As digital commerce and user expectations evolve, so do customer journey innovations.
Traditional platforms like Shopify are more difficult to customize, making it harder to bring a superlative digital experience across all the touchpoints and channels your customers and team members access.
In a monolithic system, adding an application at the backend, like a new site pop-up widget, might affect the frontend, potentially slowing down page speeds or causing a 404 error.
Headless architecture decouples the front and backend components of the commerce stack. It opens up a range of new functionalities that are quicker to implement, more flexible, and easier to manage than all-in-one, monolithic systems.
Headless architecture
Headless digital commerce harnesses the power of API and cloud-based technologies. It separates the consumer-facing storefront (the frontend, or the head that shoppers use and interact with) from the backend business-critical processes that handle data input, order and inventory management, payment processing, and shipping.
It is a way of designing a digital commerce platform that makes scaling up or down and delivery through multiple channels like a browser, mobile app, or in-store kiosk easier, as well as more flexible, robust, and faster.
It lets team members better manage critical business processes and makes it easier to personalize and improve the shopping experience for customers and end users.
By reducing the developmental dependencies between front and back, developers can make changes to one end of the architecture without compromising other parts of the commerce platform.
Composable architecture
Composable architecture takes the principles of headless architecture one step further.
Instead of simply decoupling the user interface (UI) from the underlying technologies that power your ecommerce site, composable architecture ensures that every key component of the system functions independently and is interchangeable.
It allows developers to take a modular approach to building your commerce platform for an omnichannel shopping ecosystem.
Components and specific functionalities, like Algolia AI Search, can be brought together or swapped out to deliver tailored solutions that address specific business needs.
A composable strategy reduces the risk of vendor lock-in and allows you to carefully design your commerce platform and select from available API-based applications. This means that you can choose from a range of tools that best suit the specific requirements of your digital commerce business, providing faster and more intelligent solutions to your employees, partners, and customers.
The MACH Alliance
The concept of composable IT architecture aligns with the MACH Alliance principles. MACH Alliance is a non-profit organization that promotes building modular and adaptable commerce systems. Their mission is to streamline digital experiences with open, connected enterprise technology.
MACH is an acronym for a lightweight, modern, and headless approach to IT architecture:
- Microservices:
independently deployed capabilities loosely connected via APIs
- API-first:
software that lets two applications communicate, grant access, and transfer data
- Cloud native:
software-as-a-service that enables scalable, secure capabilities
- Headless:
a frontend customer interface that is uncoupled from backend database and information processing capabilities
Why transition to headless
and composable architecture?
A headless strategy helps brands evolve as customer requirements change by making it easier for retailers to create unique multi-channel shopping experiences.
Taking a headless approach gives development teams more freedom across the whole spectrum of digital commerce functionality, from the frontend customer-facing ecommerce experience all the way to B2B sales departments and legal teams, as well as brick-and-mortar store associates checking stock levels for in-person shoppers.
Headless architecture combines existing leading solutions and eases development and deployment of custom solutions across your whole digital commerce ecosystem, whatever your needs.
Design a unique customer experience
A modern headless approach to digital commerce means you can easily create a custom interface for your online store and other important customer and team touchpoints. It frees digital commerce from the constraints of a standard interface imposed by monolithic platforms while continuing to use the commerce logic of the earlier system.
Improve speed and scale easily
Traditional commerce platforms can be difficult to scale when traffic and transaction volumes increase. A modern headless platform lets you create fast, high-performance commerce solutions that run on hybrid and multi-cloud infrastructures. It enables flexible API-based solutions that improve key functionalities like page load speeds and time spent at checkout, positively impacting sales and the customer experience.
Bring ecommerce to new channels
Digital commerce functionality includes much more than ecommerce sites or mobile applications that customers use. In addition to customer-facing social platforms and POS kiosks, your team members rely on specific channels to access and assess business processes like order tracking, inventory levels, and customer support needs.
Headless makes it much easier for development teams to create a tailored experience for each channel and modify systems quickly as needs change while at the same time ensuring consistency across different touchpoints.
Easily add commerce capabilities to CMS
Most large websites are built around a content management system (CMS). Traditional all-in-one digital sales platforms typically oblige you to use their native CMS infrastructure. In other instances, you may be adding commerce functionality to your existing CMS without migrating all your content, which risks creating a disjointed experience. Headless uses API-first applications to let you add commerce elements and functionality to existing websites run on your CMS without a migration, improving speed and efficiency while reducing time-to-market.
Now and into the future, digital commerce demands that online storefronts embrace a modularized headless architecture that easily integrates AI-powered search and powerful tools like Algolia AI search.
Applying headless commerce to AI
AI's power to help personalize and shape the user-experience online is unrivaled. The technology allows developers and merchandisers to improve business processes, delight customers, and drive bottom-line results.
Headless architecture lets you take AI integration to a new level.
Headless makes it possible to apply AI-powered solutions in more dynamic and creative ways across different touchpoints in the user journey. It also opens up creative and flexible ways to assemble a commerce stack that can respond to changing business needs.
The wrong way to do AI personalization
Users on ecommerce sites increasingly expect a unique and tailored experience when they visit an online store. However, with 63% of shoppers saying they would stop purchasing products and services from companies that take a too-intrusive approach,
it should come as no surprise that striking an effective balance when it comes to AI personalization is vital to a positive customer experience.
Monolithic, all-in-one commerce systems will often force a narrow set of AI personalization solutions on customers and all the different channels they use. If ineffective, they waste everyone's time, money, and bandwidth. But if they are too strong – following consumers across online activities and across brand properties – they become too intrusive.
In-session optimization
Clunky or intrusive shopping experiences are not the way to build customer loyalty and conversions. But increasingly, as customers switch from website to mobile app and back, retailers face challenges optimizing and personalizing digital experiences based on approaches that use historical user data.
These challenges include:
- Shoppers being able to opt in or out, block cookies, or not log in before checkout
- Increasingly restrictive global privacy restrictions
- Players like Apple driving initiatives to secure personal data and promote privacy rights
As a consequence, ecommerce players need new ways of augmenting the personalization experience for their clients.
Algolia AI search: using headless to harness multiple AI and ML functions for in-session personalization
Moving beyond the all-or-nothing approach imposed by monolithic digital commerce architecture that leaves little room for customization or fine-tuning, a headless-composable strategy opens up new ways of implementing AI-personalization solutions
In the same way as the digital commerce tech stack is disassembled into its component parts, composable architecture lets us harness the power of AI search across multiple machine learning (MML) models in real time. These models can be based on:
- Categories shoppers visit
- Search queries that are entered
- Product pages customer view
This information is reconciled and used to optimize search results. It then provides recommendations based on visited product pages.
Functionalities of Algolia AI search
Algolia AI search delivers ML capabilities through configurable UIs and programmatic APIs. This makes it easy and quick for developers to implement robust AI-powered ML models across different customer channels.
Algolia AI search streamlines the deployment of AI throughout the user journey. It operates on three main models:
- Intent-based search and navigation
Intent-based search and navigation identifies users’ shopping intent and shows them the right products whether they enter a search term, browse your digital storefront, or interact with your voice assistant application.
An influential Italian factory outlet increased its average order value by 20% using intent-based search and navigation.
- Intent-based recommendations
Intent-based recommendations predict products and proactively showcase them to shoppers based on their intent and context, such as a product or checkout page.
A retailer that developed an advanced content strategy including buying guides could pull a recommendation API on their editorial content pages to showcase products relevant to a buying guide, and the actions the shopper reading the guide took in their current session.
- Intent-based user segmentation
Intent-based user segmentation classifies shoppers based on their predicted intent, triggering a series of predefined or orchestrated scenarios to move them forward in their shopping journey. This intent can include a likelihood to purchase, a prediction for cart abandonment, or other user journey attributes.
A leading home and furniture retailer in Eastern Europe leverages intent-based user segmentation to identify shoppers with a medium probability of purchasing. The technology pushes discounts and free shipping to those shoppers to incentivize them to buy. This retailer was able to double conversion rates and increase average order value by 45%.
How Algolia integrates with a headless strategy
Algolia's AI search is designed to meet the needs of businesses operating on ecommerce platforms as they move to headless architecture. Our solutions maximize the flexible and dynamic possibilities that the new architecture opens up.
At the same time, as we enable powerful personalization and search capabilities, our search solutions also address critical issues like privacy and personal data protection concerns that are impacting the behavior of consumers and retailers worldwide.
Innovative search solutions like our Image Recommendation API take the principles that power Algolia Recommendation technology to a new, higher level. Moving beyond text and keyword search, our latest solution empowers users and their customers with a multimodal experience that enables a high-performance and lightning-fast image retrieval API.
By applying a combination of image vectorization, binary hashing, and vector retrieval technology, the Algolia Image Recommendation API can be used in a range of use cases, including:
- Suggesting similar products to customers if the items they’re looking for are unavailable
- Promoting specific product images tied to certain topics or locations
- Encouraging users to explore your catalog by displaying similar items
- Offering customers similar items that generate better margins or a lower cost option
Transitioning to headless in steps, not leaps
More than half (60%) of consumers say they will likely become repeat buyers after a personalized shopping experience with a retailer. Given the importance of search in shaping a customer's online shopping journey, it’s no surprise that search and discovery is one of the first APIs implemented in a headless migration.
What businesses running commerce platforms have to remember is that transitioning from traditional architecture to headless does not involve the lengthy and expensive process of moving from one monolithic commerce platform to another all-in-one commerce platform.
The beauty of headless is that re-platforming simply isn't necessary. Instead, you can use headless technologies to migrate small pieces of your functionality from your traditional commerce platform in discrete phases.
It can start by integrating key components like AI search, then expanding incrementally as your teams get used to the new architecture.
On the backend, Algolia AI Search helps aggregate product data from across your headless system and delivers it to the other applications and micro-services that need it. This includes a monolithic system if you still run part of your stack on one.
Algolia can power and manage the delivery of any product and content the shopper came for on your web store and different channels. You can also continue to customize your customer and employee-facing frontend as needed by implementing a range of search elements like search-powered category pages, related items, or federated search.
Headless lets you add as many customer touchpoints as you need, such as ecommerce websites, mobile applications, in-store kiosks, chatbots, and FAQs. Instead of worrying about frontend and backend dependencies, and the impact on critical backend systems, you can focus on upgrading customer interaction, AI personalization, and the overall search experience, improving conversions and bottom-line results.
Using Composable UI to get an AI-powered storefront up in minutes
In the fast-evolving and competitive B2B and B2C ecommerce landscape, profitability is all about staying ahead of the curve and your competition.
This translates to experimenting and quickly testing new iterations and configurations. You need to switch things up quickly to address the changing demands of your clients and customers.
Along with Algolia AI Search, Composable UI, an open-source Next.js storefront from Composable.com, offers a powerful combination of speed, efficiency, and advanced technology. It lets you set up a headless commerce storefront that integrates AI-driven search in just ten minutes!
Composable UI's modular architecture, flexibility, and control ensure that you can add or remove functionalities as needed, making it easy to test new features without disrupting your entire system.
Integrating Algolia with Composable UI means you can harness the power of advanced search. You can test and implement a range of functionalities without getting bogged down by complex configurations or working through time-consuming processes and dependencies.
5 steps to optimizing the shoppers’ journey: Implementing Algolia AI search on a headless commerce platform
Headless lets businesses harness the full power of Algolia's search tools and technologies to create great experiences across channels for your customers.
With the constant and rapid pace of change in the technology space, headless provides online retailers and B2B ecommerce enterprises a dynamic commerce platform that lets you evolve quickly and always remain flexible.
Here are five steps to enabling your headless transition:
1. Define a purpose and get business buy-in
An incremental or larger-scale transition to a headless implementation should be a partnership between business and IT teams. You should always start with a plan and identify which features and data to transition. We suggest starting with critical areas like mobile and web content.
2. Conduct a discovery and gap analysis
Survey your existing platforms and tools and what those platforms support. Then, determine the features like AI search that will help you generate a unified customer experience across touchpoints.
3. Build a migration roadmap
Start by focusing on migrating technologies that will sustain the current platform but create the most significant impact on the customer experience. Implementing Algolia AI search can enable a range of AI personalization features across critical customer touchpoints. It also provides IT, merchandising, and marketing teams with rich data on customer behavior and choices.
4. Define a data standard
Build a standard for modeling and consuming data with your IT, design, and merchandising teams. Keep customer experience and internal business processes in mind and make sure that the information collected can support multiple countries, be indexed within a search database, and be used by multiple API micro-service solutions and technologies.
5. Import, test, and migrate
Determine which data pieces, content, or elements can be automatically migrated and which must be entered manually. Then test the customer experience. Ensure your new features
meet customer and business process requirements. Don't forget to optimize systems for search relevance and conversions on an ongoing basis. You can use the A/B testing features that are part of Algolia AI Search to test and test again!
Meeting customer needs across channels and critical touchpoints, or supporting staff to execute customer focused outcomes, headless commerce and Algolia AI search open up a realm of expanding possibilities to delight customers and improve conversions.
The transition is all about increasing the level of customer engagement while speeding up updates and performance. For some retailers, the move to an Algolia AI Search implementation on a headless commerce platform, has increased conversion rates by 60%, while cutting production times by 90%.
With headless and composable architecture, you’re not just future-proofing — you're thriving as technology advances. Algolia AI Search brings to your customer journey what headless commerce brought to ecommerce tech stacks: flexibility and a new horizon of customer-focused processes and innovation.
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