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Why This CRM Integration Saved Me Hours Every Week

Max Mitcham · 575 words · 3 min read

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0:00What is going on guys? I wanted to go

0:02over and do a summary video on how I am

0:04leveraging my CRM Atio. Now I wanted to

0:08go over the setup and how I'm plugging

0:10in systems from every single kind of

0:14orifice I guess of triggery into the

0:17Atio and making atio like core to

0:19everything that we're doing. And the

0:21best part yet is my Atio subscription is

0:24completely free. So let's look at this

0:28at a very very high level what I have

0:31going on. So first things first I have

0:34segment. Now segment's a great tool for

0:36connecting any data and creating what we

0:40call like a data pipeline through to

0:42Atio. So in this case I've connected our

0:45Postgress and pushing through any

0:47customer data that we get i.e. someone

0:50signs up for triggery they're

0:52automatically added into our atio. So

0:55that's that section taken care of. Then

0:57what I've done is I've used uh NAT to

1:02connect the following three elements

1:04here. So we have a Slack community. So

1:07if they message us via Slack, I pick

1:10that up via NAT. I find them in Atio and

1:14then I mark that and I upload the

1:16conversation into Atio. And it's the

1:19same for intercom slash kind of bleep.

1:22if they message us, if anything happens,

1:24that is picked up and added via NA10

1:26because there's no direct integration,

1:29which is really cool because then I can

1:30understand if anyone has had any kind of

1:34issues or anything like that when it

1:36comes to doing that. And then I've set

1:38up basically a bunch of agents that I

1:40trigger through a web hook from ATIO

1:43into NA10 and then bring the results

1:45back. So, how does this basically look?

1:47Well, uh, let's start to look at a few

1:50things here. here. So, first of all, I'm

1:52in like my people uh view here. You can

1:56see that I have different bits of

2:00information and these are like features

2:02effectively if they're using the

2:03features. But one of the things that I

2:05have basically built into is uh an agent

2:09and this agent basically will go ahead

2:11and query post hog. So I have this

2:14option here where I can tick run uh user

2:17research essentially. And when I do

2:20this, what it's going to go do is the

2:22agent is now going to go and query post

2:25hog and pull back any data that we've

2:28have on them in terms of how active that

2:30person's been on the platform, how many

2:32times they've used certain things, how

2:34many times they've used certain

2:36features, and so on and so on. So it's a

2:38really really good way of understanding

2:40usage on the platform.

2:42But what it's also doing is I am

2:46starting to understand things such as

2:48like risk status. So here when we look

2:51at like our company overview, I have a

2:55section called uh churn status. If I go

2:58to uh here and you can then start to see

3:04if there are any clients that are either

3:07a medium, low or high risk churn or no

3:10risk uh at all. And that is coming from

3:13usage data. And so what I'm looking at

3:15is like how active they are and if they

3:17are active or not. Then basically uh it

3:20updates this churn status automatic

3:22automatically for me every few days.

3:26Let me just stop that there. So see

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