We decided to give scandiweb full ownership of our eCommerce ecosystem. It was the right choice!

Oskar Röös
CIO at Byggmax

About

Byggmax is a leading DIY retailer in the Nordic region, operating 160+ physical stores across three countries alongside a large-scale eCommerce operation, offering a catalog of more than 55,000 construction, renovation, and home improvement products.

In 2023, their clients were affected by inflation and growing energy prices. This meant Byggmax had to find ways to increase order value without adding friction to the buying experience or increasing acquisition spend. To reach ambitious revenue targets, they integrated a new personalization and marketing automation suite to increase average order value (AOV) and conversion rates across all markets.

Problem

Byggmax operates in a price-sensitive category with tight margins and high transaction volume. External pressures from inflation and rising operational costs heightened the importance of extracting greater value from existing demand. Small inefficiencies in order value compound quickly when applied across thousands of orders. 

Email marketing was already in use, but its impact on cart size and purchases was limited.

The issues showed up as:

• Average order value limiting revenue efficiency
• Email activity focused on communication, not fully utilized to influence purchasing behavior 
• Limited use of personalization
• Missed opportunities to surface relevant products from a large catalog
• Difficulty scaling manual optimization for high transaction volumes.

Solution

Marketing automation foundation

We integrated Dotdigital and introduced a new marketing automation setup to support core customer journeys and establish a consistent automation backbone for email communication:

• Automated abandoned cart emails
• A structured welcome flow
• Inactive customer re-engagement emails.

Personalization embedded into automation

To more precisely influence purchasing behavior, we implemented Dynamic Yield AI-powered personalization to enable 1:1 personalization at every step of the user journey. Personalization extended into email content, where product recommendations were dynamically generated based on customer behavior.

Content and recommendations were tailored for 10 distinct customer segments, allowing Byggmax to surface relevant products from its 55k+ catalog without manual curation.

Email and SMS working together

Alongside email, SMS was introduced to support high-impact moments, such as post-purchase updates and one-time promotional campaigns. SMS complements email automation by providing timely, transactional, and promotional touchpoints where immediacy matters.

Testing tied to commercial impact

We ran a structured A/B testing program for the website and email content. Variants were evaluated based on measurable commercial performance: increase in average order value and direct revenue impact.

All personalization, automation, and data usage were implemented in compliance with the Swedish Data Protection Act, ensuring that customer data handling met regulatory requirements while scaling across markets.

Outcome

Personalization and marketing automation have become core to how Byggmax supports large-scale eCommerce growth:

• Personalization and marketing automation supported eCommerce growth to $1B/year
• Average order value increased by 15%

The combination of automated email flows, 1:1 personalization for 10 customer segments, and coordinated email and SMS communication allowed Byggmax to extract more value from existing demand while maintaining operational control and regulatory compliance.

If revenue growth is constrained by order value or conversion efficiency, we can help you identify where personalization and automation will have the highest impact.

The post Driving Growth to $1b/Year with Personalization and Marketing Automation appeared first on scandiweb.

CircuitMess is a global eCommerce brand creating educational DIY electronics kits that teach children and adults how technology works through hands-on learning. The business sells directly to consumers online, serving a highly engaged but diverse audience spanning different age groups.

With products that often require explanation, education, and follow-up engagement, customer journeys play a critical role in conversion and repeat purchases. Email was already part of CircuitMess’s marketing mix, but its impact on revenue was limited.

Problem

CircuitMess had email campaigns and basic automations in place, but the channel was not built around customer journeys or buying behavior. As a result, email was underperforming relative to its potential and was not contributing meaningfully to overall revenue growth.

The issues showed up as:

• Emails not aligned to where customers were in their journey
• Limited use of lifecycle logic to guide customers toward purchase
• Generic messaging that didn’t reflect product complexity or intent
• Missed opportunities to educate, nurture, and re-engage users.

Solution

We rebuilt CircuitMess’s email program around clear lifecycle stages and customer intent. Each journey had a defined role in guiding customers with valuable, clear messaging rather than simply promoting offers. We kept our focus on practical improvements that could directly impact revenue, leveraging the channel’s existing elements and strengthening them where measurable impact was achieved.

Rebuilding core automated sequences

Core automated email sequences were rebuilt to improve structure, clarity, and conversion impact, without introducing new complexity:

• Updated layouts designed to improve readability and engagement
• Refined copy to reduce friction and support conversion
• Stronger conversion triggers within existing automations
• Ensuring automated emails followed a consistent structure and hierarchy.

Conversion-driven email templates

We created a new, unified template system for campaigns and automations, improving visual hierarchy to guide attention toward primary actions and reducing unnecessary elements that distracted from conversion. Templates were treated as conversion assets, allowing us to compare and test results reliably.

Opt-in growth and audience capture

To strengthen the email channel’s input quality, new opt-in forms were implemented, allowing email performance improvements to scale with list growth:

• Improved placement and design of sign-up forms
• Focus on capturing higher-intent subscribers
• Alignment between opt-in messaging and downstream email content.

Continuous testing and optimization

We introduced an ongoing testing approach to improve performance over time by applying A/B testing to email designs, content, and CTAs to understand what drove stronger engagement and revenue contribution. Higher-performing variants were identified and continued, while underperforming elements were refined or removed. Testing was applied consistently across campaigns and automated emails.

Audience segmentation

We refined segmentation and targeting to ensure each template performed effectively across audience groups, with adjustments made to targeting based on engagement behavior. Email content got aligned with product launches and seasonal events to support sales and retention.

Outcome

scandiweb’s team created 51 new email templates for campaigns and automations, resulting in a 24% increase in eCommerce revenue driven by new emails.

The redesigned templates created a consistent, conversion-focused foundation. Instead of isolated improvements, performance gains now compound as new campaigns and automations reuse the same proven structures.

If your email program is live but not driving measurable growth, we can help you rebuild it around customer journeys that convert.

The post Restructuring Email For Customer Intent Drives 24% Revenue Growth appeared first on scandiweb.

FELCO is a Swiss premium brand recognized globally for its professional pruning tools and garden equipment in multiple international markets, serving professional and enthusiast customers through direct-to-consumer eCommerce.

With a broad product catalog and customers returning over long usage cycles, FELCO’s eCommerce growth depends on repeat purchases, timing, and relevance across markets. As the business expanded internationally, lifecycle marketing became a critical lever for consistently and at scale monetizing existing demand.

Problem

Email activity existed, but it was not structured as a scalable revenue system. They had incomplete lifecycle automations with varied market-specific execution and uncoordinated personalization for regions and languages.

The issues showed up as:

• Fragmented lifecycle revenue potential
• Different engagement and personalization by region
• Email not operating as one of the business’s primary revenue channels.

Solution

We built a centralized email and SMS lifecycle revenue engine, designed to operate consistently across markets while remaining locally relevant.

Lifecycle automation

All core lifecycle automations were designed, built, localized, and launched to form the backbone of lifecycle revenue generation:

• Opt-in and list growth mechanisms
• Welcome flows
• Browse, cart, and checkout abandonment sequences
• Post-purchase journeys

Multi-market and multi-language rollout

The entire lifecycle system was launched within 30 days – localized across 5 markets and delivered in 3 languages. We adapted email designs to maintain brand consistency while supporting local content and language requirements.

SMS channel implementation

Alongside email, we implemented an SMS channel focused on high-intent touchpoints and key seasonal moments, ensuring messaging complemented, rather than duplicated, email journeys.

Ongoing optimization

Performance data was actively used to refine content and offers, optimize timing and cadence, and improve engagement and cross-market revenue contribution. Segmentation frameworks reflect different buyer profiles and regional behaviors, enabling more relevant communication at scale.

Outcome

Lifecycle marketing shifted from fragmented execution to a central, scalable revenue system, capable of supporting international growth without increasing operational complexity.

• €150K in monthly revenue established from lifecycle marketing
• Email and SMS became one of FELCO’s biggest marketing channels
• All core lifecycle automations were live across 5 markets and 3 languages within 30 days.

If your eCommerce business operates in multiple markets but lifecycle revenue remains fragmented, we can help you build a centralized email and SMS engine that scales globally without losing local relevance. Let’s talk!

The post Building a €150K/Month Lifecycle Revenue Engine in 5 Markets appeared first on scandiweb.

MyNextMattress is a leader in the UK mattress industry. The business operates in a category where purchase decisions are infrequent, high in consideration, and heavily influenced by timing and promotions.

Email had never been used as a sales channel for MyNextMattress. This made the approaching Black Friday and Cyber Monday a practical test case — a short, high-intent window where the company could quickly determine whether email was worth investing in as a revenue channel at all.

Problem

There was no email infrastructure in place, no lifecycle flows, no subscriber base, no campaign history, and no baseline for email performance, since email had never been tested or proven as a revenue channel for the business.

The issues showed up as:

• Peak traffic would come and go, with no way to reconnect with visitors
• Purchase consideration is lost after the session
• Email remains an untested channel with no evidence to support future investment.

Solution

To validate email as a revenue channel within a limited timeframe, we focused on rapid execution with the goal of proving email’s revenue potential during BFCM.

Email channel launch

We established an end-to-end email marketing strategy, including planning, design, copy, technical setup, and readiness for peak traffic.

High-intent BFCM campaigns

We designed and built three high-impact BFCM email campaigns, fully aligned with on-site promotions. Each campaign was created to support urgency and drive conversions. In a focused scope, we:

• Concentrated on the highest-intent moments
• Aligned offers and messaging with the eCommerce experience
• Prioritized speed and clarity over long-term complexity.

Performance-driven insights

Data from campaign performance were used to assess revenue contribution, validate email as a viable growth channel, and define next steps for scaling email and automation beyond BFCM.

Outcome

• £10,000+ in incremental revenue generated from email marketing during BFCM
• 1176% ROI
• Every £1 invested returned ~£12.75 in revenue

MyNextMattress email moved from non-existent to revenue-generating within a single peak sales window.

If email isn’t part of your eCommerce growth model yet, or isn’t performing like you want it to, we can help you launch it with a clear revenue goal.

The post Launching Email from Zero with 1176% ROI During BFCM appeared first on scandiweb.

Christmas Tree World is a UK-based online retailer specializing in high-quality artificial Christmas trees and festive decorations for homes and businesses. With nearly 40 years of tradition behind it and a reputation for realistic products and strong customer service, the company serves individual consumers and commercial clients seeking large-scale festive installations.

The business operates in a highly seasonal market, where a significant share of annual revenue is generated within a concentrated window. Their eCommerce store plays a central role in capturing peak-season demand, converting high-intent traffic, and turning first-time buyers into repeat customers year after year; therefore, the performance of owned eCommerce channels during critical seasonal periods directly impacts annual revenue. 

Problem

Christmas Tree World wasn’t short on demand, given that traffic was there, and seasonal peaks were as strong as ever. However, revenue contribution from email was inconsistent, and the channel lacked the structure required to support growth

The issues showed up as:

• Fragmented and outdated lifecycle flows
• Campaigns focused on promotions, not customer progression
• Shallow segmentation, limiting relevance and conversion
• Inconsistent email revenue
• Customer feedback and social proof not feeding back into revenue.

Solution

To maximize the value of owned channels and establish email as a reliable driver of growth, we redefined our approach around customer lifecycles and high-intent moments.

Expanded lifecycle architecture

We designed and deployed:

• Welcome flows to convert first-time subscribers
• Browse, cart, and checkout abandonment sequences
• Post-purchase journeys to encourage repeat buys
• Win-back automations for re-engagement.

Campaign strategy realigned to intent

Campaigns went from generic promotions to targeted messaging that guided customers toward conversion points based on their behavior. We also reframed messaging with clear roles, e.g., education, inspiration, scarcity, and cross-sell, instead of relying on discounts alone.

Templates were redesigned for clarity, visual hierarchy, and mobile performance, ensuring each email had a measurable conversion function embedded in its layout.

Segmentation and testing

We introduced customer segmentation by lifecycle stage, browsing behavior, and purchase history, along with ongoing testing of elements such as subject lines and offers to maximize engagement.

Outcome

In the first three months post-implementation:

• £1.2M in revenue was attributed directly to email marketing
• 18,960% ROI
• £190 generated for every £1 invested

Christmas Tree World’s email transformed from a background channel into a high-margin, predictable revenue engine, enabling more confident planning around the peak season.

If your email is “there, but not driving growth,” let’s talk about how to turn it into a reliable revenue lever, not just another promo outlet.

The post Generating £1.2M Revenue by Turning Email into a Predictable Revenue Channel appeared first on scandiweb.

How a store looks is only part of the equation. How it feels to use, how easily shoppers can find products, move between categories, and complete a purchase plays a bigger role in whether they convert or drop off. As more Shopify brands expand their catalogs and partner with third-party sellers, site structure and UX become just as critical as design. Updates to product pages, filters, navigation, and even the menu can have a direct impact on revenue, especially during high-traffic seasons.

With Q4 approaching, Salt Life needed their Shopify storefront to convert better without disrupting day-to-day operations. The catalog was expanding fast, and mobile UX issues were starting to impact discoverability and cart performance.

This case study covers the redesign of the Salt Life Shopify storefront ahead of the busiest shopping season, aiming to address key friction points, modernize the design, and support growth now, while also preparing a design system to scale the client’s wider portfolio in the future.

About

Salt Life is one of several lifestyle and apparel brands managed by Thread Collective, a Canadian company that owns and distributes recognized international clothing labels like Mexx, Nautica, Kenneth Cole, and Kanuk. Our redesign focused on the Salt Life store with a long-term vision to use components, templates, and design principles across other brands.

Project goals

Salt Life’s current Shopify store had design gaps on key pages and missed opportunities to guide users through the product discovery process. We aimed to redesign the Salt Life Shopify storefront ahead of the busiest shopping season:

• Improve the design and UX of Salt Life’s Shopify store to increase conversions and support Q4 sales
• Update core storefront templates: homepage, PLP, PDP, mini-cart, search, and main menu
• Make it easier for users to navigate a growing catalog (30+ categories expected by the end of the year)
• Introduce PDP enhancements to connect related products with different fits or styles
• Support drop shipping categories operated by third-party licensees
• Deliver updates efficiently within the existing Shopify theme to avoid disruption
• Test AI-generated product imagery, homepage banners, and video content as part of the visual refresh
• Create a scalable design foundation for future brand stores within Thread Collective’s portfolio.

Approach

Discovery revealed that the existing store structure couldn’t support the upcoming 30+ category expansion. Mobile filtering was already underperforming, and navigation issues made it harder for newer audiences to find what they needed. The storefront was struggling to keep up with the growing catalog demands and the expectations of new audiences, particularly younger shoppers and women.

UX research

We defined customer personas, key user journeys, and what success should look like from a UX and conversion perspective. Salt Life’s internal team provided valuable input early on, and we worked collaboratively through reviews to refine each page without unnecessary iterations.

We ran a UX audit, benchmarking the site against eCommerce best practices to see how top-performing eCommerce brands in the industry approach layout, navigation, and feature design. Some key issues included:

• A confusing mobile menu with non-functional chevrons and poor category hierarchy
• Lack of a clear value proposition on the homepage for new users
• Filtering issues on PLPs, particularly on mobile
• No visual product labels to highlight promotions or categories
• Cart UX that didn’t allow users to remove items, increasing friction.

Scalable design system

With plans to scale the same design across other Thread Collective brands, we approached Salt Life as the foundation for our design. 

The design system was then adapted for Thread Collective’s Ecko brand, showing how quickly the Salt Life base could support other storefronts with minimal rework.

UX upgrades introduced:

• Improved filtering with custom logic and UI
• Category sliders and product connections on PDPs
• Larger, bolder imagery with lifestyle visuals
• Better size guides with measurement support
• Clean site-wide navigation with visual hierarchy.

Shopify store redesign

We adapted the existing Shopify theme’s core templates with new high-fidelity UX-optimized wireframes (homepage, PLP, PDP, cart, mini-cart, search, and navigation), layouts, and components. This phased approach let us move quickly while preserving the client’s operational stability during Q4, i.e., the critical revenue season.

Platform workarounds

To make the growing catalog easier to navigate, especially on mobile, we needed a more intuitive way to filter collections. Shopify didn’t support it natively, so we introduced a custom workaround using meta objects to enable seamless sub-collection filtering.

Our solution was to create a new meta object called Categories, mirroring their existing Product Size Chart structure. This allowed us to:

• Pre-populate each product with collection titles via automation
• Display sub-collections in a horizontal slider
• Enable dynamic filtering with no page reload
• Maintain performance and style consistency across devices.

AI-generated visuals

Salt Life also introduced AI-generated content across the site, including homepage banners and product images. Our team ensured the visuals were supported throughout the new design, optimized for performance, and aligned with brand tone.

Results

The new storefront launched ahead of Q4 and resolved key UX friction points. Mobile filtering and navigation are now structured to support the full 30+ category catalog. Product discovery is faster and clearer, cart usability issues are removed, and content speaks more directly to new audiences.

The new design system has already been adapted for another Thread Collective brand with minimal rework, proving its scalability across the portfolio.

Planning to scale your Shopify catalog or unify design across multiple brands? Let’s identify the UX friction points that might be holding growth back and build a foundation that converts.

The post Shopify Redesign for Salt Life: Brand Refresh and Growth Foundation appeared first on scandiweb.

AI agents are already solving real problems, handling product enrichment, support tickets, forecasting, and internal workflows. And while chatbots are what most people still associate with AI agents, the reality is different. A chatbot answers questions. An AI agent gets things done: inside your systems and across your data.

That’s why more companies are now turning to AI agents to reduce manual work, speed up decision-making, and scale operations without growing headcount. But where do you start?

In this guide, we’ll give you a vetted list of 16 companies that know how to build and implement real AI agents. You’ll also find practical examples across eCommerce, sales, logistics, HR, and analytics, so you can see exactly where AI agents are already making an impact.

Key takeaways

• An AI agent is software that acts toward a goal; it uses reasoning, memory, and tools to complete tasks inside your systems, not just respond with text.
• To get the most out of AI agents, start with business problems, not tools: ask for a pilot tied to one KPI, then scale what works.
• Favor agencies that ship integrated workflows across ERP, CRM, PIM, and data warehouses, not just chat UIs.

What is an AI agent?

An AI agent is software that pursues a goal and takes actions to achieve it. It reads context, plans the next step, calls tools or APIs, updates systems, and checks the result against a target. Think of it as an autonomous layer that turns instructions and data into completed tasks.

Unlike a static chatbot that only replies, an agent can work inside your stack. It can check stock, create a draft purchase order, enrich a product record, or route a support ticket with a suggested resolution. In eCommerce, this might mean turning a shopper’s idea into a product list, checking a product feed before launch, handling returns, or flagging something unusual in your daily sales.

Every reliable agent has a few common parts. Inputs can be text, files, events, or database rows. Reasoning and policies decide what to do next. Memory keeps useful context, so the agent does not repeat itself. Tool access lets it act in ERPs, CRMs, PIMs, WMS, or analytics. Monitoring records what happened, and handoff rules send edge cases to humans.

What matters most is that well-designed agents are built around a clear KPI, not just clever prompts. They must record what they do, and be regularly tested to see how well they hit their goal. Tracking things like accuracy, speed, and cost helps teams stay focused on business impact and makes the agent safe to scale.

Best AI agent development agencies and companies

We reviewed dozens of agencies across the US and Europe and selected those that go beyond chatbots to deliver real AI agents: tools that take action inside live business systems. We focused on those with proven results, not just frameworks, and highlighted their strengths by use case and industry.

Also read:
Best AEO Agencies to Help You Get Mentioned in AI-Powered Results

1. scandiweb: Custom eCommerce agents for measurable ROI

scandiweb has spent 22+ years building and optimizing large-scale eCommerce ecosystems, delivering 2,100+ projects with 600+ in-house specialists and the world’s most certified Adobe Commerce and Hyvä teams. That depth matters when your agent must talk to Magento or Shopify, or any other eCommerce platform, besides respecting catalog logic, and updating analytics cleanly.

What they build:

• AI agents for merchandising, content, feed QA, support triage, analytics summaries, and AEO
• Multi-agent workflows that coordinate product data, marketing ops, and BI dashboards.
• Analytics copilots that summarize GA data, surface anomalies, and recommend actions.

Best for: If you need agents that live inside eCommerce processes (catalog, PDP/PLP, checkout, PIM, OMS), plus the analytics to prove ROI.

2. STX Next: Python-first agent engineering for data-heavy use cases

STX Next builds agents with a Python core and a strong data spine, then wires them into your internal systems. Their team emphasizes human-in-the-loop controls, dashboards, and gated rollouts, which suits regulated workflows. Typical projects include agents that fetch from internal APIs, process files, and post results back into CRMs, ERPs, or data warehouses. If you need a partner that treats the agent as a production microservice with observability rather than a demo bot, this is a solid fit.

Best for: Enterprises that want senior Python talent to connect agents to internal data sources and APIs.

3. 10Clouds: LLM products with RAG and vector search

10Clouds delivers retrieval-grounded assistants that draw on private knowledge bases, with LangChain and vector databases as standard building blocks. They focus on secure deployments, cloud readiness, and the practical details of permissions, tool calls, and evaluation so the agent stays on-task and auditable. Their work spans knowledge copilots, automation bots that call business tools, and production RAG systems.

Best for: Research assistants, knowledge copilots, and task agents that depend on accurate retrieval.

4. Neoteric: Conversation and decision agents for growth teams

Neoteric ships conversational agents that plug into marketing, sales, and support stacks, then tunes them on brand data and product context. Expect careful attention to prompt strategy, fine-tuning, and analytics hooks so teams can see what the agent answered and why. They also support broader AI builds when the use case needs prediction or classification alongside chat.

Best for: Support, pre-sales, and marketing assistants tied to CRM and CDP data.

5. Vstorm: Agentic automation for ops and BI

Vstorm focuses on multi-agent workflows that move data across tools, close loops, and report outcomes. Their consultants bring MLOps habits to agent projects, which helps with testing, rollout, and ongoing evaluation. If your current process bounces between sheets, tickets, and dashboards, they will model each step as a tool-using agent and orchestrate the flow.

Best for: Replacing manual hand-offs across spreadsheets, tickets, and dashboards.

6. MindTitan: Applied NLP and computer vision

MindTitan builds practical AI for the public and private sectors, with experience in NLP, CV, and robust data pipelines. Their work often targets service operations where quality of service and traceability matter, such as telecom and government use cases. They pair model work with the plumbing that feeds and monitors it.

Best for: Ticket deflection, routing, and classification with measured QoS.

7. Eleks: Enterprise AI with governance and integration depth

Eleks approaches agents as part of a larger transformation: data platforms, security, and integration patterns sit alongside the agent logic. They support agentic systems across finance, healthcare, energy, and manufacturing, and provide the governance scaffolding enterprises expect. If you need a partner that can manage multi-system rollouts with documentation and change control, add them to the shortlist.

Best for: Enterprises that need strong PMO, documentation, and compliance.

8. DataRoot Labs: R&D-grade LLM and multimodal builds

DataRoot Labs takes on higher-ambiguity work, including custom LLMs, RAG pipelines, and multimodal agents. They design evaluation harnesses so teams can measure progress and failure modes rather than rely on gut feel. When the problem requires research rigor and fast prototyping, their model-plus-engineering approach helps de-risk the path to production.

Best for: High-ambiguity projects and prototypes that need research rigor.

9. Systango: Analytics-led ML and anomaly detection agents

Systango builds agents that sit on top of predictive and anomaly-detection models to support finance, marketplace, and ops decisions. They combine data engineering with ML so agents can pull fresh signals, score risk, and trigger actions or human reviews. This is useful when outcomes must be tied to quantified thresholds rather than open-ended chat.

Best for: Finance, marketplaces, and ops teams that need data-first agents.

10. ITRex: Broad agent catalog and system design

ITRex offers a full catalog of agent types, from rule-based and goal-driven to learning agents, and handles the lifecycle from strategy to support. They are comfortable integrating with enterprise stacks and setting up the monitoring and guardrails needed for long-running automations. If you want one vendor to cover several departments, their scope fits.

Best for: Firms seeking a single partner for multiple agent types across departments.

11. HatchWorks: Strategy to shipped agents for product teams

HatchWorks pairs product strategy with delivery using a method they call Generative-Driven Development. Agents and autonomous workflows are woven into sprints, with clear ROI checkpoints and governance baked in. This suits product organizations that want working software on a predictable cadence, not a one-off experiment.

Best for: Product organizations that need a pragmatic path from idea to pilot to scale.

12. LeewayHertz: Build-to-spec agents using popular frameworks

LeewayHertz assembles task-focused agents with tools like AutoGen Studio, Vertex AI Agent Builder, and crewAI, then connects them to enterprise systems. Their value is speed: they map the use case to a known pattern and stand it up with logging, testing, and versioning so teams can iterate safely.

Best for: Rapid sprints to stand up specialized agents with known tools.

13. Markovate: Compact team for LLM agents and voice interface

Markovate develops LLM agents alongside voice interfaces for call handling, order capture, and field workflows. They can deliver a chat or voice layer and the integrations needed to fetch data, update records, and confirm actions in real time. That mix is useful when users are on the move or when phone traffic remains high.

Best for: Support and field workflows where voice matters.

14. ML6: Applied AI consultancy

ML6 is a European consultancy with deep data engineering and MLOps capabilities. They help teams move from models to reliable services and partner closely with major cloud providers. If your agents need strong pipelines, monitoring, and cost control on cloud, they bring the required discipline.

Best for: Enterprises that need reliable delivery and governance.

15. Xomnia: Data engineering and AI

Xomnia combines data engineering with agent builds so teams can stand up agents while modernizing ELT and monitoring. They frame the agent as a data product with iterative delivery and shared metrics, which helps cross-functional adoption. This approach suits organizations that need to fix data foundations while they ship value.

Best for: Organizations that must fix data foundations while rolling out agents.

16. Intercom: Customer service agents built for real-time support

Intercom focuses on AI agents that go beyond simple chatbots. Instead of just answering questions, these agents resolve issues, suggest resources, and escalate to humans when needed. They integrate with CRMs and help desks so every interaction is tied to customer history. For teams under pressure to shorten response times and reduce drop-offs, Intercom’s agents provide consistent, always-available support across chat, email, and in-app messaging.

Best for: Companies that want customer service agents to deliver instant, context-aware support across multiple channels.

How AI agents deliver real impact across different business functions

When connected to the right data and tools, AI agents can act, adapt, and support multiple parts of your operation, without needing a human to hand-hold every step. Below are practical examples of how AI agents are already helping teams get more done with less manual work.

Product information and content

Keeping catalogs accurate is a constant challenge. A product data agent reduces that burden by validating specs, correcting inconsistencies, and syncing with PIM or ERP feeds.

On the customer-facing side, content enrichment assistants step in to improve titles, descriptions, and feature lists while also helping with localization and SEO.

Merchandising and category management

Merchandising decisions often rely on guesswork, but a merchandising agent changes that by monitoring PLP data, margins, and stock levels, then suggesting new sort rules or groupings based on performance.

Campaigns also benefit from support: a promotion optimizer detects broken promo logic or overlapping discounts and recommends corrections, ensuring that promotions drive sales without undermining profit margins.

Customer service and support

In customer service, repetitive queries quickly overwhelm teams. Support copilots provide relief by answering FAQs, suggesting help articles, and routing complex issues to the right person.

Returns and complaints, another high-volume area, can also be automated: agents categorize incoming tickets, check order histories, and initiate refund or replacement workflows. Some systems also go a step further by turning email exchanges into a searchable knowledge base, making it easier for support teams to find answers and act quickly.

See a practical customer service agent walkthrough that shows how agents handle FAQs and escalate complex cases.

Sales and personalization

Personalization has become essential for digital sales. An onsite personalization agent adapts recommendations, banners, and messaging in real time by drawing on CRM and CDP data.

At the same time, cart abandonment agents reduce drop-offs by detecting exit signals and following up with tailored nudges through chat or email, escalating to a human when purchase intent is especially high. Together, these agents help recover lost revenue and make shopping experiences more relevant.

Explore how HubSpot form enrichment with AI improves lead quality and saves sales teams time.

Analytics and performance monitoring

Staying on top of performance requires constant vigilance. An analytics copilot scans sales, traffic, and conversion rates for spikes or drops, then summarizes anomalies in plain language and suggests next steps.

Looking further ahead, a forecasting assistant studies historical patterns in sales, returns, and customer behavior. Its projections inform inventory planning, marketing budgets, and staffing decisions, helping businesses prepare instead of react.

Operations and fulfillment

Finally, logistics also gain from agentic support. Supply and fulfillment agents keep an eye on carrier SLAs, stock levels, and delivery times, flagging issues and proposing alternatives such as split shipments or alternate routes.

On the other hand, order flow monitors ensure nothing gets stuck by checking statuses in real time and triggering alerts or fallback actions when errors appear.

Case study: How a Nordic DIY retailer scaled project guidance with a 24/7 sales assistant

A leading home-improvement chain in Sweden, Norway, Finland, and Denmark runs 200+ stores and exceeds $1B in annual revenue. Roughly 70% of annual revenue is concentrated between May and September, and customers come in with project ideas but no product lists. Staff expands by up to 10x, mostly temporary workers, and training is too slow and inconsistent.

In collaboration with Algoritma, we built a web-based ShopBot trained on common DIY projects and connected to the full product catalog. The assistant can advise on projects step by step and recommend SKUs, sizes, and quantities. Acting as a form of conversational commerce, it guides shoppers, generates a clear plan for customers, and supports store teams with consistent answers.

Also read:
How AEO Helped Enviropack Become a Top AI Pick for Sustainable Packaging

How to pick the best partner for AI agent development

Not every agency that builds with LLMs can deliver a reliable, goal-driven AI agent. The difference comes down to whether they treat your project as a production system or a demo. Choosing the right partner means asking the right questions—not just about model choice, but about systems, measurement, and long-term fit.

The strongest vendors will build around your KPI, understand how to work with your stack, and deliver something your team can trust, own, and improve over time. Use this checklist to compare vendors objectively and keep the focus on outcomes.

What to look for

Score each vendor from 1 to 5 on the items below.

• Business impact: Are success metrics clearly defined? Do they track accuracy, latency, cost per task, or similar KPIs?
• Data foundation: Can they access and work with data from your PIM, ERP, CRM, WMS, or analytics stack?
• Agent design: Do they explain how the agent handles memory, tool use, planning, fallbacks, and safety checks?
• Integration depth: Are webhooks, queues, API rate limits, and error handling built into the plan?
• Operations: Can they support CI/CD, secrets management, observability, and rollback? Is there a human-in-the-loop for edge cases?
• Governance and compliance: Do they have a plan for handling sensitive data (PII), red-teaming, approvals, and audit trails?
• Post-launch support: Can they monitor drift, fine-tune agents over time, and manage hosting costs?

Before you commit, ask every vendor to provide the following:

• A 3-week pilot with one clear KPI and a target success rate
• A handover pack that includes prompts, architecture diagrams, datasets, and runbooks
• An evaluation harness with example tasks, success thresholds, and test coverage
• A review process where a human approves outputs until performance is proven.

Expected future trends in AI agent development (2026–2027)

AI agents are maturing quickly. What started with single-task bots is evolving into systems that can plan, adapt, and collaborate across workflows. As adoption grows, we’re seeing clear patterns emerge around how agents are built, deployed, and governed. Here’s what AI experts are predicting for the future.

Rise of multi-agent systems

AI is moving from single-task assistants toward multi-agent systems that collaborate, critique each other, and divide complex goals into smaller steps. Forrester highlights this as part of the broader “AI agent pivot,” noting that real autonomy in production is still rare, but adoption is accelerating as frameworks mature. These systems are particularly valuable in scenarios that require planning, tool coordination, and oversight across multiple workflows.

RAG, self-hosting, and evaluation as the default stack

Retrieval-Augmented Generation (RAG) is becoming the baseline for grounded, context-aware agents. At the same time, many enterprises are turning to self-hosted or sovereign deployments to maintain data privacy, reduce latency, and control costs. This shift drives demand for evaluation and monitoring platforms such as HoneyHive, which help teams measure accuracy, safety, and cost-effectiveness before scaling agents.

Emphasis on safety, transparency, and regulation

Governance is no longer optional. The EU AI Act has entered force with obligations rolling out through 2026, while frameworks such as the NIST AI Risk Management Framework and ISO/IEC 42001 provide structured approaches to transparency, safety, and lifecycle control. Vendors that ship agents with audit trails, permission scoping, and measurable evaluation policies will face fewer roadblocks during compliance reviews.

Security as a new proving ground

Cybersecurity is becoming a key domain for AI agents. Startups like Qevlar are developing autonomous responders and analyst copilots, attracting strong investor interest. While Forrester notes that adoption in security operations is still in early stages, the potential is significant – especially for threat detection, incident triage, and automated response under human oversight.

Final thoughts

AI agents are already working behind the scenes: fixing product data, routing support tickets, flagging issues before they become problems. What’s changing is how well they’re integrated, how reliable they are, and how fast companies are putting them into production.

If you’re here, you’re not looking for another chatbot. You’re looking for something that solves real problems, connects with your systems, and supports your KPIs.

Start with one use case. Tie it to one metric. Scale what works.

And if you want a second opinion or need help getting started, we’re happy to share what we’ve learned building agents that actually ship.

Want help building your first AI agent? Join our AI Accelerator to define the use case, align on KPIs, and build a working agent in weeks. Includes workshop, roadmap, and up to 30% co-funding.

Frequently Asked Questions

What is a “real” AI agent?

A real AI agent is software that pursues a goal by planning steps, calling tools or APIs, and keeping context. Unlike a chatbot, it takes action inside systems and is measured against clear outcomes such as accuracy, speed, or cost per task.

How long does an agent take to ship?

With a clear KPI and existing APIs, a simple AI agent can go live in a few weeks. Broader, multi-system agents take longer once data work and governance are included.

What should I budget?

Expect an initial pilot in the tens of thousands, then ongoing spend for hosting, evaluation, and tuning. Data work often drives the timeline and cost.

How do we keep agents safe?

Agents are kept safe by using scoped permissions, applying rate limits, running tests and red-teaming, and adding a human-review loop. Teams also track failure modes and use an evaluation harness to monitor performance over time.

Will agents replace teams?

AI agents won’t replace teams. They take over repetitive tasks and speed up routine decisions, while people remain essential for exceptions, complex cases, and higher-value work.

About scandiweb

scandiweb is a full-service eCommerce agency helping brands build, scale, and optimize across platforms like Adobe Commerce, Shopify, BigCommerce, and commercetools. We design and implement AI agents that work inside real systems, supporting merchandising, support, analytics, and ops with measurable results.

The post Top 16 AI Agent Development Companies in 2026 appeared first on scandiweb.

Shopify provides a stable foundation for brands seeking a more manageable and reliable tech stack, as well as a storefront that’s easy to maintain over time. Many teams also use the migration as an opportunity to update outdated data and close gaps created by years of patches and workarounds.

The move to Shopify works best with a structured approach and a realistic understanding of what needs to be rebuilt, imported, or reconfigured.

This guide breaks down the Shopify migration process into clear phases, starting with an assessment of your current setup, all the way to a live, tested Shopify store. If you’re preparing for a move to Shopify, this walkthrough will help you plan ahead and build a setup that supports steady growth from day one.

Common challenges before and after migration

Most teams move to Shopify expecting things to get easier, with fewer bugs, fewer delays, and more flexibility. And in many cases, that’s exactly what happens. But for brands with complex operations or legacy systems, the transition can expose deeper issues and sometimes create new ones if not managed carefully.

These are some of the most common challenges we’ve seen before and after replatforming:

Disconnected systems

Data doesn’t flow cleanly between tools. ERPs, CRMs, PIMs, and OMSs all need to be connected with care. Without the right architecture, syncing issues and data silos continue even after the migration.

Duplicated stores for international markets

Shopify is often set up as one store per market, which leads to duplicated catalogs and separate promotions that require more manual work across regions. Without a proper plan, complexity increases rather than decreases.

Heavy reliance on apps

Quick fixes often come in the form of third-party apps. Over time, this can create potential issues when one app fails or conflicts with another, compromising the entire flow.

Checkout limitations

Shopify offers limited flexibility for custom flows – checkout adjustments tied to region, pricing logic, or customer type can be challenging to implement natively.

SEO drops

If redirects, metadata, structure, and other tech SEO essentials aren’t handled properly, a migration to Shopify can lead to traffic losses. And recovery takes time, especially if the site had strong organic performance before migration.

No single source of truth

Even after migrating, many brands still struggle with fragmented data. Customer records don’t update in real-time, and analytics fail to reflect the complete picture. Without proper integration planning, the migration only moves the problem to a new platform.

Next, let’s walk through the Shopify migration process step by step.

Step 1: Audit your current platform

Before planning a move to Shopify, take a close look at your existing setup. A technical audit should go beyond surface-level issues. Many platforms evolve through quick fixes and ongoing adjustments, resulting in unpredictable behavior and a setup that’s difficult to manage. Reviewing how your store currently functions can reveal which parts of the system need to be replaced and which ones still serve their purpose.

Start by mapping out:

• Where your data lives (product, inventory, customer, order)
• Which tools are connected and how well they sync
• How promotions, checkout flows, or product bundles are currently handled
• Any third-party apps that feel essential but are adding complexity or cost

Next, look at content and UX:

• Are product pages consistent and easy to update?
• Does the mobile experience reflect your brand?
• Is it clear where the technical limitations are slowing down marketing or merchandising?

At this stage, it’s useful to ask: if your current store were wiped tomorrow, what would you rebuild the same way? And what would you change?

Step 2: Plan your Shopify setup

Once you understand how your current store operates, the next step is creating the foundation of your new Shopify environment. Decisions made here influence your data structure, daily workflows, performance, and the level of flexibility you’ll have long term.

Begin with the Shopify plan that best suits your needs. Stores with extensive catalogs, complex rules, or multiple markets often benefit from Shopify Plus due to its expanded limits and access to advanced features. Smaller setups can run smoothly on standard Shopify. The goal is to choose a plan that supports future growth without requiring major restructuring later.

Next, define the technical layout of your store. Some operate from a single Shopify store and manage regions through Shopify Markets. Others maintain separate stores for different countries or business units. It depends on pricing rules, tax logic, language requirements, fulfillment locations, and operational ownership inside the company.

This stage is also the time to outline integrations. ERPs, PIMs, OMSs, CRM platforms, and marketing tools all need clear data paths. If your current stack contains fragile connectors or outdated plugins, note these as items to rebuild or redesign during the migration. A dependable integration plan helps avoid issues that often appear after launch, like delayed stock updates, inconsistent product data, or incomplete customer profiles.

In parallel, prepare how teams will work inside Shopify. Roles, permissions, collaborator access, and staging environments should be arranged early, creating a controlled setup and a stable base.

Step 3: Clean and export your data

Migration also exposes the quality of the data you’ve been working with and how much of it needs improvement.

Start with your product catalog. Check for duplicate SKUs, inconsistent naming, outdated items, or mismatched attributes. If different teams have been adding products over time, structure and formatting may vary across collections. Fixing this now will prevent downstream errors during import and create a better shopping experience once live.

Review your customer database next. Identify test records, unsubscribed contacts, and incomplete profiles. Decide which segments are still active and worth migrating. Cleaning customer data before export also improves targeting accuracy for marketing flows once Shopify is live.

For orders, confirm which records are needed for historical reporting. Some brands choose to migrate all order history, while others only keep recent data. Shopify allows historical orders to be imported for reference, but they won’t behave like native orders – so plan how you want to access and report on past activity.

Most platforms support CSV exports. If your setup is more custom, API access or direct database extraction may be required. Either way, the export phase is an opportunity to restructure and clarify how data will be stored within Shopify.

scandiweb’s team often runs custom cleanup workflows at this stage. For example, during one migration, thousands of SKUs needed to be standardized before import, not just for accuracy, but to ensure compatibility with advanced search and filtering logic later on. Well-prepared data helps the rest of the migration proceed more efficiently. It also reduces support tickets after launch, since product visibility, pricing, and customer records are already in order.

Step 4: Import data into Shopify

Once your product, customer, and order data have been reviewed and cleaned, you can begin importing it into Shopify. This step often happens in phases, starting with a controlled test, followed by a broader import once everything checks out.

Product imports

Shopify supports CSV uploads for standard product fields such as titles, descriptions, pricing, inventory, and variants. For more complex catalogs, additional data like metafields, vendor references, or grouped items may need to be imported using Shopify’s Admin API or other tools. Some projects also rely on custom scripts for better control.

After the initial upload, check the results for errors. Missing images, broken variant logic, or inconsistent pricing structures are common issues. Bulk editing tools in Shopify can help resolve minor issues quickly, but more significant discrepancies may require rework at the source.

Collections and categories

In Shopify, collections can be either manual (where the team selects products) or automated (where products are included based on tags, price, or other conditions). Decide early which model fits best. Automated collections save time for larger catalogs but require consistent product data. Manual collections give more flexibility for merchandising, campaigns, or curated selections.

If your previous platform used custom category logic or allowed deep nesting, prepare for some adjustments. Shopify structures categories differently, and large taxonomies often need simplification. It’s also important to plan how URLs for collections will be handled, especially for SEO continuity.

Customer and order imports

Customer data can be imported via CSV, but certain details will not be carried over, including passwords and saved payment methods. Expect to send account activation emails once the store is live. This part of the migration should be timed carefully to avoid confusion or support overload.

Historical orders can also be imported for reporting purposes. They won’t behave like new Shopify orders (e.g., no refunds or fulfillment actions), but they help preserve account context and lifetime value tracking.

The goal here is stability, ensuring that the data appears in the right place and functions reliably for customers and your team.

Step 5: Configure payments, shipping, and tax

Once your store structure and data are in place, it’s time to set up the core functions that power transactions and fulfillment. Payment gateways, shipping rules, and tax settings each carry operational weight, and gaps in this step often show up as customer complaints or failed orders that translate into lost revenue.

Payment methods

Start by enabling your preferred payment providers. If you’re eligible for Shopify Payments, it’s typically the most common option. It covers major credit cards and wallets like Apple Pay or Google Pay, and gives access to features like fraud protection, chargeback handling, and consolidated reporting.

If your store sells internationally, activate local methods commonly used in your target regions. Payment preferences vary widely by market, and improving checkout familiarity often improves conversion rates. Shopify supports location-based logic to display relevant payment methods to each shopper.

Any previously saved payment methods from your old platform will not carry over, due to compliance rules. Customers will need to re-enter their details on their next purchase, so plan communications around this to prevent confusion.

Shipping setup

Shipping rules in Shopify are managed through zones and profiles. Define where you ship and which methods apply to each region:

• Flat rates
• Real-time carrier rates
• Local delivery
• Free shipping thresholds.

If you use a 3PL, warehouse network, or dropshipping setup, connect those providers early. Make sure they’re fully integrated before launch to avoid fulfillment delays. Shipping apps or native Shopify integrations can support this, depending on your logistics setup. Test different scenarios – local orders, international deliveries, split shipments – to confirm that shipping charges and workflows are accurate.

Taxes and compliance

Shopify can calculate taxes automatically based on store location and customer address. In more complex regions, or when selling across borders, additional configuration may be needed.

Enable Shopify Markets if you plan to support multiple currencies, duties, or tax-inclusive pricing. You can also integrate third-party tools for more granular control, especially in jurisdictions with changing tax laws. Remember – Misconfigured tax settings can trigger penalties or create liabilities post-launch.

Quick test checklist

Before moving forward, confirm that:

✓ All required payment methods are active and display correctly by region

✓ You’ve tested real transactions with at least two payment types (e.g., credit card + local method)

✓ Shipping rates calculate correctly for key zones

✓ Fulfillment logic works across split shipments or multi-warehouse setups

✓ Taxes are calculated correctly based on customer location and product type

✓ Checkout totals reflect the correct currency, tax, and shipping format

✓ Manual and automated order confirmations include all expected details.

Step 6: Protect SEO during migration

Organic traffic is one of the most valuable assets your store has, and also one of the easiest to lose during a migration. Platform changes often shift how pages are structured, how content is displayed, and how URLs are generated. Without a clear SEO strategy, visibility can drop, and recovery can take months.

1. Audit your current site to identify which pages bring in the most traffic, generate conversions, or support important keywords. These high-value URLs should be preserved or mapped as closely as possible in your Shopify structure.

Shopify uses a fixed URL format, so some changes will be unavoidable. For example, product pages will always follow the /products/ path. That doesn’t mean performance has to drop, but it does mean you’ll need a detailed redirect plan.

2. Create a complete list of old URLs and their new equivalents. Use 301 redirects to guide users and search engines to the right content. Shopify’s built-in redirect manager works for this, and bulk uploads are supported via CSV.

3. Migrations also affect metadata, structured data, and internal linking. If your original store used custom logic for canonical tags, breadcrumbs, or product schema, plan how these will be handled in Shopify. You may need theme updates or app support to recreate the same structure.

4. Before going live, submit your new XML sitemap to Google Search Console. Use tools like Screaming Frog or Ahrefs to crawl your Shopify site, catch errors, and confirm that key content is indexed and discoverable. Monitor performance closely for the first few weeks after launch, especially impressions and keyword positions for your most important pages.

Step 7: Design your Shopify store

A redesign during migration offers the chance to improve how products are found, how trust is built, and how easily customers complete a purchase within a framework that supports long-term performance and day-to-day usability.

Shopify themes offer flexible sections, speed improvements, and greater control without heavy developer input. Some brands adapt a premium theme to meet their goals, but you can work with partners to build something entirely custom. If you’re looking for performance and scalability without starting from scratch, options like our Satoshi theme for Shopify can provide a fast, UX-driven foundation that’s easy to adapt and extend.

For stores migrating from legacy platforms, there’s often technical debt embedded in the frontend, manifesting as inconsistent layouts, overlapping styles, and custom scripts that are difficult to update. This is a good moment to reset. Focus on clarity and plan design systems that scale with your catalog and feel consistent from homepage to checkout.

Banners, content blocks, promotional areas, and landing pages should be editable without developer support. If you’re using Shopify Plus, additional options like Shopify Scripts or custom checkout styling may be introduced at this stage.

Where possible, carry forward high-performing layouts from the previous store, especially on product and collection pages. Shopify allows enough flexibility to preserve familiar structures while still upgrading the experience, which helps maintain conversion performance and keeps the transition smooth for returning customers.

Page speed, mobile UX, and navigation logic all contribute to how the site performs post-launch. Keep images lightweight, test on real devices, and avoid unnecessary app installations or features that slow down the experience.

Step 8: Integrate third-party tools & systems

A migration is rarely about the storefront alone. eCommerce operations rely on a network of systems, including ERPs, PIMs, CRMs, marketing tools, analytics platforms, and fulfillment partners. 

To account for these integrations, list out every system currently connected to your platform, including internal tools and third-party apps. For each, define what the integration needs to do: push product data, pull order updates, sync customer records, or support segmentation and automation.

From there, map how these systems will interact with Shopify. While some connections can be rebuilt using Shopify’s native APIs or public apps, others may need middleware or custom connectors, especially if your current setup involves multiple sources of truth or large product catalogs.

Common integration points include:

• ERP
• PIM
• CRM/ESP
• OMS/WMS
• CDP/analytics.

Think beyond day one. Integrations often break because they’re built without version control or clear documentation. And definitely consider app usage. Some migrations copy over every tool from the old platform without re-evaluating their value. Use this moment to reduce reliance on apps that introduce overhead or performance issues. Shopify’s ecosystem offers thousands of tools, but not all are worth keeping.

Step 9: Test before launch

This phase is about ensuring the entire system functions properly under real-world conditions.

Start with a soft launch environment. Shopify allows you to preview the store under password protection while running tests in a near-live setting. This gives your team space to validate functionality without exposing the site to customers before it’s ready.

Test core user flows:

• Browsing products and filtering by attributes
• Adding items to the cart 
• Proceeding to checkout
• Using discounts 
• Using gift cards
• Creating and managing customer accounts
• Completing an order with different payment methods.

Then, test operational flows:

• Order receipt and confirmation emails
• Admin order tracking and status updates
• Fulfillment syncing with warehouses
• Product updates from your ERP or PIM
• Marketing integrations – email triggers, CRM sync, analytics tracking.

Browser and device testing should also be done at this stage. Confirm that the experience is consistent across mobile, tablet, and desktop devices, with a focus on core actions such as search and checkout. Shopify themes are responsive by default, but customizations or third-party apps can introduce display issues in specific environments.

If you’re running multiple stores or markets, test behavior across regions. Pricing, currency, tax display, language, and payment options should all reflect the correct logic for each user location. Shopify Markets can handle this well, provided they are configured and verified correctly.

Real orders should be placed internally to validate the full purchase-to-fulfillment cycle. Test edge cases too, such as partial refunds, canceled orders, or out-of-stock items.

Once the basics are confirmed, focus on monitoring. Use tools like Google Tag Manager, Meta Pixel, or GA4 to track how behavior is recorded across the site. Migrations can disrupt analytics setups, especially if tag placement or page templates have changed. A well-tested store can significantly reduce launch-day stress. It also reduces the number of early support tickets from customers encountering avoidable issues.

Step 10: Launch and monitor your Shopify store

Congrats if you’ve made it to this step in your migration timeline – it’s time to go live! But what happens after launch matters just as much as what leads up to it.

Essentials to go through:

• Remove storefront password protection
• Point your domain to the new Shopify store
• Check that all redirects are active and resolving correctly
• Submit your updated XML sitemap in Google Search Console
• Monitor traffic, behavior, and error reports from the first visit onward.

Once live, confirm that key journeys still perform as expected. Add-to-cart, checkout, payment, integrations, and customer account flows should be tested again in the live environment. 

After launch, monitor:

• Page speed and uptime
• Cart and checkout abandonment
• Product visibility and search functionality
• Channel-specific tracking (Meta, Google Ads, TikTok, Klaviyo, etc.)
• Sales trends across devices, countries, and segments.

The goal of every Shopify migration launch is the same: a stable, accurate, and responsive store that customers can trust.

Case study: Magento 1 to Shopify migration for J.R. Dunn

J.R. Dunn, a leading U.S. luxury jeweler and authorized Rolex retailer, partnered with scandiweb to move from Magento 1 to Shopify, modernizing their digital store while preserving the depth and elegance of their brand experience.

The project involved migrating a highly customized catalog of over 150,000 diamonds, with complex filtering, multi-vendor feeds, and legacy data structures. Out-of-the-box tools couldn’t provide the level of control required, so we built a custom diamond management app to import product data from five vendors, handle live pricing and availability, and integrate directly with Shopify Admin for product management and reservations.

To support advanced product discovery, we also integrated Fast Simon for smart faceted filtering and instant recommendations across a high-SKU catalog. We developed custom storefront features, including a native Ring Builder tool, without third-party dependencies to ensure long-term performance and stability. For design, we used the Satoshi theme, tailored for a luxury presentation.

Results

• 150,000+ diamonds imported via custom app
• 72,000 historical orders and 68,000 customers migrated
• 1,000+ categories and 25,000+ products restructured
• Full SEO migration with a 100 SEO score at launch
• Future-ready architecture for ERP and automation extensions.

Read the full J.R. Dunn Shopify migration case study here.

Shopify migration checklist

Let’s put it all together – use this checklist to track progress across the full migration process!

Platform audit

✓ Identify pain points, limitations, and legacy issues

✓ Map all integrations and third-party tools

✓ Review catalog structure, content quality, and data accuracy

✓ Evaluate technical performance, site speed, and UX consistency

Shopify setup

✓ Select the Shopify plan

✓ Configure account settings, staging access, and roles

✓ Plan architecture: single vs multi-store, Shopify Markets

✓ Outline integration paths for ERP, PIM, OMS, CRM, and ESP

Data cleaning & export

✓ Clean product data, SKUs, images, and variants

✓ De-duplicate and segment customer records

✓ Export historical orders if required

✓ Prepare clean CSVs or API feeds for import

Data import & catalog build

✓ Import products, collections, and content pages

✓ Set up metafields, filters, and search tools

✓ Migrate customer profiles and configure account invite flow

✓ Import historical orders for reference/reporting

Payments, shipping, tax

✓ Enable Shopify Payments and/or third-party gateways

✓ Configure domestic and international shipping rules

✓ Set up tax calculations for all regions

✓ Test payment flows and shipping scenarios

SEO & redirects

✓ Audit top URLs, keywords, and content

✓ Map and upload 301 redirects

✓ Migrate metadata and structured data

✓ Submit sitemap and monitor indexing

Design & UX

✓ Choose and customize theme

✓ Align page templates with performance and brand goals

✓ Optimize for mobile, accessibility, and load speed

✓ Enable editable content zones for marketing flexibility

Apps & integrations

✓ Review and rebuild all essential integrations

✓ Limit app usage to high-value tools

✓ Test data flow across all systems

✓ Document error handling and sync logic

Testing

✓ Run full QA across customer and admin flows

✓ Test tracking and analytics setup

✓ Validate behavior across regions, currencies, and devices

✓ Place real orders using different methods

Launch & post-launch

✓ Remove password protection and go live

✓ Confirm domain, redirects, and sitemap updates

✓ Monitor SEO performance, sales, and user behavior

✓ Support customer reactivation (passwords, saved data)

✓ Kick off CRO and performance optimization.

With the right preparation and a knowledgeable partner by your side, a Shopify migration becomes an opportunity to strengthen performance and create a store that supports growth.

At scandiweb, we’ve helped luxury retailers, marketplaces, and a range of ambitious brands with complex catalogs and global setups migrate to Shopify. If you’re planning a move to Shopify, we can help you avoid common risks during migration and set up a future-ready, customized store. Contact our Shopify expert team today to discuss your migration plan.

The post How to Migrate to Shopify: A Step-by-Step Guide for eCommerce Brands appeared first on scandiweb.

Purdys Chocolatier is a Canadian heritage brand founded in 1907, operating 81 retail stores with approximately 1,600 employees. Alongside its core retail and DTC business, Purdys runs two coordinator-led sales models, Fundraising and Group Savings – used by schools, clubs, and community organizations across Canada.

Problem

Purdys’ Fundraising and Group Savings programs were running on a 20-year-old custom-built platform maintained by a single developer. Over time, this system became a single point of failure. As volumes increased and expectations grew, the platform itself, not demand became the constraint. This was no longer a question of feature gaps or technical debt. The risk sat in the foundation: undocumented logic, manual workflows, and deep dependency on one individual for a system that directly handled campaigns, payments, and coordinator trust.

The issues showed up as:

• A mission-critical fundraising platform dependent on one developer and undocumented custom logic
• Manual handling of campaigns, delivery schedules, and coordinator payouts
• Limited visibility into campaign performance and coordinator activity
• Difficulty integrating fundraising flows cleanly with ERP, WMS, and financial systems
• Growing operational risk as volumes increased, especially during peak periods
• A separate legacy Luma frontend on purdys.com that constrained performance and flexibility.

Solution

Unified Adobe Commerce foundation

The legacy Group and Fundraising system was rebuilt on Adobe Commerce and placed under the same instance as purdys.com. This removed the standalone custom platform that had become a single point of failure and replaced it with a shared, supportable foundation for retail, fundraising, and group sales.

Custom fundraising logic

Core business rules – Seasons, Campaigns, Delivery Calendars, and Withdrawals – were rebuilt as native platform functionality. This shifted operational ownership from developers to internal teams and eliminated manual handling that previously increased risk and error rates.

Coordinator-led campaign workflows

Self-serve campaign creation was implemented for coordinators, including campaign setup, public campaign pages, and automatic order linkage. Every order is now tied to a campaign by default, removing reconciliation steps that previously depended on fragile processes.

ERP, WMS, and bank integrations

ERP (Syteline) and WMS integrations were reworked to support Group and Fundraising–specific flows. A new bank integration automated coordinator payouts via e-transfer, removing manual payout processing and reducing financial and operational risk.

Hyvä storefront rebuild (retail)

The legacy Luma frontend on purdys.com was replaced with a Hyvä-based storefront to address performance and peak-readiness risks on the retail side while the fundraising platform was being rebuilt, without introducing cross-project dependency risk.

Analytics and reporting foundation

A new analytics framework was introduced across retail and GnF sites. GA4 tracking, Looker Studio dashboards, and M2BI integration provided campaign-level visibility for the first time, addressing a critical blind spot of the legacy system.

Outcome

• Fundraising and Group Savings managed directly in Magento without developer dependency.
• Campaigns launched and tracked automatically, with consistent data across ERP and WMS.
• Coordinator payouts automated via bank integration.
• Analytics and reporting active for the first time on the GnF programs.
• Retail storefront:
  • purdys.com launched on Hyvä after four months of development
  • Described by the client as the best go-live in the company’s history.
• Measured results after the Hyvä launch:
  • +136.5% conversion rate
  • +23.7% transactions
  • +32.3% revenue
  • -25% bounce rate
  • +45.9% average session duration.
• SEO results within the first month post-launch:
  • +19.7% clicks MoM
  • +11.3% impressions MoM
  • +25.9% revenue YoY from organic traffic.

Dealing with a legacy setup that’s becoming a business risk? We help teams stabilize fragile commerce foundations and get platforms back into a state where growth is possible again. Book a 50-min ROI roadmap session with scandiweb.

The post Replacing a 20-year-old fundraising system leads to a 32% revenue increase appeared first on scandiweb.

Hyvä has just made their biggest move yet: the high-performance Magento 2 theme is now entirely open source and open to use for all.

Hyvä started as a faster, cleaner frontend for Magento 2 and is now one of the most widely adopted themes in the Magento ecosystem. With the source code fully open, it’s easier than ever to get started. It’s released under standard open-source licenses (OSL 3.0 and AFL 3.0), allowing agencies and merchants to use it in commercial projects, modify it, and distribute their own versions with no license fee required. 

Get it on GitHub or request free license keys via hyva.io!

Let’s break down what this means, what’s included, what you can do with it, and how teams like scandiweb are already using it (and have been using it) to deliver results.

Why this matters

When Hyvä launched in 2021, it solved Magento’s biggest pain point: frontend performance. Today, Hyvä powers over 6,000 stores, including giants like Volkswagen, Citizen, Replay, and Nestlé, and has set the standard for Core Web Vitals performance in Magento.

Going open source expands access to performance-focused development, reduces entry barriers for smaller teams, and opens the door for broader community-driven innovation.

You can now use Hyvä Theme in projects without needing a paid license. If you plan to copy and modify Hyvä’s code, you’ll need to include the correct license file and credit Hyvä. If you’re only extending it or using it as a dependency, you won’t need to share your own code or make it open source.

What’s included

Hyvä Theme is now available under a dual license: OSL 3.0 and AFL 3.0, both of which are OSI-approved open-source licenses.

You can:

• Use the theme freely for personal or commercial projects
• Build and sell derivative themes (under open-source or proprietary licenses, depending on the license you choose)
• Access documentation, community Slack, and compatibility modules (via free keys).

Paid products still available:

• Hyvä UI – component library for prebuilt layouts and design elements
• Hyvä Checkout – high-performance, flexible checkout
• Hyvä Commerce – bundle of Theme + UI + Checkout
• Hyvä Enterprise – adds Adobe Commerce compatibility

Community support is free via Slack, while premium support is included with paid products.

All the details are documented on GitHub and hyva.io; the short version is that if you’re building for Magento and care about performance, you now have direct access to Hyvä’s codebase!

scandiweb, like many other agencies, has already used this model to build high-speed, beautiful-looking stores, reusable templates, and internal frameworks to speed up delivery. With the source code now fully open, it’s easier for others to do the same.

scandiweb’s Hyvä journey: early adopters turned Platinum Partners

At scandiweb, we recognized Hyvä’s potential early on and became one of its most active implementation partners. Today, we’re proud to be a Hyvä Platinum Partner, recognized for our deep technical contributions and performance-first approach to Magento development.

Since our first Hyvä rebuild for JYSK Canada, we’ve delivered dozens of Hyvä-based stores across different industries, including global retail brands and award-winning UX innovations. We’ve worked on some of the most complex Hyvä builds out there, often using our own internal setup framework. 

We even built the first fully open-source production-ready Hyvä storefront theme, Satoshi. Initially built for Shopify, we adapted it for Magento and shared it with the community.

Hyvä x scandiweb in action

Here’s what Hyvä has helped us achieve for our clients:

JYSK Canada’s outstanding Google CWV performance

Goal: Improve performance and pass Core Web Vitals

Approach: Partial Hyvä rollout with custom Tailwind and Alpine.js work, layout-by-layout

Results:

• -2900% total blocking time
• -242% time to interactive
• All-green CWV
• +58% unique purchases
• +43.8% transactions
• +20.1% checkout conversion rate

Read the full case study here.

Pioneering award-winning digital experience for Airthings

Goal: Redesign two subdomains into one customer-focused site

Approach: Full Magento + Hyvä rebuild with HubSpot CMS integration

Results:

• +103.4% transactions
• +105.5% revenue
• +56% engagement
• Winner of the Design Pioneer Award at Meet Magento NYC 2024

Read the full case study here.

Gear-Up YoY sales improvement

Goal: Migrate from Magento 1 and improve site speed

Approach: Magento 2 replatform with custom backend logic and Hyvä frontend

Results:

• +110.9% revenue YoY
• +47.7% orders YoY
• +124K clicks and 9.68M impressions
• Fully rebuilt custom logic and workflows

Read the full case study here.

ATX Fitness’ U.S. launch with Hyvä Commerce

Goal: Launch a US eCommerce site in time for Home Gym Expo

Approach: Full Magento 2 build with Hyvä Commerce + Checkout

Results:

• Launched in 2.5 months
• 15+ custom features delivered
• All green CWV
• 93–100% PageSpeed accessibility scores

Read the full case study here.

Umniah eshop strengthens leadership

Goal: Rebuild the eCommerce store to match modern standards

Approach: Magento 2 + Hyvä + custom integrations (ERP, GIS, personalization, payment)

Results:

• +105% revenue in Internet Plans
• +86% cart-to-view rate
• +72.1% sessions
• +300 new keywords
• Winner of the Design Pioneer Award at Meet Magento NYC 2025

Read the full case study here.

Ready to build with Hyvä?

The theme is open, and the code is yours. Hyvä Theme 1.4.0 is now available on GitHub under an open-source license. You can also request free license keys from hyva.io to access extra tools and compatibility modules. 

Congratulations to the Hyvä team on this release! You’ve raised the bar for everyone building on Magento, and we’re excited to keep pushing boundaries.

Want to see everything that’s possible with Hyvä? scandiweb is a Hyvä Platinum Partner with an extensive hands-on experience. Reach out to us if you’re exploring Hyvä for the first time or taking a new strategic step. We’re here to help and show a clear path to growth.

The post Hyvä Theme Goes Open Source: A Milestone for Magento Performance and Community appeared first on scandiweb.