Timezone and Last Active Based Audiences in Mobile Monkey
Welcome back chat about fans in this lecture. I'm going to teach you how to create to more audiences. One based on time zone one based on the last time the user was active and these are two pretty common use case scenarios, time zone say you're working in L. A. Right and you're on the West Coast and it's of the United States and it's six o'clock P. M. And you're putting together some chat blasts. It's nine o'clock P. M. In new york. And you know that at nine o'clock P. M. You're gonna have low engagement rates. People are finishing up dinner, whatever it be after a long workday. You want to only send it out to the west coast. So perfect example of that is you can create an audience of just people in the West Coast time zone and send the blast out to them and schedule a blast to go out to the East Coast time zone people um, the next morning let's say. So that's an example of when you would use the time zone audience feature. I found that to be very helpful. The other very popular way in...
one of my favorite ways of segmenting out audiences or creating audiences is based on when the user was last active, the last time the user engaged with the bot and there's two totally opposite use cases. Some businesses want to send out a chat blast or a drip campaign to people that have not engaged with the brand in quite some time. So that might be, we haven't heard from you in a month. So we want to send you out a coupon or whatever. Maybe you want to get back in touch with you. So it's a different type of marketing, a different type of campaign. That might be a good idea for let's say reset ivy, the hydration company that we've been talking to, where they know that the average user will buy once every three months because that's when their customers are taking vacations on those intervals. So they might want to send out a chat blast to everybody who hasn't been engaging with their body in the course of let's say or anybody who hasn't engaged in at least three months. The same thing might be too with a business that has a longer sales cycle might be more periodic. You might have a business like sofa mania or a business like the international culinary center where they need to get a lot of traffic to their site within a very short amount of time because they're either running campus tours or they're running a special sale and they know from previous data, you might know this in your business and this is, and if you're doing this for a client, you need to ask the client these types of questions and be able to look at analytics and get this sort of data. Do we need multiple rapid fire marketing messages to get a conversion. And if that's the case, we might only want to send a chat blast of people who have been active recently. So let's go in and build these audiences inside of the monkey. And I think the use cases are self evident. So we'll title this audience here. Um East Coast time zone adding a filter. Sometimes you have to click the button twice. Attribute is time zone equals. I'm looking for -5, I believe negative four. One of these will have to actually look this up. But you get the idea, that's exactly how you would create the value. And you can also add multiple time zones. So I can type again and add another time zone and I could have a um I can have an audience that's based off of more than one time zone. So it's either this time zone or that time zone obviously doesn't have to be both time zones. And we clicked on, we will see exactly how many contacts are in that list. 413. And now I get the time east coast time zone. Okay, 413 contacts. Now let's create an audience based on last seen. So I want to do um I want to send out a chap last, let's say to people who have not engaged in three weeks. So At least three weeks, no engagement. Wait for it to save and we're gonna go ahead and add the filter and the attribute we're looking for is last Active is greater than we want to go back and say last Active is greater than we'll go back. Let's say here And we then have, if we click done, we'll see exactly how many people are on that list. And don't worry about the specifics were not blasting anything out right now. So we have 568 people who were last active at least three weeks ago. If you want to do it within three weeks, people go, we would change the qualifier to be greater than it would be, it would be, we would change it to be less than which would mean we'd be blasting out or dripping facebook bots too. People who are new contacts within the last three weeks. So that's how you create a time zone and that's how you create a audience for based on the last engagement. And of course you can continue to go in and edit this stuff and add filter. So, if I wanted to go into this one at least three weeks ago, no engagement, I'm going to edit it. I'm gonna add another filter on top of that. And I can say, okay, um, session count they had at least Is greater than two sessions. Right? two. And I want to send out a blast to people who have at least been that have not been active in at least three weeks, but when they were active we've recorded at least two sessions. Okay, so engaged people who used to be engaged with us, it's a great list to create. I'm gonna save it and we'll see once we click done, we'll see how many people we actually have on this list, 88. You see that? So not that many people who haven't been active in at least three weeks out of 568, we only had 88 people. Um, part of this list now, but it's, it works like I happen to really like the way mobile monkeys audiences work. It's really quick, it's really nifty, it's really neat. So this is the place where you go to bucket your people into useful marketing buckets don't just create segments because you could create segments. If men and women don't make an impact on purchasing activity or your conversion rates, then there's no point in segmenting it out. If you're not gonna talk differently to men and women, if you're not gonna send them different content, there's no point in creating those audiences only create audiences that are going to be useful in your business with the way you know, how your business operates with with the distinctive and unique behavioral patterns and behavioral characteristics of your customers only create audiences around the dimensions that you know, and that you've studied and that you could reasonably predict will have an impact. If you're able to market to them in specific and unique ways in the next lecture about audiences, which will be our last lecture about about audiences right now, we're gonna talk about creating audiences off of custom variables. I will see you guys in a couple minutes on the inside.