Technology

DeepSeek & The Future of AI Models: Lessons from the Browser Wars

The trajectory of innovation in AI today reminds me of the early days of the web and the browser wars that shaped it. Back then, our ability to create and interact with the web was constrained by a single browser, limiting the fidelity of what we could produce. As competitors entered the scene, standards like HTML and CSS emerged, and the web expanded exponentially. Even with those standards, new innovations like JavaScript and Macromedia’s Flash unlocked possibilities we hadn’t imagined, breaking through the constraints of what we thought browsers could do.

AI is heading down a similar path.

The Parallel to Browsers

We’re currently in an era where innovation in AI models is being driven by a mix of proprietary players (like OpenAI and Anthropic) and open-source challengers (like Meta’s LLaMA and the newly released DeepSeek R1). Much like the browser wars, this competition is defining early standards and pushing the boundaries of what’s possible. Proprietary models bring alignment, safety, and polished performance, while open-source models democratize access and drive experimentation.

But even as we’re watching this battle for dominance unfold, I think the focus on which model “wins” is irrelevant in the long run. Just as browsers settled into a multi-platform world with innovation layered on top, I believe we’re heading for a multi-model AI ecosystem, where different models—both proprietary and open-source—work together in a modular, interoperable way.

A Multi-Model World

The future isn’t about one model dominating. It’s about how we combine and integrate different models to meet specific needs. Proprietary models will likely dominate in commercial, consumer-facing products where safety and alignment are non-negotiable. Open-source models, on the other hand, will thrive in research, niche applications, and cost-sensitive projects, pushing forward innovation in areas that proprietary players might overlook.

What’s important here is that this trend line isn’t just about scaling existing architectures or improving fidelity. It’s about creating new tools, systems, and even paradigms—like JavaScript and Flash did for browsers—that will fundamentally shift how we think about AI applications. I’m convinced we haven’t yet seen the step changes that will truly unlock AI’s potential. These will likely come from new players or hybrid innovations that combine dense, sparse, symbolic, and neural approaches into something we haven’t imagined yet.

Standards, Middleware, and the Rise of Hybrid AI

If we take lessons from the browser wars, we can see a few trends emerging:

1. Interoperability Will Drive Adoption: Just as the web couldn’t scale without standards like HTML5, the AI space will need standardized APIs, formats, and protocols to allow models to work together seamlessly. Companies don’t want to be locked into a single model—they’ll demand orchestration layers that let them mix and match tools based on need.

2. AI Middleware Will Be Key: As multi-model workflows become the norm, we’ll see the rise of platforms that act as a gateway for managing and combining models. Tools like LangChain or AutoML are just the beginning—these systems will evolve to abstract away the complexity of choosing and managing models.

3. Hybrid Architectures Will Take Over: Just as browsers now integrate multiple engines (like JavaScript and WebAssembly), AI models will likely become hybrid systems that combine the strengths of dense networks, sparse MoE architectures, and symbolic reasoning. These modular systems will be able to scale while still delivering task-specific performance.

4. Innovation Will Outpace Standards (For Now): Before interoperability catches up, we’ll live in a fragmented space where innovation moves faster than standardization. This means we’ll see exciting breakthroughs but also challenges in integrating them effectively.

Irrelevance of Individual Models

Looking at this trajectory, it’s clear that the individual models themselves are becoming less relevant. What will matter more is the ecosystem: how models are integrated, how they interoperate, and how they solve real-world problems together.

The browser wars ended with multiple players coexisting because the innovation became more important than the competition. The same will happen with AI. Whether it’s DeepSeek, Meta, OpenAI, Anthropic, or the next unknown player, the trend line points to a modular AI world where tools work together seamlessly—and innovation, not dominance, drives the future.

The big question isn’t “which model will win?” but rather, “how do we build the tools and systems to make them work together?”

Business, Technology

SaaS companies are irrelevant with AI agents

I’ve heard a few folks joking (sometimes not-so-jokingly) about how the next wave of AI agents, combined with a simple database, could potentially wipe out the entire SaaS market. It’s a compelling vision: Imagine a single AI “super-tool” that knows your business inside and out, automates everything, and relegates your CRM, HR platform, and helpdesk software to the dustbin of history. Exciting, right?

But let’s talk reality for a moment. If you look at how technology has actually disrupted industries over the past couple of decades, it never really happens overnight. You don’t just flip a switch, dump all your existing systems, and pivot to a brand-new approach. Instead, it’s more like layering new capabilities on top of old ones, seeing what sticks, and slowly consolidating the tech stack over time. AI is absolutely going to transform the SaaS ecosystem, but “transform” doesn’t automatically mean “replace.” Let’s explore why.

As a technologist, I feel this coming. As a business person always surprised by the true pace of adoption, I know it’s a ways off.

Why SaaS Isn’t Going Away Anytime Soon—But How AI Agents Will Change the Game

The Slow Burn of Disruption

Adoption of cutting-edge tech usually starts at the edges, where the stakes aren’t as high. Think about when cloud-based software began replacing on-prem solutions. We didn’t see an immediate mass exodus. Companies tested the waters in non-critical areas first (like file sharing or team messaging), and only later migrated core systems. The same pattern will play out with AI agents.

Complexity and Compliance

On paper, “an AI + a database” sounds brilliant. But throw in industry-specific compliance, security protocols, and complex workflows, and you’ll realize how much engineering and domain expertise goes into even a “simple” HR or CRM platform.

The SaaS Value Prop Still Matters

Right now, top SaaS platforms offer more than just a place to store data. They’re infused with industry best practices and workflows that have been refined by thousands of customers over time. There’s a reason marketing automation tools or e-commerce solutions do specific tasks so well—the collective learning is baked in.

And then there’s compliance. If you run a business in healthcare, finance, or any highly regulated industry, your legal team needs robust evidence that a platform meets certification standards (HIPAA, SOC 2, GDPR, etc.). Trust me, “We used an AI that’s really cool” doesn’t cut it for an audit.

The Role of AI Agents

AI agents, particularly ones powered by large language models (LLMs), are already helping us automate tasks, generate insights, and connect data dots. However, in the near term, these agents will augment rather than completely replace your SaaS subscriptions.

The big challenge? Integration. Even the smartest AI can’t do much if it’s not talking to all your relevant data sources and apps in a secure, compliant way. And that integration layer—what I sometimes call “the plumbing”—is a huge part of SaaS value. AI might handle logic and recommendations, but the orchestration behind the scenes is massive. Even the MACH Alliance is finally starting to embrace the need for middleware.

Futures to Watch

  1. AI-Led Entrants: We’ll see new AI-powered platforms disrupt established players in specific niches—like specialized virtual assistants for customer support or data analytics that run circles around older solutions.
  2. Hybrid SaaS: Expect your favorite SaaS providers to fold AI features right into their core offerings. It’s already happening as they add GPT or other LLM-based functionality into their existing products.
  3. Specialized Micro-AI Services: Rather than one giant Skynet agent, we might see (and arguably already see) micro-AI components each tackling a narrow function—like invoice processing, lead scoring, or content generation—and snapping together like Lego blocks in your tech stack.

Timing Is Everything

When I first started evangelizing experience-driven commerce, which required headless commerce, I eagerly awaited all storefronts to change within a year or two. Back then I did not fully appreciating the cost of capital and the inertia to replace existing systems. With this in mind, I think the impact to SaaS will likely drag on for a decade.

  • Short-Term (1–3 Years): SaaS solutions get more AI smarts. Expect advanced natural language features, deeper automation, and chat-like interfaces on top of the same infrastructure you’re using now.
  • Mid-Term (3–7 Years): We start seeing the best-of-breed AI platforms truly rival (and sometimes replace) older, more rigid SaaS tools. If you’re running a simple or repetitive workflow, an AI agent might do it cheaper and faster.
  • Long-Term (7–10+ Years): By this point, many simplistic SaaS solutions may well be superseded by “AI + data” systems. But for mission-critical or highly regulated operations, specialized SaaS platforms—likely with strong AI capabilities of their own—will still be essential.

Final Word

As much as I love the sci-fi idea of a single AI brain running your entire business, we’re not quite there yet—and we won’t be for a while. The SaaS model still brings real value in terms of domain expertise, compliance, and that invisible but crucial layer of data plumbing. And, the reality is most business users just want to get to their kids softball practice and will drag their adoption feet.

That said, the future is definitely AI-powered. Over the next decade, expect a continuous blurring of lines between what we call “SaaS” and what we call “AI platforms.” In the end, though, the old question remains: who can deliver a product that solves real business problems, aligns with security and compliance needs, and fits into evolving workflows? AI is going to shake things up, but SaaS isn’t going away—it’ll just look a little (or a lot) different.

We’ll all keep an eye on those AI developments, that are just getting started.

Marketing

Personalization @ Scale Includes Privacy as a Priority

Recently I had the honor of being a guest speaker in the Customer Analytics course, which is part of the University of Virginia’s Master of Science in business analytics (MSBA) program. The class is taught by Professor Ryan Wright, a longtime friend and hero of mine in academia (he never ceases to amaze me on how well he has the pulse of industry and is preparing his students to thrive in it).

One of the students asked my position on privacy within the context of personalization and whether or not I thought we have the right regulations in place. I joked a bit that if most people knew what I knew, they’d flush their phone down the toilet and disconnect everything. But in reality, it comes down to an exchange, a barter if you well. A company gives you free services (e.g., email or this platform to post my thoughts) or a more relevant service (e.g., search results or pre-filtered category pages on an e-commerce site) in exchange for insight and information about you. Now, if this exchange comes with a degree of trust and transparency or better yet, control, then you are more inclined to exchange some data about yourself for the service. I am a big proponent of this equation, as I believe many of us want to continue to take advantage of free services and better experiences. However, I do believe that while things are rapidly expanding in regard to data regulations, we have a long way to go before it’s a fair exchange.

My strategy for personalization is to lead with privacy in the forefront, while acknowledging people want you to make their lives easier. Do I want the kid’s sections of a mobile app or website to pre-filter to my children’s sizes, tastes and closet contents? Absolutely! That of course means I have to be ok with that same company keeping track of my kid’s sizes, tastes and closet contents. Now here’s where the key is in the exchange. If the business provides the right level of transparency AND control, then I am comfortable. Lucky for me, I continue to find my way to companies that share my sentiment. Beyond the standard privacy policy, Gap Inc. has gone so far as to adopt privacy principles to guide internal projects. We’re also currently recruiting for an internal privacy counsel (plug to join Gap, Inc).

To help employees understand key Privacy issues and risks, Gap Inc. has adopted Seven Privacy Principles to help guide projects and initiatives. 

1.) Consent: Obtain permission from individuals before using their personal information.

2.) Control: Give individuals meaningful choices about how their information is used.

3.) Fairness: Use personal information in ways appropriate for the context.

4.) Minimization: Collect and store personal information only as needed to provide the service.

5.) Confidentiality: Securely store and transfer personal information and only share it when necessary.

6.) Access: Allow individuals to correct or delete their personal information.

7.). Accountability: Socialize and enforce these principles.

So how do I intend to bring this to life for our brands? Going back to the “exchange”, in my opinion the barter works best when the company creating the service based on the data gives the customer ridiculously easy to find (transparency) and operate controls.

Google

Let’s step into a couple examples to illustrate the concept and show that some of the ‘big bad wolves’ actually do a decent job of this and have created a precedent in my opinion. Google for example now has most of what they do with your data consolidated into one place, with simple language as to what it is, how it’s used and really easy toggles to turn things on and off.

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Nike

If you have a Nike account, you’ll notice they’re very up front about how they want to make the experience more personalized for you and allow you to help provide input to the process. This is a good balance between letting the modern new marketing tools figure out what you’re thinking with the old school process of simply asking, “Darin, what’s your shoe size?”. If you have a Nike account, you can see how they let you opt in or out to the personalization. When setup an account via their mobile app, they do a great job of explaining things in plain English and letting you decide.

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Macy’s

While most of the customer preference center best practices have been about managing email communications, I also really like what Macy’s has done with their customer preference center. They allow you to proactively tell them your favorite sizes, brands, etc. Ironically though, after I did update mine and returned to the home page, it didn’t seem like it took my instructions into account.

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In Closing

With great power comes great responsibility. As digital marketers, we need to thoughtfully balance the power of all our new machine learning algorithms and massive ability to collect enormous amounts of data on our customers with the tools and experiences we build to empower our customers to let us know what they want us to use.

eCommerce

My Headless Commerce Experience with Adobe.com

I’ve worked in commerce for some two decades, on both the front-end and the back-end and everything in between. Over time, I’ve honed a vision for what commerce should be. I believe many of you share a similar view. Yet we struggle to deliver given the limitations of existing technology patterns and vendor solutions. In the same way I’ve challenged myself throughout my career, I challenge the industry to materialize this vision. Here’s the story of my work on Adobe.com

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A New Vision for Commerce

As shoppers, most of us are into one product category or another and some of us are into more than our finances support. For me I love gear. I love electronics gear, outdoor gear, sailing gear, hunting gear. Anything that acts as an aid to my hobbies, whether truly required or valuable, I’m all over it. Some of you may be into hand bags or collectibles, shoes or toys. Whatever your shopping vice, we can probably agree that the research and shopping portion of the journey are just as wonderful as the purchase itself.

Which is why I have always been disappointed with online shopping.

If I’m trying to buy a raincoator fancy backpacker style tent online, I want more information on why there is such a broad selection of products. What are the differences? Why is one item better than another? Retailers have been just plain lazy in how they merchandise online. Their typical, lack-luster responses to my questions include “faceted search” and ”sorts” on price or reviews.  Even manufacturers struggle to articulate why they created so many similar products in a category. We all put a lot of love and passion into product development. It’s just seemed crazy to me that we’re still mostly showcasing them as thumbnails in rows and columns online.

While at Adobe we encountered the typical challenge where we created these beautiful marketing pages and then customers had to go to an (ugly) ecommerce site to buy once they hit that point of inflection. Our goal back then was to radically shift our business from the channel to direct sales. It was obvious after looking at the analytics and going through the buy flow, we couldn’t have two sites. We had to transform that beautiful marketing site into the store.

We needed experience-driven commerce.

Who Gets Experience-driven Commerce Right?

The technology pattern that allows marketers to create any compelling experience they want and then make them shoppable has been a CMS, which in turn calls a headless commerce solution via an API. It seems simple enough, yet most of the ecommerce vendors out there are running on really old architecture patterns where the system is designed to deliver a home page, category pages, product detail pages, cart, and checkout…aka, the web shop.

When we attempted to transform Adobe.com with ATG (now Oracle Commerce) and Day Software’s CQ5 (now Adobe Experience Manager), we quickly found out ATG’s API wasn’t complete enough and had too many holes to bother with. Unfortunately, we purchased ATG as we thought we might acquire the company later. They were bought by Oracle and continue to pursue a web shop model, although they have improved their API (ten years later).

During this large program, called Adobe.com Transformation, we also had evaluated Elastic Path.

Everyone was enamored with Elastic Path. The developers loved it and marketing did too, as we knew we’d be able to weave together our dream experience. I actually think our idea of combining “content and commerce” with the CMS and ecommerce stack was largely influenced by Elastic Path’s capabilities and a key architect that joined us from Amazon (he put me on to microservices before the term was coined). We also had a lot of fun settling debates in meetings quoting Linda Bustos from getelastic.com There’s a great case study by Harvard Business Review that outlines this journey we took at Adobe, so I won’t expand on it more.

Once we implemented our vision for Adobe.com, making the site the store, we saw immediate results. Our conversion rates went up and it was not only noticeable in the analytics, but also in the actual sales reports. We were taking the same traffic and making a lot more money… In a few years Adobe.com went from a little over USD $200M annually to nearly $750M. The site now generates over USD$1B (Internet Retailer Top 100).

I began evangelizing the idea of experience-driven commerceand searching for the technology pattern required to pull it off. I switched business units and joined what became the Digital Marketing BU. My charter was product strategy and marketing for the idea, with the added goal of finding a commerce engine to acquire that would allow Adobe to deliver this capability.

While we started out dancing with Hybris (which was later sold to SAP… a story for another time), we eventually evaluated and collaborated with most of the ecommerce platforms on the market. All but one struggled to deliver full capabilities as an API so we could manage the shopping experience in Adobe Experience Managerand take advantage of other products such as Adobe Target, Audience Manager, etc.

Here’s what we found:

ATG’s API was incomplete with version 10 and only as of the latest version (11.3) is there a full REST API. But, it’s effectively on an EOL path with a novel attempt at a re-write, and Oracle’s new vision misses the point about customization. Oracle Commerce Cloud, the cloud version of ATG, limits customizations to webhooks and still focuses on the web shop pattern.

Hybris’ API was designed mostly for a mobile app. You could get product information out of it and engage the cart through checkout, but we had a lot of customers that ran into problem after problem trying to make it work. Simple use cases like being able to request a product from a staging environment were not supported by the API. The API only knew about products in the live production site. Hybris is now owned by an ERP company that created the reason for ecommerce to be a separate solution in the first place.

Magento had an old SOAP interface that had a poorly performing Rest API duct-taped on top. Even with the 2.x changes it’s still better suited for small volumes and simple web shops.

Digital River didn’t have an API yet.

Demandware wasn’t sure what to make of “experience-driven commerce”. They liked their model of forcing customers into web shop templates. Ironic given their target audience was fashion retailers with beautiful products. (I always wondered what Kate Spade really thought of her web store). This SaaS version of Intershop, now called Salesforce Commerce Cloud, was initially appealing to business owners, but they soon run into all sorts of brand problems as they try to choreograph experiences across digital touchpoints.

Intershop posed similar challenges to Demandware and we later learned that it essentially was Demandware (I’m pretty sure Salesforce didn’t know this when they bought it, but hey, they can just keep buying solutions until they get one that works for their customer base.)

IBM WebSphere Commerce came close with a recent REST Level 1 API, but it was similar to Magento in that it was a “RESTified” SOAP interface and required a great deal of expertise to use. So much so that the partner helping to integrate Adobe and IBM gave up on a couple of areas and tried to just make the argument that WCS should drive those pages (and thus the side by side pattern emerged – even though this breaks the first guiding principle of enabling marketing with a single tool for experience).

And then there was Elastic Path. Unapologetically API first. Not a REST-ified SOAP interface like WCS and Magento. Not a partial API that misses checkout like Salesforce. Not a mobile app-only API like Hybris that misses simple use cases like being able to test multiple versions and environments. Elastic Path had engineered the most advanced, and thoughtful API for marketers and commerce professionals to bring to life their ideas of enabling any commerce transaction at that point of inflection where they have excited customers enough to buy—ether by pumping the tongue of a shoe, calling out from the shower or walking into a store with a wearable device.

Elastic Path had already skated to where the puck was going (they’re Canadian, so I figured they were trained on this concept more than others). They had already envisioned these use cases and were excited to show how easily they could enable any client application or shopping experience whether through a CMS or custom app.

And the thing that stuck with me over the years? Elastic Path just worked. It worked for really large transaction companies like Symantec who wanted to embed commerce in their own applications and it worked for smaller companies across any industry. Unfortunately, sometimes you don’t get to buy or implement what the team really wants due to the normal “complexities” of a large company, but I was hooked on the idea of headless commerce.

Results

 

What about the Internet of Things and ordering through Alexa?

The smartphone gave rise to IoT. Just like the dot.com boom inspired one of history’s largest telecommunications build-outs, which later provided the bandwidth for the web to deliver the experiences marketers originally envisioned in the 90’s. Smartphone adoption paved the way for inexpensive compute inside small packages with wireless capability. Thanks to Apple, Google and the Android operating system, the bill of materials (BOM) for a device to have a sophisticated OS, great compute power and wireless connectivity dropped to a level where entrepreneurs’ could invent pool sensors that can tell you when to add chemicals.

Recruited away from Adobe by Intel to define retail solutions that would take advantage of this upcoming re-imagining of everything around us, I took a detour deep into the historic Silicon Valley. During which I learned a hell of a lot more about silicon and the integrated circuit than I would have ever imagined.

It was while working at Intel on IoT products and collaborating with many innovative retailers that I realized we not only needed to have experience-driven commerce in our mobile apps and websites, but that everything around us was going to become electronic commerce.

I worked with retailers trying to actually figure out how to identify a customer in the store and just let them walk out without going through the point-of-sale (self-checkout). We collaborated with toy manufacturers that wanted to have the box or toy itself somehow interact with a digital deviceto buy accessories (same use cases in B2B for replenishing devices in life sciences companies). There were companies with vending machines (Best Buy in airports) and many others creating new, and strange, pizza ordering experiences.

Obviously the convergence of physical and digital experiencesbecomes a reality over time (though costs still must come down). While my assertions had expanded and I had a focus on bringing the digital into the physical realm, one company kept delivering on this commerce vision, Elastic Path.

Today my aim is to help other digital commerce practitioners accomplish similar results and create e-commerce experiences we’ll all love.

IoT, Marketing

Moving “Digital” to the Physical Realm

As marketers, the pressure in recent years has centered on shifting to an all-digital approach and delivering a compelling customer experience across the vast number of digital touchpoints. Just as we’re leaving more traditional marketing channels behind, the advent of the Internet of Things (IoT), connected/ smart devices, and mobile technologies is blurring the lines between the digital, traditional and physical at a rapid rate. And with the excitement of nearly anything – in either the digital or physical realm – becoming a potential marketing vehicle, there also comes the possibility of a resurgence in data silos and fragmented customer experiences. Join Darin Archer, head of ‎IoT Industry Solutions Retail/CPG at Intel Corporation, as he explores the possibility of breaking down the barriers between disparate channels, data sets and back-office systems – and the transformational, connected marketing experiences made possible as a result.

 

 

Marketing

Ramblings for University level Principles of Marketing Class

I’d go for the disruptive approach. Marketing has so fundamentally changed. It’s all about digital marketing now. When Nike learns that it can have the same “reach” with their own digital online event as a Superbowl ad, you know we’re on a new path. Today’s it’s about engaging fans, building an audience and content marketing. It’s no longer people sitting on madison ave dictating a brand campaign for next year and taking half a year to put it together. Red Bull spends more on sponsorships, events and publishing than traditional ads (wait, a drink company has a leading magazine?). Rolex makes more money on events than watches.

Traditional Advertising

TV is dead

More young folks watch people play video games online than CBS. Oh, and these same video game players can fill a stadium easier than most bands today. But, it’s also evolving. It’s going to be more about the content and the device and knowning who’s watching than creating generic ads for massive audiences. Don’t believe me? Your setup box knows what you’re surfing on your iPad while sitting on the can and can change the ad you see when you get back to the TV (http://www.adobe.com/products/auditude.html). DVR’s were just the beginning. Now people binge watch Breaking Bad on Netflix and catch up on new shows via Hulu. This means that video ads will become more about speed and personalization. We’ll need more creatives and copy editors to come up with more versions tailored to very specific demographics.

Outdoor billboards

Notice how many are switching to digital displays. This is the first step to these all just being converted to the Google Ad network. It won’t be about a local sales force or agency buying locations to have a canvas hung for a month rather these screens will know who’s driving by them and who will be driving by them shortly. They’ll then be optimized to show ads to reach the most lucrative potential audience. This will be done by software algorithms and ad bidding networks. Might as well lump this into the SEM (search engine marketing) bucket.

Radio

Who listens to radio anymore? Spotify, Soundcloud, Pandora, Rdio and of course Apple dominate our cars and our earbuds. Honda just announced support for Apple’s CarPlay and Android Auto. If I were ClearChannel, I’d try to figure out how to buy Spotify and partner up with Google. Again, it won’t be about long drawn out campaign planning.

Print

The bookstore closed and most magazines are struggling to keep their numbers up. I can have a greater reach and real conversion with display, social or search ads. Now, it’s not to say these won’t be there, especially in our digital magazines on our Apple Newstand, but this will all merge with the display networks from Google, Apple, Bing, etc.

If I’m focused on B2B, I get more out of content marketing (webinars, emails, blogs, social) than any traditional media. I also use these new strategies and my own digital properties to build demand and measure the results. It no longer makes sense to spend money on something I can’t measure.

If I’m B2C focused, I’m all about getting close to my customer, building fans and exciting my base. Again, this is about content marketing, not Madison Avenue.

The agencies are all struggling and consolidating to hold on to revenue. Most have build digital businesses as they know they won’t be making tons of money on campaigns anymore rather they’ll be producing content. Even the ones that have done well picking up the task of online ad buying and optimization see that this will be done by software (Adobe Media Optimizer, Marin Software) and not humans.

So what do you focus on?

Analytics – understand how to read data, find audiences, determine trends and target. Psychographics dominates and demographics is worthless. Tomorrow’s marketers also have to be able to show where they see an opportunity using data and then measure their results and constantly optimize their efforts

Testing – the art of a/b testing is now multivariate. Understanding statistics and what “statistically significant” means is relevant to knowning if their idea is good or dead.

Creative – The fun stuff still exists and more marketers should get more comfortable piecing together campaigns themselves because they’ll have tools where they can take digital assets and put together something (with a good copy editor) that can be pushed out to their audience in real time (from their phone while on the way to work)

I’d have them all take $50 and build an online campaign for a trinket they sell on etsy or an ebook they publish on Amazon. If they have a friend that makes something cool or has a small business, even better. Get in and see how you can target audiences on Facebook, understand what a Pinterest buy button might mean to marketing (yep, they’ll be measured by sales tomorrow not just reach and impressions).

 

 

 

Retail

Easy Attribution for Store to Store Sale

One of the biggest challenges to a delightful customer experience across channels is executive bonuses and the KPIs that illustrate whether they (we) should get them. When we first tried to allow merchandise returns to the store from the e-commerce channel, many retailers found their store leadership pushing back hard. Was it because they wanted to tell ‘their’ customer to go take a hike? No, it was because those returns then hit their numbers negatively and it wasn’t within their control to improve the process. The industry as a whole has mostly worked through this use case, but there are still many more challenges that have not been worked through from pricing to the more recent ‘buy online, pick-up in store’ capability.

A very simple idea came to me the other day while shopping for a gift. I overheard a woman asking about a particular piece of jewelry. Unfortunately, the store we were in didn’t have it. She then asked whether it was in a store near her home and the sales associate could hardly bother. She made it clear with her non-verbal communication that reopening the application, searching for the product, and then determining whether it was in stock at another store was not of interest to her (obviously because she was being measured to not care). That’s when I realized that there should be a way to attribute that sale to this store associate, or at least some portion of it, if in fact the woman went and bought it later.

In order to track it, and handle some of the existing infrastructure, I wonder if it could be as simple as a QR code or bar code being printed off of the machine the store associate was using that would include a reference for the other store to more easily look it up and scan prior to sale allowing the tracking. Now, obviously we’ll get to the point where this customer would be able to buy there and pick-up in the store near her home and many permutations of the same, but could it be that there are some simple solutions we could implement easier between now and then?

Don’t get me wrong, I still want inventory at my finger tip in my mobile app, but I recognize this will be a journey.

eCommerce

Omni-channel Retailing Falls Short in 2014

As we approach the busiest shopping weekend of the year in the US, I see many retailers still falling short of providing a true omni-channel retail experience. Before I share my thoughts on why and how so many retailers are falling short, I want to quickly define my expectations of an omni-channel retailer. First, the word “channel” only applies to the retailer, and as many profess, the customer does not understand this construct. Even those of us in the industry will admit forgetting about the complexities of our own businesses or those that we support in the moment where we are trying to accomplish a task for our own sake. From a customer experience perspective, I see the requirements of omni-channel retailing including the following:

  1. Product Discovery – Whether I am browsing a retailer’s product catalog from the comfort of my couch with a tablet, standing in their store searching on my mobile phone, talking to a store associate, or simply browsing the store, I expect consistency around product information, price and availability. Preferably, I can also see and share my shopping lists and carts across each of these touch points to then purchase in any location. Most retailers have done a great job of having consistent product information across channels for some time as the industry found the value of a single product information management (PIM) system to ensure this some time ago. However, availability of product is still a huge challenge as most retailers have visibility into only 60-70% of their in-store inventory. This means that when a retailer takes a short cut using algorithms to determine when something is shown in stock, to minimize the risk that it is not, they not only miss potential sales, decreasing the value of capital, but could also have a customer satisfaction/loyalty issue if the customer later goes in and sees that an item is in fact in stock.
  2. Loyalty – We all want our 15 min. of fame and to be appreciated for the business we do with retailers. Feeling special is why most people engage with loyalty programs as it provides this sense of appreciation that we are always seeking in our lives. As customers shop more online or across multiple stores, we loose the customer experience of a store associate knowing who we are, what we like and how much we spend. An omni-channel retailer then has to recognize this information gap and find creative ways to expose it to every touch point from how they personalize the customer experience online or more importantly pass this insight to the store itself and the associates supporting customers.
  3. Customer Service (Returns/Exchanges) – The purchase journey, as frictionless as it hopefully is made to be, can still often result in an issue requiring a return for reasons such as: we bought the wrong item, size, changed our mind, or found a defect. An omni-channel retailer knows the customer across any touch point (channel) and can respond and support the customer’s return or exchange across any touch point. Today, nearly all of the retailers mobile apps I have on my phone (which is a lot because of my focus on the industry) do not show my past purchases in the store and often connect me with call centers that can’t react to in-store purchases. Similarly, when I go into these same retailers stores, while they may now accept my return, they are not in a position to recognize my other online purchases (lifetime customer value) and may not even have the product assortment required to support an exchange.
  4. Purchase – I have purposely chosen to make the purchase event #4 as I believe the first three have a bigger impact on “customer lifetime value” and ultimately revenues and profitability, yet I see most retailers have focused on how to enable transactions such as “buy online, pick-up in store” or “buy online, ship from store”. While it is certainly valuable to be able to see something is available in a store nearby, buy it online and then head in to grab it, we all know negative customer experiences have a much greater impact on future sales. Following I’ll share a recent experience to illustrate.

So with all the omni-channel initiatives announced and the ones you are likely executing against this year, why am I writing about seeing such a miss? Ultimately, I think in our focus on the purchase event, we have set ourselves up for some very high transaction costs and negative impacts to customer experience that will result in reduced loyalty and ultimately reduced sales.

To better explain where I see the challenges, let me share a recent, personal shopping experience with a retailer famous for its focus on customer service. While out of town for work, I had some time to kill and wanted to buy a new sport coat and maybe an overcoat. My initial shopping experience was fantastic. While I deviated from my mission and ended up looking at jeans, a store associate approached me in a very disarming way and got past my typical response of “just looking”. As a guy that is not built for the latest designer jeans, I frustratingly shared that most likely there were none for me to purchase and that we should move on to the original task at hand. This gentleman however was not convinced and was determined to prove there was a pair for me. He was an attractive man that looked like he could be a jeans model for any major brand. I laughed to myself and figured it didn’t hurt to entertain the idea on the off chance he found me a pair that fit, and I’m always in “secret shopper” mode for my job, so off we went to the dressing room. I’ll share the full story later on how we went from not only finding a couple pair of nice jeans that fit me, but also conquered the original task of purchasing a new sport coat and overcoat. All in all, the purchase was a big one for this retailer, and I even opened a new store card. The challenge came later when I didn’t receive all of my items that were tailored and shipped to my home.

A couple weeks after the purchase, I awaited delivery of all of my items. Everything needed some tailoring, so interestingly I walked out of the store with nothing but a smile and the anticipation to receive everything at home. I had even chosen to have the receipt emailed to me rather than take home a printed version. Unfortunately, when I received the shipment, I was not at home. I went to the shipping company’s pick-up location and asked for the items for my address as I had forgot the slip at home. I was sent home with a nice big box and excitedly opened it when I got back to share all my new purchases with my wife, who I knew was going to particularly like the overcoat. And here is where the problems began.

There were two items missing from my order. I went to my email to try and understand if they were perhaps shipped separately and just hadn’t arrived. As it turns out, I never got the original receipt, but did have a couple emails with the shipping notification. The two emails looked identical and listed all items from the original email, so I assumed they were identical and maybe just duplicates. When I entered the tracking number on the shipping company’s website it showed that the package had been shipped and that there was only one. What I did not notice until much later was that those emails which contained the entire order contents versus showing that some items were in one shipment and some were in another had different tracking numbers. One package had indeed not yet arrived, but I did not know this yet. As I had been checking all of this from my mobile phone standing in my living room, I also remembered that I had the retailers app and assumed that it would be the fastest way to look up the customer support number to get this all resolved. It was in fact prominently displayed in the app and easy to trigger the call.

When I got a hold of a customer service rep, which was actually quite fast, we had a very difficult time finding my order. Not having a receipt with the order number on it proved to make it quite difficult, all I had was a tracking number that didn’t seem to help them. The service rep searched for my order by phone number and name and even after giving the credit card number (store card), could not find my order. Ultimately we both realized that the customer service rep seem to only have access to online orders (the phone number is likely different for online purchase than in-store and the mobile app is set to the online call center). I then had to be transferred to someone else that could support in-store purchases. They were ultimately not much help and had to call the store direct to talk with someone in shipping to determine if the items were missing or in another package as they also couldn’t tell this in their system. I spent a great deal of time on hold through all of this and ultimately the department manage said she’d figure out what was happening, track down the package herself and call me back when she knew the answer. The order had in fact been split into two deliveries and the other ironically arrived a few minutes after I had left the shipping pick-up location. As it was late on a Friday and the pick-up location was closed on the weekends, I would have to wait until Monday to go pick up the second package.

We all have busy lives, and I couldn’t make it into the pick-up location until Tuesday. Well, for some reason the shipping company marked the second package as having been with them for over 5 business days (counting from the first shipment vs. the second package) and sent it back to the store I originally bought the items from. At this point, I had to start all over with tracking down my jackets. Knowing the mobile app was not helpful, I went online via a desktop browser and tried to log into my account associated to the credit card hoping I could find the order number before I called again. Frustratingly I had to create a separate account on a separate site for the store card than the main account on their site. Forget not doing well at omni-channel, this was a fail for one channel! Either way, nothing online was showing my order so I had to call into customer service. This time I went through the same challenges, but unfortunately had even more trouble as the customer support rep I was working with seemed to have even more trouble navigating the multiple systems that had order and customer information. After over half an hour I hung up and tried calling the store directly (I later noticed in the shipping email that this was my instruction if there was a problem – not exactly an omni-channel experience). When I got connected with the store, even they struggled to find my order. The person I originally talked to took all my information down and committed to tracking down my missing item. Frankly at this point I was considering doing a chargeback on my credit card, but realized it was their store card (will likely impact me from using it in the future). The good news is that the store was able to find my jackets and shipped them back to me, with both sides crossing our fingers that I’d receive them ok. All in all, it was quite a fiasco. If I see you at NRF’s Big Show in New York, you get to see my new overcoat.

Reflecting back on this experience, I see a few key challenge areas that if addressed would have a material impact on customer satisfaction, cost of doing business and most likely future revenue.

  • Order History – While it is unlikely anytime soon retailers will be able to standardize on one purchase system, each system can have their order history exposed as an aggregation service that can be accessed by the customer support applications the call center reps use, store associates log into, and the mobile app. This would make it so that across any touch point, all orders, regardless of channel would be visible.
  • Customer Service Call Centers – Many retailers have their online and physical store businesses divided across different executives that own separate operations by channel. With this comes different call centers that use different tools to get their job done. If you can’t consolidate these operations or tools, then minimally make sure that the tools have access to a customer’s order history across channels and have return/exchange processes outlined such that the handoff is smooth or preferably enables the first responder to resolve the problem.
  • In-store System – Store associates that have to support customers walking in and on the phone, need to have complete visibility into all purchases regardless of channel, and better yet, they should be able to see the customer’s loyalty value so that they maximize the experience for those customers that we all know can be the larger percentage of our revenue.

Each of us carrying the Internet in our pocket has radically changed retail. As more and more of the shopping experience incorporates digital features, from window displays and mobile point of sale to e-ink price tags and near frictionless checkout with mobile payments, we need to excel on the basics before introducing too many new capabilities. As you plan for 2015, I’d set a goal to at least be able to show inventory and order history on any device for both your customers and employees.

 

Originally posted via LinkedIn Pulse

IoT

Realizing the Security Needs of In-store Apps

I am adventurous when it comes to e-commerce, mobile wallets, social sign-in and all things that support digital marketing. I’ve had to be as I am responsible for pushing these industries forward. As consumers we love to take advantage of free email, instant messaging apps and news. And as marketers and business owners we welcome this barter system established to offer such services in exchange for the ability to provide advertising to such consumers, which is increasingly more targeted and hopefully more relevant to each individual.

Behind the scenes my own little fears sometimes drive me to use my American Express credit card for a purchase with a retailer I don’t know well, I almost never use my debit card as I’m not sure it’s really as well covered from fraud as my other credit cards are, and I have a specific email account I use for websites just in case they trade it or sell it. So, while adventurous, I still worry about too many of my preferences getting out, wonder how it could impact my ability to get a life insurance policy at some point in the future, or worse yet how data about me and my lifestyle could impact my ability to stay employed. But, I fundamentally believe that it is human nature to barter. The only true currency is trading goods and services of like value, … and sometimes, this may require a few participants to complete the transaction.

“A few years ago, users of Internet services began to realize that when an online service is free, you’re not the customer. You’re the product. But at Apple, we believe a great customer experience shouldn’t come at the expense of your privacy.” – Tim Cook

As Apple Pay was announced this month I smiled with enthusiasm. Many mornings I grab a bagel and coffee at my neighborhood café that uses Square. I rarely have cash and being able to just walk over with my mobile phone and the Square Wallet app is refreshing. I still have to find my keys so that I can get back into my apartment, but even that step could be eliminated if I were to get a wireless door lock.

Recently I joined Intel to drive product strategy for solutions enabling retailers to create the next revolution in the shopping experience leveraging the Internet of Things. I envision experiences where the physical store knows who I am, finds my favorite store associate who then is reminded of all my tastes and preferences, and is able to help me find what I was looking for or simply didn’t know I needed. The purchase event will of course be frictionless. As I investigate the details of how the store will detect me, how applications will look up who I am and pull back incredibly detailed information, and expose it to devices in the store such as a tablet laying on a counter or a digital sign near the dressing room, it’s become chillingly obvious that my traditional application development architectures are inadequate.

As I think about hackers carefully placing their own beacons and sensors in the store calling the same APIs as the retailers business application or simply monitoring this data as it’s passed around the room, I see now that as mobile application developers we have to begin to understand how to know our environment, challenge that it is secure and verify that only our own apps are engaged with such personal and sensitive insights of our customers. I challenge every developer to learn more about gateways that can monitor your physical space, tokenization systems that can minimize the actual storage and transfer of sensitive data and ultimately keep in mind that your customer is whispering a secret into your ear and none of us wants to be known as someone that can’t keep a secret.

I appreciate and was inspired by Tim Cook’s (Apple’s CEO) message on protecting such things with all these new capabilities from Apple Pay to the Apple Watch and iPhone 6. I am also very excited about continuing to push the industry forward while knowing Intel has created some incredible solutions to support developers everywhere helping my neighborhood café know I’m walking over to pick up my bagel and coffee.

Review

Prepper Book Review – Montana Alliance

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With all the doomsday prepper shows and natural disasters that seem to hit our planet from all directions setting back communities into distressed chaos, I certainly wonder what it would be like if all hell broke loose. For full disclosure, I am the author’s son and supporting editor of this book. This is an art of passion and not a commercial enterprise, so please forgive minor editing mistakes. We did the best we could and look forward to making corrections based on readers feedback. If you have any, please visit our facebook page facebook.com/montanaalliance and we’ll make the correction (great part about a Kindle book).
Now, all of that said, I thought this book was quite the adventure. I had a hard time getting into it at first, wondering to myself, “is this plausible?” Then I realized it doesn’t matter. Between Japan’s Tōhoku earthquake and tsunami and Hurricane Sandy in the US, it’s clear that there are many things that could set us back a bit. What was more engaging was imaging what it would be like. Living in San Francisco, we’re all told how we should be prepared for “the big one”, have extra water on hand, food, and other supplies. But what happens if “the event” makes it such that our electricity production and manufacturing abilities are minimized to the point where we’re back to hunting and gathering? That was when I got hooked on the storyline. It’s set years later, outlining the challenges and creativity of different groups of people all learning how to survive where canned goods eventually are no good and even bicycle tires have rotted. What kinds of communities will form? How will you interact with your skilled neighbor? Do you trade with him or direct him at gun point? This is where I think this storyline takes off. There is the obvious hippy camp that gives a socialist structure a try and communal living a focused strategy, and of course you have to have the crazy dictator who ceases control of weapons and thugs that will help him to power. What’s more interesting is how you’re mind wanders from supporting one group to another, questioning what alliance you will actually make. If you’re looking for an escape, and want to challenge your idea of what prepared means, take a read. Let us know if you would join the Montana Alliance!

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