G2

Maria Virginia M.

SDR

Mid-Market (51-1000 emp.)

8/17/2026

Business partner of the seller or seller's competitor, not included in G2 scores.

"GTM Data Fixed at the Source—Clean, Deduped Activity That Boosts Forecast Accuracy"

5/5

What do you like best about Nektar.ai?

It fixes GTM data at the source. Pulls activity directly from Google, Zoom, and email, cleans and deduplicates before hitting Salesforce. Our buying groups went from 2-3 contacts to 8-15 stakeholders. RevOps freed up 35+ hours/week from data consolidation. Forecast accuracy improved from 10-15% monthly miss to 2-3%. Zero friction for reps, no behavior change required. That's the difference between a tool and infrastructure. Review collected by and hosted on G2.com.

What do you dislike about Nektar.ai?

Requires mindset shift from sales leaders. Moving from "how many contacts logged" to "who's actually involved" takes training. Also won't fix reps not meeting customers, it captures reality, which is the point. Not a product issue, just a reality check for teams expecting magic Review collected by and hosted on G2.com.

What problems is Nektar.ai solving and how is that benefiting you?

We were losing visibility into deals because buying groups were fragmented across Salesforce, Gong, Outreach, and email. Reps logged 2-3 people per deal, but reality was 8-15. Our forecast missed pipeline 10-15% monthly because we were forecasting on incomplete data.

How Nektar solved it: Automatically pulls activity from Google Workspace, Zoom, and email, cleans it at ingestion, and surfaces complete stakeholder maps. Our deals suddenly showed the real buying committee.

The benefit: Forecast accuracy improved to 2-3% monthly misses. RevOps went from 40+ hours/week consolidating data to 4-6 hours. More importantly, we finally had data we could trust. Every forecast number traced back to actual customer activity, not rep logging habits. That's why I joined the company Review collected by and hosted on G2.com.