Craig Inc.
Case Study SaaS

Criag’s AE’s are having a hard time to handle all of the incoming leads and are having a hard time understanding what is their ICP and conducting market research about user behavior.

They offer an all around security for users and companies at a large scale.

Craig Inc.
Case Study SaaS

5k+

Users

3

AE’s

3

BizOps

400

Lead per month

15%+

Sales efficiency
Key Takeaways

Craig is a cyber startup in its initial phases. They offer an all around security for users and companies at a large scale.
The word about them has spread around the block and they are receiving a high volume of leads a month. Criag’s AE’s are having a hard time to handle all of the incoming leads and are having a hard time understanding what is their ICP and conducting market research about useer behavior.

The Outcome
  • 6% increase in conversion rate. The right deals are reached at time. AE’s are focusing on what matters most.
  • 7% increase in conversion rate due to focusing on the deals that matter and not wasting time on deals that will not convert.
  • Process fluency. AE’s had reported to have more fluent deals and processes due to being exposed to the data they needed in order to back up their decision and pitch.
The Challenge

Craig is a fast growing company, the efforts it is investing is in growth and scalability. Hiring expensive data scientists is difficult for them.

  • No touch funnel optimization. Lack of lead segmentation
  • AB testing. In order to conduct a simple test product team had to go through a couple of development stages rather than having access to the data themselves.
  • Lack of data visualization. Account Executives are having a hard time understanding the value customers are getting.
  • Identifying ICP. Product data did not match with projections.
The Solution
  • Automated cross funnel navigation. BLEND redirected leads into different funnels.
  • Data visibility. Usage and engagement data across all GTM platforms is now accessible to ensure data driven decisions are being made.
  • Generating insights from A/B tests without the help of a developer. Rather than relying on the R&D, product and growth teams can now gain access to tests that are being conducted on a daily basis.
  • Segmenting your customers. Blend provides the team with a data backed understanding of their customers segmentation by their usage, behavior and predictions.

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