5 min read
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AI & Automation
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July 15, 2025
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AI has quickly become the shiny new object in e-commerce and, predictably, it’s now drowning in hype. Slide decks, vendor pitches, press releases; everyone’s tossing the term around. Who knows what people even mean by AI any more.
Sure, there are the inflated promises and buzzword bingo. But there are genuinely impactful ways AI is transforming online retail. It’s no longer limited to chatbots or basic personalization. Instead, AI is woven through content management, search, merchandising, fraud detection, customer service, and analytics. The potential payoff: smoother, faster, and deeply personalized customer experiences, alongside leaner, smarter operations for the business.
Yet, as usual, the theory is a lot prettier than the reality. Actual results on the ground remain uneven, and the hype often outruns the substance.
The truth is, AI-driven gains don’t materialize without the right digital foundation. If your infrastructure isn’t composable, structured, and ready to support rapid experimentation, AI won’t magically solve your problems—it’ll just create new ones that you won't be equipped to solve. The faster AI changes things, the further behind you will get.
One of the clearest wins for AI in e-commerce has been search. Legacy keyword-driven systems often miss the intent behind what someone is actually trying to find. AI-powered search tools have stepped in to interpret that intent more effectively, serving results that align with what users mean, the context around their search, the behaviors that might illuminate the right response - not just what a user types. This leads to fewer dead-ends, less friction, and better conversion rates, especially on large catalogs.
Another area where AI has proven valuable is in content automation. AI-assisted copy, particularly translation, and increasingly image generation has started to help content teams scale campaigns faster without sacrificing cohesion. For brands with hundreds or thousands of SKUs, these tools can speed up product launches, landing page updates, and A/B testing strategies. It doesn't eliminate creative work - in fact you have to be somewhat more creative over time to get AI to do what you want - but it shifts the team’s focus to higher-impact content, the sort of thing you pay people their money for. AI isn't going to have a lot of original ideas. If you can't compete with that then the problem isn't AI.
Customer service has been the canary in the mine, with Chat being at the irritating vanguard of AI impact for multiple years now. Using AI to do routine ecommerce work today has all the frustrations you were giving customers two years ago when you thought Bots could replace your customer service agents - the forgetting things, the cheerful stupidity, the 'nearly but not quite' nature of their responses. But customer service is where to look to see how effective AI can be when it's well trained. How many times in the past few months have you interacted with a bot, wondered if it was a bot, and not asked because you didn't want to insult a human being. (For me: three times).
Generative AI is powering self-service layers that go beyond traditional FAQ bots. When properly trained on accurate business and order data, these models can help resolve common requests instantly, while escalating more complex issues to a human without losing the thread. That blend of automation and human handoff is pivotal in keeping costs down without degrading the customer experience. That's where the rubber is still making an unpleasant mark on the road. When I tell a bot my details and the human doesn't appear to have been given any of it, I'm mad. The humans and their systems are the problem now.
These gains, while sometimes incremental, add up. When AI is fully integrated into the architecture, it becomes a quiet performance multiplier. Teams move faster, experiences adapt to real user behavior, and internal data becomes more actionable. But you need a partner who understands how to put this all together, an engineering company. (Okay okay, get me a glass of water).
Despite all this, not every AI implementation delivers value. In fact, some create more problems than they solve.
A common issue is technical mismatch. Many organizations are trying to plug advanced AI tools into outdated platforms. If your e-commerce architecture is tightly coupled or monolithic, real-time personalization and AI-driven experiences will struggle to perform. The stack simply can’t handle the speed or complexity that modern AI tools require. You’ll end up with laggy site performance, inconsistent experiences, and frustrated teams. The silent part here is that if you're still on a "very" legacy version of your platform the problem might be that you don't run towards change. Get at least competent in managing the pace of technical change in our business or get rolled over.
Another problem is dirty or disjointed data. AI depends on clean inputs. When product data is incomplete, customer profiles are fragmented across systems, or tracking data is unreliable, the models being used won’t work well. This isn’t a tool issue, it’s an infrastructure issue. AI doesn't fix data problems. It magnifies them. You can't go to a trade show and buy something that does AI and hope that this solves your problems. You've got to start with a clear picture of what your capabilities are today, an honest one that acknowledges maybe you haven't changed as fast as you might have. Once you know your capabilities, know what you want to do. Focus on developing skills aggressively but incrementally, pushing and pushing for several months to develop greater understanding and ambition among your teams. Think of yourself 6 months from now and imagine AI actually can do something useful in early 2026. What needs to be true for you to take advantage? What will you wish you did now? Get on with it.
There’s also a strategic challenge. Many organizations adopt AI without a clear use case. They chase a trend, roll out an AI tool, and then wonder why it doesn’t move the needle. The ones who will see value are the ones that start with a specific outcome in mind (that picture of the world in 6 and 12 months is fuzzy, you are going to have to guess some of the details). Start with pain or greed. Pain? Do you need to reduce support costs. Pain: Improve search engagement. Greed: Could you increase campaign velocity. Then work backwards, match the skills and technology to the need and work out where to start. (Where you end up is too hard to predict. AI is developing too quickly.)
Lastly, AI is often introduced without a plan for internal ownership. So you start yourself a political AI death match at the very moment you need everyone to be working together. The most successful implementations happen when cross-functional teams are brought into the design process early. And when a small group of people get to deliver something real as a small cross-functional team. They develop trust. And that's the culture your AI initiatives will have. If only one department or one egomaniacal super-ambitious leader is responsible for your AI initiative, it not only becomes siloed, it becomes us versus them. If your best people are put in the trenches together and held accountable jointly for the first outputs, the extended team has a chance to see AI as a shared capability, it becomes part of how the business works.
When I was at London Business School, I had this professor, Costas Markides. He had a book. I still have it and I think of it in every conversation we have at 64labs about innovation. The people who run the fastest at the start of an innovation wave are not always, in fact are rarely, the companies who benefit the most. (MySpace is the easiest to think about).
I had a sports editor and friend at the Sunday Times, Chris Nawrat. He was one of the smartest people I knew. He had this thing called the "Do Nothing" strategy. "John," he would say. "Sometimes the right thing to do is nothing. Let everyone else waste their energy, while think about what the possible end games might be and prepare for them instead." He survived at the Sunday Times the longest of any executive other than Andrew Neil.
So two questions. What's the end game of AI in your business do you think. What would Nawrat be preparing for? And does it matter if you arrive at the right answer on AI slightly after the initial discoverers have found it. Save some money. Plan rather than act.
The businesses who will win at AI aren’t necessarily spending more money or hiring more engineers. They’re structuring their teams and technology in ways that support process, clarity, simplicity. flexibility, speed, and interoperability. The sort of stuff that will mean they understand how best to apply AI in their business. Not actually rushing right away to the AI bit. Prepare.
And that's why composable should be on your agenda. If you adopt composable principles at an architectural level, give yourself the ability to test, refine, and scale new tools without refactoring your entire stack. Pay off technical debt urgently. You won't be able to service it in AI land. Invest in cleaning up and centralizing your data. Choose vendors based on their coherence and connectivity with the rest of your stack and your ability to use them as tools rather than products. Get some useful experience in an IT and content architecture where you get equal parts more power and more responsibility. But don't spend a lot of money on fancy consultants who barely know more about AI than you do. Build an internal coalition of the willing—people curious enough to figure out what works right now and committed enough to turn that learning into action. Let them develop just enough expertise to be dangerous when the end game starts. Then make sure they’re building the muscle to train others and evolve the tools internally, not just depend on vendors forever.
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AI is absolutely going to shape the future of e-commerce in some way at some point. But right now it's either doing useful but banal work or it's a cute party trick. That will change quickly. But the quicker you admit you have no clue how it will affect your company exactly and start understanding the implications of that ignorance and what you can actually do about it for real, the better.
Those that approach AI thoughtfully, match it to real use cases, and modernize their infrastructure accordingly will see measurable returns. Those that treat it as a bolt-on feature or marketing bullet point will fall short. Not because the tools don’t work, but because the foundation wasn’t ready.
If you're serious about integrating AI into your customer experience, the first step isn’t to buy a new tool. It's to make sure your architecture, data, and teams are capable of supporting it.
Want a second opinion on whether your current stack is built to support modern AI tools? Let’s talk.
5 min read
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July 15, 2025
Composable
Ecommerce
How Does Composable Help Marketers and Merchants
Marketers and merchandisers in enterprise retail are often stuck in a weird paradox: they have powerful ideas, agile teams, and massive goals, but a tech stack that moves like it's 2012. If launching a promo takes 3 JIRA tickets and 2 weeks of dev time, you're not just behind, you're bleeding money.
Enter composable commerce: a modular, API-first approach to building digital storefronts. While it sounds like a developer’s dream (and it is), the biggest wins actually show up for marketers and merchants.
Here’s how.
Composable means your frontend is decoupled from your backend. So when merch or marketing wants to:
...they can do it without dev involvement (or with minimal support). Teams can use low-code/no-code tools integrated into the stack (like CMSs or visual merch tools) to make changes in hours, not weeks. And dev teams, before you get too upset, these guys have been using tag managers and personalization tools behind your back to do things they shouldn't for about 10 years now. This is better-safer-transparenter than that.
🚀 Result: Faster go-to-market, more A/B testing, more wins.
Legacy monoliths often treat personalization like a bolt-on feature, not a core capability. Composable stacks let you plug in best-in-class personalization engines (we have hard-core expertise in or Dynamic Yield) that actually talk to your content and commerce layers in real-time.
Marketers can then:
Now, it better be built correctly by a partner who knows what they are doing. (cough). And that partner better be in the weeds with your team on what it has to do where (double cough). And you better be willing to out some work into making it work rather than think it automagically improves conversions (whooping cough). But a composable architecture does unlock all this.
📈 Result: Better CX, higher conversion rates, more data to refine.
Composable gives you control over your frontend experience. Sure you have, like templates with like Bootstrap n stuff that you can play with. But repeat after me - ISML is DISML. With composable you are a world of React and Typescript and kittens. You get to control how the site looks, feels, and behaves instead of being locked into the templates someone thought were state of the art back in 2014.
This means your brand team can:
…without getting a “that’s not possible with our CMS” reply from IT.
🎨 Result: Experience-driven commerce, not catalog-driven commerce.
Move fast and break stuff they say. Yeah, great advice for a 20 year old building an app no one wil likely ever have to use. We don;t get that luxury. Marketers and merchandisers are constantly caught between "move fast" and "absolutely don’t break stuff." Composable gives us a middle ground:
🧘♀️ Result: Less stress, more autonomy, more velocity, more control.
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Worried about an old school Big Bang launch of composable? Don't be. You can put a full composable site out to a subset of users for as long as you want before you have to commit ? Don’t be. Most enterprise teams go with a split launch - maybe 5% of users to start. They iron out any kinks. Then when they realize how much the ROI will be if they switch over like right now, they switch.
You can go incremental of course.
You can plug in a headless CMS (like Contenstack or Amplience), run it headlessly within your legacy stack for a while, and prove ROI before ripping anything out. Or un composable with a new CMS in one region for six months to give yourselves some experience of both before rolling out globally.
🛠️ Result: Low risk, high reward — easy to minimize risk and you keep IT on your side.
In a world where campaigns move at the speed of culture and conversion windows last minutes, composable lets marketers and merchandisers do what they do best: create, launch, measure, and optimize without waiting for devs, approvals, or outdated systems to catch up.
5 min read
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August 7, 2025
Composable
How a Composable Storefront Pays for Itself
If you're leading digital at a large retailer or a multi-brand group, this has probably come up already: "How fast do we get a return on a composable build?"
Fair question. Composable projects do require upfront investment. They need time, budget, and executive attention. But the payoff isn’t just in the tech you launch. It's in the legacy systems and workflows you leave behind.
The value shows up when your teams stop waiting for dev queues, start shipping faster, and no longer rely on expensive workarounds to do basic things.
A composable storefront doesn't just pay off the build. It clears the debt that’s been building inside your stack for years.
Most people frame ROI too narrowly. They ask if composable saves money compared to what they’re already doing. And if it makes money if all they do is change the front-end framework. It does both. But the better question is whether it clears the friction that keeps your teams from doing their best work.
Here’s where the real value tends to land:
✅ Faster time to market Marketing and merch teams push campaigns, content, and experiments without waiting for staging, QA, or a dev sprint to open up.
✅ More autonomy across teams No more Jira tickets for basic content updates. A well-structured CMS lets non-technical teams work directly inside the experience. This autonomy stretches right through to some elements of structure like menus.
✅ Less tech debt When you replace rigid templates and legacy CMSs with modular systems, maintenance gets lighter and upgrades stop being emergencies.
✅ Better customer experience Faster front-ends and personalized flows drive stronger engagement (+20-40%) and better conversion (~+20% on mobile). That has real revenue impact.
✅ No wasted license spend Composable means using the tools you actually need. You’re not paying for a suite full of features no one uses. This somewhat relies on your ability to negotiate good deals from new vendors and better deals from your platform. But composable opens this door and all of these guys want your business a great deal.
Not every composable build hits its targets. The architecture helps, but the outcome depends on the process.
Don't start at the starting line Many accelerators other SIs brag about are just reskinned versions of the composable storefront sample storefront from Salesforce. They are essentially worthless. The 64labs accelerator is an integrated set of code, process, and embedded expertise where key decisions have been made based on experience, where full-feature integrations have been pre-built with the vendor overseeing, where there is a way to getting the site done quickly that we stand behind in our contracts. With 64labs you start a 100m race 40m from the finish.
Pick the right partners Composable tools only deliver if they play well together. That’s why we work directly with partners like Contentstack, Amplience, Algolia, Vercel, Adyen and Dynamic Yield to build fast and smooth. But your key partner is your engineering partner. There are some other good partners out there. But no one has the experience and focus on composable of 64labs.
Enable internal teams We don’t just ship the site. We do a handover right. Your team gets documentation, training, and structured onboarding. They have helped build parts of the site. They retain access to our top people post-launch even without a contract. If they can manage the platform without us, we’ve done it right. If you want us to stick around and keep the momentum of the build going - and there can be a strong case for that for some retailers upgrading in other areas of the enterprise stack (ERP, OMS, WMS) whose team cannot own the architecture right away - 64labs can hold the fort and improve the weaponry while that work gets done.
Legacy platforms come with hidden costs. Every delayed release, every workaround, every missed campaign window adds up.
If your team is stuck supporting brittle code, locked into slow cycles, or limited in personalization, the price isn’t just technical. It’s operational debt. And it compounds every quarter. And AI is not going to slow that baby down.
Composable cuts that cycle. It unlocks execution speed and lets your teams push ideas out into the world instead of waiting for backlog relief.
If your business has complexity—multiple brands, regions, or fast-moving teams - composable is not optional. It's the structure that lets digital teams actually run.
And if you're on Salesforce Commerce Cloud, the backend is already strong. Composable is how you level up the front-end to match.
Done right, it doesn’t just pay for itself. It gives your team the flexibility they’ve been asking for and the momentum your business needs.
Let’s Talk. Want to see what ROI from composable could look like for your storefront? Contact us here.
5 min read
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July 15, 2025
Composable
Ecommerce
Monolithic vs. Composable Commerce: Which One Actually Lets You Move
Monolithic commerce platforms still dominate the legacy install base. But composable architecture is quietly and quickly becoming the default for brands that want to move fast, personalize better, and scale smart. Here’s why.
At some point, every digital team hits the same wall: is your commerce platform pushing you forward, or is it quietly holding you back?
Monolithic platforms are familiar. Everything in one place. One contract, one vendor, one roadmap to follow. That made sense when stability was the goal. But the game has changed.
Composable commerce is built for movement. It splits the stack into parts—CMS, search, checkout, personalization—and connects them through APIs. So each part of your business can evolve on its own terms.
This isn’t a backend engineering preference. It’s a strategic foundation for shipping faster, experimenting more, and building digital experiences that keep up with the customer.
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Modern brands move on short timelines. Product drops, geo-expansion, A/B tests, loyalty programs, AI-driven content—none of that fits neatly inside the old dev cycle.
Monolithic platforms slow things down. One small update means full regression testing. Teams queue up behind each other. Deadlines slip. Innovation fades.
Composable fixes that. You want to try a new CMS? Plug it in. Want to update the frontend? Do it without touching the checkout. Want to test two search vendors? Go for it.
Decoupled systems let every team move at their own pace. No more waiting for a single system to catch up.
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There are still situations where a monolith makes sense. Simpler teams, tighter budgets, fewer moving parts. If your business needs one site and one language, all-in-one can be fine.
But once you scale, that simplicity becomes a constraint. You’ll find yourself spending more time working around the platform than improving your experience.
Composable takes more planning upfront. You need to pick tools, define APIs, structure your stack. But once it’s in place, you’re in control. Not locked to a vendor’s roadmap. Not bottlenecked by a bundled release schedule.
Say your team wants to relaunch the site, overhaul search, add personalization, and expand to three new countries. And marketing still needs to push campaigns live weekly.
In a monolithic setup, that’s a six-month program with a lot of dependencies and delays.
In a composable world, content updates go through the CMS, personalization gets tested in isolation, and the frontend evolves alongside the rollout. Each stream moves independently. That means fewer collisions and more shipping.
Monolithic platforms had their moment. And for some teams, they’re still good enough. But if your brand is growing, diversifying, or trying to accelerate, composable is probably the better fit.
It gives your teams control. It frees you from outdated timelines. And it lets your tech stack evolve with the business, not behind it.
Let’s Talk. If you’re wondering what composable could unlock for your business, We’d be happy to show you.