When it comes to ShopperSuite, there's a number of benefits that we are providing for agencies to come back to their clients with. One is innovative, or what we refer to as a future-proof technology. ShopperSuite's cookieless technology was really built around the ability to drive more conversion from people coming to your client's websites. Scalable marketing activation, the ability to market instantly to households and from multiple touchpoints, so there's scalable marketing activation.
On top of that, there is more in-depth data, trends, insights, as it relates to your client's data, not industry data, not regional data, but actually how it relates to your client because it's their data and trends. And lastly, for an agency, it's improved customer retention; you've given them a really strong technology to make a difference in their business, and in addition, a revenue source.
There are four important concepts that will help explain what FullThrottle is doing, what we want to solve for our agencies, and how it differs from what most agencies are used to.
- These two things don't get along; Google analytics and location-based insights and information.
- Almost every agency, brand, and media company is using Google analytics to some shape or degree, right? We use it to look at goal conversions. We look at new users. We look at things like bounce rate and time on site. It is a great 101 to understanding what is website behavior on my website. But where Google analytics stops short is around location. It does not use specific location data to help identify and resolve households. So, for a lot of agencies and businesses, especially those that are retail-focused, where location is crucial in your ability to sell and increase your conversion rate and increase your business, it is really important to evolve and look beyond Google analytics for something that can help support the very location-specific business.
- Big insight is that assessing propensity is hard, right? With Google Analytics, a lot of people look at bounce rate, sessions, users, pageviews, month over month vs year over year, but we really have no idea how in market is this particular shopper, right?
- For whatever product or service that this shopper is interested in, how do we know where they stack up against all the other households that are shopping on our digital property? So, how do we get Google analytics, which is focusing on sessions, users, bounce rate, time-on-site, etc. to really segment our audiences into understanding what their true propensity is, so that when we talk about activating marketing, it's that much more impactful?
- AI is something that is very big in the world today. It is very expensive to undergo and extremely valuable. How do we think about using different types of algorithms, whether they're pre-programmed algorithms or they are machine learning algorithms?
- Some examples of things that FullThrottle does is; we like to think of things in the old school way of left side of your brain and right side of your brain, right? So, your left side of your brain might be more of a regression-based model, which is something that we explore and train on, which is looking at the probability and propensity of purchase based on average predictions. Your right side of the brain will look at something that is a true classification base. It's yes or no. Will someone buy in the next 30 days based on the machine learning models that we're training on all this data? So, doing that by yourself is very difficult, training data engineers, data scientists, getting access to data. So, what we're trying to solve for agencies is, say, how do we get them something that's out of the box, delivers them propensity, delivers them AI, without these massive investments that are really only available to some of the biggest agencies in the world?
- Most agencies today, especially in a retail type of business, live in two worlds.
- We have an online world where it is fully anonymous, where we're looking at similar things like metrics. And then, you have your second world, which is when someone becomes a lead by giving us their information. They may come into a store to buy a piece of furniture or to test drive a vehicle, and when they are doing that, you are able to measure it. But you measure typically across two worlds very separately and you do your best to bridge the gap, but it is very difficult to do so. How does Full Throttle help agencies solve for this problem And wouldn't it be so nice just to live in one world where your online world and your offline world, your entire footprint, everything that your household has done online, and everything that your household has done offline in a store, merge together to have a true 360-degree complete footprint of your customers?
What you get out of it and how to interpret what you're seeing on the screen.
What we do is resolve and identify households; you can see that in any date range and any mile radius. We're looking at devices, households, pieces of influence. And we're constantly measuring that propensity. So, what do we do with that information? There are a couple of different things.
We can actually go pull insights from all on screen.
Example: If I am an agency how do I look at and interpret the data that I'm seeing on the screen today?
Answer: It's actionable data. There's a lot of tech and ways we can get data. But to be able to provide actionable data, and I mean that in a couple of ways. One is that the technology because it's continuously learning, is able to get into that marketing activation. It's making some marketing moves on its own based on the intelligence. However, it's also providing actionable data for the agency. So, an agency can look into the probability of where people are in the buying funnel. If you're looking on the left-hand side of the screen, where are the people coming to our site? Where is the probability of where they are in the decision-making process? You can look at this in a couple of ways. I mean, what you really look for is you would hope that you kind of have each segment of the funnel, that we're building awareness, heavy in market, ready to buy. You'd like that to be...a perfect world, it would be even distribution. However, that's never always going to be you like that. But as an agency, if I'm looking at this and this is my client, I'm looking and saying, "Okay. We're doing a good job of getting people coming to the site that is ready to buy that they're looking to move forward. That's great. However, what we want to caution here is we want to make sure we're continuing to drive people at the top of funnel as well."
Again, we might have some good call-to-action campaigns going on, but let's make sure we're also building awareness and we've got some longer-term programs going out there, making sure the names out there to continue to drive people to the site. Of course, if that was reversed, and we've had these conversations with clients before, okay, great, top of the funnel, people are coming to the site, but they're not spending the time. They're not looking at what we want. They're not showing those decision-making processes, or they're not making the activity that they're showing on sites, not bringing them to a point where it looks like they're ready to make a decision. And if that's the case, then you might want to have a stronger call to action campaign.
On the agency side, they would always broaden unique types of retargeting campaigns, programmatically, not necessarily people base and it was hard to understand exactly where people were in the funnel. They might say, "Well, if they hit this page, retarget them with this and f they hit this other page, re-target them with that." But that wasn't really indicative of where someone was in in the funnel, how long they've been shopping, what day of their journey they are on, etc. Now having experienced that for years, we have the ability to activate this data, and have true AI activation based on propensity.
There's so much that goes into what we're measuring and the multiple data points. We've had the ability over the last few years to track, end-to-end, from the identification of the household, down to a purchase with a client over tens of millions of customers.
What does AI Activation Look Like with FullThrottle Cookieless Technology?
Let's go back to really what that AI activation looks like. Keeping it simple, we look at everything that we understand about that household. For example, how many times they've been on the site, what kinds of pages they're looking at, how many people on the site, or people in the household are shopping, across how many devices are they shopping. Imagine, there are a couple of different advanced formulas and some we can't fully share. One is more similar to like a weighted average, where we weigh each one of those things with a different part, a different weight, within an overall average. We're constantly having the machine do that average thousands and thousands of times a day to see if our prediction was right.
Did that person actually come in and purchase or buy a service for that particular client. And as that runs, we essentially send that average back into the system and say, "How correct were we? Maybe we need to adjust the weights a little bit." Essentially, it's looking at, on average, 15 to 20 different attributions for each household. Now, it depends on what type of client, it depends on what we know about that household, etc. We're trying to basically come up with that estimate on what will actually happen with this household. Then, we measure ourselves against that estimate and constantly have the AI learn from itself. Really oversimplifying, that's what our AI does and once you have a foundational algorithm that really drives that, then everything else here makes sense. You can use cities, zip codes, and insights to really determine how to adjust your marketing activities. That is what shopper insights are.
How to Interpret Buyer Journey
This is one of the dashboards that becomes very telling to clients, especially after they've been on FullThrottle for 90, 120 or 150 days, because they actually start seeing a pattern of the people who are coming to their website. On that bottom left-hand chart, we're measuring from the time the person's come to the site and they've been identified, to the time they purchased a product or service. Different industries and regions will see that change, different regions, but once you see the pattern established for your client, you're able to watch each month. Well, does anything change? A lot of the time, we'll see the U shape, where a third of people buy within a week of two, and a third buy within two to four weeks, and lastly a third will purchase six weeks plus.
It almost seems obvious, right? Whether you're talking about a car or you're talking about a piece of furniture, maybe you spill something on your sofa or your dog messed it up, you need to go get a new one quickly. Or you may be more of an impulse buyer, and then, there are a large portion, if not a majority that, if you're spending more than a thousand, $2,000, if it's a big purchase, you're going to be taking 30 to 40 plus days.
It does seem like an obvious moment when we say it that simply, but it's unique as an agency to be able to show your clients, "Hey, this isn't just some white paper that you're reading, right? This is your specific data. We understand the entire buyer journey for your particular set of sales and data in this particular month or in this particular timeframe," which is a unique asset to be able to bring as a value add to agency-client relationships.
Once you see a pattern laid with clients, there have also been shifts. This gave them another set of analytics to be able to look back and say, "What did we do differently last month that brought more people ready to buy? Did we have a stronger campaign? Did we have a stronger call to action? Did we spend more money on marketing? What shifted? What do we normally see as a pattern?"
Another example with e-commerce clients, who are under the impression that most people are buying within the first day they come to their website. Some of our clients were surprised, especially in the e-commerce vertical, that people don't necessarily buy right away. Maybe they know what they're looking for, but they're going to continue to do a little bit of shopping, whether they're on your site or another site. When we've been able to show back, some of these analytics, it just painted a different picture for them with actionable data.
Return on Ad Spend
Let's talk about our next screen, return on ad spend. The reason that most people operate that way, is really because of Google Analytics and the way that we've been trained to think. In Google Analytics, there are sessions, and then there are goals, which show you if someone converts to whatever the goal conversion is. What Google Analytics doesn't have as easy as a time-telling is that a more complex buyer journey. For e-commerce, you open an email, click on it, but don't have time to do anything? So later on, you see a Facebook ad and click on it, but again no time to do anything. That pattern can go on for a long time. What ends up happening is that people go in organically through Google search and because they have more time they're going to actually spend 20 minutes looking for that sofa, looking for that barbecue equipment, whatever it may be and filling out a form. Ultimately, what ends up happening is that agencies become classically trained to say, "Well, they didn't fill out the form, so, therefore, the only thing that really works from what Google analytics is showing me, is Google organic search". This thought process is a little self-serving, but also not how marketing is designed.
So when we look at buyer journey and return on ad spend, we look at what channels are working and not working. This is the method to understanding how to bridge those two worlds. Being able to break down your own marketing, seeing what is moving people to your site, from not only an overview, but then being able to drill down as you are right now into the digital marketing, and really seeing, "Well, where are people coming to the site?"
We've all been exposed to Google Analytics, and the sources that bring people to a site, but no one can ever close the end of that piece. And that piece being, did they actually purchase from us? Everyone claims ROI, but no one has the ability to be able to show where it came from and the fact. With Shopper Suite, we've identified the household first, and that gives us the ability to go end-to-end in a conversion to a transaction point with actionable data.
Sneak Peak of Live Keyword Sets
This screen, which is actually live for most of our agency clients today, is where you can see keyword sets, in Paid Search through Google, which most everyone has a sizeable investment in Google Paid Search. You are able to see the keyword sets that are available, what users have clicked on, percentage of sales that those keywords have influenced, all fully in the journey. Then, there's an efficiency score showing you, "Well, out of all the people that clicked on an ad that had this keyword set, how many of them actually came in and purchased as well?" So, you see the total percentage of sales, so that it's weighted that way.
Also, for each keyword set, you can see how efficient that keyword really is in terms of grabbing the market share. On the right-hand side, you will see keywords that shoppers did engage with, but they never came in and purchased on. This is a great way to see what all the keywords you're spending on that really didn't convert and bring value to your business in a long span of time. This is a valuable way to bridge the gap between the online world and the offline world.
As we wrap up, we want to remind our agencies and audience, the five things that FullThrottle is here to do by providing innovative future-proof cookieless technology.
- FullThrottle is cookieless.
- It's insulated from all the Apple changes that have come out with iOS 14.5 and the mobile ID changes.
- It's for helping to increase online conversion and creating marketing activation that's scalable.
- When you have more business, you have to hire more people. So, how do you invest in technology that keeps your margins down, but helps you really scale? How do you have out-of-the-box sizzle and data and insights, out of one platform?
- How does all of that help you deliver improved customer retention and really looking at your revenue source?