In the fall of 2024, a growing B2B SaaS company headquartered in the Northeast reached out to Vivify with a challenge that we hear regularly: their legacy Salesforce instance was bloated, poorly configured, and their sales team actively resisted using it. The company had 20 salespeople, including 12 full cycle Account Executives, 4 Sales Development Representatives, and 4 Sales Directors. They covered three geographies and had aggressive revenue targets that seemed increasingly difficult to hit with their current infrastructure.

The problem was not their people. It was their systems. Over the next six months, Vivify worked with this organization to completely rebuild their revenue operations, their technology stack, and their sales methodology. The results speak for themselves: pipeline velocity improved 34 percent, rep quota attainment moved from 62 percent to 84 percent, and average deal size increased by 19 percent.

When we arrived for our initial assessment, the company had been running Salesforce for six years. The system had grown organically, accumulated technical debt, and become a source of frustration for the sales team. Reps were spending 90 minutes a week on manual data entry. Forecasting was inaccurate because the data in Salesforce did not match reality. And there was no integration between the CRM and the prospecting tools they were using, which meant every lead had to be manually created in Salesforce after being sourced elsewhere.

They were also running on Microsoft Office for productivity. While robust, the Microsoft ecosystem was not well suited to the kind of collaborative, real time work that modern SaaS sales teams need. Docs lived in multiple places. Spreadsheets existed in email inboxes rather than a central repository. There was no single source of truth.

For prospecting, they were using three different tools: LinkedIn Sales Navigator, Hunter.io, and a basic list building tool. Each tool operated independently. Once a prospect was identified, a sales development representative had to manually move that information into Salesforce, and the pipeline of prospects was invisible to the broader team.

HubSpot became the central nervous system. Every prospect, lead, account, and opportunity flows through HubSpot. We configured it to match the company’s actual sales process, not a generic template. We mapped their five stage sales cycle into custom HubSpot pipelines and built custom properties for information that mattered to this particular SaaS business: contract value, use case, industry vertical, champion contact, and implementation timeline.

HubSpot also became the engine for all workflow automation. Leads from inbound marketing were automatically created in the system. Certain prospect behaviors like website visits, email opens, and demo requests triggered workflows that either auto assigned the prospect to an SDR or escalated the opportunity to an Account Executive.

We integrated ZoomInfo into HubSpot as the engine for company research and prospect identification. ZoomInfo’s database of B2B contacts is the most comprehensive available for the markets this company served, spanning fintech, adtech, and SaaS. When an SDR does account research, they no longer hunt across multiple tools. They log into HubSpot, search for a company, and ZoomInfo integration returns contact information, organizational data, job changes, and funding intelligence. This single integration eliminated hours of prospecting busywork per week.

We implemented Clay as a supplementary prospecting tool for campaigns that required highly targeted list building across multiple data sources. Clay integrates with HubSpot, so SDRs could build a sophisticated prospect list in Clay, validate it, and then sync it directly into HubSpot. This was particularly valuable for vertical specific campaigns targeting fintech companies with 50 to 200 employees in specific geographies that recently raised Series A funding.

We implemented Asana as the central hub for all cross functional work, including sales operations projects, implementation timelines, and internal initiatives. While HubSpot owned customer and opportunity data, Asana owned project workflows and accountability. This created a clean separation of concerns.

The company migrated entirely to Google Workspace. Gmail replaced Outlook. Google Docs and Sheets replaced Word and Excel. Google Drive became the central repository for all files. We configured Gemini Pro as an embedded AI assistant across the entire ecosystem. Sales reps used Gemini to generate personalized prospecting emails, summarize lengthy customer conversations, draft follow up proposals incorporating data from HubSpot, and analyze competitive positioning documents.

We implemented Gong, which records, transcribes, and analyzes all sales conversations across calls and video meetings. Gong integrates directly with HubSpot, so every call is logged to the opportunity record automatically.

The real value comes from Gong’s AI analysis. The platform identifies which sales conversations included specific talk tracks, which ones mentioned pricing, which ones touched on specific pain points, and which ones ended with clear next steps. Over time, this data reveals patterns: which talk tracks result in the highest close rates, which reps are most effective, and which customer profiles are most likely to advance. We use Gong data for two things: live coaching where managers observe calls and provide real time feedback, and training where the sales leadership team reviews winning calls and extracts best practices for the entire SaaS sales enablement program.

Six months post launch, the numbers told the story across every metric that matters for a B2B SaaS sales organization.

Pipeline velocity improved 34 percent. The average time from first touch to opportunity creation dropped from 34 days to 22 days, primarily because SDRs had better tools for prospecting and qualification.

Rep quota attainment moved from 62 percent to 84 percent. This came from a combination of better methodology execution, better pipeline management, and reps spending less time on administrative work and more time selling.

Average deal size increased 19 percent. We believe this was driven by MEDDIC discipline. Reps who properly identified the economic buyer and mapped the decision process were more likely to uncover the full scope of the opportunity.

Sales cycle length decreased from 87 days to 71 days. Faster qualification, better discovery, and better deal management all contributed.

Time spent on non selling activities dropped by approximately 40 percent. Automation and integration eliminated most of the manual data entry and tool switching that had previously consumed sales time.

Forecast accuracy improved significantly. Because the data in HubSpot was cleaner and more consistent, leadership could rely on the forecast without needing side spreadsheets and manual adjustments.