I like that we can look beyond the number of chats we're generating and understand which entry points are actually contributing to pipeline. Knock AI's Chat Performance analytics lets us analyze conversations by source and touchpoint, along with qualification and downstream deal outcomes. That makes it easier to evaluate whether a particular website placement is attracting serious buyers or simply generating activity. Review collected by and hosted on G2.com.

There's still some work involved in interpreting the data and deciding which touchpoints deserve more investment. I'd like the analysis to make it even easier to turn these insights into clear optimization priorities. Review collected by and hosted on G2.com.

I lead the marketing ops, and my favorite thing about Knock is the quality of the Salesforce integration.

We have a lot of records and fairly complex CRM processes, so I care a lot about what gets written to Salesforce, when it gets updated, and whether I can actually trust the data.

We were using Qualified before, and we had some frustrating issues there. The deal and pipeline numbers we saw in their dashboard didn’t always match what we expected from Salesforce, and we also had cases where data didn’t sync the way we expected. As our volume grew, the dashboards also became very slow for us.

With Knock AI, the integration has been much cleaner.

The chat history, qualification data, meetings, enrichment, attribution and routing information are connected back to the Salesforce record, and we can actually use that Knock data in other Salesforce workflows.

That last part is really important to me. Knock isn’t creating data that only exists inside Knock.

It becomes part of our CRM infrastructure. Review collected by and hosted on G2.com.

As we use Knock for more of our CRM infrastructure, I’d like even more flexibility around debugging and auditing complex Salesforce syncs and API workflows. Review collected by and hosted on G2.com.

I like that Knock AI doesn't treat booking a meeting as the end of the buyer journey. After a prospect books, the conversation can continue through messaging links, including LinkedIn and WhatsApp. Reps can share relevant resources and pre-meeting context through Slack, while the buyer can continue the conversation in their preferred channel. Keeping that context available makes the handoff from initial interest to the actual meeting feel much more connected. Review collected by and hosted on G2.com.

Getting the workflow right takes some planning. We need to decide which pre-meeting messages, reminders, and follow-ups are useful without overwhelming buyers with unnecessary communication. Review collected by and hosted on G2.com.

What interests me regarding Knock is the way it manages the shift from an AI interaction to a human representative. While it is useful to receive the first response from the AI, the experience can break down if the customer then has to go over all the same points once a sales representative joins. Knock keeps the transition within the same conversation; its AI agent is able to interact with the buyer, answer questions by referring to the predefined knowledge sources, and collect information about the buyer's qualification. Once a human representative replies, ownership passes to that person and the AI ceases to respond. Our team can manage the conversation through Slack while the buyer keeps on using their usual messaging channel. I also prefer that the handover should be guided by intent, enrichment, and routing rules rather than depending on a general chatbot escalation. The system is able to send different conversations to the right representative or team according to the rules we have set up. The key point is that the AI is not regarded as a separate interaction which terminates before the actual sales process starts; the conversation can carry on with a human worker, the previous context being available to enable them to take up where it had left off. Review collected by and hosted on G2.com.

I want greater visibility regarding how smoothly the conversations move from AI to human agents, particularly in cases where the handoffs stall or need intervention. This will make it easier to identify any gaps in the customer experience and adjust our agent settings and routing configuration accordingly. Review collected by and hosted on G2.com.

One thing that has always bothered me about working with customer and prospect data is that the information is usually there, but the full story isn’t. You can open a CRM record and see the contact, company, and some activity, but that doesn’t necessarily tell you how the person knows your team, what conversations have happened before, or whether someone else in the company already has a relationship with them.

What I find interesting about Knock is its Private Relationship Graph. Rather than looking at every person or account in isolation, it can connect available CRM history, previous interactions, professional relationships, and engagement context. That gives you a broader picture of the relationship instead of making you piece everything together manually.

I also like that the context isn’t limited to one contact. Understanding who your team already knows at an account, which relevant people you’ve interacted with, and where relationships are missing can be useful when you’re trying to understand the account as a whole.

For me, the important distinction is that this goes beyond having more data in a record. It’s about making the information around a relationship more useful when someone needs to act on it. Review collected by and hosted on G2.com.

Currently, their site has less documentation regarding the integrations. Would love to see more documentation around integrations with other GTM tools. Review collected by and hosted on G2.com.

One thing that I like about Knock AI is the way it handles follow-up once prospects interact with the meeting links. We used to think that if a meeting was booked, we were already halfway to converting the prospect. But that's not always how it works. People can lose interest before the call, and sometimes qualified prospects leave without booking at all. With Knock AI, the follow-up depends on what the prospect actually did. If someone books a meeting, Knock sends a personalized LinkedIn message from the rep they'll be meeting, confirms the meeting, and asks if there's anything they'd like to cover. If someone qualifies but doesn't book, Knock follows up and invites them to choose a time. I like that we're not treating both situations the same way. The messages are relevant to what happened, and the rep doesn't have to remember to send each one manually. Plus, when a prospect replies, the conversation and lead details show up in Slack, so the rep can pick things up without having to search for the original interaction. It's a small part of the sales process, but it's an important one. Getting someone interested is one thing. Keeping that conversation going until the actual meeting is another. Review collected by and hosted on G2.com.

The only downside is that each rep needs to connect their LinkedIn account, and the routing rules must be configured correctly before the automated follow-up works. Review collected by and hosted on G2.com.

What I like is that Knock helps sales understand what happened before a lead reached them. It's not always enough to know that someone showed interest. The sales rep also needs some context about the person, what they were looking at, and whether anyone on the team already knows them.

Knock brings that information together and helps route the lead to the right person. That way, the rep has more to work with when following up instead of starting with just a name and an email address.

I also like that the conversation can continue without making the person repeat everything they've already shared. Review collected by and hosted on G2.com.

Getting the workflows set up takes some thought. You need to decide how leads should be qualified, who should receive them, and what information sales needs. It can take some time to get everything working the way your team needs it to. Review collected by and hosted on G2.com.

One of the biggest improvements for us has actually been the visibility between marketing and sales. Before Knock AI, our marketing team could see that we generated a lead or a meeting, but after that it became much harder to understand what actually happened. We didnʼt know if they actually attended the meeting and if the meeting was good. Our ad agencies asked me about meeting quality, and I had no easy way to answer them. A lot of that depended on CRM updates or asking the sales team directly. With Knock, we can follow the whole journey easily. We have full visibility on Slack and in their live reports. We can see the original source and campaign, the conversation, who owned it, whether a meeting was booked, what happened with that meeting, and how the account progressed afterward. That has made the conversations between marketing and sales much better because weʼre finally looking at the same funnel. Review collected by and hosted on G2.com.

One thing Iʼd like to see is even more flexibility in the reporting for marketing. We can already follow conversations, meetings and sales progress, but Iʼd love to be able to build more customized funnel views around the exact stages and metrics our team cares about. Review collected by and hosted on G2.com.

What I like about Knock is that it gives us a way to make account-based marketing more actionable. Personalization shouldn't stop at mentioning a prospect's company name in an email or LinkedIn message. The experience they land on should also be relevant to their account and make it easy to take the next step. Marketing Cards are particularly interesting for this. We can create a branded, focused destination with relevant resources, a short introduction, and clear calls to action. Instead of sending every target account to the same generic page, we can tailor the experience and give prospects a direct way to message our team or book a meeting. I also like how this fits into the broader Knock workflow. Account enrichment, segmentation, intent signals, and relationship intelligence can help provide context for outreach, while chat and scheduling give interested prospects a way to continue the conversation. The biggest advantage is the ability to connect account context with an actionable experience. We're not just thinking about what message to send; we're also thinking about what happens after someone clicks and how to make the next step as straightforward as possible. Review collected by and hosted on G2.com.

One area that could be improved is managing personalized experiences at scale. Creating a card for a specific account is useful, but when you're running ABM campaigns across a large number of accounts, keeping each experience relevant and up to date can require additional effort. I'd like to see more options for managing and updating account-specific cards in bulk, so teams can scale personalization without creating unnecessary manual work. Review collected by and hosted on G2.com.

We put a lot of effort into getting our content and campaigns in front of the right people, but we don't always get to see what happens next. Someone might click a link from LinkedIn, check out a review, or show interest in something we shared, then disappear without ever filling out our website form.

I like that Knock gives us another way to turn those touchpoints into actual conversations. We can place trackable links in different assets, let buyers reach out through a channel they're comfortable with, and keep the conversation connected to the sales process. It feels like we're making better use of the interest we're already generating instead of relying on everyone to come back and fill out a form. Review collected by and hosted on G2.com.

When links are shared across several campaigns and channels, keeping the naming and tracking consistent takes some discipline. Otherwise, it becomes harder to compare which placements are actually bringing in meaningful conversations. Review collected by and hosted on G2.com.