Reva: You’re listening to Next in Retail from Publicis Sapient. The podcast that shares insights on unlocking what’s next in digital transformation.
Retailers have been focused on better leveraging their data for what feels like ages now. Since loyalty programs and ecommerce rolled around many years ago, retailers have gained access to tons of valuable data, but not necessarily the valuable insights to match. To help crack this case, our data experts hosted an event and discuss the space in greater depth. This discussion featured a panel of experts from Publicis Sapient and Adobe and was hosted by Sheryl Kingstone, Commerce Lead at 451 Research. In this special episode, we're going to share this live session. Now let's dive in.
Sheryl: Hey everyone. Welcome to today's session. I want to welcome everyone and we're here for a very lively discussion and a topic around the importance of leveraging data and all the facets around that, so that we can really unlock the value and improve the customer experience. And so we're here to share some great insights for some unique research that both Publicis and Adobe have come together, and we're going to review that. I know some of you have already seen this data, so I am joined today by Hilding Anderson, who is the retail strategy lead from Publicis and Michael Klein from the retail lead from Adobe, so if you guys would like to just say a few words about yourself then we'll dive right in.
Hilding: Hey, Sheryl, yeah great great to be on. I’ve spent the last two decades with Publicis Sapient focused on digital strategy and really helping define the future of retail and so thrilled to be here today.
Michael: Thanks, Sheryl. Michael Klein, and I joined Adobe in 2009 when Adobe acquired Omniture, which is the foundation of Adobe analytics. I head up Industry Strategy, which is the team that is responsible for the messaging and the point of view of Adobe in retail traveling consumer goods. Before that, I spent 20 years as a retail merchant.
Sheryl: Absolutely great, and I am Sheryl Kingstone. I'm from 451 Research, which is a part of S&P global market intelligence. I've been an industry analyst for 20 years and what I really like to focus on is improving the customer experience. I have customer experience in Commerce and a lot of my research is all about being dated for that and so we have a great topic today and we're going to dive right in and we're going to give some real-life examples that we can share. And so before we begin, I really just want to give the fact that and set the stage where improving the customer experience is going to be front and center, even admitted what we're doing today with the coronavirus and the pandemic has really escalated the economic impact and the acceleration of the adoption of being more data driven. It's changed and pivoted towards more of those online experiences, and the pressure to deliver consistent and engaging and immersive customer experience was really important prior to COVID. It's important during, and it's going to last. And the data plays a really pivotal role in delivering those optimized customer experiences. It's everything from modernizing supply chains to understanding predictive models, and that's what we're here to talk about today. We're talking about the potential value that retailers can do to unlock their data, but it's really staggering on how many are really just struggling to meet the needs. And we're just skimming the surface of what we're doing, and so this research really does prove it. And, so, when we talk about the value that this really plays out, this is where the questions are going to turn out to be. So, Hilding, I'm going to kick things off with you, and the question really comes down is: you surveyed 150 C-Suite leaders in the retail firms, and so you did find some really pretty interesting insights. Can you really touch on some of those ah-ha stats that popped out for you?
Hilding: Yeah, Sheryl, thanks and thrilled to be here. So, you know, I think when you think about our vision as as you think about the future of retail, we like to think about this you know, we think the next decade is that going to be the decade of algorithmic retailing. And that means organizations that are able to use this topic of data and this kind of powerful engine of data to drive every aspect of their business from, the kind of the personalization area all the way through to supply chain, too. We think there's a huge opportunity around merchandising dynamic pricing, pricing and promotion even internal operations around, HR and and other areas. So in finance is another one that we've we've looked at, so against this backdrop of course this question of how does how does retail better use data becomes incredibly critical, and that's what drove this focus, which on this survey was we reached out to 150 C-suite and senior leaders to understand how how are they using data in their organization.
And the results were certainly mixed, and so a couple of the ah-ha moments that I had, you know, kind of reflecting on this. First, 69% believe that customer data is valuable for personalization. That to me, that's pretty table stakes at this point. We know that the use cases associated with personalization are some of the most robust, and you'll see 15-25% left if you're if you're not doing that personalization layer as a baseline, but the other kind of only 47% in the research only 47% of these organizations are using algorithmic modeling, more advanced modeling, for customer intelligence and personalization. We’ll talk about what that might mean a little bit later, and just 39% are using journey-driven personalization, which again is something that I feel like still lies in that category of kind of table stakes versus really differentiated at this point. Yet the research shows that it's not top of mind for the senior like senior leaders. And then as we think about the the broader shift, the opportunities here, the really the top performing organizations and data we expect to see 120 plus percent increase in cash flow over the next 10 years and the laggers, the ones that aren't able to make this transition to algorithmic retail, are going to see a drop of 10 to 20% in their top line. And and you already start to see hints of this with Amazon's dominance in the market and how quickly they are able to move in the way that they integrate data into demand planning and other areas.
And so in the research we wanted to probe a little bit more around some of the specific use cases that you may be places like Amazon and others are doing to make use and better value out of their data, so and we found that most are using data in a very limited manner outside of that personalization function. So just 37% in our research say they're currently using data to detect or predict a life event. Only 35% are actually actively experimenting with artificial intelligence today. And one of the table stakes use cases is customer 360 right, so the ability we found that just 40% are creating customer 360 sort of these holistic views using transactions site behavior, data profile demographics, impressions, and 3rd party data only only that 40% are using there.
One of the other areas we probed on is around search. You know, we know that search on most landing pages is what 70-80 plus percent of the total total traffic driver, and only a third of our respondents are using cognitive search, and that's such a huge miss, whether you're in grocery, there's huge opportunity to use what you previously bought to inform the search experience that you have. You know, if I'm if I always get organic yogurt why when I searched for yogurt why aren't why isn't that at the top of the search results? Instead you show me, every kind of every permutation of yogurt as I go through there. In retail and apparel, there are many similar use cases, so the fact that only 1/3 of executives say they're using cognitive search I think is a considerable red flag in personalization. We talked about the 69% of personalization. What we also found on a better note that 65% are actually using data to offer discounts and recommendations, so it's good that there are you as an industry we're starting to see some use there, but only 46 only 46% are using personalized bundling as part of those recommendations and that drops for 44% for conversational recommendation systems, which I'm sure as many of you know is a major area of investment and exploration for a lot of retailers.
So, in some and there's a lot more detail of course in the report, and we'll talk more about it today, but most retailers are using data for personalization, but there's a major miss in that they're not involving data and embedding data into their other areas, particularly around merchandising and around supply chain. And in fact I think there's a bit of hubris here too when one of the one of the notable stats is 60% of all retailers report their above average when it comes to their competitors, and if you think about that for a second, I think kind of reflects on where we are because I think a lot of retailers and a lot of certainly executive leaders probably don't understand the full potential upside here and that to me that's the biggest takeaway, Sheryl.
Sheryl: Yeah, absolutely. It really is about not understanding what you don't know. It's about not really understanding the value of the data and the fact that we're only using it really in silos. And so when we talk about the silo data part of what I see is that there's a lot of retailers that think they have that 360-degree view or still trying to build it, but they just don't know how, they don't really have that ability. So, Michael, let's talk about what exists as an opportunity to address some of this challenge here, especially when we talk about silos using that 360-degree view and then really unlocking the potential.
Michael: Yes, and it’s both, Sheryl and Hilding, a bench and the 360 view of the customer, the holistic view of the customer, whatever you want to call it, is certainly the Holy Grail that everyone's looking for. I'd say that in working with many of our customers because it's some of the challenges of the silos the online and the offline elements of retail in particular and other businesses we’re probably seeing it best, our customers getting to a 300 degree view of the customer with still some gaps in that. There are a lot of options out there, and I know we'll talk a little bit later about the crawl, walk, run, and I think it also depends on where you are in size of organization. We have many of our large enterprise customers who in the past few years have been investing in the idea of a data lake. We're working very closely with Microsoft in particular and building a lot of our data solutions on top of Microsoft Azure and their data lake, and that might not be an option for everybody depending on the size of your business, but there are other options.
If it's not a huge data lake that is bringing in and trying to break down some of those silos, we get into the world of acronyms, CDPs and DMPs, so those acronyms relate to DMP as the data management platform, CDP being the customer data platform and some of that also relates to where you're going to sit and have your governance, your PII, because in the data lake, there's going to be a lot of data that you're not going to want to expose to all parts of the business, and that's where you need to start to have that governance as well. And we see some great use cases on the use of a data management platform that allows you to bring in the second- and third-party data and still protect privacy in that PII. The other option with the CDPs, which Adobe has a CDP that sits in the Adobe experience platform on top of Microsoft Azure data lake, and that's where customers are going to have that option to blend both PII and non-PII data to really be able to then personalize, do the dynamic pricing, some of those use cases that Hilding just referenced.
As we think about the different options and of course the analytical tools that the different parts of the organization. As I indicated, I come from the legacy of Adobe analytics, and we have many customers that they’re in dashboards, they're in reporting, they may not even be touching the CDP or the DMP, but they are getting the benefit of those data sources coming together in both with governance and with privacy protection and PI being in the right places, so that we continue to honor the consumer behaviors in the desires to to maintain privacy because we know that's also a hot button. So, it is a journey in terms of getting to true omni-channel analytics that we might refer to sometimes and being mature in that of going from dashboarding typical mobile analytics being able to understand traffic conversion rate and then moving all the way through to the maturity cycle to predictive analytics multi-channel attribution and being able to really deliver that personalization at scale through AI in ML.
Sheryl: Absolutely, and it really is understanding that alphabet soup and bringing a little bit more clarity because the bar has risen. And we've been talking about the whole CRM and DMP and the growth of CDP, but the Holy Grail is to make sure that we're able to get that single view of the customer but also act on it. And so businesses are really trying to learn from others, and it's great that we've pointed out about how they think they're doing well and the fact that we're using some machine learning and AI out there and we're expanding and getting the data across multiple different departments, but, Hilding, the fact that some companies are still potentially still learning… do you have some examples of what this looks like? And I'm going to start with you – if you can walk me through an example of how that businesses are really, or retailers are really using the data in some innovative compelling ways?
Hilding: Yeah absolutely, Sheryl, and this is a moving target right, there's a huge amount of exploration happening even, on the most advanced, partners that we have in clients that we have. I look across our entire North American business and we've got a range of clients in different levels of maturities. I'll tell two stories today about the clients at different different levels. And Publicis Sapient itself is kind of purpose-built for digital transformation, so this role of kind of thinking through data and building a solution around data is is pretty fundamental. And so the first example kind of story all tells around a large multinational retailer with a major financial arm as well as a very robust apparel. And they also have a home improvement and grocery business. And the data across each of those was of course was noisy like most retailers. Retailers push out 40 terabytes of data every hour across the industry. But but for this client, they were struggling with not just the individual silos of the individual business units, but also cross-country data challenges as well, and so one of the things we help them with is well so and furthermore their individual retail hardware and grocery businesses were unable to access any of that data on their own because it was in silos right and in fact had duplicative data, so they had different households had different views around what the what the income looks like and what the preferences are as related to their core business.
They also often had duplicative loyalty programs for each, and you could imagine how complex that got very quickly and so ultimately the leadership I think went out will talk more about kind of the broader vision, but they were able to say OK we have a vision for moving the needle for algorithmic retailing and centralizing this data to the extent that we can certainly at the country level across all of our business units. And to do so, there's a whole bunch of work related to building this kind of core platform and in this case it was a customer data lake with some additional layers of of insights on top of it as well as a whole sort of set of activity and work around data cleansing and data purification as part of the of the intake process into that CDL, so to have that CDL and this was we were able to do this over kind of nine months 12 months’ timeline to build to go from zero all the way to a full solution even though even with a custom cloud-based platform.
And now the results are pretty exciting. So first of all, this was at the C-suite and the CEO of this entire organization signed off on it, the board was being talked about it, so it had the kind of executive-level visibility that you need to have with some of these programs. And we've created now over 25 active use cases. We have another 25 that are in flight, that includes both some of the core elements, like the customer 360 customer genome as well as more advanced analysis around customer lifetime value, for example, and the ability to enrich data from any of those buying areas any of the business silos and to get a single view into those. We are also, so on the marketing side's a lot of initial use cases that we see with our clients is the values around that initial marketing and personalization. We saw a 10 to 50% improvement in click-through rates for the marketing campaigns, which obviously flows directly through to the bottom line. And then you also see we had over 150 people who who have been trained on the platform and are now rolling it out across the individual business units and very soon into two other countries as well as this is a large multinational, so this kind of custom CDP from idea to actually execution to providing a single version of truth, and this customer views been hugely impactful for this for this client.
The second example I'd highlight is kind of a fun one around food and beverage, so this is one of the leading multibillion-dollar food and beverage organizations. And they really struggle, they’re I would say a little bit earlier in their journey in that they have some personalization, but really don't have a good view in house holding data, don't have a single view into who their customers are an and haven't really thought fully about this connection between the loyalty program and how do you activate merchandise on top of it. So, for example, my wife and I have different taste in red wine, right? I'm more of a French red tannin red wine drinker, she's more of a California red, and and we both like champagne, and so for a food and beverage organization I talked earlier about this the challenges of bundling right and providing product recommendations. Our research showed that just 46% of respondents are using personalization for personalized bundles. In the food and beverage is a great example of how you could better combine that, why not create an offer that makes sense for my specific household where you have a mix of these different types of red wines and white wines and champagne, and offer it at a compelling price? And even offer a subscription model on top of it. And then you dynamically do the pricing depending on seasonality or some other variable, so you start to see and you look at customer lifetime value, so you can make a good decision about is my household of the right customer to drive loyalty since I haven't ordered there for for 60 days I'm at risk of churning, and so I can target them with a specific offer. So you really you start to see how data becomes integrated into the the all every aspect of the business strategy that these types of companies are grappling with.
And then the third one is just kind of a smaller firm, I mean, a couple billion, small relatively speaking, smaller firm that we're doing some interesting conversations around supply chain, so we think that there's huge we know that there are massive opportunities in supply chain and for this 6 billion-dollar firm we actually have found opportunities in two areas in supply chain. One is around returns optimization and that's identified valuable close to $6,000,000 just in the returns optimization. And the other one is order optimization, so kind of just using data to decide where and how you source products for the greatest efficiency and that too was another incremental $6,000,000. And these are by the way cost reduction, so they're actually equivalent to profit dollars, which means about 10x the value of a revenue dollar that that come down so really speaking to how what were the patterns we're seeing from our clients are that yes you're doing personalization, but there's more that you can do as you think about bundling and others and very quickly you need a platform to help you pivot to those algorithmic questions that pivot to those core operational questions that are going to be what separates the laggards from the leaders over the next decade.
Sheryl: Absolutely, and that's what we’re all here about, is to understand how they can be more of a digital leader. And those are three great examples specially with respect to personalization and digital transformation and the data lake. A lot of companies are really investing in data lakes, but yet they don't have the layer of data governance, and they're not really using it to the full extent. They're just using it like let's throw all our data in here. And so, Michael, when we talk about these digitally driven retailers and how they're really trying to be more advanced, and we talk about the dollar values, so my research shows that there's like multiple billion-dollar catalyst for improvements here in personalization and cross-channel buying options. There’re so many different ways to reduce customer friction points, and data is at the heart of that. So what are the innovative ways in the compelling ways that you're seeing for your clients that are really taking advantage of data and being much more digitally driven?
Michael: So I'll bring up two examples, and the first is a smaller company 250 stores based in Australia, Petbarn. Before COVID hit, they were leveraging average order value in tying that to their different levels of loyalty and being able to understand what type of offers they needed to and discounts they needed to provide their different levels of their loyalty program based on AOV and how they could move that needle of AOV up and down and bring in some other data points. But AOV was one of their primary data points that they were basing some of their segmentation on and in looking at the different layers and tiers of loyalty. But then as COVID hit and they started to have that challenge of stores that either were dark or consumers just didn't want to go to the store, they needed to quickly pivot and be able to offer delivery and curbside pickup. But then they also had the challenge of could they meet the demand and in order to be able to do that they relied on the data as well as the personalization engine to be able to understand where they needed to kind of increase the gas or pull back on the gas so to speak in terms of where they were going to offer and they had the ability they started to see supply chain and fulfillment start to get choked a little bit, they're able to then quickly determine that they needed to stop or just not offer it to certain segments. Same day delivery was part of their program that they were offering as well for their local customers. And they then seemed to use those same data points that they were using for same day delivery, curbside, buy online, pick up in store, which we know from our research the Adobe digital insights huge 200 plus increases in BOPIS over the past six months depending on the month we're looking at, they were able to use the same tactics on how they were rolling out their chat features. So really taking data and kind of getting a hypothesis working in one area and then taking those same hypotheses and those same tactics to other parts of their business going from loyalty, going to fulfillment, buy online, pick up in store, curbside, same day and then bringing them over to chat.
The other customer the other example we've been working for many years with Home Depot. They started on a journey with us now 10 years ago where they really wanted to transform digitally and many of you who are consumers of Home Depot probably are seeing some of the benefits of how they can get us through a store very quickly and way find us. One of the biggest challenges for Home Depot over the years has been they have two sides of their business they have professionals and they have consumers, and it's critical for them with 108 billion dollar business to be able to understand on a Monday, Tuesday, during the work week seven AM 8:00 AM, they've got a line of trucks outside their stores waiting to pick up their goods for the day, the materials for their particular project they're working on is the professionals. But you and I on a Saturday are walking in and trying to figure out what we're doing in terms of our DIY or, you know, the honey-do list as we sometimes joke about what we need to take care of for the weekend, and we know also in the face of COVID, that home improvement gardening is huge spike in sales for ecommerce as well as in store because we're at home and we're trying to make our homes look a lot better everyone can see what my home office looks like and these paintings weren’t up on the wall when a few months ago, so yeah home improvement is a huge…
Hilding: It looks great, Michael.
Sheryl: Yeah, it does.
Michael: Yes, ah, I take no credit - that's my wife. But they are now using the data management platform the CDP that Adobe is providing for them to be able to personalize and understand whether they're in front of a professional or they’re in front of a consumer, that's related to a 20% increase in online sales even before COVID hit. 50% increase in online orders that are being picked up in the store by consumers and again this case study is from just before the COVID pandemic hit us, and I'm sure they’re still and continue to see the benefits from that and they do a great job with their mobile applications and how they optimize those applications to not only give you awareness through the data of what inventory is available, but where it physically is in the store and giving you the ability to way find right to that location through the mobile application.
So two different enterprises, one a little bit smaller based out of Australia with only 250 stores that may seem depending on who you are maybe like a lot, but if you're somebody like a Home Depot at 100 billion plus in sales of which I think over 10% of that is online two different examples of large and small retailers.
Sheryl: Absolutely, and I was shocked when all of a sudden I got the consumer research and showed home improvement skyrocketing in March-April, and then it just continued right outside of PPE stuff, so really interesting, glad that Home Depot was really above the curve on that, and that they were able to optimize their business strategies because of it. And that's really something that retailers are really struggling with today, and if you think about the business strategies and managing the inventories and then the fact that we have Amazon and all these different marketplaces then we have to manage assortment strategies. And, Hilding, you have a take on on some of this in how they can handle the different types of places that they're trying to sell and some of the marketplace scenarios and assortment strategies that are coming into play there.
Hilding: Yeah, our management consulting teams, that's one of the top questions that we get of course is: how do I compete and more importantly how do I add more value for my customers, using looking at my question around assortment? And that's really where marketplace starts to start to emerge as a key factor, so we're we're helping a lot by the way a lot of different kinds of marketplaces, right? So you've got the peer-to-peer marketplace where you want to create a platform to let people buy and sell new or used gear, you have often you will see kind of customers who to professional, trying to schedule services at at a home improvement store. There are many different, watching entirely new business models associated with the subscription platforms. Another very very common ask that we get and we try to grapple with, how how large is the opportunity? Does it make sense here? And it all, by the way, ties back to this question of data because to compete in this next decade, you're going to have to rely on your data as a differentiator and your understanding and knowledge of customers needs to be more than just I'm I'm a transactional brand, right? They can. It's so easy now to transact with anybody else.
You have to have a reason as a competitor in that space for that customer to want to come to you, and that's why we've seen this blossoming of loyalty programs that's why, you know, subscription models are so critical because it's a recurring it's a creates a reason and aligns incentives, so that both parties have a reason to go and use more value and give feedback. So we really think that we're seeing a kind of this massive shift towards retailers saying look we've got to be, almost a passion brand for your customers, and we've got to create reasons for you to come into the store. We have to create a reason for you to go to our site versus one of our competitor’s sites, and that of course drives immediately to the marketplace question and sort how much assortment do we need, how do we do pricing, and promotion. All rooted in how well we understand our customers – how well we use data.
Sheryl: Absolutely, and so these business strategies are really all over the place. I've seen the subscription economy really grow very quickly, and it does add a lot of complications. Michael, what have you seen?
Michael: Yeah, I’d echo a lot of the idea about marketplaces that Hilding indicated. It all in some respects, comes under the umbrella of this idea of endless aisle – of really being able to offer much larger assortments that we may not be able to have confined within 4 walls of either a physical store or even a distribution center. We've been working now through our Magento Commerce and our partnerships with miracle with Albertsons on their marketplace. And their marketplace is really about giving, not only their existing vendors, but vendors that have never been on the shelf, the opportunity to sell to and merchandise their product to Albertson’s – the different 18 brands that they have in the consumers in different states cottage industry food products that may not have ever hit the shelf before.
They've talked about one particular peanut butter brand called, I think it's Home Plate. It's a brand that was developed by a couple of ex-baseball players and, it's this really high-end peanut butter, and they are now able to offer products like that to thousands and thousands of customers through this idea of a marketplace in terms of the product. The other interesting part of these marketplace relationships is going back to the focus of today's conversation around data is the ability to share data. And we see many customers who whether it's having a physical marketplace or perhaps just a marketplace of data in some respect or some question or or some respect of being able to understand segments and work with their vendor community large CPGs where there's been kind of a black hole.
CPGs, I've always wanted to have more information and understanding of what's happening with their products and how do they get more targeted with their relationship in their offers to the consumers for a particular retailer, so not only being able to offer products through a marketplace, but we see some of our large enterprise customers leveraging a data management platform to be able to with respect to PII and through privacy anonymously share segments and offer those two particular CPG companies, so that they’re co-marketing their shopper marketing is much more targeted, and they're getting a better return on their investment. And we see that with many of our grocers in particular mass merchandise retailers that have large relationships with the consumer goods companies being able to really strengthen those relationships, not only through product marketplace, but through data marketplaces.
Sheryl: Absolutely, and one of the things that really requires this shift in business strategy has to do with the complexity. And so I always get the question of, how do you handle the complexity of planning and orchestrating and managing the overall customer experience? Is there one department, are there new leaders coming into play? You know who are you seeing the new leaders that are stepping up to really help navigate this? I'll throw it out to both of you.
Hilding: Do you mean leaders in terms of the different sectors or different different organizations?
Sheryl: Yeah, so so what are you seeing things like one of the things I'm chief data officers, chief digital officers. There’s new executives that really need to step up and you can also look at it from an IT and line of business standpoint, but I do think there's new executives that are really heading the game here, like the CDO.
Hilding: Yeah, I can I can take this because we do a lot of kind of consulting and support of organizations as they try to transform, right? And part of that transformation, it's really starts and ends with leadership. What we find though is that there's no there's no one answer it depends on on the organization, but broadly where we've seen the most success is when you have a leader that is probably not at the at the CEO level, but you have a chief digital officer or chief data officer who can paint the vision and can really sell the organization on the change that has to be made. And so when we think about this kind of leader, it's somebody who usually has a relationship with the CEO, usually has a relationship with the board, so it’s that level of leader, it's not it's not you're not 4 levels down, 5 levels down. This is somebody who is, has been at the organization often for many years and has very skilled kind of relationship manager who can navigate the complexities of the silos, who can navigate the complexities of the different political organizations within within the company.
But they also understand the technology well enough that they can lead a team of data scientists on on her team or his team to drive outcomes, and that's that's only one one model, and then the question of course is so well should we be federated? Are we, are we centralized, are we decentralized? And that really varies, but certainly as the research shows where I believe fairly early in the algorithmic journey for a lot of organizations particularly as most organizations today are focused on personalization to get to the next level of transformation really requires a centralized organization for a period of time. After which you have to have to really democratize access to the data, so for this initial phase when you are trying to go from maybe 5 miles an hour to 60 to get on to merge onto the highway where Walmart and Amazon are already speeding by an 18 Wheeler, you need that tight controlled leadership who has the knowledge and the ability to sell the P&L owners within the within the business units for example on the on the potential outcomes that are ahead of you. So that's that's certainly what I've seen in my work.
Sheryl: Yeah and even with data leadership – here's the thing, so we're seeing democratization of data, we've seen the importance of the data scientists come into play, all the CX executives come into play, and, let's face it, even though data leadership is there, retailers are still struggling with that data cleanliness. And, Michael, you've seen some ways that we can focus on really improving that over the years, so that we’re able to make sure that we have the right data at the right time.
Michael: Yeah, I think, and, as a follow on in terms of what Hilding was indicating about the CDOs, we're seeing the CDOs really push for the idea of a center of excellence, especially with large enterprises that might have the multinational retailer or enterprise that Hilding indicated that is in banking they’re in travel they've got variety of businesses apparel home improvement. And each of those businesses have certain nuances that they all want to have somewhat, and it goes the same with kind of the consumer brands house of brands customers that we think about, but many of them are building a center of excellence that is driven by the CDO. And that's not to say that everything comes out of the center of excellence, but they are the ones who are making sure that there is data integrity. They're helping make sure that there is great governance and best practices occurring across the organization and typically they're holding up either one business unit or one brand to the rest of the organization, and they're the pilot for everything else that's going on across the whole enterprise.
Two customers that we've been working with for a while a couple of years ago I had Laurence Steinberg, who heads up digital for Loblaw up in Canada, and she was on stage with us at Summit a couple of years ago and they've made some significant shifts in how they set up their center of excellence, what they're doing to drive a culture of testing and really tapping into the data, and we're seeing great things coming out of what they're doing up there. I see Sheryl smiling because she's based out of Toronto. She's just probably a Loblaws customer, but, and I constantly see whether it's on LinkedIn or other areas that always looking for new talent because while we have CDOs and we have these centers of excellence, one of the big challenges is how do we get the right skill set in the right talent in the organization? Sure, we can continue to work closely with our partners and like a Publicis that brings great thought leadership and expertise and strategy to be able to handle this, but I always talk about three legs of the stool to be able to really get the most out of your investment, and that is your internal resources, the technology that comes from Adobe in our platforms, and then the great partners like we have with Publicis Sapient to really give you that leading thought leadership and be able to get the most out of the resources you have internally as well as externally.
The other gentleman that I worked had worked with in David Walmsley, who's the CEO of Pandora Jewelry based out of Copenhagen. David's been on quite a journey. He was at Marks and Spencer. He was at John Lewis. He now is CDO over at Pandora. And they're making big strides along with Microsoft as I mentioned or to build out the right infrastructure the foundation that center of excellence in Copenhagen, but as we know, they’re a global organization, and they've got offices on the East Coast of the US and they can't control everything, but they can deliver the right capabilities, the right best practices, the right data integrity to the organization, and that's where I see a lot of the magic happening where we've got that CDO that center of excellence, and then we allow those best practices to proliferate to the different lines of business in the different constituents whether it be even on a smaller organization might not be as large as the Pandora or Loblaw or a Home Depot, but smaller one and being able to allow as Hilding indicated, this has to touch supply chain. It has to touch merchandising, it it's not certainly Adobe we're very focused on marketing and personalization at scale, and that's a big part of what we do, but there are so many other parts of the business that have to be affected by this center of excellence and the chief digital officer.
Hilding: That's the start of the journey, right? I mean, that's that's where, that's and that's where a lot of the immediate business value come from, but that's not the end.
Sheryl: Yes, so regarding Loblaws, like I always say, that experience, not price and products, will be the differentiator in the future. But I will let you know, that experiencing their President’s Choice Decadent Chocolate Chip Cookies is a product worth experiencing. So on that note, I do want to also remind people to put their questions in place. We will try to get to some of those, and one of the ones that did come in, and I just want to throw it out to you guys, is it's the question of the return on investment. And so do you have any insight on how you're going to – we talked a lot about data lakes and a CD customer data platform and investments in the data – but what does the research show from a payback period? And I know you can look at it from a crawl, walk, run, so just going to throw that out, the ROI. How are we going to do it?
Hilding: Yeah, the study asked about that specifically, and what the C-suite respondents said is it's kind of two years, two to three years type of payback period. I actually think that's a little high. We generally are seeing payback periods of even shorter. Again, depending on the complexity, if you're doing a full custom build that's one solution, it's going to be, you're not going to be done with the build for at least six months, but the for more of a package based solution, you're seeing much shorter ROIs. So and then in terms of magnitude, I think in the research we saw kind of an average probably median magnitude of 40 plus percent ROI expected over that period. And yeah as high as 100 so, pretty pretty significant when you combine multiple use cases, and you link it to the core operations of the business it's a, it's a pretty, this is why when we talk about the broader opportunity size, you're talking about really discontinuous jump of the line is not just oh it's at 5 or 10% it's 120-ish percent over over five years, so…
Sheryl: Yeah, Michael, what have you seen with businesses trying to create that business plan and understand that study, so that they can get that return on investment?
Michael: Yeah, and as we've indicated, it's definitely a crawl, walk, run as I talked about a couple of our customers. You know, Home Depot, we started on this journey with them 10 years ago, and they’re they’re continuing to see benefits. The Petbarn example, they were able, Petbarn, to stand upa couple of our solutions around personalization and data, and the loyalty piece that they had in place to get very quick results in less than six months. You know, we've seen the likes of some of our health, beauty, and pharmacy customers, like a Rite Aid, that invested and then had very specific goals for their flu campaign in 2019. And in leveraging only three of our solutions we’re able to exceed their expectations for the flu campaign in the month of December, before they even got to the end of the season in March. But, as Hilding indicated, it's not an event, it's a journey. And it's a journey that's going to take a while, and if you really want to get to full maturity, it is going to take a little bit longer to get to true leveraging of predictive AI and ML. You know, the the magic number sometimes for us we see, and we've done some studies as well where customers that are investing in five of our solutions, are seeing about a 2x return on their investment in less than a 12 to 18-month period. But there is a lot of heavy lifting that goes in that and again it goes into that that magic trilogy of the three-legged stool of partner, technology, and internal resources.
Sheryl: Absolutely, and the crawl, walk, run is really important because you if you make this 2, 3, 4, 5-year view of the world things change, and you'll never achieve success, and everyone wants to have that success, and it can be very difficult. So one of the questions we actually did come in – it has to do with being a dominant, like competing, again this space with a dominant player and what was really interesting about this question is one of the key players is very dominant in their space and how do you win customers’ trust? And that's what's most important here is around trust because over this past year my research shows that the trust has actually been depleted, and customers are much less trusting of businesses than they were a year ago, so this question that was asked is really apropos, so I'm going to throw it out. Hilding, I know you saw it, you can answer it. Michael, and you can answer it, too, so so far because trust is so important to build.
Hilding: Yeah, one of the other pieces of research that we've had recently that would answer this question is around what do customers care about the most in terms of making buying decisions. And I don't I don't know is what sector you're in or or details about what your business is, but ultimately the what we found in the research anyway was that the number one criterion is product quality, the second most is around convenience, and the third is price. And obviously this varies substantially by industry sector and other things, but if we just think about that major changes have happened around convenience, it didn't used to be that convenience was number two, price was almost always number one or number two, and I think what we're seeing is a little bit of a reshaping in the market between how do you prioritize and what is important to these individual customers where convenience suddenly, next day two day three day type of or pick up in store at particularly accentuated by COVID becomes critical aspects to the to the value offer that you have to make. But it still falls second to product quality, so understanding what, what the sector is and how you think about it I think you start to then think about what does product quality mean for your customers? How do you drive higher loyalty? Who do are you able to identify the highest customer lifetime value customers that you have today? Are you doing everything you can to keep them from churning? What type of promotional strategies do you have associated with that? What's your supply chain look like? Is it using data effectively? So there's a whole diagnostic that we go through when we have a new client to help them assess what's their data maturity.
Sheryl: Absolutely. Michael, do you have anything to add?
Michael: Yeah, as Hilding indicated, I think where we were seeing early in the year price product being top of the list, coming out of COVID and the pandemic, that shifted a bit. We've also just released a study demographically, and the idea of safety and security is also, kind of, is rising on the list of consumer trust. And not only the convenience piece that we also see, and I would echo that as well from Hilding – that that idea of convenience allows me to transact with you the way I want to transact with you, and whether that be delivery, whether that be the buy online, pick up instore, 250% plus buy online pick up in store increase for the month of August. You know, huge numbers. We don't see that. Certainly I don't think we'll have 200% plus increases every month on focus, but it certainly is going to be double digit, if not triple increases, for BOPIS in the coming months and certainly going into next year. But, and then, there's a distinction between what the younger demographics are looking for because they are willing to share that information, and that comes back to this whole idea of data, and they're a little less concerned about the privacy. It's kind of interesting, as long as you give them value for that experience, they're willing to share that information and maybe not be as concerned around privacy because they understand the quid pro quo of if I give you my information, it could definitely benefit me in terms of either better offers, better experiences. But then the older demographics are certainly still concerned about convenience, supporting the local retailer, and making sure that they have a safe and secure experience either around the privacy of their information, or that they're not going to get sick by going into the store.
Sheryl: Yeah, absolutely. So what we were seeing also is a heightened demand for convenience, context, and control. And control is very much around the data, and the experience, and knowing that value in understanding that brand trust that came along with it. So another question – we talked earlier about this, but maybe you need to just summarize it a little bit more of, is breaking down the silos is still a struggle for a lot of organizations, and do you have any suggestions on how to go about doing that?
Hilding: I mean, what we see is that you've got to have this broader framework, right? So you've got to have executive-level sponsorship and a clear commitment to breaking down and to telling the story to those silos about why it's in their interests to consolidate, probably consolidate, the data. I mean, I remember one client, it took us I think, it took us three months to get the business silos on board, and there were 1,000 excuses, right? There is the ‘Hey we can't, we need this data in this lake because it feeds all of our core ERP systems,’ or ‘Hey, the data is noisy, and it's going to be too painful to transform it’ to ‘we don't have the people.’ I could, there's just a lot of excuses, but ultimately, it came down to are you bought in? Do you understand the business benefits and the impact that you're going to get from this transformation? And if you tell that story, everything else will come along.
Michael: I would echo that. I think that comes under the whole idea of democratization and there's there's if personalization is somewhat the Holy Grail in many respects, there's also the content piece that needs to be considered as well on this because we're now at a point where the data management platforms, the customer data platforms, allow us to get to that segment of 1-to-1 to 1-1-many, whatever that may be, but then part of the challenges is how do I then connect a piece of experience or a piece of content, and we've got like the likes of like an Under Armour that is using great tools of ours to be able to tag all their content on the fly and not have people manually injecting metadata into their content. So that's hugely important, and we're seeing also under this whole idea of democratization, when the creatives in the other parts of the business that aren't responsible for the data start to see the data and you can't argue with numbers really, that's where you also see some of that great magic happening because they are then brought into the fold, and they're starting to really be feel like they're part of it, and there's a lot of ah-has that go on across the business.
I know in my earlier career at Omniture Adobe I was doing a lot of optimization of internal search and navigation, and how many times did I go into customers and talk to the merchandising group, and they never saw a null search report. They never knew what people were searching for as merchants that were getting null results, and how that could inform their business of the products that they should be going after, and their assortment that they didn't already have because there was consumer demand being pent up in all of this information that nobody was sharing. So, I think the idea of democratization, and then really proliferating that, not only across the digital teams and the data teams, but also for the for the creative teams and merchants and fulfillment folks.
Sheryl: Absolutely, and we're really, we're coming up to the close, so I want to just give one last question to our wonderful panelists and thank them for their time. But what do you really see, just very quick, what's the future? And where do you want to take it up to this next year? There's been a huge shift this year with COVID and everything's going digital.
Hilding: Well, I can share our point of view. I think we we put together, we have this conversation regularly, and I think what you see is that, this is a hopefully a once in a lifetime type of type of event here, but it has made a long-term change in how customers act, and behave, and shop, and so although we're not going to go back to, I think it was 35%, 33% of all retail sales happening digitally, you immediately we are on a different line. We're on a different trajectory than than we expected to be at this point, and, by some measures, werre five years we’re 10 years beyond where we expected to be. The ramifications for that are still reverberating in the market, and the the mall – the pressure on the mall-based retailers – the restructuring of stores, the changing storyline about how people shop, we think it's a real and permanent shift, and that retailers need to adapt to this new environment. And it's one that's where digital is going to be more important. It’s one where data is absolutely essential in terms of creating relationships with your customers and building and sustaining those relationships over time.
Sheryl: Absolutely, totally agree. Michael, what do you see?
Michael: Yeah, just a couple of quick data points to just reinforce what Hilding indicated. So in Holiday 2019, November-December, we saw a 14% increase year-over-year in ecommerce sales. For the last three months, it's going back to June, we saw, and while it's slightly declining, 77%, 55 and 45% increases in ecommerce sales for the last three months – June through August. Mobile – we know mobile is taken over in terms of traffic. Sixty percent of traffic in August came from a mobile device in North America. Forty percent of ecommerce revenue came from the mobile device, so mobile is going to continue to grow. We predict that sometime in the third quarter of 2022, mobile revenue will eclipse desktop, and that might even come sooner, especially as we think about 5G. But if you're not already optimizing and putting a lot of time and effort into mobile, it's time to get on that bandwagon.
Sheryl: Absolutely. Great way to close it out. The future is actually here, and we have to manage for it. Data is essential, and it's all about understanding how you can get on that maturity model to succeed and using data to improve the overall customer experience. I want to thank Hilding and Michael for their excellent input and the data that they have in this report, and feel free to follow up with any of us.
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