Hubs

Company Background

Hubs, a subsidiary of Protolabs (NYSE: PRLB), is an online manufacturing platform founded in 2013 and headquartered in Amsterdam, Netherlands. With 200-1,000 employees and approximately $25M in revenue, Hubs connects engineers and procurement teams with a global network of manufacturing partners for CNC machining, 3D printing, injection molding, and sheet metal fabrication. The platform streamlines the process of sourcing custom parts — from instant quoting through quality inspection and delivery — serving companies ranging from startups prototyping their first product to Fortune 500 enterprises managing complex supply chains.

Hubs' go-to-market strategy includes a strong outbound component. Their BDR team prospects engineering leaders, procurement managers, and manufacturing directors at companies that need custom parts — a technical audience that demands specificity and relevance in sales outreach. A generic "let us help with your manufacturing needs" email will not resonate with a mechanical engineer who has already evaluated multiple suppliers. The outreach needs to reference something specific: a product launch that implies new part requirements, a supply chain consolidation initiative, a hiring surge in the engineering team, or a technology shift that creates manufacturing complexity.

The Challenge

Hubs' BDR team faced four interconnected obstacles that were suppressing their outbound pipeline. Each problem compounded the others, creating a cycle that could not be broken through hiring alone.

Personalization quality was not meeting the bar. Hubs' buyers are technical professionals who can immediately distinguish between a genuinely researched email and one that swaps in a company name and job title. The BDR team struggled to consistently produce emails that felt personalized to each prospect's specific situation. Some reps had the research instincts to find compelling angles, but many did not — and even the best researchers could not maintain quality at the volume the team needed. The result was a significant gap between the personalization the team aspired to and what they actually delivered day to day.

Open and reply rates were below target. Generic messaging was the direct cause of low engagement. When emails do not reference anything specific about the recipient's company, role, or recent activity, they read as spam — regardless of how well-crafted the copywriting is. Hubs' reply rates were well below the benchmarks needed to hit pipeline targets, and the team recognized that the solution was not more volume but better relevance. They needed a way to make every email feel like it was written specifically for that prospect.

SDRs were spending too much time on research instead of selling. The manual research workflow was consuming a disproportionate share of each rep's day. Reps were spending significant time on LinkedIn scanning prospect profiles, checking company updates, reading industry news, and looking for relevant triggers to reference. For each prospect, the research-to-send cycle took approximately 12.5 minutes — time that could have been spent on live conversations, follow-ups, and demo scheduling. Across the team, this research overhead was creating a hard ceiling on the number of prospects that could be reached each week.

New hire ramp time was unacceptably long. When Hubs brought new BDRs onto the team, it took months before they could produce effective outbound messaging independently. New reps did not yet understand Hubs' product deeply enough, were not familiar with the manufacturing industry's buying patterns, and lacked the research skills to identify compelling outreach angles. During the ramp period, their output was low volume and low quality, which meant the pipeline contribution from new hires was minimal for an extended period after they joined.

Why Autobound

Stephen Murphy, Hubs' Sales Director, evaluated several approaches to solving the personalization challenge before selecting Autobound. The team had considered hiring dedicated research analysts, investing in generic AI writing tools, and building custom research workflows using internal resources. None of these approaches addressed all four problems simultaneously.

Autobound stood out for its combination of research depth and speed. The Insights Engine pulls from 400+ data sources to surface real-time signals about each prospect and their company — funding events, product launches, hiring patterns, leadership changes, technology stack, and more. This is the kind of contextual intelligence that Hubs' best reps were spending 12+ minutes per prospect to manually compile, delivered in seconds.

Equally important was Autobound's role as a coaching and onboarding tool. For new reps, the AI-generated drafts served as examples of what good personalized outreach looks like — which signals to reference, how to connect them to Hubs' value proposition, and what tone to strike with technical buyers. This dual function as both productivity tool and training resource was unique among the solutions Hubs evaluated.

The Solution

Hubs deployed Autobound across their BDR team, replacing the manual research and writing workflow with an AI-assisted process that maintained personalization quality while dramatically increasing throughput.

30x faster prospect research. Autobound's Insights Engine instantly surfaces comprehensive research for each target prospect, including their professional background, company news, hiring activity, competitive landscape, and technology decisions. Research that previously took 10-15 minutes of manual LinkedIn browsing and web searching is now completed in seconds. Reps see the most relevant insights highlighted and ranked by potential impact, making it easy to identify the best outreach angle for each prospect.

5x faster email personalization. Using the surfaced insights, Autobound generates personalized email drafts that reference specific, timely details about the prospect and their company. Writing time dropped from approximately 12.5 minutes to 2.5 minutes per email, including the rep's review and any adjustments. The emails reference concrete events and connect them to relevant Hubs capabilities — for example, if a prospect's company recently announced a new product line, the email might reference the engineering scaling challenges that typically accompany product expansion and position Hubs' rapid prototyping capabilities as a solution.

AI-assisted coaching for new reps. One of the most valuable aspects of the deployment was the impact on new hire onboarding. New BDRs gained immediate access to Autobound's research and messaging capabilities from their first day on the team. Instead of spending months developing the industry knowledge and research skills needed to write effective personalized emails, new reps could review AI-generated drafts that demonstrated proven approaches. This served as a hands-on training mechanism — reps learned by seeing which insights the AI selected, how it connected those insights to Hubs' value proposition, and what messaging structure yielded the best results.

Consistent quality across the team. By standardizing the research and personalization process through Autobound, Hubs eliminated the quality gap between top performers and average reps. Every email sent by the team was backed by the same depth of research and signal intelligence, regardless of the individual rep's experience level or research instincts. This consistency was critical for maintaining Hubs' professional brand image with their technical buyer audience.

The Results

The deployment produced measurable improvements across pipeline generation, efficiency, and team productivity — results that were tracked over the initial evaluation period and continue to compound as the team refines their approach.

The 7% contact-to-opportunity conversion rate was the standout metric. In B2B outbound, conversion rates from cold email to qualified opportunity typically range from 1-3%. Hubs' 7% rate — more than double the high end of that range — demonstrated that the AI-powered personalization was resonating with their technical buyer audience in a way that generic outreach never could. Prospects were responding because the emails referenced specific, relevant details about their situation, making the outreach feel like a genuine conversation starter rather than a mass email.

The 150+ opportunities and 60+ deals won represented significant pipeline that would not have existed without the productivity gains from Autobound. At the previous per-email time investment, the team would have been able to reach only a fraction of the contacts they ultimately engaged, leaving substantial revenue on the table.

The 3x increase in overall sales productivity was the result of compounding efficiencies: faster research, faster writing, more emails sent, and higher conversion rates on those emails. The team was doing more work, faster, and getting better results per unit of effort — the ideal combination for scaling outbound without proportionally scaling headcount.

What the Team Says

"Autobound enables a new rep to come onboard and do two things, really be more efficient as a salesperson earlier on and also learn about our company and customers."

— Stephen Murphy, Sales Director

"It has saved me so much time in research while still being able to add personalization."

— Lindsey H.

"Autobound is the ChatGPT for sales outreach emails! So helpful. It gives me back my time to SELL!"

— Sherise V.

"I'm already seeing increased response rates, and their product team is pumping out powerful new features every other day."

— Madeline B.

What's Next

Hubs is expanding their Autobound deployment to include their enterprise account team, where the platform will be used for strategic account research and multi-threaded outreach within large manufacturing organizations. They are also piloting the use of Autobound's signal monitoring to trigger outreach based on real-time manufacturing industry events — such as supply chain disruptions, new product announcements, or facility expansions — allowing the team to reach prospects at the precise moment when their manufacturing needs are most acute. As part of the broader Protolabs organization, Hubs is evaluating opportunities to extend the Autobound deployment to other business units within the group.