Case Study

Neysa

Driving demand and attribution clarity for a complex AI cloud platform selling to multiple enterprise stakeholders.

Attribution Google Ads LinkedIn Ads SEO

" he entire marketing investment was recovered through a single client billing. This validated our go-to-market approach completely. "

Ney

Neysa Team

Enterprise AI & Cloud

Enterprise accounts tracked

via account-level attribution

Multi-channel influence mapped

across SEO, Google & LinkedIn

Sales-ready inbound conversations

from high-intent companies

1Context

Neysa is an enterprise AI cloud platform offering GPU infrastructure, inference services, and AI acceleration solutions for large enterprises and deep-tech teams in India.

Their buyers range from CTOs and ML engineers to procurement and business leaders.

2The Real Problem

Neysa operates in a highly complex B2B category:

  • AI infrastructure is hard to explain simply
  • Buying decisions involve multiple stakeholders
  • Sales cycles are long and non-linear

At the same time:

  • Traffic existed, but intent quality was unclear
  • Attribution across SEO, Google Ads, and LinkedIn Ads was fragmented
  • The team could not confidently answer: which channels were actually influencing pipeline

3Why This Mattered

Without clarity on:

who was engaging

from which accounts

through which touchpoints

Scaling spend or content would mean guesswork, not growth.For a high-value enterprise product, that risk was unacceptable.

4Our Thinking

Instead of treating SEO and Ads as lead machines, we treated them as stakeholder education and intent-mapping channels.

Our approach focused on:

  • mapping content to technical and business personas
  • aligning paid and organic efforts across the buyer journey
  • solving attribution first, not last

Only after this foundation did we scale execution.

5Execution

SEO

  • Built intent-driven content clusters around AI infrastructure, GPUs, inference, and enterprise AI adoption
  • Created pages tailored for technical evaluators as well as business decision-makers
  • Focused on discovery across Google and LLM-driven search behaviour

Google Ads

  • Ran tightly controlled search campaigns focused on high-intent AI infrastructure queries
  • Avoided broad awareness waste and prioritised relevance

LinkedIn Ads

  • Targeted decision-makers across enterprise accounts
  • Used content-led campaigns to support longer consideration cycles

Tracking & Attribution

  • Implemented Factors for account-level identification
  • Connected anonymous traffic, known leads, and CRM data
  • Enabled visibility into which companies were engaging before form fills

6Measurement & Attribution

Instead of last-click metrics, success was measured through:

  • account engagement
  • channel influence on pipeline
  • repeat visits from target companies
  • alignment between marketing touchpoints and sales conversations

This allowed Neysa to finally trust the data behind marketing decisions.

7Outcomes

  • Clear visibility into which channels influenced enterprise accounts
  • Better alignment between marketing and sales conversations
  • Improved quality of inbound discussions
  • Confidence to scale content and paid efforts strategically

8What This Proves

Complex B2B products do not fail due to lack of traffic. They fail due to lack of clarity across stakeholders and attribution.

9CTA

If your product has a long sales cycle and multiple decision-makers, this approach applies directly.

Need revenue before brand fame?

This approach works. Let's discuss how we can apply it to your business.