Creating a Unified RevOps System | Evan Dunn, Director of Growth Marketing at Syncari

B2B organisations track two connected realities: conversations with people and commercial relationships with companies. A sale can involve revenue operations, data, IT, finance, procurement and legal stakeholders, while the company receives the invoice. Systems must represent contacts, accounts, meetings and qualification stages.

Legacy CRM structures add difficulty. Salesforce separates lead, contact and account objects, but leads do not attach to true company entities until conversion. This structure created demand for lead-to-account matching software. As demand generation and ABM moved towards company lists, the model conflicted with team workflows.

Company attributes shape buying behaviour. Dunn contrasts ten-person companies with little procurement, hundred-person companies with emerging processes and thousand-person companies with stricter ones. For ABM teams, the company—not an isolated lead—is the natural unit for segmentation, targeting and planning.

Teams need reliable account information across systems. Even company domains must be accurate, deduplicated, merged and unified. Marketers can then build campaigns, while sales teams create Sales Navigator lists for intended segments. Without dependable account data, target lists can look coherent while activation systems contain conflicting or duplicate records.

Early-stage founders or marketers should capture enough data to reveal where experiments fail. Fast learning matters more than broad averages. Overall conversion rates or total customer acquisition cost can help boards but not identify narrow segments supporting a healthy business. Teams should track core segments throughout the customer journey.

A company size within one industry can have low acquisition costs but low lifetime value. That can produce short-term growth without a durable customer base. Dunn suggests identifying segments with the desired lifetime value, then working backwards to improve acquisition cost. Systems must preserve attributes that distinguish segments and track their behaviour over time.

Analytical data supports periodic evaluation, such as a monthly executive dashboard review. Operational data supports daily action. It helps marketers select companies, salespeople build relevant lists and customer success managers protect or expand relationships.

A warehouse can consolidate information for business intelligence without repairing source applications. If CRM, marketing automation and customer success tools remain inconsistent, a clean dashboard offers little help during execution. Dunn argues that relevant attributes should span these systems. Teams can then use consistent segmentation and establish feedback loops throughout the customer journey.

When operational systems lack useful information, teams often share anecdotal updates in Slack. A salesperson can compare one company with another, but one or two conversations provide weak signals. Dunn says teams need ten, twenty or a hundred conversations before building a business case. They should capture insights in forms suitable for segmentation, comparison and testing.

Fragmented tools also burden frontline staff. Dunn describes a customer success team consulting Zendesk, an internal tool, Slack, a Google Sheet and Salesforce for one ticket. Work taking five minutes can consume an hour, degrading the customer experience.

Executives must recognise the problem because frontline staff focus on their roles, not data infrastructure. Giving sales teams ten, twenty or thirty tools does not ensure support. Each login, meeting and enrichment process takes time from research, outreach or customer work.

RevOps or go-to-market teams must show leaders how poor data and fragmented systems slow execution. Cultural resistance can include blaming users instead of infrastructure. Dunn asks leaders to imagine people finding necessary context in one core tool. Specialists can still require multiple platforms, but first-party customer data should not remain fragmented across them.

First, map the customer experience from end to end. Whether called a customer journey or full-funnel bow tie, the map should show the customer lifecycle. RevOps can translate it into a data model covering contacts, companies, opportunities or deals, tickets and billing accounts.

Teams should then define each entity’s fields and their use across applications. The strategic question is what model accurately reflects the customer journey, not how to accommodate current tool limitations. RevOps should govern systems instead of letting default schemas govern strategy. Teams can then create an implementation plan and secure support from IT and data teams.

An early win is deduplicating and merging account and contact data across connected systems. Dunn says teams in messy environments can stop taking notes because they distrust where information belongs. Clean records can restore confidence, improve usability and reduce manual CRM cleansing.

RevOps practitioners should also study data modelling, architecture and strategy, not only dashboards and integrations. Dunn recommends practitioners Rosalyn Santa Elena and Jeff Q, plus communities such as MO Pros and RevOps Co-op. He advises assessing vendor narratives carefully. A warehouse, dashboard or integration does not form a full strategy if it neglects operational systems or data quality.