Go from Zero to Booked Meetings on Your Website in 2 Weeks

TigerGraph was using Drift when the Holndr data breach hit. Drift shut down their services with almost no warning, and support was nearly unreachable. The website chat went dark overnight.

“Getting a response from anyone from Drift was awful,” says Braden Looper, Manager of Revenue Operations at TigerGraph. With a lean team of two running go-to-market, they needed a fast, reliable replacement. Not another mess to manage.

Get Warmly live and generating pipeline in two weeks by following TigerGraph’s lean onboarding approach.

Step 1: Let your CSM do the heavy lifting

• TigerGraph’s CSM did not just guide them. He took proactive action and handled configuration himself.
• With one RevOps manager and one CMO running the whole motion, Braden leaned on his CSM fully. You do not need a big team to get this done.

Step 2: Load your knowledge base in week 1

• Feed Warmly your full website and any technical documentation you have.
• TigerGraph sells into financial services with a technical ICP. Getting the knowledge base right upfront meant the bot could hold its own in deep product conversations from day one.

Step 3: QA the bot with real technical questions

• Have technical team members visit your site and ask real, hard questions as if they were a prospect.
• They report back: is it answering correctly? Tune and repeat until quality is confirmed.
• This step separates a bot that books meetings from one that frustrates prospects.

Step 4: Use chat as a top-of-funnel educator

• Let the bot train visitors on your product before any human interaction.
• The goal: by the time someone books a demo, they already understand the basics. Shorter sales cycles, warmer leads.

5 meetings booked from the website in the first 6 weeks, up from zero. TigerGraph calls that over 100% ROI on their baseline.

“We went from not booking anything from our website to now booking meetings,” says Braden. “It’s a strong signal.”

The goal now is to grow that number month over month as the bot gets more refined and pipeline compounds.

Read the full case study

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