Optimove's Science-First Relationship Marketing Hub delivers dynamic customer journeys, true uplift measurement and self-optimizing campaigns.
Hello, everybody. It’s great being here. It’s my first Finovate, so very excited. My name is Pini Yakuel. I’m one of the founders and CEO of Optimove. And I’ll give you a brief description of Optimove and then I’ll talk about three main notions that I would like to convey here, and I think it will be pretty thought-provoking to you, guys. So first of all, Optimove is in the MarTech space, we’re a marketing technology company. And we are, to be more specific, we are a Science-First Relationship Marketing Hub.
So let’s talk about relationship marketing. Essentially, relationship marketing is…some people call it CRM marketing, retention marketing, customer marketing, but this is…our partners, they use great relationship marketing to achieve measurable growth. This is the thing we can help our customers achieve. And to be more specific, we help our partners to autonomously transform customer data into actionable insights, which then power thoughtful customer communications at scale.
Now, today, I’m going to deliver three main ideas that I think will be interesting. The first one is shifting from a static customer journey to a dynamic customer journey. The second one is this notion of a true uplift measurement when running relationship marketing campaigns. And the third one is this notion of self-optimized campaigns, which epitomize the best way of humans and machines working together. So let’s get started with the first notion.
Shifting to Dynamic Customer Journeys
So what you see here on the screen is you see the Optimove calendar. This is, well, it’s kind of like mission control where we run all of our marketing. And think about the customer journey that most software vendors are offering today, it’s a typical flowchart, right? You see kind of like different points in the customer life cycle and there’s decision points. But this thing is not scalable and suffers from many diseases, one of them is that you…the things you don’t plan for, you just don’t respond to. The dynamic journey is a different mindset where the colors represent the different channels, but every row here represents a specific customer state.
So customers could be at multiple different states, and then the data runs every day. And as customers change their behavior, they would get a different message and a different communication at that point in time. This makes the journey dynamic and it lets every customer plot their own path. So it allows brands to move at the speed of their customers and not fall behind or lag behind. Those states is generated both by our predictive model and both by the marketers themselves. So this journey, as the marketing department works on it, it becomes ever more kind of like it complements all the different types of paths and journeys that could happen, but marketers can only think about individual ideas that they want to offer. So this is the first notion.
Shifting to True Uplift Measurement
The second notion is about…if you see in this calendar, everything is measured with test versus control. So all of those bolded numbers is how much money we made on individual campaigns. And the reason that’s very important is because we want…in marketing, we want to get to the truth, right? This is something that historically has been very hard in marketing, but today with digital marketing, we’re able to be so much more analytical.
And every Optimove campaign is designed as an experiment. You can see there’s a test group, a control group. The campaign hygiene is being protected, so nothing else runs in parallel to make sure that both test group and control group are only exposed to this individual message. And we can see then how many people responded and how many people actually bought in both test and control group, and this gives us the monetary uplift, by looking at what is statistically significant in both of these figures. That thing is embedded across Optimove, across the system, where you can see this number goes in any portion of the system. We aggregate this number back into the top and we can look at test versus control in multiple metrics as our customers require.
Shifting to Self-Optimized Campaigns
And the third notion, which I want to cover, is this notion of a self-optimized campaign. So we’ll be going there. So a self-optimized campaign is pretty interesting. And as I said, I see it as the epitome of men and machine working together. So what humans are very good at is essentially designing experiments, right? So if I want to run an ABC test, where A could be a certain value proposition, it could be something that, you know, runs, for example, in a specific mix of channels, it could be many different things, and humans are very good at figuring out what questions should we ask? The question represents the experiment. What’s our hypothesis going into that experiment? But once we set the experiment, we want to run it and automate it. After that, we need the machine to help us understand from the multiple micro-segments and variations of the data what could happen. So this happens here in the self-optimized process. And what you can see here, the gray boxes represents the micro-segments. You can see that although action A is the winning action, you can see that actually action C on one of the micro-segment, it’s essentially the winner.
And all of these micro-segments are coming from the Optimove predictive model, but what happens is that as marketers, we’re no longer required to pay the price of generalization. Yes, action A is the best action but not to every type of micro-segment, not to every type of customers. So through smart mix and match, we’re able here to continuously optimize, and in every iteration, this campaign gets smarter and smarter and smarter. And the beauty is that us as users, we use our creativity but then we let the machine help us with optimization and the granularity, which is what computers excel at. So essentially, these are the main three notions. Again, the dynamic journey versus the static journey, which enables brands to run journeys that are suitable for each and every customer, each individual as they change in their data, they get their own specific marketing communication, this notion of true uplift measurement using control groups, running them properly, governing and orchestrating all of your marketing calendar with all of those control groups so there’s no overlaps and the priorities do not collide, and last but not least is the notion of self-optimized campaigns.
As a company, we work with financial services, we work with retail and work with gaming. In the financial service space, we work with Chubb as an example, in retail, we work with Stitch Fix as an example, and in gaming, we work with Bethesda as an example. We’re looking for more customers in the financial services space. We’d love to see you at our booth and show you more. It’s booth number 104. Thank you so much.