How Automation Works Tutorial

3.2 Introduction

This is Matt Bailey, president of SiteLogic presenting marketing automation. In this module, we're going to cover how it works and the multiple applications of marketing automation. We're only going to be able to hit the highlights, as there are so many ways that automation is being implemented right now. We're going to look at some of the most exciting.

3.3 Marketing Automation Overview

As I had mentioned before, marketing automation runs on sets of rules. As you identify specific segments, specific actions, or qualifications of people as they come in as leads or customers, then you set up a rule that tells your marketing automations system how to respond. What message to send, what action to take, what information to provide, or what offer goes to specific groups of people. We're not talking to people as they are large groups of people and sending out batch emails. No, we're sending them one at a time, specific to people, based on information and behaviors that they have given you or exhibited.

3.4 Dynamic Segmentation

The primary way that we can look at how marketing automation works and some of the applications, is dynamic segmentation. By that we look at how people behave on websites, if they tend only look at one informational category, if they only tend to look at one product category and then maybe they order or contact you. Well, the record we have on them tells us that they are only interested in this product or this information. As they continue to look at the website or interact with you, that can either be confirmed by measuring additional behaviors and seeing that they have a preference for only this type of information or only these types of products. And so as a response, a marketing automation system then sends them offers, sends them information, that are only about the specifically expressed information that that user has provided. So, as you have your information ready to go out and segmented, this user will only receive the communications that you have tagged for that specific purpose. But the dynamic part of this is as people look at information, download information, interact with your emails, click links. Your CRM and marketing automation systems are able to assign users to specific segments that you have developed, and then, you can interact with them almost on a personal level, because of the information that they've provided. So it goes beyond a simple subscription or a download that, okay they downloaded this white paper, we add them to this list, not only of just customers, but people who are interested in this subject matter. So now that they're on that list they receive that information, maybe to take it a little bit further, let's say we have a pet website. If someone subscribes and they download something about dogs, and the only information they've visited is about dogs, then obviously we're going to add them to the dogs list. They have dynamically segmented themselves for us by their behavior on the site, and so the worst thing we can do is send them information about cats or about pets in general. You see we're getting away from the batch and blast approach where we send the same thing to all customers because the only thing this customer has expressed is an interest in dogs. And so the last thing we want to do is give them information that's not specific, wanted, or they've even expressed an interest in receiving. And so because of that we can be much more targeted in our communications to that customer. It's based on the conversation that the customer initiates with us through the website and through interactions and then providing them the information that they've asked for.

3.5 Segmented, Relevant Content

In dealing with a lot of customers. And especially in South Dakota tourism, they have found that when they segmented their communications to people based on how they visited and their expressed interests, they found that there was a dramatic increase in engagement from all communications. And so if someone was there just for a family vacation, then those are the only types of emails that they receive. If someone is there for winter time, for skiing, snowmobiling, three wheeling, then those are the types of information that they receive. And then also they have a large hunting population, and people that visit the state for hunting. They don't get emails for vacations. They get emails specifically for hunting and all the things they need to know for gathering licenses and travelling and areas that they can hunt. And so when they move to providing segmented, relevant content for each group of visitors, they saw their engagement rates climb dramatically. Because they were giving personalized content based on the expressed behavior and conversation of the user.

3.6 Automated Personalization

The next thing we can do with marketing automation is provide automated personalization. You see as you know more and more about your customers you're building a very large customer file. So automatically every communication with your customer should be a personalized communication. As we know more about transactions that they've had on the site, their buying history, what they tend to browse and what they tend to look at on the site and then also any contacts or anything that goes on. That all goes into our data management and we can also go to third party providers to get additional information so that we can know what more can we have in terms of conversation. So, for example, knowing more information, such as credit reports, their scores, purchases, past loans, we can know much more about somebody. For example, if someone comes to a website, a woman, and she buys shoes, then chances are you're going to have conversations about shoes of that style. But if a third party information provider is able to provide more data to find out that, well, she's married, she has children, and so we can also send communications about children's shoes and see how she reacts to that. And if she responds positively by clicking on the links, browsing the information, then you have been able to introduce a new conversation. Or a new facet of the conversation and expand the potential of providing relevant offers to this woman. And so, we can personalize and we can automate that personalization through conversations, through additional information, through purchase histories, and so all the information that this person receives. Can be personalized based on who they are and how they interact and the information they want from your company.

3.7 Personalized Offers

One exciting methodology of this is building personalized, real time offers. And this can be based on credit score, and a propensity to pay. One publisher was offering a free magazine, for signing up. And they could get a free trial, or they could get a bill me later. And so as someone filled out the form, within 300 milliseconds of pressing a submit button, that information was able to go through a data management provider, double check the addresses, look for the algorithm of their credit score and payment history, and then create a model score. And so if they had a high propensity to pay on time, then they would get the free offer. If they would have a low propensity to pay, then they would have to get another hurdle in the process, such as calling a 1-800 number, talking to an operator or maybe paying up front for a discount. The beautiful part about this is that it created a personalized, real-time offer based on the data that was accumulated about that specific customer. And so for that company, being able to screen and give specific, personalized offers based on that data, they were able to decrease their servicing costs. Which by moving up those servicing costs, they increase their profits by 10% by providing those dynamically generated real time offers through automated processes.

3.8 Big Data Sources

>> You see, what's driving a lot of this is big data. Now, a lot of people still, when it comes to big data, they still shutter. And there's really no great definition for it. But let's look at the sources of data, because that is critical to understanding how we can build these automated models. The sources of big data overall, number one, are transactions. Filling out lead forms. Buying products. Interacting with companies on multiple levels through their mobile phones, through call centers. Any way that a customer or client interacts with a company is a transaction. And then, log data from websites, specific events and emails. Just those four things, if we tracked what people did and then we customized our communications based on those events, that would be significant enough. Of course, when we look at all the other types of sources, all of a sudden now we can see how if we know this information is coming, if we define rules as to how to react to it, we can automate even more things.

3.9 Mobile-Personal Marketing

Now, I mentioned mobile and of course, mobile is growing substantially when it comes to marketing automation, and will be an amazing player as we go forward. The main reason is because everyone carries their mobile device with them. And through Passbook campaigns, where people can pay through their device, they've seen that there's more conversions using Passbook. And then also when people are prompted in the store to sign up and redeem, people are doing that, as well as increasing their average orders because of that. So having a device that can, in real time, respond with automated offers and events to customers, they have seen that that has a positive response. That this is now a mobile personal automation that we can market to people and get immediate response through the mobile device. Now, as I said, this is just going to increase significantly, as smartphones are growing at a faster rate. Traffic is increasing through smartphones, and the ability for people to interact via apps, text messaging, and many other methods enables another level of communication, of course, not only communication. It's just the amount of information, that once you get a customer to download your app, use your app and interact with it, you're able to get amazing amount of information. Flurry is a mobile analytics company and they are collecting data now for over 1 billion users across 300,000 apps, and of course, they're getting big data. They're getting transaction data. They're getting location data. They're getting time data, all types of information. And so one of the rewards of doing automation on mobile platforms is the ability to gain an even greater amount of data in return. Web data, log data from visits, emails, we're getting clicks. We know where people are from. But when it comes to data generated from a mobile device, all of a sudden that data is more personalized and focused based on that user. And so the amount of feedback and the amount of data accumulated from mobile allows and lends itself to even more automated potential.

3.10 Mobile Automation

One hotel has implemented a mobile checkout. So, automated from the system, the customer gets an email early in the morning that asks them if they want to checkout, or do they want a late checkout or extended stay. And in given these options, they have already seen that customers are responding positively to it. And taking advantage of an automated process of checking out late or even extending their stay. The software, the implementation is already driving 140% return on investment from implementing this program. Of course the next level is getting the customer to download your app and interact with it. Because as I mentioned, not only is the customer gaining more information about the company through the app, the company as the app provider, is also learning more about the customer. Maybe not even through the interactions through the app, but just simply how often they're using it, where they're using it from. What offers are they responding to? What are they browsing? You can think about all the information that's available through a customer based app and all the information that's pushed back to the company. So, a frequent traveler who opens up an app to find the location of a Dunkin' Donuts, they're going to know that they're a frequent traveler and maybe they can speak to them differently or give them different offers.

3.11 Location Automation Beacons

And so then we start getting into more location based information. And right now where that is moving is beacons. That there can be an in store beacon that knows the proximity of a customer based on their mobile device. So if that customer has enable notifications, even when they're outside the store, they can get an offer that prompts them to come to the store. Or even while they're in the store, they can get the offer if they're spending a specific amount of time dwelling in front of products. And just checking in, they can get coupons, or anything like that. Now the company, through these beacons, can also track how long people are in the stores. Where do they spend the most amount of their time? What pathways do they take through the store? And what products do they look at the most? And so there is a transaction going on here of the customers are getting notifications and coupons and the company is getting real intelligence about how people will interact with the physical store. And so what beacons are enabling is a real time automated offer system or communication with the customer. In fact stores that are using beacon technology right now have seen that there is a 73% increased likelihood to purchase when someone receives an in-store notification. They've also seen it 60% of people that receive an offer generated from an automated beacon, it can influence a higher spend from buying additional products where offers, or discounts were offered. One of the more exciting numbers is that 30% of customers who received an automated beacon offer, 30% of customers redeemed that offer at the point of purchase. That is amazing because what it says, is that people were open to receiving brand offers in the store, and that 30% of people acted on them at the point of receiving that offer. Marketing automation is going to continue to grow and take over many aspects of the customer and client relationship. As big data grows and as people learn to respond to specific data events, it's only going to grow and only by terms of our creativity will it be limited. As we find new ways to respond to events that people generate throughout their customer life cycle. This has been Marketing Automation, how it works, with Matt Bailey, President of SiteLogic.

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