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Interview by Darius Vasefi, RetailTechPodcast

Craig Alberino – CEO, Grey Jean Technologies

Product: Genie – Uses predictive analytics to increase conversion

Interview with Craig Alberino, CEO of Grey Jean Technologies on AI-powered recommendations and the future of commerce personalization

I had the opportunity to sit with Craig Alberino, CEO of Grey Jean Technologies based in New York to discus what Genie, their flagship product does and how it helps retailers, both e-commerce and omni-channel. Grey Jean’s AI-powered (Artificial Intelligence) recommendation engine, Genie, provides highly accurate predictions of consumer purchase behavior based on transaction history, demographics, location, time, social media activity, preferences and behavior.

DV: Intro.

CA: What we (Grey Jean Technologies) do for them (retailers) is we analyze past behavior patterns in order to predict the future. With 72% accuracy we can actually predict their customer’s next likely purchase.  And what does that mean for a marketer? What that means is that they can tailor their communications around the actual purchase behavior and create that surprise and delight that marketers are actually looking to do.

DV: Ok so let’s say the retailers actually have a website and an app – where does your technology actually fit within their stack?

CA: Are we talking about a pure play ecommerce or somebody with a store also?

DV: If you have examples tell me the stores as well. Omni-channel.

CA: Let’s start with e-commerce because that’s the easiest and then we’ll build out into omni-channel. With an ecommerce implementation if we’re looking at someone running a Magento platform we would integrate with their customers, their CRM, their transaction history, everything that’s occurred on the website, promotional calendars, etc. etc. Then we’re going to look at past successes and failures of promotions. We’re going to look at things like the impact of weather, the demographics of the zip codes that are actually purchasing from them, how many hours a day their customers spend in their office versus at home and overall household income. With that we’re going to help them make smarter decisions with what they should be marketing out to their customers.

Now, let’s be more specific. We’re looking at a bunch of data, and using the term big data (which I’m not a fan of the term). But we’re looking at an awful lot of data and we’re applying advanced algorithms. We can call it artificial intelligence, but it’s really just math. It’s statistics and math. Everybody that went to elementary school can actually do big data.

So what we do for the online retailer, as the first example we’re going to address, is we’re going to look at all this data and we’re going to help them optimize the way they go to market. You know, what should a promotional campaign look like? Can we target a deal down to the individual level? So instead of broadcasting a deal you’re going to narrow-cast a deal down to the individual level, and with 72% accuracy we can actually predict that customer is going to take advantage of that deal. So your success rate will be over 72% in an email campaign in terms of a redemption of an offer if you implement Genie.

You also asked about the mobile app and how we integrate with that. We integrate on the back-end using a set of restful APIs – very easy integration. We’ll actually do a lot of the heavy lifting on your (customer’s) behalf. You just point to us the data and we’ll parse the data appropriately because we understand that sometime retailers don’t have the technical staff to do it. On the front end, if you have a mobile app that you’re in love with – which I don’t know any retailer that’s actually in love with their mobile app – we can take our SDK and with a simple, less than 1 day integration, we can put our SDK into your mobile app. That allows us to send a push notification or an advertisement to an individual in order to execute a transaction.

So we’ve learned that Darius prefers to be contacted at a particular time of the day or when he’s at a particular location. For example, his office. Perhaps he has a down time at quarter after 3 in the afternoon. He’s slugging from after lunch and he’s grabbing a coffee and we can get his attention. If we know he’s going to buy something at that time, that’s when we’re going to deliver the message – not when you decide you want to push out an email broadcast to everybody. So it’s the appropriate time and place to communicate with somebody and deliver the optimal message at the right time.

Now if we’re going to broaden the scope out to an omni-channel retailer to include brick and motor stores, sometimes that’s going to be a bit more complicated due to diversity in the back-end POS system, the CRM system and the ESP / email service provider that’s providing that technology. We’re going to have to do the integrations there as well because we do need to have the back-end integrations in order to know the historical data in order to predict the future. It really isn’t a heavy a lift as it sounds like because we have a team of very qualified people.

My CTO and his team come from a Wall Street background, as well as advertising agency, and have worked with retailers before – and I did one of the first large, multi-lingual ecommerce integrations for back in the early 2000’s when the technology was not there and people were not outsourcing these things. So we know full-heartedly that retailers need help. We’re here to help – we’re not an IBM or an Oracle where we’ll charge you a ton of money to come in and help you. We’re a light-weight implementation. We’re a SaaS model.

DV: So it’s SaaS model?

CA: Yes, it is. So we’re going to bring in a lot of data from different places into a data warehouse / DMP, using more modern technology like Spark on the back-end to enable you to make decisions in real time, which you would not be able to do even if you had thousands of staff members.  We’d like to say that we’re an actions company rather than a data and insights company. So we actually help you take an action with your customer rather than presenting you with a bunch of data that you don’t know what to do with.

DV: And I would add to that point that even if you could do it, you should not do it. You should focus on your main strengths, which is figuring out how to serve your customers better instead of creating technology.

CA: If there is commodity behavior that can take over for you at a fairly low cost, rather than hiring 20 staff members that are going to cost you a couple hundred thousand dollars a year each, why not go with somebody that’s like a SWAT team? Come in, fix what you need to fix, and get it integrated in less than 2 months – our average implementation is 6-8 weeks. After that it’s a lightweight SaaS model, and we’re here to support you.

DV: So what about after the sale? What should your customers do to become successful after the implementation is done and everything is running?

CA: Sure, and that’s a great question. What we’re finding is that – and again, the technologies we’re working with are very new and there are larger players out there doing it – if you’re talking IBM or Oracle they’re going to want to put a staff with you. For us, we’ll do what is needed to get implemented and we’ll stay on-site for as long as you need to run certain programs and campaigns. But we’d like to be able to train staff members at the retailer how to operate the system, how to execute campaigns, so that they can be self-sufficient. Then we’re just basically in the back-end supporting them from a technology perspective.

Now that being said, I’ve also worked in the agency world and I know some people need more handholding than others. We have built up a customer success team that is highly skilled and familiar with retail and can help you execute campaigns as needed as long as you need them. However, that is at an additional charge above and beyond the SaaS that we’re talking about.

DV: I think that’s very important. Just from my experience, the technology is really the first half of the equation. It’s how to use it which will really complete the cycle. A lot of companies implement the technology for however long it takes, but then they don’t use it correctly for various reasons. That’s where the people part of it comes into play and training, and sometimes it’s a culture change. You can’t just throw the best technology at a team that just doesn’t understand the value of it and how they can actually use it. That’s why I ask this because I’ve seen it so many times.

CA: I think that’s a great point. One of the things that we do upfront and as part of our due diligence, is we vet our customers as much as they’re vetting us. We don’t like to get into situations where we can’t make them successful despite everybody’s good intentions. So one of the things we try to do upfront is to understand from the top down what is the mission of the company that year – what is the CEO actually trying to accomplish? We don’t solve from the bottom up, we solve from the top down. We work with the CEO and the board members, investors and shareholders to try to understand what they’re trying to accomplish for the next one or two years, and then reverse engineer that into a solution that’s going to work. Then we wrap our product around that solution. So every single customer that we work with is going to be extremely prescriptive. This sounds counter intuitive when you’re dealing with SaaS and you want to get to scale, but it actually makes the most sense because every retailer has their unique needs and their consumers have unique needs.

DV: I think that’s very smart and I would add my own point of view on SaaS in general. The concept that people think they’re just going to sign up and things will magically happen is just not true. Signing up for the software is just the beginning of the work. We all know that, but we just need to be reminded sometimes not to forget.

CA: It’s just another license model. When I worked with the Microsoft organization a few years ago there were two metrics that the sales people worked off of. One was “I have to sell you the software.” The other one was the deployment metric, because if they didn’t get you to deploy the software as a customer then they weren’t going to be able to sell you more software a couple of years down the road. The thing for us is I want my customers to be lifetime customers, and I want to continue to drive their success for years to come. So if the need is to not just deploy, but to stay with them and support them from a customer standpoint, that’s what we’re going to do.

DV: Great. So a couple more questions. First, how do your customers use your software? Is there a separate dashboard to log into, or it is a part of the platform, such as Magento?

CA: Great question. So our product is called Genie – that’s what delivers the magic to your consumers. The customers log into the Genie dashboard and Genie aggregates all of that internal, omni-channel data within the customer systems. So if you’re using Magento we’re pulling data from Magento. If it’s the POS system within your store, we’re going to do that. If ATG is running your loyalty system, we’ll take a look at that as well. It all gets pulled into Genie and then you create something called a fingerprint in Genie. Then we have offers, marketing messages and campaigns. Our metaphor is the people, the product, the campaign. Then we report back to you using our internal dashboard tools and on the back-end. Right now we’re using Tableau, but if you happen to be a powerBI user and you want to check out our success on powerBI we can use that. Again, we’re an actions company, so our reporting back to you is on our success.

DV: Great. And the data is all on your servers in the cloud?

CA: Right, we are housing anonymized versions of customer data. My business partner likes to say it’s like baking a cake. You’ll put in the butter, I’ll put in the flour and there might be other ingredients coming from other places, but the cake is ultimately what we baked. You can’t get the butter back out, you can’t get the flour back out – but we’re anonymizing the data in order to create these fingerprints and the personas in order to deliver the individual deals. So yes, we do store the data, but it is an abstract of the data that makes sense to us and nobody else.

DV: Which, if done right, is an added benefit so the customer doesn’t have to worry about another place or another set of data they have to maintain and watch out for.

CA: Not to drill into privacy concerns too much, but really what we’re doing is we’re trying to teach the retailers be better arbiters of their end consumer’s data because we’ve seen a lot of gaps over the past couple of years with using customer’s data. Through our terms and services, we ask that the retailer must inform the consumer that they’re sharing the data with us so that they can get them the deals in return. So there is a fair value exchange for the consumers, and we’re going to be overt about it because we don’t want to be an Axciom.

DV: Right. It’s better to be upfront about it than let consumers find out by themselves later.

CA: And everybody is selling your data today anyway, so why can’t you (the consumer) sell your data? And why can’t you get something in return? What you should be getting in return is less noise from the marketers and hopefully subsidized products and better deals.

DV: In 30 seconds, can you tell me what you think is the future of retail?

CA: You’re throwing me zinger, Darius. It’s going to take 30 minutes to answer, but I’ll try to answer it quickly. Jerry from Hudsons Bay this morning was talking about all-channel versus omni-channel – where are you ordering the product, how are you fulfilling the product and where does it actually get delivered to. I think he’s right in saying it not omni-channel, it’s all-channel. You need to deliver surprise and delight to your customer at a point and time that’s relevant and provides context to them. If you can do that, you’re going to get them to be more engaged with you and that engagement drives loyalty. We see a consolidation in the way consumers are behaving now. They want to do business with less and less brands, and they want to do business with brands that are speaking to them in their own voice. I didn’t even touch on our political and cause engines in Genie, but the things is, speak to the customer in the way they want to be spoken to at the specific point of time and deliver value to them. Could that be in a brick and mortar store? Sure. Could that be online? Absolutely. The mobile is the most personal device and in the simplest form the future of retail is mobile and it’s going to be your mobile phone.

DV: I agree. Thank you so much. How should people contact you if they want to follow up and learn more?

CA: They can contact us at (email), on the web or on Twitter @GetGenie.

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