Startup Spotlight Growth Series: Scale AI

October 23, 2020

Start-up Spotlight Growth: Yuri Maruyama, CMO of Scale AI

LinkedIn Marketing can play an important role for B2B startups looking to scale. But what are the learnings and strategies fueling their growth? We’re excited to help answer this question with our new Growth Series: an inside look at startup marketers’ approach to successful growth. As your team builds your own marketing strategy, perhaps the perspectives shared here will help you optimize, learn, and grow faster.

For this month’s installment in this series, we’ve interviewed Scale AI’s Marketing Lead, Yuri Maruyama.

LinkedIn: In a sentence, tell us about Scale AI. What is a fun fact about Scale AI that we wouldn’t find on your LinkedIn Page or website?

Yuri Maruyama: Scale AI’s mission is to accelerate the development of AI applications. We do this by turning our customers’ raw data into high-quality training data that reliably educates their AI systems. A fun fact you wouldn’t find on our LinkedIn or website is our culture of creativity and humor. Everyone from our design to engineering to operations teams gets into the spirit from developing custom Slack emojis and gifs to April Fool’s landing pages

LinkedIn: What does growth mean to your team? How does your team measure growth?

Yuri Maruyama: Growth for us means landing customers working on cutting-edge AI systems. How we execute and measure "growth" tactically within marketing is still evolving. Our sales team has a set of target accounts but given how quickly the field is evolving, we're focused on identifying new companies and use cases.

LinkedIn: What’s something you wish you knew when first getting started with your paid growth strategy?

Yuri Maruyama: I wish we had taken the time to properly set up lead to account matching and lead routing workflows before starting with our paid growth strategy. In the early days, we weren’t always able to track lead sources and also had high-intent and valuable leads fall into black holes and not properly nurtured or followed up on. 

LinkedIn: How did your team identify and optimize your ICP's buyer’s journey? 

Yuri Maruyama: With lots of experimentation and tight feedback loops with our sales and BDR teams. We hold weekly syncs with our BDR team. If we made slight changes on the audience targeting, we would get almost immediate feedback on the quality of net new leads since making those changes. This tight feedback loop allowed us to quickly experiment with different messages, audience skills, and audience job functions.

LinkedIn: What adjustments have you made to your growth strategy over time that have had a significant impact on results?

Yuri Maruyama: We’ve run a handful of experiments and implemented various strategies since first starting to use the LinkedIn platform. Testing different audience targeting tactics (e.g. seniority, function, and skills) has had the most significant impact on results both in terms of the volume of leads as well as the quality of leads we can generate with LinkedIn. 

LinkedIn: How do you balance your sales cycle and measuring ROI from paid marketing initiatives?

Yuri Maruyama: As a B2B company with a highly technical and complex set of products, our sales cycle can be quite long. This makes measuring ROI from paid initiatives more challenging. We invested quite a bit of time and effort into our marketing operations to enable us to track marketing-sourced leads through the pipeline and to understand all of the touchpoints marketing initiatives and campaigns had both before and after opportunities are created.

LinkedIn: How do you achieve and measure successful alignment between sales and marketing?

Yuri Maruyama: The sales and marketing team at Scale AI both roll up to the same GTM leader. This makes alignment easier and feedback loops extremely tight. Going beyond that, my team and I hold ourselves accountable by actively tracking how the leads we produce progress through the sales pipeline and we seek qualitative feedback from BDRs and AEs if we see a low conversion rate from MQL to SQL or SQL to SAL.

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