This is not a new idea. Several years ago this was a common conversation topic when I worked at Oracle, and I believe some such as Walmart (big MSFT partner) and Kroger have already moved on these opportunities. If you attract a huge online audience then yes, this is great! Monetize your data, sell access and insights to suppliers as part of the overall trade relationship. It can be a win/win - so long as the advertising is relevant and not distracting or damaging to the CX. But I agree with Nikki Baird in the first comment of this discussion. Not all retailers are able to attract a large enough audience to be an ad platform that suppliers can prioritize in terms of their ad spend. In the end, of course, Mr. Nadella is making a business case to have Azure be the platform for all of this (that was the idea at Oracle too) so it's both self serving and a bit true IMO.
I don't know if the advantage is "sizable," however it's clear that there is a large segment of shoppers to whom this sort of CX, when executed well, really appeals. That is the key takeaway IMO here. Being a shopper myself, when you procrastinate and experience at least a few delayed online purchase deliveries, the idea of getting in the car and picking up the merch you bought online becomes really appealing.
Retailers have a lot of incentive to make this a really easy experience: "82 percent of BOPIS users are likely to shop for additional items at the store."
To that end obviously it's important to ensure inventory is tracked as much in real time as possible and updated online and at the store level. So that the merch a customer buys is held for pickup in the store, and confirmed as such beforehand.
Nice to know this was a theme: "It was also encouraging to see technology vendors take a more practical approach to the challenges faced by their customers."
Hype has been rampant in recent years, but I expect many retailers are fatigued by ill conceived promises of transformative tech to address the huge challenges in the retail landscape over the past few years.
Practical, measurable and timely steps are what most retailers need today, especially around how to best apply and scale AI and other advanced analytics. It's truer today more so than ever: you can't manage what you can't measure and a business model in flux is not easy to work with. I expect to see a lot retailers take parallel paths to get their data houses in order, while at the same time moving on AI use case opportunities with an eye on learning and scaling.
Also theme-wise, the whole cloud to on-prem IT strategy seems to be taking hold as it becomes clearer the advantages of a hybrid strategy. Not long ago we are all going "cloud cloud cloud!" Love it, but in practice it's not likely to be that cut and dry.
Loyalty programs are usually presented as a "give to get" whereby there is a value exchange. If the consumer perceives less value from the "get" they won't join.
Unfortunately for the retailers trying to grow their programs, the equation includes giving more than just an email address and some basic information. It includes giving you my attention and opening the door to more email in the already full inbox.
It might be a good idea to look at your loyalty program in two ways. One, think about your existing loyalty base. Each person has already given you something of value. Why not treat this as a treasure as opposed to a commodity to basically spam each week? If you really want me to do more than redeem a coupon, why not try a bit harder? Is it any wonder why loyalty program success examples are few? The ones that reportedly do best seem to have a few more dimensions to them.
The other way is to look at how to grow your program membership while reducing attrition. What are the reasons I should spend time giving you my information, looking at your emails, downloading your application? Is it really just to get a few dollars off a purchase which may be architected to give the retailer the most margin - like pushing an offer on a shirt but not the big brand shirt, or an offer for dollars off my first purchase of a service that includes an ongoing fee?
None of this sounds interesting, certainly not enough to bank on. Instead of "loyalty programs," most of these should just be called "communication programs" because they inspire nothing resembling loyalty in the brand sense.
Most only feed consumers' desire to save money, and we all know consumers that demonstrate loyal behaviors (I love Nike, or I love Apple, or I love Amazon) have a limited consideration set across categories and price is not usually the switching trigger.
What this all points to is that if retailers really want a “loyalty program,” it needs to be something that encompasses more than emails, apps and offers. It should be a living example of the retailer’s compelling brand identity. When you don’t have that identity in your pocket, what are you left with? Today's loyalty struggles, in my opinion.
Giving customers any reason to visit a store outside a crafting or making occasion is a great idea. The inverse of this news though may be just as interesting. UPS is doing this with as many retailers as possible to fend off Amazon's delivery business. For that reason, retailers competing with Amazon have a vested interest in working with UPS.
A different way to debate this question would be to re-phrase it as: why are boards and execs hesitant to implement more modern and accurate business performance measures? The answers to this question might span: old habits die hard, the market expects certain measures, or maybe the company has no ability to support the required analytics for new metrics.
It's probably a bit of all this - but like many retailer challenges, I think this comes back to a lack of maturity and flexibility with regards to analytics and information architecture. Retailers need to rectify this to be able to more quickly adapt and measure their business, from the top line to all the constituent business processes. Without it, how is any executive to have confidence in being able to accurately implement any form of new measurement system?
It's a tremendous solution, especially since it reinforces the business' position as a convenient shopping experience relative to all the other competing shopping options available to consumers. It would be cool if they could dynamically assess market basket building in real time to propose complementary products or offers on the consumer's mobile device.
This makes absolute sense. It's sort of like vertical integration: "The companies will partner in the development of cloud-based solutions for restaurant operators designed to better connect customers via mobile ordering, third-party deliver solutions and more."
Regarding the comparison to Amazon, I'd say be careful and look closely at the differences if you are a retailer considering this. I once interviewed with AWS for a marketing job for retail and posed the question of how you sell the service to businesses that view you as competitive? The answer was they operate AWS separately from Amazon Retail -- which is a fine point lost on most people in the retail space. It's all Amazon, right? One business losing money, propped up by a high margin business. Brands selling on Amazon to improve sales is one thing, but for retailers the thought of using AWS for anything is hard to swallow when you are in competitive category. Big opportunity for Microsoft and Google.
I think both Walmart and Kroger have made similar moves already or are considering them. These are not food service like Starbucks but it's good for the overall health of the retail space that options to AWS for competitive cloud services exist, especially ones tailored to industry needs and which are complementary.
An interesting trend that for retailers makes sense. It's also yet another point of contention between retailers and suppliers. Productive collaboration remains an admirable objective and the more consumer insight a supplier has about its own products the more it can equally collaborate with retail partners.
The challenge over time with retail/CPG brands is that both are starting to realize the benefits of ruling the consumer relationship. It's leading companies like Kroger to vertically integrate and offer more of its own private label brands to reduce dependency on suppliers. It's leading retailers like Walmart and Target to build digital advertising marketplaces to monetize data and sell new digital products to suppliers. It's leading CPGs to figure out more direct to consumer channels themselves and invest in better analytics and consumer insight.
Drop shipping is just a symptom of a rapid evolution in the retail and consumer goods industries.
Anything that attracts a monetizable audience is a great promotional channel. Consider how much retailers spend to create and continuously improve their online properties and this is a great idea to capture more value. Hopefully CPG brands realize the opportunity to fold this activity into trade promotion and shopper marketing plans.
Hope isn't a good strategy here: "marketers are increasingly hoping that artificial intelligence (AI) can take personalization to another level." Are AI (rules or ML) solutions for marketing personalization worth exploring? Absolutely. Is it a good idea to explore this in isolation from a corporate or enterprise plan for leveraging data, AI and advanced analytics? No way - there's no evidence to show that companies are winning in that way. Personalization is one use case of many. Companies should prioritize and have a plan to test new methods relative to the current state.
I think it’s important to put examples like this into context. Walmart’s investment in analytics and AI is probably only matched by Amazon, to a lesser degree Kroger. These use cases are terrific, but require a LOE that few retailers or their CG partners can understand, let alone have the resources to execute.
Most companies need to step back and check their analytics maturity while mapping out a plan to leverage data inline with their business strategy. The first use cases that fall out of this exercise will focus less on complete store transformation like this Walmart example, and more on pilots for marketing personalization or supply chain planning. Success with initial use cases funds the type of lab concept you see here.
Walmart’s application of AI relative to Amazon is notable by retaining the use of store associates as part of the overall CX. It’s also helpful to showcase the technology and tracking in the store itself to overcome customer concerns about transparency and trust.
AI or advanced analytics of any form for demand forecasting or any use case continues to be a confusing topic for retailers, consumer goods companies and really any industry. Viewed as a one and done point solution or one time effort, it’s certainly possible that the hype exceeds the reality. The challenge companies have is developing analytics as a competency, and having the ability to test, learn and improve. The reality is the analytics leaders are using AI to improve forecasting because they make the investment in the right people, processes and technologies. For any other company they need a plan beyond looking at a single use case with a fixed outcome. The reason this is so challenging for retail and CPG is because of silos, decades-old processes and challenges to meet earnings quarterly. It’s a hard problem, but IMO it’s one that retailers thriving in five to 10 years will have overcome.
I liked Bob Amster's comment. He's talking about the elephant in the room here which is peronsalization of the CX, which consists of numerous elements including price. It's the optimization of the personalized experience that is the challenge - which isn't easy, but obviously worth exploring. You can look at price in a silo and all the related factors (competitors, demand), but I think future retail winners are going to balance price with other CX elements like as Bob suggests assortment, store size/format, online/offline fulfillment, loyalty, offers and content.
Personalization needs to be driven by the CX a retailer is trying to execute. My sense is that it’s becoming table stakes to personalize on transactional and behavioral data where the outcome is a more tailored sales offer. The contrast with travel, hospitality and insurance sectors that rely less on transactional data is interesting. I think about how these other service industries use personalization throughout the customer relationship (your life stage, family situation, interests, etc. – relying on a lot more than just transactional and browsing behaviors). The challenge retailers have is determining the role of personalization beyond offers to really delivering a differentiated CX – I think too many fixate on marketing offers. That's an analytics problem requiring a good data foundation and strategy.