.
- It is interconnected with seamless workflows across integrated systems, data, and functions.
- It is observable by providing visibility into execution and outcomes across the revenue process.
New tools are needed to maximize this movement with the realization that:
- The revenue funnel is a complex, dynamic, distributed operation
- Heterogeneous and disparate systems lead to low visibility
- Distributed teams add to the friction and context leakage
As adoption of the RevOps model grows in B2B SaaS and beyond, the third attribute of “observability” will grow in importance. Without it, the potential of RevOps remains unfulfilled.
Several Revenue Intelligence tools have emerged to optimize certain aspects, but they do so in a siloed approach.
RevOps teams and their stakeholders have many questions unanswered due to the sheer inability to stitch together the different aspects of the Revenue Funnel.
We feel that RevOps needs an observability layer that can enable end-to-end visibility across the funnel, tracing the lead's journey from source to revenue conversion and beyond, and help correlate the most granular activities to the aggregate metrics and outcomes.
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